Kenya’s construction industry is experiencing exponential growth in tandem with construction trends globally. With the growth experienced in the industry, there has been significant growth in the economy and a 50% contribution to the world’s landfill waste and pollution to the adjacent environment. Globally, the construction industry is among the largest consumers of natural resources and significant contributors to pollution. This has given rise to high pressure to adopt environmentally sensitive approaches in the construction industry to present a competitive advantage. It is, therefore, crucial to address the need for sustainability measures for Landscape Architecture projects to increase knowledge and awareness, create incentives geared towards supporting sustainable practices, and leverage legal instruments and policies. Green construction practices and strategies have positively impacted the environment and the Kenyan construction industry’s social and economic performance. However, there are several barriers to the adoption and improvement of monitoring and evaluation of sustainable practices, thus slowing down the industry in taking charge of sustainability.

Recently, 3D printing techniques gained much attention in solid dosage form production. Even though the methods are increasingly studied, there are still many challenges in establishing an accurate content of active ingredients in the final products. In the present study, new experimental design techniques and statistical software were developed to identify and optimize a formula to predict the mass of the tablet to be 3D printed before it actually is. The first step was to develop a virtual 3D object in the FreeCad Software, then, using a CURA slicer software, the G-code Format was obtained. The tablets were printed using a Cartesian 3D printer based on the generated data. Finally, adapting the object sequencing mode, a predicted drug mass value was obtained. As expected, the oblong tablet's scaling directly influences its mass. The software generates a correlation coefficient (r) of 0.84, confirming the directly proportional relationship between scaling and tablet weight. However, the r values progressively decreased, indicating a poor correlation between tablet weight and other factors: infill density percent (r = 0.403) and wall thickness (r = 0.185). After repeating the 3D printing with the values ​​suggested by the software, tablets with a practical value of 1066 mg were obtained. Considering that the confidence interval calculated is [834.95—1165.05] and the experimental value is 1066 mg, it can be certified that the proposed model is valid.

The control of the three-dimensional (3D) polymer network structure is important for permselective materials when specific biomolecules detection is needed. Here we investigate conditions to obtain a tailored hydrogel network that combine both molecular filtering and molecular capture capabilities for biosensing applications. Along this line short oligonucleotide detection in a displacement assay is set within PEGDA hydrogels synthetized by UV radical photopolymerization. To provide insights on the molecular filter capability, diffusion studies of several probes (sulforhodamine G and dextrans) with different hydrodynamic radii were carried out using NMR technique. Moreover, fluorometric analyses of hybridization of DNA oligonucleotides inside PEGDA-hydrogels shed light on the mechanisms of recognition in 3D, highlighting that mesh size and crowding effect greatly impact of hybridization mechanism onto polymer network. Finally, we found the best probe density and diffusion transport conditions to allow the specific oligonucleotide capture and detection inside PEGDA-hydrogels for oligonucleotide detection and the filtering out of higher molecular weight molecules.

Solar Insolation is the major contributor of earth’s radiation and energy budget. The insolation reaching the surface is a prime input for eco-physiological processes such as evapotranspiration and photosynthesis. Therefore, it is as critical component to assess bio-energy and bio-fuel resources. It is also a crucial input to crop simulation model for yield forecasting and its further applications in solar energy solutions. Although ground observations are better for accuracy purpose, they have challenges of maintenance, regular calibration and upkeeping etc. This call for the continuous spatio-temporal satellite based observations barring the acceptable accuracy. In case of INSAT3D/3DR, Bhattacharya et al. (2015) have derived the surface insolation product which is being used widely. We propose a method of improvement in this product. It is envisaged that a correction applied with the help of ground truth estimates may enhance the utilization of insolation products derived from INSAT3D/3DR datasets. In the present study, surface insolation product derived from INSAT 3D/3DR data at an interval of 30 minutes each (collectively 15 minutes interval) with 4 km spatial resolution was used for duration from May-2017 to Apr-2019 over Nagpur. Ground truth observations for same duration were carried out with CNR4, which were used to correct the INSAT 3D/3DR surface insolation product using the statistical best-fit method. Corrected INSAT 3D/3DR products are found correlating with the ground values well with differences of approximately < 1 W/m2. Best-fit parameters evolved in the present study uses only 2 years of simultaneous ground and satellite data which can be further improved by multi-year data base. We propose better utilization of INSAT 3D/3DR based surface insolation products in the assessment of solar resource mapping over Nagpur (and possibly other regions, such as Bhandara) with the help of best-fit parameters as assessed in the present study.

Recently there has been growing interest in the application of game theory (GT) to solve many diverse problems in the field of construction, including i.a.: tender preparation, selection of a contractor for construction works, negotiating terms and conditions of cooperation of the parties to the contract, analysis and modeling of investment risk. In the authors opinion, the use of GT by general contractor (GC) of construction works to indicate the best strategy leading to winning court proceedings in a situation of conflict with investor (IN), so far has not been the subject of research. Taking into account the above, the aim of the presented paper is to indicate the optimal strategy from the GC point of view in the conflict situation with IN. The article presents a list of the most common causes of conflicts between parties of the construction works' contract, defines the background of the problem and the cause of the dispute, and on its basis, the authors generate the theoretical model of the game. Based on the analyzed game model, expected payoffs for players were calculated and the probability border value at which GC should apply the indicated strategy determined. The results of the study show that in the case when the probability of issuing a judgment favorable for GC is at least equal to 69.23%, it is justified to use an aggressive strategy. The analysis also confirms that from the financial perspective, litigation in most cases of conflicts in the area of construction should be the last choice.

The electrocardiogram (ECG) was the first biomedical signal where digital signal processing techniques were extensively applied. By its own nature, the ECG is typically a sparse signal, composed of regular activations (the QRS complexes and other waveforms, like the P and T waves) and periods of inactivity (corresponding to isoelectric intervals, like the PQ or ST segments), plus noise and interferences. In this work, we describe an efficient method to construct an overcomplete and multi-scale dictionary for sparse ECG representation using waveforms recorded from real-world patients. Unlike most existing methods (which require multiple alternative iterations of the dictionary learning and sparse representation stages), the proposed approach learns the dictionary first, and then applies an efficient sparse inference algorithm to model the signal using the learnt dictionary. As a result, our method is much more efficient from a computational point of view than other existing methods, thus becoming amenable to deal with long recordings from multiple patients. Regarding the dictionary construction, we locate first all the QRS complexes in the training database, then we compute a single average waveform per patient, and finally we select the most representative waveforms (using a correlation-based approach) as the basic atoms that will be resampled to construct the multi-scale dictionary. Simulations on real-world records from Physionet's PTB database show the good performance of the proposed approach.

To improve the measurement accuracy of three-dimensional rotation angle of the spherical joint, a novel approach is proposed in this study, which combines the magnetic detection by Hall sensor and surface feature identification by eddy current sensor. Firstly, a permanent magnet is embedded in the ball head of spherical joint, and Hall sensors are set and distributed in the ball socket to measure the variation of magnetic flux density when spherical joint rotating, which are related to 3D rotation angle. In order to further improve measurement accuracy and robustness, we also set grooves on the ball head and use eddy current sensors to synchronously identify the rotation angle of the ball head. After the combination of two signals is adopted, a measurement model is established using the RBF neural network by training, and realized real-time measurement of the 3D rotation angle of spherical joint. The feasibility and superiority of this method are validated through experiments. The experimental results indicated that the measurement accuracy is promoted substantially compared to the preliminary measurement scheme based on spherical coding, the average measurement error of single axis is reduced by 9'9". The root mean square errors for the measurement of 3D rotation angles in this proposed method are as follows: the pitch angle α has an error of 1'8", the yaw angle β has an error of 2'15", and the roll angle γ has an error of 29'6".

The unsolved problem in three-dimensional surgical planning for patients with facial deformity, dysgnathia, or asymmetry is the lack of a normative database of “norm skulls” that can be used as treatment objectives. A study was conducted on 90 Eurasian persons (46 male and 44 female adults) with normal and balanced facial appearance, skeletal Class I pattern, and proper interincisal relationship with normal occlusion. Cone-beam computed tomography was performed. 18 landmarks were digitized and 3D cephalometric measurements of overall facial features, skull, midface and mandible were performed and analyzed by means of proportions calculated from the landmarks. Male and female skulls were analyzed as well as subdivisions revealed by cluster analysis. The data showed that four subtypes of skulls were distinguishable with statistical significance (p< 0,05). A male and a female type subdivided in a brachiocephalic and dolichocephalic phenotype could be identified. For each type then a mean shape was calculated by a Procrustes transformation, which in turn was used to create four template skulls from a male and a female skull by means of a thin plate spline transformation. The normative data of the subtypes can individually serve as a guide for orthodontic surgery, especially helpful in 3D plan-ning and execution of craniofacial operations.

3D bioprinting holds great promise in the field of regenerative medicine as it can create complex structures in a layer-by-layer manner using cell-laden bioinks, making it possible to imitate native tissues. Current bioinks lack both the high printability and the biocompatibility required in this respect. Hence, the development of bioinks that are capable of both properties is needed. In our previous study, a furfuryl-gelatin based bioink, crosslinkable by visible light, was used for creating mouse mesenchymal stem cell-laden structures with high fidelity. In this study, lattice mesh geometries were printed in a comparative study to test against the properties of a traditional rectangular-sheet. After 3D printing and crosslinking, both structures were analysed for swelling and rheological properties, and their porosity estimated using scanning electron microscopy. Results showed that the lattice structure was relatively more porous but sturdy and exhibited a lower degradation rate compared to the rectangular-sheet. Further, the lattice allowed encapsulation of a greater number of cells, allowing them to proliferate to a greater extent compared to the rectangular-sheet that retained a lesser number of cells initially. All of these results collectively affirmed that the lattice poses as a superior scaffold design for tissue engineering applications.

Additive manufacturing, commonly referred to as 3D printing, is an exciting and versatile manufacturing technology that is gaining traction and interest in both academic and industrial settings. Polymeric materials are essential components in a majority of the “inks” used across the various 3D printing technologies. As the environmental ramifications of sole or primary reliance on petrochemicals as a resource for industrial polymers continue to manifest themselves at a global scale, a transition to more sustainable bioderived alternatives could offer solutions. In particular, cellulose is promising due to its global abundance, biodegradability, excellent thermal and mechanical properties, and ability to be chemically modified to suit various applications. Thus far, cellulose has typically been incorporated in additive manufacturing applications as a substrate, filler, or reinforcement for other materials. However, due to its versatility and desirable properties, the exploration of all-cellulose 3D printing materials and associated methodologies is increasing. This review will discuss the progress and status of all-cellulose 3D printing approaches, associated challenges, and their potential as a key player in a more sustainable industrial future.

When a limb suffers a fracture, rupture, or dislocation, it is traditionally immobilized with plaster. This may induce discomfort in the patient, excessive itching and sweating, which creates the growth of bacteria, leading to an unhygienic and difficulty to keep clean from treatment. Furthermore, if the plaster remains for a long period, it may cause lesions in the joints and ligaments. To overcome all these disadvantages, orthoses have emerged as important medical devices to help patients in rehabilitation, as well as for self-care of deficiencies in clinics and daily life. Traditionally, these devices are produced manually, which becomes time-consuming and error prone. From another point-of-view, it is possible to use imageology (X-ray or computed tomography) to scan the human body; a process that may help orthoses manufacturing but induces radiation to the patient. To overcome this great disadvantage, several types of 3D scanners, without any kind of radiation have emerged. This article describes the use of various types of scanners capable of digitizing the human body, to produce custom orthoses. Studies have shown that photogrammetry is the most used and most suitable 3D scanner for the acquisition of the human body in 3D. With this evolution of technology, it is possible to decrease the scanning time and it will be possible to introduce this technology in clinical environment.

Melanoma is a highly aggressive type of skin cancer produced by malignant transformation of melanocytes and it is usually associated with a poor prognosis. Clinically, melanoma has several stages associated with migration and invasion of the cells through the skin layers, rapid cell spreading and formation of tumors in multiple organs. The main problem is the emergence of resistance of melanoma to the applied methods of treatment, thus it is of primary importance to find more crucial signaling pathways that control the progression of this type of cancer and could be targeted to prevent melanoma spreading. The main life-threatening stage of melanoma is metastasis formation, and 3D cell spheroids are better suited for the study of this process. Using a combinative approach (RT-PCR, immunofluorescence, patch-clamp and calcium imaging) we showed the functional expression of mechanosensitive Piezo1 channels in SK-MEL-2 aggressive melanoma cell line. We found that chemical activation of Piezo1 by its selective agonist Yoda1 completely prevents melanoma spheroid formation, and could be considered as a novel approach for the prevention of melanoma development.

Beyond semantic segmentation,3D instance segmentation(a process to delineate objects of interest and also classifying the objects into a set of categories) is gaining more and more interest among researchers since numerous computer vision applications need accurate segmentation processes(autonomous driving, indoor navigation, and even virtual or augmented reality systems…) This paper gives an overview and a technical comparison of the existing deep learning architectures in handling unstructured Euclidean data for the rapidly developing 3D instance segmentation. First, the authors divide the 3D point clouds based instance segmentation techniques into two major categories which are proposal based methods and proposal free methods. Then, they also introduce and compare the most used datasets with regard to 3D instance segmentation. Furthermore, they compare and analyze these techniques performance (speed, accuracy, response to noise…). Finally, this paper provides a review of the possible future directions of deep learning for 3D sensor-based information and provides insight into the most promising areas for prospective research.

Polystyrene as a thin film on arbitrary substrates or pellets form defective graphene films or powders that can be dispersed in water and organic solvents. The materials were characterized by visible absorption, Raman and X-ray photoelectron spectroscopy, electron and atomic force microscopy and electrochemistry. Raman spectra of these materials show the presence of the expected 2D, G and D peaks at 2750, 1590 and 1350 cm^-1, respectively. The relative intensity of the G vs. the D peak is taken as a quantitative indicator of the density of defects in the G layer.

Numerical weather prediction is an initial-value problem, for determination of the initial conditions, there are many methods and one of the most classical methods is variational methods in three dimensions, or 3D-Var. In this approach, with a defined cost function proportional to the square of the distance between the analysis and both the background and the observations, one can obtain the analysis. In the cost function, the background and the observations are reshaped to vectors; within this step, the order of the background error covariance matrix and the observational error covariance matrix becomes huge, which is not convenient to one to obtain the analysis. In this paper, according to the matrix analysis approach, we put forward some possible improvements to the dimension-reduction algorithm of 3D-Var, so that provide some references for data assimilation.

Due to the complexity, high-risk, and conservative character of construction companies, advanced digital technologies do not become widely adopted in the short term, while vendors make determined efforts to overcome this and disseminate their technologies. This paper presents the methods of an investigation addressing the extremely complex issues related to the current practices of digital technology adoption in construction. It discusses how construction companies follow a specific logical process linked to need, project objectives, characteristics of the adopting organization, and the characteristics of the new technology to be adopted. The study aims to demonstrate a novel method of data collection and analysis including data and methodological triangulation techniques including the use of NVivo and AHP to explore how companies make the decision to uptake a new technology (e.g. advanced crane, tunnel boring machine or drones) by focusing on customer and vendor activities, their interactions, contributing factors, and people involved in the process. The major original contribution of this paper is to develop an innovative methodological Cube for investigating the Construction Technology Adoption Process (CTAP) covering technology adoption, acceptance, diffusion and implementation concepts. CTAP is a framework that delineates the phases of the process that customer organizations use when deciding to adopt a new digital technology and the parallel vendor activities. The significance of these contributions is that they enable vendors to understand how to match their strategies with customer expectations in each phase of the CTAP. It also provides a benchmark for new construction companies to use the current best practice of decision making. Future research is warranted to more clearly delineate any differences with developing nations or related industries such as mining and property management.

Regeneration of biological tissues in medicine is challenging, and 3D bioprinting offers an innovative way to create functional multicellular tissues. One common way in bioprinting is bioink which is one type of the cell-loaded hydrogel. For clinical application, however, the bioprinting still suffers from satisfactory performance, e.g. in vascularization, effective antibacterial, immunomodulation and regulation of collagen deposition. Many studies have incorporated different bioactive materials into the 3D printed scaffolds to optimize the bioprinting. Here, we review a variety of additives added to the 3D bioprinting hydrogel. The underlying mechanisms and methodology for biological regeneration are important and will provide useful basis for future research.

Metal 3D printing technology is a promising manufacturing method, especially in the case of complex shapes. The quality of the printed product is still a challenging issue for mechanical applications. The anisotropy of the microstructure, imperfections, and residual stress are some of the issues that diminish the mechanical properties of the printed sample. The simulation could be used to investigate some technical details, and this research has tried to computationally study the metal 3D printing of austenitic stainless steel to address austenite microstructure and local yield strength. Two computational codes were developed in Visual basics 2015 to simulate the local heating/cooling curve and subsequent austenite microstructure. A stochastic computational code was developed to simulate austenite grain morphology based on calculated thermal history. Then Hall-Pitch equation was used to estimate the yield strength of the printed sample. These codes were used to simulate the effect of temperature of the printer’s chamber on microstructure and subsequent yield strength. The austenite grain topology is more columnar at a lower temperature. The percentage of the equiaxed zone will be increased at a higher chamber’s temperature. Almost a fully equiaxed austenite microstructure will be achieved at 800 C chamber’s temperature, but the last printed layer, which is columnar and can be removed by cutting then. The estimated local austenite grain size and the local yield strength in the equiaxed regions are in the range of 15 to 30 μm and 270 to 330 MPa at 800 C temperature of printer’s chamber, respectively.

Development of novel anti-cancer peptides requires a rapid screening process which can be accelerated by using appropriate in vitro tumor models. Breast carcinoma tissue is a three dimensional (3D) microenvironment, which contains a hypoxic center surrounded by dense proliferative tissue. Biochemical clues provided by such 3D cell mass cannot be recapitulated in conventional 2D culture systems. In this experiment, we evaluate the efficacy of the sandalwood peptide, cyclosaplin on established in vitro 3D silk breast cancer model using invasive MDA-MB-231 cell line. The anti-proliferative effect of the peptide on 3D silk tumor model is monitored by alamar blue assay, with conventional 2D culture as control. The proliferation rate, glucose consumed, LDH, and MMP-9 activity of Human breast cancer cells are higher in 3D constructs compared to 2D. A higher concentration of drug is required to achieve 50% cell death in 3D culture than 2D cultures. The cyclosaplin treated MDA-MB-231 cells showed significant decrease in MMP-9 activity in 3D constructs. Microscopic analysis revealed the formation of cell clusters evenly distributed in the scaffolds. The drug treated cells were less in number, smaller and showed unusual morphology. Overall, these findings indicate the role of cyclosaplin as a promising anti-cancer therapeutics.

Malignant cells cultured in three-dimensional (3D) models have been found to be phenotypically and biochemically different from their counterparts cultured conventionally. Since most of these studies employed solid tumor types, how 3D culture affects multiple myeloma (MM) cells is not well understood. Here, we compared MM cells (U266 and RPMI8226) in a 3D culture model with those in conventional culture. While the conventionally cultured cells were present in single cells or small clusters, MM-3D cells grew in large spheroids. We discovered that STAT3 was the pathway that was more activated in 3D in both cell lines. The active form of STAT3 (phospho-STAT3 or pSTAT3), which was absent in MM cells cultured conventionally, became detectable after 1-2 days in 3D culture. This elevated pSTAT3 level was dependent on the 3D environment, since it disappeared after transferring to conventional culture. STAT3 inhibition using a pharmacological agent, Stattic, significantly decreased the cell viability of MM cells and sensitized them to bortezomib in 3D culture. Using an oligonucleotide array, we found that 3D culture significantly increased the expression of several known STAT3 downstream genes implicated in oncogenesis. Since most primary MM tumors are naturally STAT3-active, studies of MM in 3D culture can generate results that are more representative of the disease.

Background: Wilms tumor (WT) is the main renal tumor in children. SIOP-UMBRELLA Guidelines admit Nephron sparing surgery (NSS) in syndromic patients, and in small (&lt;300 ml) nonsyndromic unilateral WTs, without lymph node involvement, and with a substantial expected remnant renal function, after neoadjuvant chemotherapy. We report our prechemotherapy transperitoneal robot-assisted partial nephrectomy (RAPN) in a unilateral non-syndromic Wilms tumor. Methods: A 6-year-old-child showed an exophytic 3.6 cm diameter solid rounding mass involving the upper right renal pole at an incidental abdominal echotomography. CT-scan and abdominal MRI proved no local infiltration neither lymph node involvement was appreciated, suggesting an exophytic mass easily resectable through a NSS robotic approach, with a low risk of rupture and no subverted renal anatomy. The preoperative imaging was not suggestive for WT. A virtual 3D reconstruction of the tumor was performed. Results: the oncologic board approved a robot-assisted partial nephrectomy with the intraperitoneal approach. The histopathologic analysis displayed a WT. The patient underwent 10 vincristine-doses adjuvant chemotherapy. 28-months follow-up showed no tumor recurrence. Conclusions: Intraperitoneal RAPN can represent an opportunity for WT and needs to be assessed as a challenging possibility. This case suggests a potential role of prechemotherapy RAPN in the near future for highly selected patients.

In this paper, we present the idea of Self Supervised learning on the Shape Completion and Classification of point clouds. Most 3D shape completion pipelines utilize autoencoders to extract features from point clouds used in downstream tasks such as Classification, Segmentation, Detection, and other related applications. Our idea is to add Contrastive Learning into Auto-Encoders to learn both global and local feature representations of point clouds. We use a combination of Triplet Loss and Chamfer distance to learn global and local feature representations. To evaluate the performance of embeddings for Classification, we utilize the PointNet classifier. We also extend the number of classes to evaluate our model from 4 to 10 to show the generalization ability of learned features. Based on our results, embedding generated from the Contrastive autoencoder enhances Shape Completion and Classification performance from 84.2% to 84.9% of point clouds achieving the state-of-the-art results with 10 classes.

Using a combination of pan proteomic platform associated with systemic biology analyses, we demonstrate that neonatal microglial cells derived from cortex and spinal cord expressed different phenotypes upon the physiological or pathological conditions. They also highlight great variability in protein production on both cellular and exosome levels. Bioinformatics data indicate for the cortical microglia anti-inflammatory and neurogenesis/tumorigenesis characteristics, while for the spinal cord microglia involvement in the inflammatory response. We confirmed these results by performing functional testing including neurite outgrowth assays in DRGs cell line, and glioma proliferation analysis in 3D spheroid cultures. Results from these in vitro assays indicate that the microglia located at different CNS areas reveal differential biological functions. While both microglia sources enhanced growth of DRGs axons, only the spinal microglia significantly attenuated glioma proliferation. Overall these findings are pointing to the fact that the origin of neonatal microglia affects the physio-pathological function, which may address the prevalence of the glioma in the brain in comparison with the spinal cord in adult.

Resistive patch array incorporating with metallic backplane provided an effective way to the achievement of broadband metamaterial absorbers(MAs). When loading metallic metamaterial to resistive MA, the outstanding construction helps realize more flexible and diversified forms of broadband absorption. In this paper, we attempted to load metallic resonators(MRs) to resistive MA in the three-dimensional construction, which benefits further enhancement of lower-frequency absorption. Simulation showed that the partial absorption band was separated to lower frequency, while the rest of broadband absorption was unaffected. Meanwhile, after combining multi-unit of the proposed MAs, the stair-stepping broadband absorption was also achieved. At last, three samples were fabricated. The agreements between simulations and experimental results demonstrated that resistive MA loaded with MRs provided an effective way for further enhancement of lower-frequency absorption with almost no change of the absorbing structure and areal density. Thus, it is worthy to expect a wide range of applications to emerge inspired from the proposed attempt.

Micro-blade design is an important factor in the cutting of single cells and other biological structures. This paper describes the fabrication process of three dimensional (3D) micro-blades for the cutting of single cells in a microfluidic “guillotine” intended for fundamental wound repair and regeneration studies. Our microfluidic guillotine consists of a fixed 3D micro-blade centered in a microchannel to bisect cells flowing through. We show that the Nanoscribe two-photon polymerization direct laser writing system is capable of fabricating complex 3D micro-blade geometries. However, structures made of the Nanoscribe IP-S resin have low adhesion to silicon, and they tend to peel off from the substrate after at most two times of replica molding in poly(dimethylsiloxane) (PDMS). Our work demonstrates that the use of a secondary mold replicates Nanoscribe printed features faithfully for at least 10 iterations. Finally, we show that complex micro-blade features can generate different degrees of cell wounding and cell survival rates compared with simple blades possessing a vertical cutting edge fabricated with conventional 2.5D photolithography. Our work lays the foundation for future applications in single cell analyses, wound repair and regeneration studies, as well as investigations of the physics of cutting and the interaction between the micro-blade and biological structures.

Leasing and recycling are important issues to achieve low-carbon sustainable development of construction machinery industry, however there are some dilemmas bothering which is caused by excessive restriction of product service life. Focusing on the problem of pricing and coordination, a two-stage model of leasing closed-loop supply chain based on the Industrial Internet platform practical application was proposed. Under the centralized and decentralized decision-making scenarios, the price of leasing and selling, maintenance effort and recovery rate are calculated respectively. By using the Shapley value method to optimize the selling price, and the two-part pricing contract to calculate the compensation fee, the global profit is reasonably distributed, while the supply chain achieving Pareto optimality. The performance of different contracts on the improvement of supply chain profit was investigated. And the correlation among parameters was also explored through sensitivity analysis and numerical simulation. The findings showed that maintenance and recycling of construction machinery can be improved with the advantage of the Industrial Internet platform, while achieving the supply chain coordination by contracts. The enhancement of maintenance effort can decrease the remanufacturing cost which is positively correlated to the selling price and leasing price of product, furthermore promoting the recovery rate of used products. In the future, reasonable control of platform cost can help improve the recycling of construction machinery.

This study aimed to compare the flexural strength, surface roughness, and microhardness of a resin for three-dimensional (3D) printing and a conventional composite resin and to evaluate whether the printing orientation influences these properties. To evaluate the flexural resistance, test specimens were produced and divided into four groups: three groups of resins for 3D printing with inclinations of 0°, 45°, and 90°, and one group of conventional composite resin. Forty discs were produced and subjected to a sandpaper-polishing sequence, and the surface roughness was measured using a roughness meter. The Vickers microhardness test was performed at three different points, and the average was obtained. The results were subjected to ANOVA statistical analysis and Tukey's test. There were statistical differences in the flexural strength and microhardness between the conventional resin and the resin used for 3D printing. No statistical difference in surface roughness was observed. The resin for 3D printing exhibited lower flexural strength and microhardness than conventional composite resins. We concluded that the resin for 3D printing had lower flexural strength and hardness than the conventional composite resin but similar surface roughness. The printing orientation did not affect the flexural strength, whereas the hardness increased as the printing angle increased.

3D bioprinting is the process of manipulating cell-laden bioinks to fabricate living structures. 3D bioprinting techniques have brought considerable innovation in biomedicine, especially in the field of tissue engineering, allowing the production of 3D organ and tissue models for in vivo transplantation purposes or for in-depth and precise in vitro analyses. Natural-derived hydrogels, especially those obtained from the decellularization of biological tissues, are promising bioinks for 3D printing purposes, as they present the best biocompatibility characteristics. Despite this, many natural hydrogels do not possess the necessary mechanical properties to allow a simple and immediate application in the 3D printing process. In this review, we focus on the bioactive and mechanical characteristics that natural hydrogels may possess to allow efficient production of organs and tissues for biomedical applications, emphasizing the reinforcement techniques to improve their biomechanical properties.

In the construction sector, the integration of biobased materials has emerged as a pivotal aspect of EU policies, aimed at promoting sustainable practices throughout the value chain to mitigate resource consumption and carbon emissions. This paper explores the development and validation activities of a bio-based façade system within the Basajaun H2020 project, focusing on enhancing the utilization of biobased components within building envelopes to replace conventional solutions with eco-friendly alternatives. This paper reports the methodologies employed to detect requirements and outline the testing protocols undertaken to validate the façade system design devised within the project focusing on the original façade components as the bio composite profile. Vision and opaque façade modules are prototyped and tested following curtain wall standards standard for performance and acoustic assessments, to showcase the efficacy of the developed solution. The conducted tests demonstrate the feasibility of integrating bio-based components into building envelopes, aligning with project expectations, and prevailing standards for curtain wall façade solutions. Notably, the designed façade system meets technical conditions and project objectives. Nevertheless, the research underscores the need for further refinements to facilitate solution industrialization and explore broader market applicability. Future efforts will focus on addressing these improvements and assessing the scalability of the solution.

AliAmbra is a project developed to explore and promote high-quality catches of the Amvrakikos Gulf GP to Artas’ wider regions. In addition, this project aimed to implement an integrated plan of action, to form a business identity with high-added value and achieve integrated business services adapted to the special characteristics of the area. The action plan for this project was to actively search for new markets, create a collective identity for the products, promote their quality and added value, engage in gastronomes and tasting exhibitions, dissemination and publicity actions, as well as enhance the quality of the products and markets based on the customer needs. The primary focus of this publication is to observe and analyze the data retrieved from various tasting exhibitions of the AliAmbra project, with a target goal of improving customer experience and product quality.

Tailings generated by mining account for the largest proportion of global waste from industrial activities. Copper is relatively uncommon world-wide, with low concentrations in sediments and waters, yet is very elevated around mining sites. On the Keweenaw Peninsula of Michigan, USA, jutting out into Lake Superior, 140 mines extracted native copper from the Portage Lake Volcanic Series, part of an intercontinental rift system. Between 1901-1932, two mills at Gay (Mohawk, Wolverine) sluiced 22.7 million metric tonnes (MMT) of copper-rich tailings (stamp sands) into Grand (Big) Traverse Bay. Here we examine: 1) 3D coastal elevation and reef bathymetry, 2) particle dispersal, 3) copper concentrations and leaching, plus 4) shoreline toxicity. About 10 MMT of tailings created a migrating coastal beach that stretches 7 km from the Gay pile to the Traverse River Seawall. Another 10 MMT are moving underwater on the coastal shelf, threatening Buffalo Reef, an important lake trout and whitefish breeding ground. Aerial photos, ALS (plane) LiDAR, and relatively inexpensive UAS (drone) surveys characterize shoreline structure and aid initial remediation. Because sands (natural beach quartz, stamp sand basalt) are silicates of similar density, particle dispersal is similar and challenging. However, stamp sand beaches contrast greatly with natural sand beaches in both physical profile and chemistry. Dispersing particles retain copper, and release toxic concentrations. Leaching is elevated by exposure to high DOC and low pH waters. Field experiments, shoreline seining, and benthic sampling confirm serious impacts on aquatic biota, supporting tailings removal.

Distributed Manufacturing (DM) is becoming increasingly important in operations management due to its potential to support sustainability goals, reduce risks in global supply chains, and boost local economies. However, previous analyses of the advantages and disadvantages of DM have mainly focused on operations, overlooking additional benefits across the supply chain. For example, DM can enable local sourcing, better serve end-users, and tackle reverse supply chain challenges. While economies of scale are essential for reducing costs and improving productivity, highly centralised manufacturing can increase transportation costs, vulnerability, and supply chain disruptions, particularly during pandemics or other times of restricted transportation. To address these challenges, this study introduces a Multi-attribute Decision Support System (MADSS) and assessment process that considers impacts across the supply chain and guides stakeholders, academics, and decision-makers. The MADSS handles quantitative and qualitative information, missing data, and uncertainty, and a team of experts from academia and industry in New Zealand has developed the evaluation. The MADSS was used to analyse DM and traditional construction alternatives from economic, social, environmental, and resilience perspectives in New Zealand. The research contributes to a better understanding of the impacts of DM across the entire supply chain. Also, it proposes a flexible decision-making framework to engage with stakeholders and support decision-making in other industries and regions.

As the largest energy consumer and carbon emitter, China has made substantial efforts to improve energy efficiency for decrease energy consumption, while the energy rebound effect determines its effectiveness. The embodied energy consumption of construction projects accounted for nearly one-sixth of the total economy's energy consumption in China. This paper is based on the logical relationship among capital input, technological progress, economic growth, and energy consumption, adapting an alternative estimation model to estimate the energy rebound effect for the construction industry in China for the first time. Empirical results in our paper reveal that the energy rebound effect for the construction industry in China is about 59.5% for the period of 1990–2014. The results indicate that the energy rebound effect does exist in China’s construction industry and it presented a fluctuating declining trend. This implies that half of the energy savings by technological progress is achieved. In addition, China’s government should implement proper energy pricing reforms and energy taxes to promote the sustainable development of China’s construction industry.

Although conventional immunohistochemistry for neurotropic Rabies virus (RABV) usually shows a high preference for neurons, non-neuronal cells are also potential target cells and abortive infection of astrocytes is considered a main trigger of innate immunity in the CNS. While in vitro studies indicated differences between field and less virulent lab-adapted RABVs, a systematic and quantitative comparison of astrocyte tropism in vivo is lacking. Here, a recently developed solvent-based tissue clearing technique was used to measure the RABV cell tropism in infected brains. Immunofluorescence analysis of 1 mm-thick tissue slices enabled 3D segmentation and quantification of infection frequencies of astrocytes and neurons. Comparison of highly virulent street virus clones from fox, dog, and raccoon with three lab strains of intermediate and low virulence revealed remarkable differences in the ability to infect astrocytes in vivo. While all viruses and infection routes led to comparable neuron infection frequencies, striking differences were detected for the infection of astrocytes. Consistent and inoculation route-independent astrocyte infection by field viruses, together with route-dependent or undetectable astrocyte infection by lab-adapted or vaccine viruses strongly suggests a model in which the ability to establish productive astrocyte infection in vivo functionally distinguishes field and attenuated lab RABV strains.

Type 1 diabetes is a chronic condition that results from the destruction of insulin-producing β-cells in the pancreas. Current treatments for type 1 diabetes, such as insulin therapy and pancreatic islet transplantation, have several limitations and, hence not quite effective in the long run. As current therapy methods fail to slow disease development, novel strategies such as the development of a bioartificial pancreas are being seriously considered. Over the last decade, research has focused on tissue engineering, which aids in the design of biological alternatives for the repair and replacement of non-functional or damaged organs. Three dimensional (3D) bioprinting technology which employs 3D printing technology to generate 3D tissue-like structures from biomaterials and cells, offers a promising solution for the treatment of type 1 diabetes by providing the ability to generate functional endocrine pancreatic tissue. Bioprinted structures are therefore an important aspect of tissue engineering because they have been found to replicate the native extracellular matrix, promoting cell survival and proliferation. In this review, we extensively discussed about bioprinting endocrine pancreas for the treatment of type 1 diabetes particularly focussing on the choice of cells, biomaterials, growth factors, and essential considerations. Additionally, the key challenges and perspectives towards recapitulation of the pancreatic function of the pancreatic organ engineering technologies have also been discussed.

Digital infrastructure is the basic guarantee for digital transformation, it is of practical significance to discuss how to effectively use digital infrastructure construction to promote the digital transformation of tourism enterprises. This paper examines the impact of digital infrastructure construction on tourism enterprises based on the "Broadband China" policy as a quasi-natural experiment. A-share tourism listed enterprises from 2010 to 2021 are studied using the double difference method. Findings indicate that digital infrastructure construction positively and significantly influences the digital transformation of tourism enterprises, driven by digital leadership and innovation capabilities. State-owned, small-scale, and high-growth tourism enterprises benefit more from this transformation. The results suggested that the state should develop differentiated digital infrastructure plans based on the specific conditions of different tourism enterprises. Additionally, tourism enterprises should enhance digital leadership and innovation capabilities through strategic changes and digital applications to amplify the impact of digital infrastructure on their transformation.

The application of solvent method in the preparation of polypropylene powders was investigated, including the influence of various technological conditions, such as the raw material melt index of polypropylene, processing temperature, dosage of the solvent and the packing pressure. The experimental data show that using solvent method can effectively produce polypropylene powder, and the optimal technological conditions are: melt index of polypropylene being about 17.8 g/10min, processing temperature being about 166.0 ℃, dosage of the solvent being about 0.067g/ml and the packing pressure being about 0.7MPa.Under this technological conditions, polypropylene powder with excellent sphericity could be prepared, the apparent density of powder can reach 0.40 g/cm3 and the prepared powder displayed a narrow size distribution with the mean size of about 42.7 µm.

The state of BIM adoption and implementation in facility management in Africa has been regarded as a developmental discourse gradually gaining grounds. While several studies have focused on manual review of the intellectual progression of BIM research, this confined review however understates the evolution of BIM in facility management. This approach therefore is not always representative of the picture of BIM in facility management at its formative stage. This paper aims to present a scientometric review of BIM in facility management exploring the intellectual progress made so far by authors. The state of the art of BIM in facility management research and practice and the challenges debilitating against BIM in facility management research. The review revealed a considerable amount of research endeavours limited by inadequate collaboration acorss organizations and institutions. The study also revealed the low degree of awareness amongst researchers in the AEC sector. While North America and China were leading countries due to the activity of few universities, Africa wasn’t as visible in research endeavours. The study recommended an increase in awareness drive across countries and increased government effort, joint funding for research to include gaps in practice issues.

This research is aimed at evaluating two different scenarios, firstly, appraising the impacts of employing the concepts of Total Quality Management (TQM) to the construction projects in Saudi Arabia. The results of the study were obtained through utilization of a descriptive analytical approach, where 300 questionnaires were distributed to engineering firms and companies with a response rate of 200 questionnaires, hence achieving the study sample for this research. The data gathered was analyzed by applying the Statistical Package for Social Science (SPSS) program and calculating the Relative importance index (RII) and the mean values. From the research conducted, the outcomes showed that the management’s ability to commit using TQM while applying BIM obtained a relative importance of (0.717), while the relative importance for the management’s ability to commit using TQM without the application of BIM is (0.552). The results showed that construction projects in Saudi Arabia still sustain setbacks from applying TQM concepts and suffer from the lack of administrative, scientific and technical applications. In a second scenario, a hybridized support vector regression (SVR) Harris-hawks optimization (HHO) (i.e., SVR-HHO) were used to predict the TQM. The performance accuracy of the models was checked through three different evaluation metrics namely; mean square error (MSE), correlation co-efficient (CC) and Nash-Sutcliffe efficiency (NSE). the hybridized emerging SVR-HHO outperformed the other two data driven approaches in both the training and testing stages based on the employed evaluation metrics. Overall, the obtained results showed that both the machine learning and metaheuristic approaches were capable of predicting TQM.

This pioneering study presents an in-depth biomechanical examination of soccer's diving header, aiming to quantify its impact on ball speed enhancement (BSE) and effective offensive range (EOR). Despite the diving header's widespread acclaim and historical significance, there remains a dearth of scientific scrutiny into its biomechanical intricacies. Employing an innovative research design featuring a static hanging ball at varied offensive distances and heights, the study replicates diverse header scenarios. The results of 3D motion quantification have shown that a physically excellent player (identified through the maximal standing long jump test) could reach an EOR around 2.64 times his body height. Furthermore, the study unveils that proficient players could attain BSE surpassing 9 m/s, signifying the diving header's heightened efficacy compared to traditional heading techniques, which could only result in 4.5 m/s. Correlation analyses unveil noteworthy relationships, highlighting the pivotal role of head speed at impact and the influence of minimizing speed-drop and temporal disparities for amplified effectiveness. Considerations for optimizing diving header execution are introduced, emphasizing the necessity for targeted training programs. Despite acknowledged limitations inherent to its pilot nature, this exploration furnishes foundational knowledge to guide subsequent research and practical applications, providing valuable insights into soccer training and skill development through a biomechanical lens.

Selective laser sintering (SLS) has drawn attention for the fabrication of three-dimensional oral dosage forms due to the plurality of drug formulations that can be processed. The aim of this work was to employ SLS with a CO2 laser for the manufacturing of carvedilol personalised dos-age forms of various strengths. Carvedilol (CVD) and vinylpyrrolidone-vinyl acetate copolymer (Kollidon VA64) blends of various ratios were sintered to produce CVD tablets of 3.125, 6.25 and 12.5 mg. The tuning of the SLS processing parameter laser intensity, improved printability and impacted the tablet hardness, friability, CVD dissolution rate, and the total amount of drug re-leased. Physicochemical characterization showed the presence of CVD in the amorphous state. X-ray micro-CT analysis demonstrated that the applied CO2 intensity affected the total tablet po-rosity, which was reduced with increased laser intensity. The study demonstrated that SLS is a suitable technology for the development of personalised medicines that meet the required specifications and patient needs.

Background: Anthropometric measurements play a crucial role in medico-legal practices. Actually, several scanning technologies are employed in post-mortem investigations for forensic anthropological measurements. This study aims to evaluate the precision, in-ter-rater reliability, and accuracy of a hand-held scanner in measuring various body parts. Methods: Three independent raters measured seven longitudinal distances using an iPad Pro equipped with a LiDAR sensor and specific software. These measurements were sta-tistically compared to manual measurements conducted by an operator using a laser level and a meterstick (considered the gold standard). Results: The Friedman’s test revealed minimal intra-rater variability in digital measurements. Inter-rater variability analysis yielded an ICC=1, signifying high agreement among the three independent raters. Addi-tionally, the accuracy of digital measurements displayed errors below 2%. Conclusions: Preliminary findings demonstrate that the pairing of LiDAR technology with the Polycam app showcases high precision, inter-rater agreement, and accuracy. Hand-held scanners show potential in forensic anthropology due to their simplicity, affordability, and porta-bility. However, further validation studies under real-world conditions are essential to es-tablish the reliability and effectiveness of handheld scanners in medico-legal settings.

Fabrication of scaffolds via 3D printing is a promising approach for tissue engineering. In this study, we combined 3D printing with cryogenic crosslinking to create biocompatible gela-tin/oxidized alginate (Gel/OxAlg) scaffolds with large pore sizes, beneficial for bone tissue re-generation. To enhance the osteogenic effects and mechanical properties of these scaffolds, we evaluated the impact of hydroxyapatite (HAp) on the rheological characteristics of the 2.86% (1:1) Gel/OxAlg ink. We investigated the morphological and mechanical properties of scaffolds with low, 5% and high 10% HAp content, as well as the resulting bio and osteogenic effects. Scanning electron microscopy revealed a reduction in pore sizes from 160-180 µm (HAp-free) to 120-140 µm for both HAp-containing scaffolds. Increased stability and higher Young’s moduli were measured for 5% and 10% HAp (18 and 21 kPa, respectively) compared to 11 kPa for HAp-free constructs. Biological assessments with mesenchymal stem cells indicated excellent cytocompati-bility and osteogenic differentiation in all scaffolds, with high degree of mineralization in HAp-containing constructs. Scaffolds with 5% HAp exhibit improved mechanical characteristics and shape fidelity, demonstrate positive osteogenic impact, and enhance bone tissue formation. Increasing the HAp content to 10% did not show any advantages in osteogenesis, offering a minor increase in mechanical strength at the cost of significantly compromised shape fidelity.

Coronary artery disease is the most prevalent cardiovascular disease, claiming millions of lives annually around the world. The current treatment includes surgically inserting a tubular construct called as a stent inside arteries to restore blood flow. However, due to lack of patient-specific design, the commercial products cannot be used with different vessel anatomies. In this review, we have summarized the drawbacks in existing commercial metal stents which face problems of restenosis and inflammatory responses, owing to the development of neointimal hyperplasia. Further, we have highlighted the fabrication of stents using biodegradable polymers, which can circumvent most of the existing limitations. In this regard, we elaborated on utilization of new fabrication methodologies based on additive manufacturing such as three-dimensional printing to design patient-specific stents. Finally, we have discussed on the functionalization of these stent surfaces with suitable bioactive molecules which can prove to enhance their properties in preventing thrombosis and better healing of injured blood vessel lining.

Corneal opacity is a leading cause of vision impairment and suffering worldwide. Transplantation can effectively restore vision and reduce chronic discomfort. However, there is a considerable shortage of viable corneal graft tissues. Tissue engineering may address this issue by advancing xeno- keratoplasty as a viable alternative to conventional keratoplasty. In particular, livestock decellularization strategies offer the potential to generate bioartificial ocular prosthetics in sufficient supply to match existing and projected needs. To this end, we have examined the best practices and characterizations that have supported the current state-of-the-art driving preclinical and clinical applications. Identifying the challenges that delimit activities to supplement the donor corneal pool derived from acellular scaffolds allowed us to hypothesize a model for keratoprosthesis applications derived from livestock combining 3D printing and decellularization.

The current paper is focused on the rapidly developing field of nano-/micro three-dimensional production of inorganic materials. The fabrication method includes laserlithography of hybrid organic-inorganic materials with subsequent heat treatment lead-ing to a variety of crystalline phases in 3D structures. In this work, it was examineda series of organometallic polymer precursors with different silicon (Si) and zirconium (Zr) molar ratios, ranging from 9:1 to 5:5, prepared via sol-gel method. All mixtureswere examined for perspective used in 3D laser by manufacturing by fabricating nano-and micro-feature sized structures. Their deformation and surface morphology wereevaluated depending on chemical composition and crystallographic phase. The appear-ance of a crystalline phase was proven using single-crystal X-ray diffraction analysis,which revealed a lower crystallization temperature for microstructures compared tobulk materials. Fabricated 3D objects retain a complex geometry without any distortion after heat treatment up to 1400^oC. Under the proper conditions, a zircon phase (ZrSiO₄ - a highly stable material) can be observed. In addition, the highest newrecord of achieved resolution below 60 nm has been reached. The proposed prepara-tion protocol can be used to manufacture micro/nano-devices with high precision andresistance to high temperature and aggressive environment.

The capacity of 3D printing (3DP) technologies to initiate speedy polymerization of solvent free resins accounts for their utility in the manufacturing of medical devices. Nonetheless, independent biological evaluation of 3D printed materials is recommended due to the unique parameters of the manufacturing process, which can influence their physical, chemical, and biological properties. In this study, E-Shell 450 material indicated for 3DP of hearing aid shells and inner ear devices was examined for biological safety using zebrafish bioassays adapted to OECD fish embryo test. In addition, the proprietary material was characterized for composition using headspace gas-chromatography mass spectrometry (GC-MS). To initiate test, newly fertilized zebrafish eggs were cultured on non-treated and ethanol-treated materials in glass petri dishes with ultrapure water, incubated at 28.5°C and assessed for developmental endpoints of toxicity at 24h interval until 96h. Data confirmed non-treated material was extremely toxic in bioassays within 24h whereas ethanol-treated material showed a relative lower toxicity possibly due to ethanoic-aqueous interactions as observed by GC-MS. With the current influx of 3D printing materials, users are urged to exercise caution. Operators must also take cognizance of the potential toxicity of the chemicals used in 3DP and implement safety measures to limit their exposure.

To address the severe distresses of asphalt pavement, a new type of pavement maintenance treatment, porous ultra-thin overlay (PUTO) with small particle size was proposed. The PUTO has a thickness of 1.5~2.5 cm and a large void ratio of 18~25%. As a newly asphalt mixture, the structure characteristics differ from traditional pavement. Therefore, it is necessary to investigated the fabrication schemes in laboratory and on-site, respectively. In this study, the optimal fabrication schemes, including compaction temperature and number of blows of PUTO were determined based on Cantabro test and volumetric parameters. Then, the corresponding relationship between laboratory and on-site compaction work was then established based on the energy equivalent principle. On this basis, the numbers of on-site rolling passes and the combination method were calculated. The results show that increased compaction temperature and number of blows reduce the height and enhance the compactness of the Marshall sample. With the same temperature and number of blows, the scattering resistance of coarse gradation (PAC-1) is better than that of fine gradation (PAC-2), and the increased asphalt viscosity significantly improves the scattering resistance of the asphalt mixture. To ensure the scattering resistance and volumetric characteristic, the initial compaction temperature of the PAC-1 and PAC-2 should not be lower than 150 °C and 165 °C, respectively. Then, the laboratory compaction work and on-site compaction work were calculated and converted based on the principle of energy equivalence. Consequently, the on-site compaction combination of rolling machines for four asphalt mixtures was determined. According to the volumetric parameters, the paving test section proved that the construction temperature and the on-site rolling combination determined by laboratory tests are reasonable, and ultra-thin overlay has good structural stability, drainage and skid resistance.

There has been considerable research on reconstructing 3D shapes from single-view images; however, preserving the detailed information of the input image remains difficult. In this paper, we propose the application of a gradient map to train a network, aimed at improving the visual quality of fine-grained details such as the thin and tiny components of generated shapes. Each gradient map was created from the original voxel data, and each value represented the amount of information per volume. Here, the gradient map was defined by several methods that mathematically quantify and represent the detailed structure of an object. By applying this map to the loss function in training, we could induce the network to intensively train partial details, such as thin and narrow parts. We demonstrated that the detailed information was well-recovered when a weight that is proportional to the gradient value was applied to the loss. Furthermore, it is expected that our method will contribute to the development of 3D technologies related to the construction of virtual space for simulation and new customer experience.

To explore the spatial network structure characteristics and driving effects of carbon emission intensity in China's construction industry, the investigation combined the modified gravity model and social network analysis method to deeply analyze the spatially associated network structure characteristics and driving effects of carbon emission intensity in China's construction industry, based on the measurement of carbon emission data of China's construction industry from 2006 to 2017. The results show that the regional differences of carbon emission of construction industry are significant, and the carbon emission intensity of construction industry show a fluctuation trend. The overall network of carbon emission intensity shows an obvious “core-edge” state, the hierarchical network structure is gradually broken. Economically developed provinces generally play a leading role in the network, and play an intermediary role to guide other provinces to develop together with them. Among the network blocks, most of the blocks play the role of “brokers”. The block with the leading economic development has a strong influence on the other blocks. The increase of network density, the decrease of network hierarchy and network efficiency will reduce the construction carbon emission intensity.

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.

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.

Recently, new semantic segmentation and object detection methods have been proposed for direct processing of three-dimensional (3D) LiDAR sensor point clouds. LiDAR can produce highly accurate and detailed 3D maps of natural and man-made environments and is used for sensing in many contexts due to its ability to capture more information and its robustness to dynamic changes in the environment. In addition, the cost of LiDAR sensors has decreased in recent years, which is an important factor for many application scenarios. The challenge with 3D LiDAR sensors like the Velodyne HDL-64E S2 is that they can output large 3D data at up to 1,300,000 points per second, which is difficult to process in real time when applying complex algorithms and models for efficient semantic segmentation. Most existing approaches are either only suitable for relatively small point clouds or rely on computationally intensive sampling techniques to reduce their size. As a result, most of these methods do not work in real-time in realistic field robotics application scenarios, making them unsuitable for practical applications. Systematic point selection is a possible solution to reduce the amount of data to be processed, but although it is memory and computationally efficient, it selects only a small subset of points, which may result in important features being missed. To address this problem, we propose a new approach to semantic segmentation in forestry that uses a systematic sampling method in which the local neighbors of each point are retained to preserve geometric details. Our approach has been shown to process up to 1 million points in a single pass. It outperforms the state of the art in efficient semantic segmentation in large datasets such as Semantic3D. We also present a preliminary study on the performance of LiDAR-only data, i.e., intensity values from LiDAR sensors without RGB values for semi-autonomous robot perception.

In engineering, connections between components are often weak areas. Unreasonable connection methods can easily reduce the strength of components, resulting in unpredictable failure modes. In nature, numerous connection methods for biological structures with excellent mechanical properties have evolved. Studying the connection methods of organisms in nature can inspire new ideas for bionic connection methods. When the diabolical ironclad beetle is under pressure, the elytra are not easy to separate, which ensures the stability of the beetle's external structure, thus making the beetle extremely resistant to pressure. The reason for this is the interlocking and toughening effect of the unique jigsaw connection between the elytra. Therefore, in this paper a theoretical analysis model is established and used to analyze the mechanical behavior of the diabolical ironclad beetle's jigsaw connection during the drawing process and determine the influence of factors such as quantity, angle, and geometric characteristics on the mechanical properties of the jigsaw connection. The results of the theoretical analysis are then compared with the results of experiments and ABAQUS finite element simulation.

Three-dimensional (3D) printing has allowed for production of geometrically complex 3D objects with extreme flexibility, which is currently undergoing rapid expansions in terms of materials, functionalities, as well as areas of application. When attempting to print 3D microstructures in glass, femtosecond laser induced chemical etching (FLICE) – which is a subtractive 3D printing technique – has proved itself a powerful approach. Here, we demonstrate fabrication of macro-scale 3D glass objects of large heights up to ~3.8 cm with an identical lateral and longitudinal spatial resolution of ~20 μm. The remarkable accomplishment is achieved by revealing an unexplored regime in the interaction of ultrafast laser pulses with fused silica which results in aberration-free focusing of the laser pulses deeply inside fused silica.

Centimeter-level localization and rotation angle estimation of flatbed trucks are major problems in unmanned forklift automated loading scenes. To solve it, this study proposes a method for high-precision positioning and rotation angle estimation of flatbed trucks based on BeiDou and vision. First, an unmanned forklift equipped with a ToF camera and double antenna mobile receiver for BeiDou positioning collects depth images and localization data near the front and rear endpoints of the flatbed. Then DDRNet-23-slim was used to segment the flatbed from the depth image and extract the straight lines at the edges of the flatbed using the Hough transform and compute the set of intersection points of the lines. A neighborhood feature vector was designed to locate the endpoint of a flatbed from a set of intersection points by feature screening. Finally, the relative coordinates of the endpoints were converted to a customized forklift navigation coordinate system by BeiDou positioning, and rotation angle estimation was performed by the front and rear endpoints. Experiments showed that the endpoint positioning error was less than 3 cm and the rotation angle estimation error was less than 0.1°. The precision of the method meets the demand for automated flatbed truck loading by unmanned forklifts.

For enhancing the efficiency of cantilever casting the construction in the bridge, a novel rhombus traveling track of hanging basket was developed and optimized. The civil software titled Midas was applied to analyse the mechanical properties of the hanging basket with full load and control load. The strength and distortion of the walking mechanism were within the specified range when the maximum beam unit internal force of 149.69Mpa, which was less than the allowable stress of steel 175Mpa, and the anti-overturning safety factor of the hanging basket was 2.5 to meet the requirements. Through the comparative analysis of the key components and the finite element calculation, it was found that there was about 30% redundancy in the structure performance. Therefore, further optimization of each structure was carried out, and the front elevation of the main truss of 20° was achieved. It obtained the best performance in all aspects.

Building carbon footprint analysis is a key instrument for assessing the impact of different constructions on climate change. Several standards and methodologies are available to calculate the footprint of buildings, including standards and norms, life cycle assessment (LCA), and dedicated software tools. The use of BIM software for these calculations is both scientifically justified and very practical. This scientific publication focusses on the application of a BIM-based research methodology for the analysis of the carbon footprint of a single-family house. The research process included the following steps: (i) design of a single-family house with timber frame construction using Archicad BIM software, (ii) simulation of the building energy performance using the EcoDesigner Star plug-in, (iii) life cycle assessment (LCA) using the plug-in for Archicad, (iv) preparation of a second model with traditional masonry construction for comparison, and (v) comparative analysis of the single-family house models with timber frame and masonry construction. Analysis of the results highlights significant differences in CO2e emissions between masonry and timber buildings and the varying impact of individual elements on the total CO2e emissions of the buildings studied. These findings are relevant for future work on sustainable building design and construction, which aims to minimise negative environmental impacts. The goal of minimising the cumulative carbon footprint of buildings is critical to achieving the Sustainable Development Goals and combating climate change.

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.

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.

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.

The global coronavirus (COVID-19) pandemic has created a whole new set of risks in construction industries generating unprecedented delays, disruptions, and uncertainty on construction projects, and has forced the industries in adopting more sophisticated technologies while combating the reduced workforce on job sites. Further, the post-pandemic era of construction is expected to be a lot different as the industries will embrace the technology as the augmentation and collaboration strategy. Thus, it will be extremely hard to sustain for construction industries in the absence of effective risk management. The existing risk plans need to be inspected for their capability of handling new risks arising from COVID-19 and the project managers will need to make the necessary revisions as needed. This paper discusses on past (NORM), present (NEW NORM), and future (Post COVID-19 NORM) of the construction industry and highlights key strategies for managing projects and construction risks during and post COVID-19 pandemic.

Synthetic polymer-based gradient foams have considered as promising category of functionally graded materials with unique properties. In this study, the carbon dioxide (CO₂) foaming technology has used for PET-PEN (Polyethylene Terephthalate - Polyethylene Naphthalate) copolymer towards porous functional materials with thermal insulation with reasonable mechanical strength. Through scanning electron microscope based morphological characterization, a potential to fabricate gradient foam structures with micro-pores has identified. It has shown that variation of post-foaming temperature can tune the pore size distribution although the very high post-foaming temperature tends to cause structural instability. Thermal measurement data set the limits of operation, confirmed by simultaneous differential scanning calorimeter and thermo-gravimetric analysis. Mechanical stress and thermal conductivity also has measured to find rationale of thermal insulation with reasonable mechanical strength and to elucidate the actual 3D grid foam of copolymer.

Thermal infrared imagery provides temperature information on target objects, and has been widely applied in non-destructive testing. However, thermal infrared imagery is not always able to display detailed textures of inspected objects, which hampers the understanding of geometric entities consisting of temperature information. Although some commercial software has been developed for 3D thermal model displays, the software requires the use of expensive specific thermal infrared sensors. This study proposes a cost-effective method for 3D thermal model reconstruction based on image-based modeling. Two smart phones and a low-cost thermal infrared camera are employed to acquire visible images and thermal images, respectively, that are fused for 3D thermal model reconstruction. The experiment results demonstrate that the proposed method is able to effectively reconstruct a 3D thermal model which extremely approximates its corresponding entity. The total computation time for the 3D thermal model reconstruction is intensive while generating dense points required for the creation of a geometric entity. Future work will improve the efficiency of the proposed method in order to expand its potential applications to in-time monitoring.

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.

ATTO 565, a Rhodamine-type dye, has garnered significant attention due to its remarkable optical properties, such as a high fluorescence quantum yield, it is a relatively stable structure, and has low biotoxicity. ATTO 565 has found extensive applications in combination with microscopy technology. In this review, the chemical and optical properties of ATTO 565 are introduced, along with the principles behind them. Then, the functionality of ATTO 565 in confocal microscopy, stimulated emission depletion (STED) microscopy, single-molecule tracking (SMT) techniques, and fluorescence correlation spectroscopy (FCS) is discussed. These studies demonstrate that ATTO 565 plays a crucial role in areas such as biological imaging and single-molecule localization, thus warranting further in-depth investigation. Finally, we present some prospects and concepts for the future applications of ATTO 565 in the fields of biocompatibility and metal ion detection.

Immediate load of full-arch rehabilitations over implants, specially over 4 implants are very well documented in the literature. More recently, the use of computed surgical guides to help the planning and the execution of these treatments, in many situations without the need of raising a flap, and diminishing the appearance of hematomas, bleeding and with less trauma to the patient has gained preference among implantologists. The objective of this case report is to show a clinical case of an immediate load full-arch fixed rehabilitation over 4 implants produced by 3D printing manufacturing technology, and placed with a computed surgical guide, in the same appointment, and the 24 months follow-up. The patient returned after 3 months to replace the immediate temporary fixed prosthesis for a new one, with metallic bar, better teeth and more delicate. Soft and hard tissue around the implants seemed to be stable, without signs of inflammation, either on the 3 or the 24 months follow-up. 3D printing of implants by direct metal laser sintering is a technology that seems to be promising for oral implantology, with solid studies showing reliable results, as seen in this single case. More clinical studies are necessary to testify its efficacy.

The three-dimensional Ising model on the m$\times$n$\times$l cubic lattice with the screw boundary condition along the ${\bf X}$ direction and the periodic boundary conditions along both ${\bf Y}$ and ${\bf Z}$ directions is exactly solved by using the $2^{mn}$-dimensional representation of the rotation group in $2mn$-dimensions, similar to the Kaufman's spinor approach in two dimensions. The exact partition function is obtained from two sets of $2^{mn-1}$ eigenvalues of the $2^{mn}$-dimensional transfer matrix {\bf V} corresponding to the even and odd eigenvectors, respectively. Such the eigenvalues are determined by the angles of the 2mn-dimensional rotation associated with {\bf V}.

In this article, metallic additive manufacturing (AM) processes were classified and demonstrated. AM technology can be applied to a wide range of industrial areas because of its great feasibility in the design and manufacturing of various complex parts. The main factor that distinguishes various metallic AM processes from each other is the deposition method. Deposited metal can be imported in the form of melt or semi-solid. AM technology also covers a wide range of materials like aluminum, titanium, and many other alloys. Some of the common applications of metallic AM processes are the quick manufacturing of the parts which utilized in various industries like medical, automotive, aerospace, and jewelry industries. AM can help to fabricate parts that are impossible to be manufactured by other processes.

Existing methods for 3D human pose estimation mainly divide the task into two stages. The first stage identifies the 2D coordinates of the human joints in the input image, namely the 2D human joint coordinates. The second stage uses the results from the first stage as input to recover the depth information of human joints from the 2D human joint coordinates to achieve 3D human pose estimation. However, the recognition accuracy of the two-stage method relies heavily on the results of the first stage and includes too many redundant processing steps, which reduces the inference efficiency of the network. To address these issues, we propose the EDD, a fully End-to-end 3D human pose estimation method based on transformer architecture with Dual Decoders. By learning multiple human poses, the model can directly infer all 3D human poses in the image using a pose decoder, and then further optimize the recognition result using a joint decoder based on the kinematic relations between joints. With the attention mechanism, this method can adaptively focus on the most relevant features to the target joint, effectively overcoming the feature misalignment problem in the human pose estimation task and greatly improving the model performance. Any complex post-processing step, such as non-maximum suppression, is eliminated, further improving the efficiency of the model. The results show that the method achieves an accuracy of 87.4% on the MuPoTS-3D dataset, significantly improving the accuracy of end-to-end 3D human pose estimation methods.

Along with the popularity of the Internet, people are exposed to more and more ways of micro-videos, and a huge amount of micro-video data has emerged. micro-videos have gradually become the Internet content preferred by the public, and a large number of micro-video apps have also emerged, such as Tiktok and Kwai. Intelligent classification and mining of micro-videos can greatly enhance user experience, improve business operation efficiency and enhance user experience. Through deep intelligent analysis and mining of micro-videos, important information in micro-videos can be extracted to provide an important basis for beautifying videos, content appreciation, video recommendation, content search, etc. In the past, content understanding for short videos often used human work annotation, but in recent years, with the great success of deep convolutional neural networks in image recognition, short video content understanding based on this method has gradually developed. Nowadays, most recognition algorithms extract the feature representation of each frame independently and then fuse them. However, while extracting the feature representation, some low-level semantic features are lost, which makes the algorithm unable to accurately distinguish the category of the video. At present, the algorithm of micro-video recognition based on deep learning has surpassed the iDT algorithm, making these traditional methods fade out of people’s view. In this paper according to the micro-video classification task, a new network model is proposed to concatenate features of each modality into the overall features of various modalities through the network, and then fuse the various modal features with the attention mechanism to obtain the whole micro-video features, which will be used for classification. In order to verify the effectiveness of the algorithm proposed in this paper, experiments are conducted in the public dataset, and it is shown the effectiveness of our model.

This article describes the methodology used to identify the mathematical model that describes the correlations between the input parameters of an experiment and the parameters being followed. As a technological process, the aerodynamic separation was chosen, respectively, the behavior of a solid particle within an ascending vertical airflow. The experimental data obtained were used to identify two parameters, the average linear velocity, and the angular velocity, and through the Table Curve 3D program was developed a mathematical model which describes the dependence between the input parameters (the shape and size of the solid particle and the velocity of the airflow) and the monitored parameters. In order to determine a single mathematical equation that describes as accurately as possible the correlation between the input variables and those obtained, a pyramid-type analysis was designed. The determination of the mathematical equation started from the number of equations generated by the Table Curve 3D program, then the equations with a correlation coefficient greater than 0.85 were chosen, and finally, the common equations were identified. Respecting the working methodology was identified one equation which has for the average linear velocity a correlation coefficient r2 between 0.88-0.99 and 0.86-0.99 for the angular velocity.

Three-dimensional (3D) printing techniques have received considerable focus in the area of bone engineering due to its precise control in the fabrication of complex structures with customizable shapes, internal and external architectures, mechanical strength, and bioactivity. In this study, we design a new composition biomaterial consisting of polylactic acid (PLA), and halloysite nanotubes (HNTs) loaded with zinc nanoparticles (PLA+H+Zn). The hydrophobic surface of the 3D printed scaffold was coated with two layers of fetal bovine serum (FBS) on the sides and one layer of NaOH in the middle. Additionally, a layer of gentamicin was coated on the outermost layer against bacterial infection. Scaffolds were cultured in standard cell culture medium without the addition of osteogenic medium. This surface modification strategy improved material hydrophilicity and enhanced cell adhesion. Pre-osteoblasts cultured on these scaffolds differentiated into osteoblasts and proceeded to produce a type I collagen matrix and subsequent calcium deposition. 3D printed scaffolds formed from this composition possessed high mechanical strength and showed an osteoinductive potential. Furthermore, the external coating of antibiotics not only preserved the previous osteogenic properties of the 3D scaffold but also significantly reduced bacterial growth. Our surface modification model enabled the fabrication of a material surface that was hydrophilic and antibacterial, simultaneously, with an osteogenic property. The designed PLA+H+Zn may be a viable candidate for the fabrication of customized bone implants.

AbstractWhile the technology is relatively new, low cost 3D printing has impacted many aspects of human life. 3D printers are being used as manufacturing tools for a wide variety of devices in a spectrum of applications ranging from diagnosis to implants to external prostheses. The ease of use and availability of 3D design software and low cost has made 3D printing an accessible manufacturing and fabrication tool in many research laboratories. 3D printers can print materials with varying density, optical character, strength and chemical properties providing platforms for a huge number of strategies that can be chosen for user’s needs. In this review, we focus on applications in biomedical diagnostics and how this revolutionary technique is facilitating development of low cost, sensitive and often geometrically complex tools. 3D printing in fabrication of microfluidics, supporting equipment, optical and electronic components of diagnostic devices is presented. Emerging diagnostic 3D bioprinting as a tool to incorporate living cells or biomaterials into 3D printing is also discussed.

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.

Over the past few decades, the quantity of construction waste has steadily risen in tandem with the expansion of construction activities and the rapid pace of development and urbanization. This problem is rooted in the practice of delivering materials to construction sites without totally using them for their intended purpose. The primary aim of the JIT tactic is to ensure that the precise materials required for production are available at the precise location, exact time, and appropriate quantity, thereby facilitating timely production. Presently, the use of ready-mix concrete is the most typical instance of a just-in-time construction process Developed countries have benefitted immensely from the use. However, the reverse is the case in developing countries like Nigeria, where indigenous contractors still employ traditional in-situ concreting even when faced with restrictive site space. This study focuses on investigating Ready-mix concrete, to project its immense benefits and effectiveness in minimizing lean construction waste. A survey research design and case study were adopted for this study, with the population being the management staff of construction firms in Lagos State, Nigeria. The questionnaire was used to collect data and the targeted respondents were purposively selected from the population. A total number of 112 questionnaires were administered with a response rate of 51%. Percentage, mean, standard deviation, and ANOVA were used to analyze the data. The mean value is above 3 on a Likert Scale of 5, while faster construction speed and uniform quality of concrete are the topmost benefits derived from adopting Ready-mix Concrete in Nigeria. The Case study also revealed the effectiveness of Ready-mix concrete in minimizing the two lean construction wastes that were examined, namely; waste of overproduction and waste of waiting. It is recommended Just-in-Time technique should be extended to other construction materials aside from concrete to improve waste minimization through the adoption of an overall JIT policy for the construction process.

Cropland area is closely related to food production. More previous focuses were paid on impacts of extreme events on food production, but less on cropland dynamics. This study took the Farming-Pastoral Ecotone of Northern China (FPEN) as a case area, to investigate its cropland area dynamics and driving factors in view of perspectives of extreme events, environmental conditions, socioeconomic development, urban expansion, and ecological construction. We used ridge regression approach to quantify contributions of these drivers to cropland area dynamics. Results showed that cropland area increased significantly at a rate of 333.5km2/a during 1992−2020 and were spatially clustered in east of the FPEN. Impact extent and size each driving factor on cropland trend presented large spatiotemporal differences, but ecological construction (EC) had overall the greatest impact on cropland area changes, followed by urban expansion (UE). In comparison, TL10p has the smallest. UE-dominated areas increased 41.9% since 2010s, but still less than EC. Furthermore, we found that extreme events effects on cropland area trend evidently increased. Particularly, TH90p displayed the most increase (~99.4%). Cropland area changes dominated by extreme temperature events in 2010−2020 increased nearly six times than that in 1992−2010. These findings suggest that increasing impacts of extreme weather events on cropland area changes should be cautioned.

As part of our research for new leads against human African trypanosomiasis (HAT), we report on a 3D-QSAR study for antitrypanosomal activity and cytotoxicity of aminosteroid-type alkaloids recently isolated from the African medicinal plant Holarrhena africana A. DC. (Apocynaceae), some of which are strong trypanocides against Trypanosoma brucei rhodesiense (Tbr) with low toxicity against mammalian cells. Fully optimized 3D molecular models of seventeen congeneric Holarrhena alkaloids were subjected to a comparative molecular field analysis (CoMFA). CoMFA models were obtained for both, the anti-Tbr and cytotoxic activity data. Model performance was assessed in terms of statistical characteristics (R², Q² and P² for partial least squares (PLS) regression, internal cross-validation (leave-one-out) and external predictions (test set), respectively, as well as the corresponding SDEP and F-values). With R²=0.99, Q²=0.83 and P²=0.79 for anti-Tbr activity and R²=0.94, Q²=0.64, P²=0.59 for cytotoxicity against L6 rat skeletal myoblasts, both models were of good internal and external predictive power. The regression coefficients of the models representing the most prominent steric and electrostatic effects on anti-Tbr and for L6 cytotoxic activity were translated into contour maps and analyzed visually, allowing suggestions for possible modification of the aminosteroids to further increase the antitrypanosomal potency and selectivity. Very interestingly, the 3D-QSAR model established with the Holarrhena alkaloids also applied to the antitrypanosomal activity of two aminocycloartane-type compounds recently isolated by our group from Buxus sempervirens L. (Buxaceae), which indicates that these structurally similar natural products share a common SAR and, possibly, mechanism of action with the Holarrhena steroids. This 3D-QSAR study has thus resulted in plausible structural explanations of the antitrypanosomal activity and selectivity of aminosteroid- and aminocycloartane-type alkaloids as an interesting new class of trypanocides and may represent a starting point for lead optimization.

The digital representation of various signals allows, at the subsequent stages of their transmission, to apply correction codes that provide protection against possible errors arising from the action of interference in the communication channel. At the same time, it is important that, with the required correcting ability, these codes have the maximum possible speed. The article presents the results of calculations for linear codes, showing their really achievable limiting capabilities.

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.

Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor-object interface. In this paper, we present an optical-based 6-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate local XYZ force and displacement at ten distinct locations, and provide global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of individual sensing units that form the overall sensor, providing distributed 6-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over an local force range of approximately ±1.5 N in X and Y and 0 to -2 N in Z. The local displacement precision in the X, Y and Z axes is 56.70 μm, 50.18 μm and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to -1.5mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task which generate changing global forces and torques.

The poly lactic acid (PLA) is one of the most used bio-derived thermoplastic polymers in 3D and 4D printing applications. The determination of PLA surface properties is of capital importance in 3D/4D printing technology. (1) Background: The surface thermodynamic properties of PLA polymer were determined by using the inverse gas chromatography (IGC) technique at infinite dilution. The determination of the retention volume of polar and non-polar molecules adsorbed on the PLA particles filling the column allowed us to obtain the dispersive, polar, and Lewis’s acid-base surface properties at different temperatures from 40 °C to 100 °C. (2) Methods: the applied surface method was based on our recent model that used the London dispersion equation and the new chromatographic parameter function of the deformation polarizability and the harmonic mean of the ionization energies of the PLA polymer and organic molecules. (3) Results: The application of this new method led to the determination of the dispersive and polar free surface energy of adsorption of molecules on the polymeric material, as well as the glass transition and the Lewis acid-base constants. (4) Conclusions: four interval temperatures were distinguished showing four zones of the variations of the surface properties of PLA as a function of the temperature before and after the glass transition.

After proving, in a purely categorial way, that the inclusion functor InAlg(Σ) from Alg(Σ), the category of many-sorted Σ-algebras, to PAlg(Σ), the category of many-sorted partial Σ-algebras, has a left adjoint FΣ, the (absolutely) free completion functor, we recall, in connection with the functor FΣ, the generalized recursion theorem of Schmidt, which we will also call the Schmidt construction. Next we define a category Cmpl(Σ), of Σ-completions, and prove that FΣ, labeled with its domain category and the unit of the adjunction of which it is a part, is a weakly initial object in it. Following this we associate to an ordered pair (α,f), where α=(K,γ,α) is a morphism of Σ-completions from F=(C,F,η) to G=(D,G,ρ) and f a homomorphism in D from the partial Σ-algebra A to the partial Σ-algebra B, a homomorphism ΥαG,0(f):Schα(f)B. We then prove that there exists an endofunctor, ΥαG,0, of Mortw(D), the twisted morphism category of D, thus showing the naturalness of the previous construction. Afterwards we prove that, for every Σ-completion G=(D,G,ρ), there exists a functor ΥG from the comma category (Cmpl(Σ)↓G) to End(Mortw(D)), the category of endofunctors of Mortw(D), such that ΥG,0, the object mapping of ΥG, sends a morphism of Σ-completion in Cmpl(Σ) with codomain G, to the endofunctor ΥαG,0.

Two antimicrobial agents such as silver nanoparticles (AgNPs) and titanium dioxide (TiO2) have been formulated with natural polysaccharides (chitosan or alginate) to develop innovative inks for the rapid, customizable, and extremely accurate manufacturing of 3D printed scaffolds useful as dressings in the treatment of infected skin wounds. Suitable chemical-physical properties for the applicability of these innovative devices were demonstrated through the evaluation of water content (88-93%), mechanical strength (Young’s modulus 0.23-0.6 MPa), elasticity, and morphology. The antimicrobial tests performed against Staphylococcus Aureus and Pseudomonas Aeruginosa demonstrated the antimicrobial activities against Gram+ and Gram– bacteria of AgNPs and TiO2 agents embedded in the CH or ALG macroporous 3D hydrogels (AgNPs MIC starting from 5 µg/ml). The biocompatibility of chitosan was widely demonstrated by cell viability tests and was higher than that observed for alginate. Constructs containing AgNPs at 10 µg/ml concentration level did not significantly alter cell viability as well as the presence of titanium dioxide; cytotoxicity towards human fibroblasts was observed starting with AgNPs concentration of 100 µg/ml. In conclusions, the 3D printed dressings here developed own the features to be cheap, highly defined, easy to be manufactured and further applied in personalized antimicrobial medicine applications.

The fast-paced evolution of artificial intelligence (AI), machine learning (ML), natural language processing (NLP), large language model (LLM) applications, and generative pre-trained transformer (GPT) have set the stage for improved and autonomous project scheduling models. This study demonstrates how project scheduling can be enhanced by employing building information modeling (BIM) to predict reliable schedules for each project element. The research is based on design science research (DSR) methodology and focus group discussion. The proposed system consists of six components: project analyzer, data warehouse, activity identifier and sequencing, activity magnitude and direct cost calculator, activity duration calculator, and schedule analyzer. Unlike other solutions, the proposed solution sequences activities based on an ML model rather than constraint matrices. The proposed solution thus enhances project performance through proactive planning and risk management. Integrating the autonomous project scheduling solution with the other components of an autonomous project management system would surmount schedule challenges and would result in greater cost efficiency and fewer delays.

This research delves into the integration of green roofs with Building Information Modeling (BIM), a pivotal advancement in sustainable urban construction. Aligning with the United Nations Sustainable Development Goals, particularly Goal 11, the study explores how this integration can address global challenges like climate change and resource depletion. Using the Dynamo Visual Programming Language within Autodesk Revit, the research develops a computational modeling approach for green roofs, focusing on their thermal and structural characteristics under varied environmental conditions. Key findings demonstrate the significant influence of substrate and drainage material combinations on green roofs’ thermal performance, highlighting the need for tailored designs based on climatic conditions. The study also emphasizes the importance of considering structural performance in both dry and saturated conditions for overall building integrity. The research identifies gaps in current practices, such as limited focus on specific green roof materials and reliance on certain software tools, suggesting the need for broader material selection and software adaptability. Future research directions include expanding material selections, exploring diverse environmental conditions, and integrating green roofs with various BIM software platforms. The study's implications extend to stakeholders in the construction industry, offering a framework for architects, urban planners, and policymakers to design and implement green roofs aligned with environmental goals. This work contributes to the field by proposing a novel approach to sustainable construction, integrating ecological design with digital technology, and setting a new benchmark in the integration of green roofs with BIM. By addressing these aspects, the research paves the way for future developments in sustainable urban construction, enhancing the efficiency, sustainability, and resilience of urban communities in line with global sustainability objectives.

The construction industry, characterized by its intricate network of stakeholders and diverse workforce, grapples with the challenge of managing information effectively. This study delves into this issue, recognizing the universal importance of safeguarding data, particularly amid rising concerns of unauthorized access and breaches. Aiming to harness the potential of blockchain technology to address these challenges, this study used a hypothetical biographical and safety data of construction workers and securely stored on a Hyperledger Fabric blockchain. Developed within the Amazon Web Services (AWS) cloud platform, this blockchain infrastructure emerged as a robust solution for enhancing data security and privacy. Anchored in the core principles of data security, the model emerges as a potent defender against the vulnerabilities of traditional data management systems. Beyond its immediate implications, this study exemplifies the marriage of blockchain technology and the construction sector, potentially reshaping workforce management, especially in high-risk projects, optimizing risk assessment, resource allocation, and safety measures to mitigate work-related injuries. Practical validation through transaction testing using Hyperledger Explorer validates the model's feasibility and operational effectiveness, serving as a blueprint for the industry's data management. Ultimately, this research not only showcases the promise of blockchain technology in addressing construction data security challenges but also underscores its practical applicability through comprehensive testing, heralding a new era of data management that harmonizes security and efficiency for stakeholders' benefit.

This research describes a detailed analysis in the enactment of a Lean Tool, the Last Planner System during pandemic period which helps in optimizing the resources for better coordination among all stakeholders in pandemic period. LPS as it is known, focusses on minimizing the factors such as uncertainties, barriers and variability to make construction projects more flexible for better project management. These include variations and deviations, supervision, delays in approvals, change resistance, subcontractor dedication which are all related to various stakeholders in the project. Following that, a Design Science Research technique is used to evaluate the effect of applying LPS in buildings. An action strategy is being used to attain this goal, and four case studies were being documented which were concerned in the implementation of LPS in the building of the Boy's Hostel, Research Scholar Quarters, Faculty Housing, and Girls' Hostel at Chennai, Tamilnadu, India. Data was gathered by observation of site activities, interviews, documentation analysis, and a questionnaire survey and grouped into various factors. While adopting the LPS tool in the research the factors affecting the implementation were found in the covid-19 pandemic period. Further these factors were anlayzed, measured, ranked and validated for adopting in projects.

According to a recent estimate by UN Habitat, approximately 3 billion individuals will require suitable housing by the year 2030. This staggering demand translates to the need for around 96,000 affordable housing units to be constructed each day. However, the conventional construction methods that rely on cement-based concrete and masonry are outdated, lacking innovation, efficiency, and sustainability. In light of these challenges, cold-formed steel emerges as an appealing alternative to traditional construction materials like masonry and concrete. It offers numerous advantages, including easy fabrication, lightweight properties, energy efficiency, the ability to reuse the material at the end of its service life, and a higher level of recyclability. Cold-formed steel buildings are also recognized for their superior insulation and lower energy consumption during operation. Cold-formed steel (CFS) members are created by rolling structurally sound steel sheets into the required shapes using a forming machine, without the need for heat as in the case of hot-rolled steel. While the thickness of these members can range from 0.01 mm to 7 mm, commercial construction of load-bearing walls, roof trusses, and floor joists typically utilizes steel thicknesses of 0.7 mm to 1.2 mm. This paper tries to illustrate the materials and methods employed in the construction of cold-formed steel modular buildings in Sri Lanka[1]. It delves into the material and durability characteristics of cold-formed steel, the design philosophy behind these structures, the development of the building envelope, and the energy efficiency features of the building elements. The findings of this study demonstrate that cold-formed steel buildings can be a highly sought-after alternative for residential construction, offering faster construction timelines, cost-effectiveness, and energy-efficient practices.

The Agile Building Adaptation (AgiBuild) framework is the adoption and adaptation of the large-scale agile framework for building adaptation projects. The agile methodology is proven to drive innovation by focusing on adaptation to change and user centricity. Similarly, the authors envision that the AgiBuild framework can fundamentally change the way that buildings are re-designed, refurbished, and operated. The AgiBuild framework is developed from the need of the building adaptation industry to manage uncertainties, overcome communication barriers, and improve innovation. In this study, a literature review of Agile and its impact on building adaptation projects is undertaken. Based on this systematic literature review, this paper defines the AgiBuilt framework and provides its benefits and barriers to implementation. A key finding of the literature review is that leadership influence, and adequate training form the key foundation for the implementation of the AgiBuild Framework. In defining the AgiBuild framework, the paper describes its components and how its implementation is likely to proceed. The authors propose that by adopting the AgiBuild framework, the industry can transform itself into a highly innovative and user-centred industry to improve productivity and performance of the construction industry..

We study the hadron-quark hybrid equation of state (EOS) of compact-star matter. The Nambu—Jona-Lasinio (NJL) local SU(3) model with vector-type interaction is used to describe the quark matter phase, while the relativistic mean field (RMF) theory with scalar-isovector $\delta$-meson effective field adopted to describe the hadronic matter phase. It is shown that the larger the vector coupling constant, the lower the threshold density for the appearance of strange quarks. For a sufficiently small value of the vector coupling constant, the functions of the mass dependence on the baryonic chemical potential have regions of ambiguity which leads to a phase transition in non-strange quark matter with an abrupt change in the baryon number density. We show that within the framework of the NJL model, the hypothesis on the absolute stability of strange quark matter is not realized. In order to describe the phase transition from hadronic matter to quark matter, the Maxwell's construction is applied. It is shown that the greater the vector coupling, the greater the stiffness of the EOS for quark matter and the phase transition pressure. Our results indicate that the infinitesimal core of the quark phase, formed in the center of the neutron star, is stable.

Buildings use 30-40 % of all energy resources and are thus their main consumers in modern society. Moreover, buildings require a vast amount of different raw materials. During the last two decades, several green building certifications have been created in order to consider social, economic and environmental aspects of sustainability of buildings. One of the most famous and widely used of these certifications is Leadership in Energy and Environmental Design (LEED). So far, the use of LEED has concentrated in the US and other developed countries. One reason that restricts the use of this point-based system certification in developing countries is the limited data about its costs. In this study, the extra cost of the certification process will be evaluated besides the changes needed in the design of the building to reach the points required by LEED. At the first stage, the number of points the case study earns in its current format (Scenario 1) were found out, then the cost difference of getting either the Certified (Scenario 2) or Silver (Scenario 3) level LEED certification for the building was studied. It was found that besides some technical considerations, filling the criteria of the Certified and Silver level increases the total costs of construction by 3.4% and 5.9%. Further improvement of the building’s energy efficiency would enable the attainment of a higher-level certification. The results of the study could help to promote the use of green building certifications in Western Asia.

In the Korean construction industry, legal and institutional safety management improvements are continually being pursued. However, there was a 4.5% increase in the number of workers’ deaths at construction sites in 2017 compared to the previous year. Failure to wear safety helmets seems to be one of the major causes of the increase in accidents, and so it is necessary to develop technology to monitor whether or not safety helmets are being used. However, the approaches employed in existing technical studies on this issue have mainly involved the use of chinstrap sensors and have been limited to the problem of whether or not safety helmets are being worn. Meanwhile, improper wearing, such as when the chinstrap and harness fixing of the safety helmet are not properly tightened, has not been monitored. To remedy this shortcoming, a sensing safety helmet with a three-axis accelerometer sensor attached was developed in this study. Experiments were performed in which the sensing data were classified whether the safety helmet was being worn properly, not worn, or worn improperly during construction workers’ activities. The results verified that it is possible to differentiate among wearing status of the proposed safety helmet with a high accuracy of 97.0%

In the contemporary construction management, poor project performance, cost overrun, and low-quality construction have become a central point of attention for improving project performance including information, interaction and communication management. virtual design and construction and building information modelling play indispensable role in improving the project performance. The aim of this study is to propose a Virtual Information Modeling as a novel information and communication technology method with potential to overcome problems in the construction industry. Using one-sample t test with Kolmogorov-Smirnov approach, we analysed data collected from structured questionnaire survey involving project managers working at architecture, engineering and construction industries in Tehran, Iran. The results suggest that the most important benefits and challenges of using Virtual Information Modeling are related to the area of integration, and implementation of Virtual Information Modeling has the greatest impact on this area of project management knowledge. Thus, integration should be considered a top priority for construction companies implementing Virtual Information Modeling in their projects. Policymakers should understand that careful management of virtual information is essential for improving the performance of projects and enhancing the process efficiency.

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&lt;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&lt;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&lt;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.

The construction industry is one of the most fatal industries, so it is important to pay more attention to safety solutions. Even though work-related accidents are known as major waste in construction projects, little attention has been paid so far to incorporating safety into the lean construction framework. In this research, lean construction theory is reviewed through the lens of safety. That being so, the identified challenges in previous research on improving safety in construction projects are categorized and those related to the concept of lean project delivery are introduced. Then, the principles of the lean construction framework are explained and the relevant changes for incorporating safety into the framework are introduced and discussed. It is expected that this hybrid model would further enrich the lean construction framework. The careful attention of project executives to this model may improve the safety situation in construction projects.

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.

3D facial surface imaging is a useful tool in dentistry and in terms of diagnostics and treatment planning. Between-groups PCA (bgPCA) is a method that has been used to analyse shapes in biological morphometrics, although various “pathologies” of bgPCA have recently been proposed. Monte Carlo (MC) simulated datasets were created here in order to explore “pathologies” of multilevel PCA (mPCA), where mPCA with two levels is equivalent to bgPCA. The first set of MC experiments involved 300 uncorrelated normally distributed variables, whereas the second set of MC experiments used correlated multivariate MC data describing 3D facial shape. We confirmed previous results of other researchers that indicated that bgPCA (and so also mPCA) can give a false impression of strong differences in component scores between groups when there is none in reality. These spurious differences in component scores via mPCA reduced strongly as the sample sizes per group were increased. Eigenvalues via mPCA were also found to be strongly effected by imbalances in sample sizes per group, although this problem was removed by using weighted forms of covariance matrices suggested by the maximum likelihood solution of the two-level model. However, this did not solve problems of spurious differences between groups in these simulations, which was driven by very small sample sizes in one group here. As a “rule of thumb” only, all of our experiments indicate that reasonable results are obtained when sample sizes per group in all groups are at least equal to the number of variables. Interestingly, the sum of all eigenvalues over both levels via mPCA scaled approximately linearly with the inverse of the sample size per group in all experiments. Finally, between-group variation was added explicitly to the MC data generation model in two experiments considered here. Results for the sum of all eigenvalues via mPCA predicted the asymptotic amount for the total amount of variance correctly in this case, whereas standard “single-level” PCA underestimated this quantity.

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.

The consistently positive Australian economic environment and stable population increase have led to a higher demand for new houses in recent years. Prefabrication is a promising method to help alleviate the issues related to housing shortage and affordability due to reduced material wastage, construction delays due to weather conditions, unexpected costs, shortage in labour and onsite risks. With the advancements in automation and manufacturing methods such as Design for Manufacturing and Assembly (DfMA), the quality and precision of prefabricated materials is tightly controlled, and the fabrication and assembly period are reduced. However, the full potential of prefabricated construction is yet to be realised in part due to most of developments being focused on its superstructure. A review of the current available options suitable for houses is necessary to understand the present state of the residential footing industry, which will help evaluate the necessary innovations for the growth of the Australian construction industry considering the local reactive soil conditions. This paper presents a summary of existing footing systems and potential prefabricated footing solutions for low-rise residential structures with one storey to two storeys. This paper also reviews the benefits and challenges of designing, manufacturing, transporting, handling and installing of prefabricated footings on site, which have great influence on the acceptance of these innovative footing systems.