Deformation behavior of MXene based polymer composites with bioinspired brick and mortar structures is analyzed. MXene/Polymer nanocomposites are modeled at microscale using bioinspired configurations of nacre-mimetic brick-and-mortar assembly structure. MXenes (brick) with polymer matrix (mortar) are modeled using classical analytical methods and numerical methods based on Finite Elements (FE). The analytical methods provide less accurate estimation of elastic properties compared to numerical one. MXene nanocomposite models analyzed with FE method provide estimates of elastic constants in the same order of magnitude as literature reported experimental results with good consistency. Bioinspired design of MXene nanocomposites results in the effective Young’s modulus of the nanocomposite increase by 25.1 % and the strength (maximum stress capacity within elastic limits) increase by 42.3 %. The brick and mortar structure of the nanocomposites leads to interlocking mechanism between MXene fillers in polymer matrix, resulting in effective load transfer, good strength, and damage resistance. This is demonstrated in this paper by numerical analysis of MXene nanocomposites subjected to quasi-static loads.

E-commerce has gained increased popularity over the last decade. To date, there is an open debate as to whether e-commerce or brick-and-mortar shopping is environmentally less sustainable, especially due to the growing mobility resources needed for e-commerce distribution. The analysis at hand compares the CO2-equivalent emissions of e-commerce and brick-and-mortar shopping of pharmaceutical products considering spatial aspects and the typical transport modal mix of consumers when doing online and offline shopping. The object of analysis is a retailer of pharmaceutical products, more precisely medicines, which offers, both, brick-and-mortar shop and online shopping possibilities. The results show that spatial aspects concerning the residential location of consumers, the vehicles used for shopping trips, the shopping basked size, and trip-chaining effects have a crucial impact on the mobility demand and CO2-equivalent emissions of the two commerce forms. In general, for rural and sub-urban areas, e-commerce results in lower CO2-equivalent emissions, while in urban areas, brick-and-mortar shopping is the favourable solution, if the consumers walk or cycle to the next pharmacy.

Increasing traffic loads and changes in code provisions lead to deficits in shear and flexural capacity of many existing highway bridges. Therefore, a lot of structures in Europe and North America are expected to require refurbishment and strengthening in the future. This projection is based on the current condition of many older road bridges. Different strengthening methods for bridges exist to extent their service life, all having specific advantages and disadvantages. By applying a thin layer of carbon textile reinforced mortar (CTRM) to bridge deck slabs and the webs of prestressed concrete bridges, the fatigue and ultimate strength of these members can be increased significantly. The CTRM-layer is a combination of a corrosion resistant carbon fibre reinforced polymer (CFRP) fabric and an efficient mortar. In this paper, the strengthening method and the experimental results obtained at RWTH Aachen University are presented.

During the MoDeCo2000 scientific and research project on mortars used in the territory of the Roman Danube Limes in Serbia, the biggest challenge was the quest for the provenance of used raw materials. The area where the largest city in the province of Moesia Superior developed, with millennial continuity of land use and settlement, was selected as a case study for deeper research. The material and immaterial values of Roman Viminacium have survived in the later life of the landscape, through the preserved building remains and artifacts, secondary use of building materials, but also toponyms, customs, and stories. Recycling of materials is commonly recognised in the modern age as the industrial processing of existing products in order to obtain raw materials and later prepare new products, representing one of the basic elements of sustainability. However, people throughout history have always used what they had at hand and the building remains were reused, but also recycled for new constructions. In this study we follow the presence of the specific material we call natural brick in the historical Viminacium landscape, focusing on Roman construction and specifically its potential use in lime mortars, connecting humanistic and natural sciences.

To achieve sustainable development during urbanization, construction waste is recycled for use as an aggregate in recycled concrete (RC). To determine the influence of the brick content in coarse recycled aggregates on the damage sustained by the resultant RC, the RC was first divided into seven phases: natural crushed stone, old gravel inside waste concrete, bricks, new mortar, old mortar on waste concrete surfaces, and new and old interface transition zones. The Monte Carlo method was then applied to establish a two-dimensional random aggregate model of the RC made with coarse brick aggregates. The ABAQUS software package was used to simulate a uniaxial compression test, the results of which were combined with those of a macro-test to determine the internal damage change rule of brick-containing RC. The stress–strain curves obtained from the simulation coincided well with that of the macroscopic tests. As the brick content increased, the damage zone inside the specimen and the number of microcracks increased. The stress concentration area decreased, as indicated by a lower compressive strength in the macro-test. The results indicate that higher brick contents in RC yield more initial damage inside the concrete and a lower compressive strength.

The production of biomass fly ash has been increasing every year in Europe, reaching 5.5 million tons in 2020. Biomass fly ash is not yet accepted in the standards as a substitute material for cement in mortar and concrete. In a first approach, the substitution limit of biomass fly ash is determined by comparing the mechanical strengths, fresh state properties and hardened properties of mortars produced with biomass fly ash to those of mortars produced with classical coal fly ash. Then, masonry and rendering mortars have been designed with different substitution rates of biomass fly ashes from wood combustion in thermal power plant. Although there is an overall decrease in performance, mortars made with biomass ash retain properties that make them suitable for use in masonry or rendering.

Self-compacting concrete (SCC) production is a complex operation that requires finding a good combination and a suitable dosage of each of its constituents. Several formulation methods have been developed to meet the workability requirements of SCC. In this paper, the relationships between the fresh properties of SCC based on local metakaolin (MK) and the spreading of its mortar was investigated. The results showed the existence of good correlations between the spreading of the mortar and the fresh state properties of the related SCC and that the MK substitution rate did not affect these correlations. The choice of the mortar flow rate should target appropriate fresh properties of the SCC and a viscosity enhancing agent (VEA) could be used if the mix is too fluid and present an instability.

3D printing with earth-based mortar is still under development and faces challenges. Optimizing the mortar mixture, improving structural strength, determining the relationship between printing speed and the amount of extruded material, and ensuring long-term durability are areas that are still being refined. Additionally, regulatory and certification issues must also be considered to ensure the safety and compliance of 3D printed structures. This paper presents for discussion the records, analyses, studies, and considerations regarding the initial initiatives involving 3D printing with the extrusion of earth-based mortar developed at the Faculty of Engineering of the University of Porto - FEUP. Through this work, it is possible to strengthen and reaffirm that 3D printing with earth-based mortar has significant potential in the construction industry and that the incorporation of dispersed kraft paper fibres from the recycling of cement bags is an excellent resource to achieve good constructability in 3D printing with earth-based mortar.

The main objective of this work is to study the effects of carbon nanotubes (CNT) on the strength and electrical properties of cement mortar. Molecular dynamic simulations (MDS) were carried out for the mechanical and electrical properties of the cementitious composite and the associated mechanisms. To model the atomic structure of the Calcium-Silicate-Hydrates (C-S-H) gel, tobermorite 11Å was chosen. Single-walled carbon nanotubes (SWCNTs) embedded in tobermorite structure were tested numerically. In particular, the effect of the concentration of CNT in cement paste was studied. An innovative experiment of electrical characterization of a cementitious composite of carbon nanotubes has been developed.

This study aimed to investigate the impact of incorporating Refuse Derived Fuel (RDF) into a production brick mixture in order to mitigate difficulties encountered in the production environment. Three distinct tests were conducted to assess the preparation process. The first test served as a reference, utilizing 100% clay material without RDF. The second test involved the inclusion of 10% RDF, obtained from a waste factory, with a grain size less than 20mm. In the third test, the RDF was mixed with silica sand after undergoing hammer milling with a 2mm sieve, followed by a 10% incorporation into the mixture. The primary objective was to comprehend the behavior of these mixtures in two critical stages: extrusion and drying. Extrusion performance was evaluated by examining the shaping process from the mold, vacuum conditions within the extruder, and the cutting of wet sample bricks. Furthermore, the drying procedure was assessed in terms of shrinkage, drying sensitivity, and appearance. Comparisons were made among the three test scenarios to identify the influence of RDF on these key parameters. Preliminary results indicate that the inclusion of RDF impacted the extrusion process. The addition of RDF resulted in variations in the flow characteristics of the mixture, affecting the shape formation from the mold and the vacuum conditions within the extruder. Additionally, the cutting of wet sample bricks exhibited some differences compared to the reference test. Concerning the drying phase, the presence of RDF influenced shrinkage behavior and drying sensitivity. The mixture with RDF showed different shrinkage patterns compared to the reference, and its drying sensitivity was altered. Moreover, the appearance of the bricks after drying exhibited notable variations due to the incorporation of RDF. In conclusion, incorporating RDF in the brick mixture introduces changes in both the extrusion and drying stages. The alteration in flow characteristics and vacuum conditions during extrusion, as well as the variations in shrinkage, drying sensitivity, and appearance during drying, suggest that further investigation is necessary to optimize the incorporation of RDF for improved brick production. These findings contribute to the understanding of the challenges and opportunities associated with the utilization of RDF in brick manufacturing processes.

In view of increasing concerns over non-renewable resource depletion and waste management, this study aimed to apply the Taguchi optimization technique to determine the process conditions for producing bricks by incorporating thin film transition liquid crystal displays (TFT-LCD) waste glass powder with reservoir sediments. An orthogonal array L₁₆(4⁵) was adopted, which consisted of five controllable four-level factors (i.e., cullet content, drying method, preheat time, sintering temperature, and error). Moreover, the analysis of variance method was used to explore the effects of the experimental factors on the density, water absorption, shrinkage ratio, loss of ignition, porosity, and compressive strength of the fired bricks. The microstructures of the fired specimens were investigated by scanning electron microscopy. Then, the large-scale production techniques for fired bricks containing recycled TFT-LCD glass cullet and reservoir sediments was developed in a commercially available tunnel kiln. The test results showed that the structure of fired specimen was loose at a sintering temperature ranged from 900–950 °C. However, the fired specimen showed a significant densification at the sintering temperature of 1050 °C. In addition, Taguchi method is a feasible approach for optimizing process condition of brick using recycled TFT-LCD glass cullet and reservoir sediments and it significantly reduces the number of tests. On the other hand, the characteristics of fired bricks developed in the tunnel kiln were in compliance with Chinese National Standards class Ι building bricks criteria.

In this article, we first present and discuss eighteenth-century descriptions of minerals that contributed decisively to the development of crystallography. Remarkably, these old crystallographic descriptions included morphologies with symmetries incompatible with an internal periodic order of atoms, which, however, have been recognised to be characteristics of quasicrystals. Moreover, we also review a number of studies of minerals with aperiodic crystal structures, including recently reported natural quasicrystals of extra-terrestrial origin. Finally, we discuss the current investigations addressing the search for new quasicrystalline minerals in nature.

The annual construction and demolition waste (CDW) generated from EU construction sector was 850 million tons, which represented 31% of the total waste generation and about 28% of CDW was ceramics (bricks and tiles). In this study, the feasibility of using CDW brick powder as the precursor of alkali activated mortar (AAM) and extruded polystyrene (XPS) as the lightweight aggregates to form lightweight brick powder AAM (LW-BP-AAM) for non-structural applications was investigated. The thermal conductivity of LP-BPAAM was 0.112 W/m·K with density of about 1,135 kg/m³ which was lower than the counterparts with similar density in literature. The acid resistance of LW-BP-AAM is comparable to conventional fly ash based AAM and superior than ordinary Portland cement. From the scanning electron microscopy with energy dispersive X-ray spectroscopy, there was no severe damage on the surface of LW-BP-AAM but aluminate was removed from the matrix which was further verified in Fourier transform infrared spectroscopy. The mass and strength loss of LP-BP-AAM was 1.5% and 33%, respectively. Although the compressive strength of the LP-BP-AAM was low (about 1.8 MPa), it can be improved by optimising the particle size of the XPS aggregates.

Structure/material requires simultaneous consideration of both its design and manufacturing processes to dramatically enhance its manufacturability, assembly and maintainability. In this work, we present a novel design framework for structure/material with requested mechanical performances in virtue of the compelling properties of topological design and origami techniques. The framework comprises four procedures, including topological design, unfold, reduction manufacturing, and fold. Topological design method, i.e. Solid Isotropic Material Penalization (SIMP) method, serves to optimize the structure to achieve preferred mechanical characteristics and origami technique is exploited to make the structure rapidly and easily fabricated. Topological design and unfold procedures can be conveniently completed in a computer; then, reduction manufacturing, i.e. cutting, is performed to remove materials from the unfolded flat plate; the final structure is finally obtained by folding the plate of the previous procedure. A series of cantilevers, consisting of origami with parallel creases and Miura-ori (usually regarded as a metamaterial), made of paperboard are designed with least weight and required stiffness by using the proposed framework. The findings here furnish an alternative design framework for engineering structures which could be better than 3D printing technique, especially for large structures made of thin metal materials.

Urbanization is a global phenomenon and as the economies are shifting from rural based subsistence to services based, the net flow of migration is inevitable. Unfortunately, In India, migration is very poorly understood. India is next to China in production of bricks, accounting for nearly 13% of global annual bricks’ production. The condition of brick-kiln workers is pitiable, especially due to poor care available. They are exposed to health hazards such as various communicable diseases, sexually transmitted diseases and occupational health hazards. The diseases such as respiratory problems, allergies, gastrointestinal ailments and malnutrition are frequent in these populations. This paper reflects upon various policies that exist for the welfare of unorganised sector but do these workers qualify for these benefits? This paper provides empirical basis for paradigm shift for policy formulation to provide safety nets for migrant population and have better urban planning for future.

This study identifies new Alkali Activated Composite Mud Mortar to alternate Cement Mortar used for laying masonry works. This study handles both experimental and numerical analysis of strength and durability for mortar, especially bond strength along mortar and brick joints have studied detail and compared with ANSYS. The bond strength has estimated through the triplet brick prism of shear behavior. The strength and deformation characteristics of masonry constituents obtained from these tests depend on the actual composite conduct of masonry. There is always a good reception for environmentally friendly, low energy, new construction materials, and used in preparing mortar/brick unit combinations all around the world. Also, this study fulfills those requirements. Especially, masonry laid with the mud mortar meets all. Fly Ash, Ground Granulated Blast furnace Slag, and Quarry Dust have utilized the new composites' preparation with 8Molority, 10Molority developed excellent strength. The composite specimens are having compression and bond strength, ranging from 4.84-5.14 and 0.12-0.18N/mm2. The mixed ratio of materials has taken (0.5 parts of Fly Ash, 0.5 parts of Steel Slag, 1.75 parts of Soil, and 0.25 parts of Quarry Dust). The samples tested resistance against acidic, sulfate, and alkalinity indicated PH values less than 7 and 9 simultaneously. Compression strength varied from 10-20% and gained more and fit composite used for mortar in masonry works.

This study presents an innovative approach for the utilization of industrial by-products and municipal waste in the production of sustainable and environmentally friendly cement mortar. We explored stabilized stainless-steel reduced slag (SSRS) and polyethylene (PE) plastic waste as partial replacements for aggregates. Various engineering properties of the resulting cement mortar specimens, including slump, slump flow, compressive strength, flexural strength, tensile strength, water absorption, and ultrasonic pulse velocity (UPV), were investigated through comprehensive experimental tests. The influence of different water-cement (w/c) ratios and substitution amounts on the engineering properties of the cement mortar samples was thoroughly examined. The findings revealed that an increase in PE substitution adversely affected the overall workability of the cement mortar mixtures, whereas an increase in SSRS amount contributed to enhanced workability. As for the hardened properties, a consistent trend was observed for both cases, with higher w/c ratios and substitution amounts leading to reduced mechanical properties. Water absorption and UPV test results validated the increased formation of porosity with higher w/c ratios and substitution amounts. This study proposes a promising method to effectively repurpose industrial by-products and municipal wastes, transforming them into sustainable construction and building materials. Additionally, a comparative analysis of transportation costs and carbon footprint emissions between SSRS-cement mortar and PE-cement mortar was conducted to assess their environmental impact and sustainability. Generally, higher w/c ratios and replacement levels corresponded to reduced carbon footprint. The geographical location of the source of SSRS and PE remains a challenge and studies to overcome this challenge must be further explored.

The objective of this study is to conduct a mineralogical and chemical characterization of the mortars Roman archaeological site of Volubilis to rebuild spare mortars for restoration. We take samples of mortar, broken tile palate garden, and pavement mosaic Falavius Germanus houses. The analysis by X-ray diffraction reveals the coarse mortar Flavius Germanus is made of quartz and calcite with feldspar and probably, mica and dolomite in small amounts. The binder end is formed calcite and quartz. However, the broken tile mortar is formed by coarse particles, clay base mixed with a binder phase dominated by calcite. These results allowed us to reformulate spare mortars for the restoration of damaged Roman mosaics. The mortars are made up by 63.6% of lime and 36.4% of sand(with 4.19% of large grain, 71, 04% of coarse sand, 24.22%, of fine sand and 0.55% fines parts).The performance of these mortars was tested by mechanical testing.

In order to fully perform their functions and be durable, mortars for renders and plasters are requested to have a set of characteristics that can vary with the type of exposure to external environmental actions and the type of substrate. Generally, they need moderate strength, high deformability, some water protection capability, good adhesion to the substrate, and compatibility with the pre-existent materials. The presence of water and its movement inside the pore structure of the mortars are among the most significant causes of degradation. Moreover, several authors consider that the main factors for durability and good performance of lime-based mortars are mostly related with the good quality of the binder and the use of adequate aggregates. This paper intends to study the effect of ageing on the properties and durability of air lime mortars, using aggregates of different mineralogy. For this purpose, different mortars compositions are exposed to an accelerated weathering test under defined conditions. The obtained characteristics are discussed and compared with the results obtained with the same mortars tested in laboratory conditions. The effects of the aggregate type on the durability of mortars seem to be linked to their effects on the mortars porous structure.

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.

The current study aims to develop a methodology for obtaining topology-optimal structures made of short fiber-reinforced polymers, which include the fluid-structure interaction. Accounting for the molding process during the internal iterations of topology optimization makes it possible to enhance the weight efficiency of structures—a crucial aspect, especially in aerospace. Anisotropy is considered through the fiber orientation tensor, which is modeled by solving the plastic molding equations for non-Newtonian fluids, and then introduced as a variable of the stiffness matrix during the structural analysis. The materials used were non-linearly modeled using an exponential-and-linear hardening law. The evaluation of weight efficiency in structures composed of short-reinforced composite materials using a dimensionless criterion is addressed. Experimental verification was performed to confirm the validity of the developed methodology. The evidence illustrates that considering anisotropy leads to stiffer structures and structural elements should be oriented in the direction of maximal stiffness. The load-carrying factor can be expressed in terms of failure criteria. The presented multidisciplinary methodology can be used to improve the quality of the design of structures made of short fiber-reinforced composites (SFRC) where high stiffness, high strength, and minimum mass are the primary required structural characteristics.

This paper proposes an AI-based approach to overcome the limitations of the SHM system in measuring global stress with limited sensors. Feature elements are selected based on correlation analysis among finite elements and used as stress-measured points. An ANN is used to establish the solution relationship between the feature and correlation elements. The proposed method is applied to the connector structure of an offshore platform, and an optimal ANN is established to optimize accuracy by considering factors like the number of sensors, neural network framework, and convergence criteria. The accuracy of the ANN is verified through a real-scale model test, demonstrating 93.6% accuracy. This technology represents a significant advancement, enhancing the practicality of the structural health monitoring (SHM) system from “point monitoring" to “field monitoring".

The biofibres wide application as mortars enhancement have been so far restricted by factors related to their chemical composition and hygroscopic nature. Their hydrophilic behavior increases the water demand of mortar-mixtures and diminishes their adhesion to the matrix, while further moisture-related fibre degradation issues may arise. Additionally, the natural fibres seem to be susceptible to degradation caused during the exposure to alkaline environments conditions, such as those of cement mortars, restricting their utilization in construction industry. Therefore, the current study focusses on the potential of fibre modification through treatments that would permanently alter their structure and chemical composition in the whole mass or surface towards their performance improvement. In this study, mild hydrothermally treated wood fibres of black pine and beech species were prepared and incorporated in cement mortars to assess their performance, applying the proportion of 1.5% v/v in the mortar. The mortars workability (at fresh state), physical, hygroscopic, chemical, thermal, and mechanical characteristics at the age of 28, 90 and 365 days and weathering performance by subjecting them at different artificial ageing environments (freeze-thaw cycles or outdoor exposure) were examined. The results indicated the beneficial role of the treated fibres in the dimensional stability, flexural strength, thermal insulation properties and capillary absorption of the mortar specimens, especially during ageing process, with the black pine fibres to reveal the highest improvement. The hydrothermally treated wood fibres seem to ensure the integrity maintenance of cement mortars under all ageing conditions, proving that the specific bio-additives could provide low-cost and eco-friendly mortar enhancement pathways.

Taking into consideration the seismic vulnerability of older buildings and the increasing need for reducing their carbon footprint and energy consumption, the application of an innovative system is investigated; the system is based on the use of textile reinforced mortars (TRM) and thermal insulation as a means of combined seismic and energy retrofitting of existing masonry walls. Medium scale tests were carried out on masonry walls subjected to out-of-plane cyclic loading. The following parameters were investigated experimentally: placement of the TRM in a sandwich form (over and under the insulation) or outside the insulation, one-sided or two-sided TRM jacketing and/or insulation, and the displacement amplitude of the loading cycles. A simple analytical method is developed and is found in good agreement with test results. Additionally, numerical modeling is carried out and is also found in good agreement with test results. From the results obtained in this study the authors believe that TRM jacketing may be combined effectively with thermal insulation, increasing the overall strength and energy efficiency of the masonry panels in buildings.

This study investigated the physical properties of section-restoration mortar with calcium nitrite and carbon dioxide (CO2) nanobubble mixing water to develop materials and methods for the repair and reinforcement of cracks in reinforced concrete (RC) structures. As the calcium nitrite content increased, the generation rate and generated amount of nitrite-based hydration products increased, owing to the rapid reaction between NO2- ions in calcium nitrite and C3A(Al2O3). Further, the reaction with C3S and C2S was accelerated, thereby increasing the generation rates of Ca(OH)2 and C-S-H. Further, the large amount of Ca2+ ions in these hydration products reacted with CO32- ions in CO2 nanobubble water, thereby increasing the generation of calcite-based CaCO3 in the cement matrix. This appears to have affected the strength development and durability improvement via the densification of the structure. These results suggest that the performance of polymer cement mortar for repairing concrete structures can be improved if calcium nitrite and CO2 nanobubble water are properly combined and applied.

The brick manufacturing sector in Bangladesh is experiencing rapid growth, leading to notable environmental and health concerns. The primary objective of this research is to examine the Savar Upazila, a region of significant economic significance owing to its favorable brick manufacturing conditions and proximity to Dhaka city. Brick kilns, among other sources, constitute significant contributors to air pollution. The study utilized primary and secondary data to examine brick kiln emissions' effects on the surrounding area's environment and public health. The collection of primary data was conducted in multiple zones within Savar Upazila, which is home to a significant number of brick kilns. The utilization of secondary data provided valuable insights regarding the toxic pollutants discharged by these kilns and the corresponding health risks they pose. The participants provided accounts of various health ailments, such as dermatological conditions, optical difficulty, and respiratory complications, further aggravated by brick kilns' incidents. The prevalence of crop losses, soil degradation, and reduced agricultural yields was confirmed by 74% of the respondents. The trees and crops in the surrounding area experienced adverse effects due to the deposition of dust particles. During periods of inactivity, the concentrations of sulfur oxide (SOx) were between 6 and 9 times lower compared to periods of operation. Similarly, nitrogen oxide (NOx) levels were observed to be 4 to 6 times lower during non-operational phases. The degradation of water quality in adjacent bodies has been attributed to the deposition of dust and ash originating from brickfields, resulting in substantial repercussions on aquaculture. A significant proportion of participants indicated experiencing diverse health issues, notwithstanding the employment prospects generated by brick kilns, thereby underscoring the adverse consequences on both the environment and the local economy.

The purpose of this study is to investigate the different types of bricks as a construction material. In this study, monitoring different technical specification or characteristics of the bricks. At the end of study, Brick Quality Index (BQI) evaluated. According to BQI, bricks were classified poor to excellent quality.

In a concrete beam initially crack is generated at the tension side under the effect of flexure, shear and torsional loadings. Accordingly, these weak concrete members require repair and/or strengthening to increase or restore their internal load capacity. In the current experimental and numerical investigations on concrete beam having different width to depth ratio of notch on its ultimate flexural load under one-point loading was considered. Further, the flexural behavior performance of notch concrete beam repaired with the three repair materials cement mortar, bacterial mortar and adhesive was also examined. Consequently, a comparative study is imple-mented between the experimental and numerical results. Concrete Damage plasticity (CDP) model was used for finite element numerical analysis of beam. The differences in numerical and experimental measured results ranges from 0.65 - 22.20 % for the ultimate load carrying capacity. As the notch size increases the ultimate load carrying capacity of beam was reduced. Addition-ally, linear regression model is used to predict the ultimate load values at an interval of 5 mm notch width up to maximum width of notch 100 mm. It can be observed that the ultimate load capacity for repaired beam is increased as compared to the notch beam for all the three repairing materials under consideration. The maximum ultimate load was increased in case of notch beam repaired using adhesive. As compared to the cement mortar the performance of the bacterial mortar in terms of the ultimate load was more. The bacterial mortar is found more sustainable and more durable as a repair material for the concrete structures.

The mortar’s composition, porosity, mechanical properties, entryways’ orientation, and condi-tioning status of the tunnels made by the Najdian Termite, Microtermes najdensis located at Hada Al-Sham village, Makkah Province, Saudi Arabia were studied. The most prevalent infected tim-ber trees by this pest were Tamarix aphylla, Pithecellobium duce, Zizyphus spina christi, Leucaena leu-cocephala, Ficus infectoria, and Phoenix dactylifera. Climate, soil, healthy wood (Wh), and termite nest skeleton (TNS) were the four components of the termite system that were investigated physi-cally, chemically, spectroscopically, and by FTIR, XRD, SEM, and TEM. It was noticed that the entryways of the termite nests are located at the southwest direction for all the infected trees studied at Hada Al-Sham village that promotes better ventilation. Concerning to the air-conditioning status within the their nest, the internal temperature (IT) was found to be milder than that for its analogous value for the outer temperature (OT) in which the IT was wormer than OT during cold durations, while it was colder than the hottest OT in hot days and vice versa. The IT’s trend had more constantancy with minor fluctuations compared to that for the OT. Moreo-ver, the IT was found to be tended to the upper OT’s limit otherwise its colder one. This finding means that these termite species prefer the hotter atmospheres comparing the colder circumstanc-es. Lignin is the prominent tracer of the organic matter used as a binder for the TNS due to its gluing ability, resistance to enzymatic degradation by the termites and their accompanied fungal community habituating the nests. The presence of both microcrystalline cellulose (MCC) and nanocrystalline cellulose (NCC) was discovered for the first time in the nest mortar reinforcing Klason lignin as the main binder. Their presence was proved by FTIR, XRD, SEM and TEM anal-yses and we satisfied that they were naturally-synthesized by the action of enzymatic hydrolysis excreted by the termites and their accompanied fungal community habituating the nests. The gross heat of combustion (GHCs) of the Wh and TNS were studied to try to find an important uti-lization of the infected woods as renewable energy resources instead of disposal them without economic benefits. These findings may be used for interpreting the durability of the termite nests to the different environmental stresses. Biomimicry of the termites’ nest from the perspective of its magic mortar with a suitable permeability, the entryways’ orientation, and the air-conditioning status can lead to modify the current construction’s designs to be more green and ecofriendly.

Alkali-silica reactivity (ASR) is one of multiple reactions responsible for premature loss in concrete infrastructure service life. ASR is a deleterious reaction initiated when highly reactive silicious content of aggregates reacts with alkali hydroxides content within portland cement in the presence of moisture. ASR results in the formation of expansive, white-colored gel-like material which results in internal stresses within hardened concrete. ASR induced stresses result in concrete cracking, spalling, and increased reinforcement steel corrosion rates. The main objective of this research is to improve the conditions of concrete infrastructure projects conditions by mitigating ASR damaging effect. The expansion of accelerated mortar bars poured using fine aggregates collected from different sources is measured versus time to evaluate aggregate’s reactivity. Different percentages of supplementary cementitious materials (SCMs) including class c fly ash, micro-silica, were used in remixing mortar bars to evaluate the efficiency of different types of SCMs in mitigating mortar bar expansion. Research findings showed that SCMs can mitigate ASR, thus, decrease the mortar bar expansion. The efficiency of SCMs in ASR mitigation is highly dependent on the incorporated SCM percentage and particle fineness. Silica fume, having the least particle size, displayed higher rates of ASR mitigation followed by fly ash, respectively. The outcomes of this research will assist design engineers in avoiding future losses due to ASR cracking in concrete infrastructure projects, and reduce the excessive need to maintenance, repair, and replacement activities.

Research results of the relationships between air-volume in air-entrained cement paste, mortar and concrete, all designed according to PN-EN 480-1 guidelines are presented in the paper. The cement paste, mortar and concrete, with w/c=0,5 ratio, were prepared using innovative air-entraining cement CEM II/B-V. The air-entraining cement CEM II/B-V was produced using two methods: mixed together with natural or synthetic aerated admixture. The air volume test of the volumetric method was carried out in case of fresh cement paste, mortar and concrete mix. Fresh concretes were evaluated in terms of stability of air entrainment and consistency for 5, 20 and 40 min. The porosity structure parameters, like summarized air-content, specific surface of air voids, air-voids spacing factor and micropores content of hardened concrete, were estimated using computed tomography with a resolution of 2-5 μm. The aim of the research was to determine the dependence between air-content of cement paste, mortar and concrete on the measurement of air-entrainment of cement paste or mortar with the same w/c ratio and type of cement, all designed according to PN-EN 480-1 guidelines. Test results proved that there is a good correlation between the measured air-content of the cement paste, mortar and concrete. Therefore, it is possible to predict the aeration of concrete on the air-entrainment of the mortar.

The global focus on geopolymer binder production has increased due to the adoption of waste materials and industrial byproducts. Given the gradual decline of the availability of fly ash and ground granular blast furnace slag (GGBFS) resulting from the decarbonization process in electricity and steel productions, waste clay brick powder (WCBP), could be a viable substitute of these pozzolanic by-products. This research is dedicated to thoroughly investigate the techno-eco-efficiency performance of WCBP when utilized as a geopolymer precursor. The favorable mechanical characteristics exhibited by fly ash-GGBFS-WCBP-based geopolymer binder emphasize the importance of assessing its sustainability alongside its technical viability. The study employed life cycle analysis (LCA), following ISO 14040-44 standards, and using the Simapro software, to evaluate the environmental implications of the use of WCBP-based geopolymer mixtures. Human toxicity emerged as the primary impact. Moreover, the analysis of life cycle costs highlighted key financial factors, with around 65-70% attributed to alkaline activators of the total cost. The production of alkaline activators was identified as a critical point for both environmental impact and economic considerations due to energy consumption. While WCBP-rich samples exhibit a 1.7-0.7% higher environmental impact compared to the control mix (CM), their high mechanical strength and cost-effectiveness make them technologically and economically efficient geopolymer mixes. In conclusion, the portfolio analysis for techno-eco-efficiency affirms that mixes containing 40%, 30%, and 20% WCBP are more efficient than those using 10% and 0% WCBP, respectively.

In this study, seven mortar mixes were prepared by replacing natural sand by crumb rubber ,CR, (10%, 25%, 50%, 60%, 75% and 100%). The properties of mortars, both in their fresh and hardened states, were studied. Key characterisitcs, including density, water absorption coefficient, porosity, thermal conductivity, heat capacity, shrinkage/swelling, elastic modulus, compressive strength, flexure strength, fracture energy and performance after exposure to heat, were evaluated. The results obtained showed that as the CR fraction increased, density, initial setting time, and workability decreased but mortars with CR fractions ranged between 25% and 50% are lightweight and can be used for repairing as they fulfill satndards. It was observed that strengths and stiffness decreased with higher CR content while shrinkage increased for CR percentage higher than 60%. However, up to 50% of CR content the mortars obey to the standards for repair. Interestingly, incorporating up to 50% waste tires proved to improve comfort and thermal resistance without affecting thermal inertia. A slight increase in the mass loss is observed when mortars are exposed to high temperatures. Mortars containing CR between 25% and 50% can be classified as lightweight and thermally insulating mortars, suitable for repairing concrete structures in accordance with industry standards.

To understand the relationship between water permeability and the pore structure of cementitious materials, literature that studied both water permeability and the pore structure are reviewed, and their correlation is studied. Although the majority of this data is for cement paste, mortar, concrete, and cemented soil are also included. Based on this study, it is established the determination coefficient between water permeability and the total pore volume is very low; however, those between water permeability and the critical, threshold, and median pore diameters, respectively, are moderate. On the other hand, the threshold pore diameter, derived based on the percolation theory, exhibits a very high determination coefficient. The calculated water permeability, using the Katz and Thompson equation, agrees with the reported water permeability quantitatively to a certain level, but is overestimated.

Nowadays the preservation and restoration of historical building needs to be faced in accordance with a novel sensibility regarding environment to preserve the future generations. In this context, the scientific community is focusing on novel and sustainable materials and techniques allowing durability and mechanical performances and at the same time compatibility with the existing heritage. Alkali activated materials represent a great challenge to produce new materials starting from the existing ones with reducing consumption, emission of greenhouse gases and environmental impact. This study deals with the valorization of waste materials coming from demolition and construction activities in the manufacture of geocomposites suitable for restoration and conservation of historical heritage. In particular, waste from tuff sawing and brick grinding were used as raw materials, then the geopolymeric samples produced were characterized from physical-chemical and mechanical point of view in order to investigate their performance and evaluate their suitability as materials for historical buildings recovery. Brick waste based geocomposites resulted to be more compact than the tuff-based ones as showed by the higher density values and the lower values of open porosity and water absorption and as further confirmed by the trend of the mechanical performance. Moreover, experimental data showed that physical and mechanical properties of both bricks and tuff waste-based geocomposites, even with different waste content, are compatible with existing building materials and to all the traditional repairing products.

The exploration of three-dimensional (3D) DNA structures marks a pivotal shift in genomics, offering unprecedented insights into the intricacies of cellular regulation, disease genesis, and the potential for novel diagnostic and therapeutic strategies. This study delves into the dynamic nature of 3D genome organization, investigating how these structures influence cellular functions in response to environmental changes and over time. Through a combination of real-time imaging and advanced computational models, we aim to unravel the complex interplay between 3D DNA structures, non-coding RNAs, and chromatin organization, and their collective impact on gene expression and cellular differentiation. A significant focus is placed on understanding the role of 3D DNA structures in the development and progression of genetic disorders. By employing comprehensive genomic and epigenomic profiling, this research seeks to identify structural aberrations linked to diseases, paving the way for the development of targeted diagnostics and therapies. Additionally, the study explores the potential of genome editing technologies, such as CRISPR-Cas systems, in correcting these structural abnormalities, while also addressing the ethical, legal, and social implications (ELSI) of such interventions. Integrating data from various genomic analyses, we propose the development of advanced computational models to predict the effects of 3D DNA structures on gene expression and cellular function. This integrative approach not only promises to enhance our understanding of genomic regulation but also sets the stage for groundbreaking advances in genomics-based diagnostics and therapeutics. The findings of this study have the potential to revolutionize our approach to treating genetic disorders, offering a new frontier in personalized medicine.

3D printing with cement-based materials is a promising manufacturing technique for civil engineering applications that already allows for the design and the construction of complex and highly customized structures using a layer-by-layer deposition approach. Usually, in this type of additive manufacturing, a mixture of cement, water, aggregate and additives is extruded through a specific print head and deposited in successive layers to form the desired shape. The extrusion mechanism is one of the most expensive parts of the 3D printer. Also, for low scale 3D printers, based on the shape of the extruder and the geometry limitation of the mixing blade, the 3D mixture is often limited to a narrow range of materials due to the risk of layer splitting or blockage. Therefore, there is a need to develop affordable and feasible alternatives to the current design-fabrication-application approach of 3D printers. In this paper, various new designed mixtures of fiber reinforced mortars that can be 3D printed using only a commercially available screw pump are analyzed based on their fresh properties and mechanical characteristics. The reduced facility requirements in this approach allow 3D-printing to be more available for civil engineering applications. With further innovation in the future, this method and mixtures can be extended for sustainable and economically feasible printing of single-family housing units.

Samples of mortar mixtures were prepared substituting the cement Portland (CPC-30R) by 0 (standard), 10 and 15% of fly ash and the structural evolution and compressive strength at 3, 7, 14 and 28 days were determined. The results for standard mortar samples showed the mineralogi-cal species portlandite, calcite, ettringite, iron oxide, silicon oxide and sillimanite. Magnetite was identified in the mixtures of mortars with portland cement substitution by 10% and 15% fly ash. The peaks corresponding to the portlandite, and ettringite showed an increase in their intensities with increasing curing time attributed to the consolidation of mineral species. The SEM tech-nique results showed that the mortar samples without fly ash addition contained mainly port-landite and ettringite while the samples with cement substitution by 10 and 15% of fly ash at 28 days further contained particles of fly ash coated with portlandite and ettringite, particles with a smooth surface and particles of fly ash with signs of attack on its surface. An increase inc was observed when the age of the mortar and the substitution of Portland cement by fly ash were increased from 3 to 28 days and from 0 to 15% respectively. The maximum value of c was reg-istered for the mortar sample with Portland cement substitution by 15% fly ash at 28 days of curing with 17.38 Mpa.

Deterioration of concrete subjected to freezing and thawing climatic conditions is one of most important factors affecting the durability of concrete infrastructure in cold climates. The freeze-thaw resistance of cementitious materials like concrete and mortar can be determined by the CDF test (Capillary Suction of De-icing chemicals and Freeze-Thaw Test). Here, concrete specimens are subjected to repeated freeze-thaw cycles with simultaneous addition of de-icing salt and the amount of material weathered near the surface is determined. For concretes with adequate freeze-thaw resistance, this test method works very well. However, specimens with inadequate or unknown performance often experience increased edge weathering, which is caused by the detachment of the lateral isolation tape. The increasing edge influence thus leads to a falsification of the results and consequently to an underestimation of the actual freeze-thaw resistance of the material. In materials research in particular, however, concretes with high levels of weathering are studied in order to be able to investigate various factors of influence on the freeze-thaw resistance of concretes in a targeted manner. This paper presents a novel methodology that delivers new information regarding the weathering of CDF test samples and the associated distribution function of the height decrease using high resolution 3D scan data. The results indicate a correlation between the progression of the distribution function and the sample's maximum aggregate size. The change of the sample volume can be used to support the weathering results of the standard CDF methodology. The increase of the surface area is used to estimate the tortuosity of the sample surface. It indicates an asymptotic curve approaching a specific maximum value, which is dependent on the the weathering depth of the sample.

Marine mortar was the goal material and its multi-scale physical-chemical-mechanical characteristics were the principal interest in this study. The on-line multi-scale damage detection experiments art was designed to quantify the characteristics mathematically and graphically. The normal cylinder specimen with 70-day age was produced and investigated by dynamically global MSHCT scan and local detection of EDS, SEM and XRD. The experiments results indicated that the marine mortar offered the appreciable strength at the early age at least, although some saline minerals were generated during the preparation. The micro-interfacial behavior and the parental foci controlled the damage development of the marine mortar the performance of which was still the adjustable one by the composition optimization.

The paper is aimed to develop an improved acoustic-based Structural Health Monitoring (SHM) and Non-Destructive Evaluation (NDE) techniques, which provide the waves directivity emitting by the angle-beam wedge actuators in the thin-walled structures made of plastic materials and polymeric composites. Our investigation includes the dispersive analysis of the waves that can be excited in the studied plastic panel. Its results allowed to find two kinds of the generated acoustic waves - anti-symmetric Lamb waves A0 and shear horizontally polarized SH waves SS0. The bounds of the chosen frequency range for the experimental and numerical studies were accepted as a compromise between the desire to obtain high defects resolution by generating short waves, their adjustable directivity and maximum propagation length. The finite element model for the transducer was built by using the results of actuator structure experimental study. The frequency response functions for the actuator current and oscillation amplitude of the footprint surface demonstrated good agreement. The found eigenfrequencies of actuator's structure were used for the numerical and experimental study of the Lamb and SH wave generation and propagation in a thin-walled plastic panel. Our results convincingly demonstrated the satisfactory directivity of the actuated waves at their excitation on the frequencies that corresponded to the natural modes of the actuator oscillation. The authors assume that an efficient use of the proposed technique for other analyzed quasi-isotropic materials and applied actuators can be provided by a preliminary research using the similar approach and methods presented in this article.

As shown earlier, the algorithmic complexity, like Shannon information and Boltzmann entropy, tends to increase in accordance with the general law of complification. However, the algorithmic complexity of most material systems does not reach its maximum, i.e. chaotic state, due to the various laws of nature that create certain structures. The complexity of such structures is very different from the algorithmic complexity, and we intuitively feel that its maximal value should be somewhere between order and chaos. I propose a formula for calculation such structural complexity, which can be called - structuredness. The structuredness of any material system is determined by structures of three main types: stable, dissipative, and post-dissipative. The latter are defined as stable structures created by dissipative ones, directly or indirectly. Post-dissipative structures, as well as stable, can exist for an unlimited time, but at the micro level only, without energy influx. The appearance of such structures leads to the “ratchet” process, which determines the structuregenesis in non-living and, especially, in living systems. This process allows systems with post-dissipative structures to develop in the direction of maximum structuring due to the gradual accumulation of these structures, even when such structuring contradicts the general law of complification.

In this study, a novel porous geopolymer mortar (GP) was produced and tested experimentally. Industrial waste materials/by-products were used as constituents of the GP, along with dune sand. One sample was produced as a control sample for benchmarking. For the rest of the samples, 15%, 30%, and 45% by volume, the solid constituents were replaced with expanded polystyrene foam (EPS) beads. These mortar samples were heat cured to depolymerize the EPS to cause porosity inside the samples. Indoor experiments were conducted to evaluate the response of produced porous GP to high heat flux. The porous samples were able to reduce heat transmission across the opposite surfaces. Induced porosity resulted in a decrement in compressive strength from 77.2 MPa for the control sample to 15.8 MPa for 45% porous sample. However, the limit lies within the standards for partitioning walls in buildings and pavements in urban areas to absorb rainwater.

Accumulating reports have suggested that an inability to clear dead cells is a cause of inflammation and cancer and that the fascia is associated with cancer metastasis. Novel corpuscle-connected filiform structures (CCFSs) entangled on the fascia of the internal organs of rats were selectively visualized with high repeatability (93%) under vital staining with Janus Green B (JGB). Serial sections of CCFSs stained with haematoxylin and eosin and with Mattson Trichrome were microscopically examined. In parallel, the immunohistochemistry with CD31, Lyve 1, scanning electron microscopy, and transmission electron microscopy (TEM) were also used to investigate the novel properties of the CCFSs. All of the CCFSs enclosed JGB-stained granules, which was verified by the impromptu coupling of stereo and light microscopes and fluorescence-activated cell sorting. The functions of the CCFSs were discovered under fluorescence microscopy and confocal laser scanning microscopy to be implicated in cell death: fragmented DNAs and f-actins with extracellular DNAs. The dead cells in the CCFSs were verified by using terminal deoxynucleotidyl transferase dUTP nick end labelling and TEM. Moreover, the CCFS had a relatively-high concentration of calcium, a main element for cell death in tissue, which was measured in 2-dimensionally images using time-of-flight secondary ion mass spectrometry. Taken these results, we report for the first time that novel reticular CCFSs are widely entangled on the fascia of the internal organs of rats with the implication for cell death.

Geopolymer, as a new type of solid waste-based inorganic cementitious material, exhibits outstanding Behavior in terms of physical and chemical performance, macro-mechanical properties and long-lasting stability, and features potential application development tendency in the field of repair and reinforcement of existing concrete structures. This paper investigates the interfacial Behavior of geopolymer mortar with OPC concrete substrate under different slag, fly ash and red mud mixing proportions, while cement mortar was used as a control group for the research. The interfacial bonding properties of the geopolymer mortar to the OPC concrete substrate were elaborated by carrying out split tensile test, two-sided shear test and three-point bending test. The scanning electron microscopy (SEM) and X-ray diffraction (XRD) were employed to further analyse the microstructural characteristics and physical phase components of the interfacial transition zone between the geopolymer mortar and the OPC concrete substrate. The results indicated that the compressive strength of slag-fly ash-red mud-based geopolymer mortar under different mixing ratio conditions was consistently superior to that of cement mortar. Overall, the interfacial bonding properties of the geopolymer mortar to the OPC concrete substrate gradually increased with the increment of the slag content, however, an evolutionary trend of minor enhancement followed by a gradual reduction was observed with the growth of the fly ash and red mud content.

This article introduces simulations of theoretical material with controlled properties for the evaluation of the effect of key parameters, as volumetric fractions, elastic properties of each phase and transition zone on the effective dynamic elastic modulus (Ed). The accuracy level of classical homogenization models was checked regarding the prediction of Ed. Numerical simulations were performed with finite element method (FEM) for evaluations of the natural frequencies and their correlation with Ed, through frequency equations. An acoustic test validated the numerical results and obtained the elastic modulus of concretes and mortars at 0.3, 0.5 and 0.7 water-cement ratios (w/c). Hirsch calibrated according to the numerical simulation (x = 0.27) exhibited a realistic behavior for concretes of w/c = 0.3 and 0.5, with 5% error. Nevertheless, for w/c = 0.7, Ed approached Reuss model, similarly to theoretical triphasic materials. Hashin-Shtrikman bounds is not perfectly applied to theoretical biphasic materials under dynamic situations.

Abstract: During firing from a mortar, an important issue is the parameters of compressibility of the ground on which the mortar is placed. This affects the operation of the mortar (including safety). During the qualification tests of the mortar, the influence of different types of substrate on its strength and work during shooting should be examined. Until now in the Polish standardization documents was no clear description about the substrate parameters used for this kind of tests. Analysis of the literature also did not allow to determine the dependence of the mortars displacement in the function of the type of substrate and its geotechnical parameters. Therefore, the authors carried out analytical and experimental analysis of the use of geotechnical methods to determine the parameters of the substrate for mortar testing. The paper presents the proposed types of standardized soil and their research methods. Preliminary tests were also carried out using the prescribed measurement methods and a comparative mortar firing test. Subsequently, an analysis of the results was carried out and the possibilities of using the proposed methods of measuring the parameters of soil compressibility were determined.

This paper is referred to a top frontline research in life science, showing that in spite of the large variation of the physiological architecture and behavioral forms of the living systems, the fundamental structure of their informational system is basically the same, allowing the body growth/development by micro to macro-structuration processes, maintaining the same informational configuration and functions like the basic unit of life – the eukaryotic cell. Starting and based on the determination of the special/specific info-operability in living structures and the role of information in structuration and their functionality, there are discussed the informational functions of the eukaryotic/prokaryotic cells, the simplest units of life and is elaborated and presented the Informational Model of the Living Structures, showing that these structures operate on the basis of two main informational systems: one of them defined as the Programmed Informational System, composed by three components, assuring respectively the info-generation, maintenance and the proliferation/reproduction, and another one defined as the Operative Informational System, necessary for the continuous communication with the environment for adaptation, consisting in four main components referred to memory, decision, sentience and info-connection/info-selection. The revealed properties are compared with the Informational System of the Human Body, as a prototype of a living system on the top of the evolutionary scale, showing/demonstrating the compatibility of structuration and functions on the entire scale, from prokaryotic/eukaryotic unit cells to multicellular organisms – plants, animals and human, by means of a continuous adaptation process, which always follows the same line of micro to macro-structuration process based on the same Info-organization and functionality. These models are new and revolutionary in the information and life sciences

A multiscale model that enables quantitative understanding and prediction of the size effect on scattering properties of micro- and nanostructures is crucial for the design of LED surface textures optimized for high light extraction efficiency (LEE). In this paper, a hybrid process for combining full-wave finite-difference time-domain simulation and a ray-tracing technique based on a bidirectional scattering distribution function model is proposed. We apply this method to study the influence of different pattern sizes of a patterned sapphire substrate on GaN-based LED light extraction from the microscale to the nanoscale. The results show that near-wavelength–scaled patterns with strong diffraction are not expected to enhance LEE. By contrast, microscaled patterns with optical diffusion behavior have the highest LEE at a specific aspect ratio, and subwavelength-scaled patterns that have antireflection properties show marked enhancement of LEE for a wide range of aspect ratios.

The delineation of the clinical target volumes (CTVs) for radiation therapy is time-consuming, requires intensive training and shows high inter-observer variability. Supervised deep learning methods depend heavily on consistent training data, thus state-of-the-art research focuses on making CTV labels more homogeneous and strictly bounding them to current standards. International consensus expert guidelines standardize CTV delineation by conditioning the extension of the clinical target volume on surrounding anatomical structures. Training strategies that directly following the construction rules given in the expert guidelines or the possibility to quantify the conformance of manually drawn contours with the guidelines are still missing. 71 anatomical structures that are relevant for CTV delineation in head and neck cancer patients according to the expert guidelines were segmented on 104 CT scans to assess the possibility to automate their segmentation by state-of-the-art deep learning methods. nnU-Net models were trained to automatically segment those 71 structures on planning CT scans. We report the DICE, HD and sDICE for 71 + 5 anatomical structures for most of which no previous segmentation accuracies have been reported. For those structures, for that prediction values have been reported, our segmentation accuracy matched or exceeded the reported values. The predictions from our models were always better than those predicted by the TotalSegmentator. The sDICE with 2mm margin was larger than 80% for almost all structures. Individual structures with decreased segmentation accuracy are analyzed and discussed with respect to their impact on the CTV delineation following the expert guidelines. No deviation is expected to affect the rule-based automation of the CTV delineation.

This comprehensive review paper provides a detailed analysis of the extraction methods employed in the dimension stone industry. Natural rock materials used in construction, have been historically extracted using primitive techniques such as thermal shock, hammer and chisel, and plug and feather. However, significant technological advancements have revolutionized the industry, leading to the widespread adoption of mechanized methods. One highly efficient technique is diamond wire cutting, which involves the utilization of diamond-engraved bits affixed to a tensioned steel wire. This method has demonstrated remarkable capabilities in minimizing waste generation and ensuring exceptional machining quality. Nonetheless, challenges such as high operating costs and wire breakage persist and require further investigation. In addition to diamond wire cutting, this review explores the utilization of circular diamond saws and frame sawing as alternative extraction methods. The geotechnical characteristics of the stone play a critical role in the selection of appropriate machinery, and researchers worldwide have conducted numerous studies to investigate the impact of each parameter on the extraction efficiency of these mechanized techniques. Moreover, controlled blasting with explosives emerges as a promising alternative for dimension stone extraction, warranting further exploration and optimization.

Repair mortar is commonly used to rehabilitate reinforced concrete structures or components that exhibit a relatively high level of distresses. Yet, this repair mortar can be contaminated by salt from its service environment. This work employs a two-dimensional finite element model to investigate the transport behavior of ionic species in salt-contaminated and water-saturated repair mortar under an externally applied electric field. The model was experimentally validated and then utilized to evaluate the effectiveness of electrochemical chloride extraction (ECE) with or without electrical injection of corrosion inhibitor (EICI). In the case study, both the ECE alone and the ECE+EICI treatment was found effective in decontaminating the zone in front of the steel rebar. In both techniques, the magnitude of current density has a significant effect on removing chloride out of the mortar and increasing the pH of the pore solution near the rebar, whereas the treatment time any not have a significant effect under some scenarios. The injection of the organic corrosion inhibitor significantly slowed down the removal of chloride. Changes in the ionic distribution in the mortar were generally beneficial in reducing the corrosion risk of the steel rebar and thus extending the service life of the repair mortar.

The present paper deals with an improvement of the strengthening technique consisting in the combined use of straps—made of stainless steel ribbons—and CFRP strips, to increase the out-of-plane strength of masonry walls. The straps of both the previous and the new combined technique pass from one face to the opposite face of the masonry wall through some holes made along the thickness, giving rise to a three-dimensional net of loop-shaped straps, closed on themselves. The new technique replaces the stainless steel ribbons with steel wire ropes, which form closed loops around the masonry units and the CFRP strips as in the previous technique. A turnbuckle for each steel wire rope allows the closure of the loops and provides the desired pre-tension to the straps. The mechanical coupling—given by the frictional forces—between the straps and the CFRP strips placed on the two faces of the masonry wall gives rise to an I-beam behavior of the facing CFRP strips, which begin to resist the load as if they were the two flanges of the same I-beam. Even the previous combined technique exploits the ideal I-beam mechanism, but the greater stiffness of the steel wire ropes compared to the stiffness of the steel ribbons makes the constraint between the facing CFRP strips stiffer. This gives the reinforced structural element greater stiffness and delamination load. In particular, the experimental results show that the maximum load achievable with the second combined technique is much greater than the maximum load provided by the CFRP strips. Even the ultimate displacement turns out to be increased, allowing us to state that the second combined technique improves both strength and ductility. Since the CFRP strips of the combined technique run along the vertical direction of the wall, the ideal I-beam mechanism is particularly useful to counteract the hammering actions provided by the floors on the perimeter walls, during an earthquake. Lastly, after the building went out of service, the box-type behavior offered by the three-dimensional net of straps prevents the building from collapsing, acting as a device for safeguarding life.

Recently many researches of EOS (Electric Arc Furnace Oxidizing Slag) on application to construction industry have been carried out with increasing its production and limited reclamation site. EOS can be used as a fine aggregate for construction material, however, its engineering properties vary with the manufacturing process and producing district, causing a quality differences in material performance. In the work, EOS is obtained from steel manufacturing plants in South Korea and the engineering properties are evaluated for EOS and the cement mortar with EOS, respectively. From the tests, EOS is mainly made up of CaO, SiO₂, and FeO with 18.2% of larnite which has a crystal structure of β-C₂S with similar cement mineral. EOS mortar shows an increasing compressive strength with more EOS content, which is affected by a considerable amount of larnite (β-C2S) in EOS. The EOS based mortar with ERS (Electric Arc Furnace Reduction Slag) shows unsatisfactory results over the criteria for rate of change, which implies that more consideration must be taken for the usage of the mixed ERS and EOS for cement mortar due to swelling effect of ERS on dimensional stability.

Considering Cu(tda) chelate is a receptor for adenine and related 6-aminopurines, now we report the synthesis, molecular and crystal structures, thermal stability, spectral properties and DFT calculations on the [Cu(tda)(9heade)(H2O)]•2H2O (1). N7 is found to be the preferred donor atom of 9heade, that can favor the cooperation of a Cu-N7(9heade) bond and an (9heade)N6-H•••O(tda) interligand interaction. But unprecedentedly, the Cu(tda)-9heade molecular recognition in 1 is essentially featured the Cu-N1(9heade), without any N6-H•••O(carboxyl tda) interligand interaction. Nevertheless, being N1 the most basic donor for N9-substituted adenines, this Cu-N1 bond is now assisted by an O2-water mediated interaction (N6-H•••O2 and O2•••Cu weak contact). Also in the crystal packing, the O-H(ol) of 9heade interacts with its own adenine moiety by an O3-water mediated interaction (O(ol)-H•••O3 plus O3-H36•••π(adenine moiety). In turn these water-mediated interactions seems to be responsible to serious alterations on the physical properties of crystalline or grounded samples. Density functional theory calculations were used to evaluate the interactions energetically. Moreover, the quantum theory of atoms-in-molecules (QTAIM) in combination with the noncovalent interaction plot (NCIPlot) were used to analyze the interactions and rationalize the existence and relative importance of hydrogen bonding, chalcogen bonding and π-stacking interactions.

The rock joint fissure slope in cold regions is prone to deformation and failure problems such as relaxation, tension and collapse under freeze-thaw (F-T) cycles. Based on the ideology of clean production and promoting the structural integrity of geotechnical projects in cold areas, this study designed and prepared aeolian-sand (AS) to replace part of river sand as a filling mortar material by taking advantage of the low cost and easy availability of AS. Investigations were carried out to determine the impact of varying proportions of AS in mortar on the microstructure and shear properties of the mortar-rock interface under F-T cycles. Therefore, F-T cycle testing, nuclear magnetic resonance (NMR) testing and shear testing were carried out on grout with different proportions of AS. The results show that the right proportion of AS replacement could enhance the shear deformation resistance and F-T resistance of the mortar-rock interface, and 30% proportion is the optimal proportion. By increasing of F-T cycles, the three types of specimens showed different degrees of particle spalling, shedding and cracking. The slurry-rock interface layer in the A (0%) group exhibited the most severe F-T deterioration, while the B (15%) group showed a lesser degree, and the C (30%) group performed the best. T2 spectrum curve and total spectrum area change law from the microscopic point of view to verify the 30% AS proportion mortar-rock interface F-T resistance is the strongest, followed by 15% AS proportion mortar, the weakest is ordinary mortar. The degradation of the mortar-rock bond is primarily due to the conversion of solid to liquid phases and the movement of internal water caused by fluctuating temperatures. The extent of F-T deterioration in the slurry-rock interface layer is greatly affected by the varying proportions of AS. The shear strength and shear stiffness of specific proportion of AS decreased with the increase of F-T cycles. For same F-T cycles, the shear strength and shear stiffness of group C (30%) were the highest, followed by group B (15%) and group A (0%). The grout material not only reinforces the F-T joint fissure slope, but also reduces the cost of grout reinforcement and promotes the clean production of geotechnical structures.

In Geo Polymer bricks (GPB), fly ash content which is a waste from power plants is converted into bricks by chemical treatment. GPB can be dried by using appropriate curing methods. Conven-tionally electric oven curing is one of the prominent methods. Using solar dryer instead of elec-trical oven gives added advantage of saving high grade electrical energy. So in this work solar dryer with PCM (Phase Change materials) Paraffin Wax and without PCM is used for curing ap-plication. GPB are gaining added advantage when compared to conventional bricks like cement and sand bricks in terms of strength. GPB has been taken as specimen for comparing the com-pressive, tensile split strength and flexural strength by electrical energy based curing and solar energy based curing. It is experimentally observed that solar energy based curing with PCM and without PCM exhibits higher compressive strength, higher tensile split strength and flexural strength when compared to electrical energy based curing. Solar curing with PCM shows higher compressive strength, higher tensile split strength and flexural strength when compared to Solar curing without PCM. Open solar curing is a traditional technique but nowadays aggressive cli-matic conditions can lead to severe damage of Geo polymers. The novelty of this work is to suggest to study the effect of PCM like paraffin wax in solar drying on curing time, mechanical properties of GPB.

The area of Central and Eastern Europe, and thus Poland, is not exposed to effects of seismic actions. Any possible tremors can be caused by coal or copper mining. Wind, rheological effects, the impact of other objects or a non-uniform substrate are the predominant types of loading included in calculations for stiffening walls. The majority of buildings in Poland, as in most other European countries, are low, medium-high brick buildings. Some traditional materials, like solid brick (>10% of construction materials market) are still used. But autoclaved aerated concrete (AAC) and cement-sand calcium-silicate (Ca-Si) elements with thin joints are prevailing (>70% of the market) on the Polish market. Adding reinforcement only to bed joints in a wall is a satisfactory solution (in addition to confining) for seismic actions occurring in Poland that improves ULS and SLS. This paper presents results from our own tests on testing horizontal shear walls without reinforcement and with different types of reinforcement. This discussion includes 51 walls made of solid brick (CB) reinforced with steel bars and steel trusses, results from tests on 15 walls made of calcium-silicate (Ca-Si) and AAC masonry units reinforced with steel trusses and plastic meshes. Taking into account our own tests and those conducted by other authors, empirical relationships were determined on the basis of more than 90 walls. They are applicable to design and construction phase to determine the likely effect of reinforcement on cracking stress that damage shear deformation and wall stiffness.

This paper presents a theoretical analysis of an International conflict, i.e. East Pakistan Crisis, 1971, and reveals that unequal development creates conflict in society. Natural resource scarcity and environmental degradation can also become a source of conflict, so marginalised and excluded people fight for their rights through non-peaceful means. This essay supports the theoretical approaches of poverty, environment, and conflict nexus and reveals that unequal development and resource scarcity deepens the poverty and creates conflicts in the society, causing harm to the environment. The degraded environment increases the poverty as environment and poverty are interlinked, and the poor have limited choices other than to degrade the environment for their survival. This vicious downward spiral link between poverty and degradation of the environment requires working extensively for poverty alleviation to reverse the environmental decline.

This paper reinterprets, differently from the existing literature, the relationship between law and economics not from the point of view of a lawyer-economist but rather from the point of view of an economist-mathematician, and it raises a methodological issue. To do so, some of the elements of the theory of sets are borrowed to argue that behavioral economics, its application to behavioral law and economics, and behavioral economists have generalized the pioneering work of Judge Calabresi, with reference to the famous books ‘Tragic Choices’ and ‘The Future of Law and Economics – Essays in Reform and Recollection’. Even if the usage of the theory of sets made in this paper is intuitive, some of its basics are reviewed in the appendix.

Ethylene, a gaseous phytohormone, is emerging as a central player in the intricate web of plant developmental processes from germination to senescence under optimal and stressed conditions. It is present in different plant parts, encompassing the stems, leaves, flowers, roots, seeds, and fruits. This review aims to provide a comprehensive overview of ethylene's fascinating roles in shaping various plant growth and adaptation aspects. It intricately examines the multifaceted impact of ethylene on pivotal aspects of plant development, including but not limited to cell division and elongation, senescence, abscission, fruit and flower development, root hair formation, chloroplast maturation, and photosynthesis. This comprehensive assessment encompasses the intricate pathways of ethylene biosynthesis and signaling, providing a snapshot of the regulatory mechanisms governing ethylene production. Understanding ethylene's multifaceted functions has significant implications for agriculture, biotechnology, and our fundamental comprehension of plant biology. This review underscores the need for continued investigation into ethylene's intricate mechanisms and its potential to revolutionize plant development and crop management.

Satisfactory weatherproofing of buildings is vital to maximise their design life and performance which requires the careful design of external sealing technologies. Systems commonly available have served well in conventional construction however with many prefabricated systems emerging in the building industry new and novel means of weatherproofing between panels and modules need to be developed purpose specific to this application. This paper presents a holistic and fundamental methodological approach to Design and Development of waterproof seals and has been applied specific for prefabricated panelised and modular systems. Two purpose specific weatherproof seals are finally presented. Flow charts of the overview of the suggested methodological approach and the processes within which include DfMA that have been incorporated into understanding and developing seals for this practical application. These strategies have enabled a resourceful and holistic set of processes that can be adapted and used for similar forms of product research in new and developing areas of construction such as prefabrication. The design and development process is thoroughly explored and has resulted in an exploration of the technical challenges and potential solutions which take into consideration factors from installation limitations to building tolerances.

We study on the sums of powers of consequtive integers and alternating sums of power of consequtive integers. We derive many identities and correlations including Bernoulli, Euler and Genocchi polynomials and numbers.

The difficult current environmental situation, caused by construction industry residues containing ceramic materials could be improved by using these materials as recycled aggregates in mortars, with their processing causing a reduction in their use in landfill, contributing to recycling and also minimizing the consumption of virgin materials. Although some research is currently being carried out into recycled mortars, little is known about their stress-strain (σ-ε); therefore this work will provide the experimental results obtained from recycled mortars with recycled ceramic aggregates (with contents of 0, 10, 20, 30, 50 and 100%), such as: the density, the compression strength, as well as the σ-ε curves representative of their behavior. The values obtained from the analysis process of the results are those of: σ (elastic ranges and failure maximum), ε (elastic ranges and failure maximum), and Resilience and Toughness; in order to finally obtain, through numerical analysis, the equations to predict their behavior (related to their recycled content). At the end of the investigation it is established that mortars with recycled ceramic aggregate contents of up to 20% could be assimilated just like mortars with the usual aggregates, and the prediction equations produced could be used in cases of similar applications.

Introduction: Since its discovery in late 2019, the novel coronavirus (SARSCOVID-2) that causes COVID-19 has spread fast, prompting the World Health Organization (WHO) to designate the disease a worldwide pandemic on March 11, 2020.The epidemic has profoundly altered the preexisting global sexual and reproductive health landscape .The virus’s load has put ordinary services in jeopardy and harmed other health priorities. This encompasses both the provision and the supply of contraceptives, sexual health, new born and maternal health services. This Scoping review therefore mapped the availability evidence on the impact and effects of the COVID-19 disease outbreak on sexual and reproductive health. Methods: The methodological framework by Arksey and O’Malley guided this scoping review. A literature search was conducted from the following databases: Embase, PubMed, CINAHL, Scopus, WOS, and AJOL. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram and the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) checklist were used to document the review process. The Strobe critical review checklist was used to determine the quality of the included studies. Results:19 studies were reviewed, out of which 4 were cross sectional studies, 1 was an observational study, 1 was a descriptive analytical study and the rest were qualitative studies .Majority of the studies showed evidence on the impact of COVID-19 and family planning service, maternal and child services, and three studies reported on COVID-19 and sexual behaviour. Five of the nineteen included studies reported on the impact of COVID-19 and family planning service. Conclusion: This scoping review has granted the assessment of the impact of novel SARS-CoV-2 on Sexual and reproductive health services with regards to sexual behaviour, family planning and maternal, neonatal and child health. From the 18 articles identified and reviewed, the overall responses stipulated a significant reduction in client’s utilization of services due to challenges experiences in service implementation such as stock outs. In addition, low demand for reproductive health services by clients due to restrictions imposed on the movements of people to curb the spread of the virus. It is therefore important that Governments and relevant stakeholders in Maternal and Sexual Reproductive Health prioritize development of policies and practices that protect women from the impacts of the pandemic. Furthermore, regular audits to detect trends in MSRH are necessary to inform on going mitigation efforts.

This paper analyzes the political and economic changes in the world after the drastic changes in eastern Europe, starting with Chinese President Xi Jinping's viewpoint "the biggest change in a century". Also, the new international situation and new development in the post-epidemic as well as the development path and direction of China in the post-epidemicera are expected.

The objective of this study is to determine the impact of COVID-19 on the performance of Pakistani Stock Market. This study uses the data of COVID-19 related positive cases, fatalities, recovers and the closing prices of PSX 100 index of the first half of 2020. The findings of the study suggest that only COVID-19 recoveries are influencing the performance of the index and the daily positive cases and fatalities are insignificantly related to the performance. Further studies can be performed by incorporating other variables such as economic growth, interest rate and inflation rate along with the COVID-19 related variables at a cross-country level.

Biomolecular structure drives function, and computational capabilities have progressed such that the prediction and computational design of biomolecular structures is increasingly feasible. Because computational biophysics attracts students from many different backgrounds and with different levels of resources, teaching the subject can be challenging. One strategy to teach diverse learners is with interactive multimedia material that promotes self-paced, active learning. We have created a hands-on education strategy with a set of fifteen modules that teach topics in biomolecular structure and design, from fundamentals of conformational sampling and energy evaluation to applications like protein docking, antibody design, and RNA structure prediction. Our modules are based on PyRosetta, a Python library that encapsulates all computational modules and methods in the Rosetta software package. The workshop-style modules are implemented as Jupyter Notebooks that can be executed in the Google Colaboratory, allowing learners access with just a web browser. The digital format of Jupyter Notebooks allows us to embed images, molecular visualization movies, and interactive coding exercises. This multimodal approach may better reach students from different disciplines and experience levels as well as attract more researchers from smaller labs and cognate backgrounds to leverage PyRosetta in their science and engineering research. All materials are freely available at https://github.com/RosettaCommons/PyRosetta.notebooks.

To better understand how immunity develops against SARS-CoV-2 during the pandemic period of 2020 to 2022, we analyzed the immune response of a small group of university staff and students who were either infected or vaccinated. We investigated the levels of receptor-binding domain (RBD)-specific and nucleocapsid (N)-specific IgG and IgA antibodies in serum and saliva samples taken early (around 10 days after infection or vaccination) and later (around 1 month later), as well as N-specific T-cell responses. One patient who had been infected in 2020 developed serum RBD and N-specific IgG antibodies, but declined 8 months later, then mRNA vaccination in 2021 produced a higher level of anti-RBD IgG than natural infection. In the vaccination of naïve individuals, vaccines induced anti-RBD IgG, but it declined after 6 months. A third vaccination boosted the IgG level again, albeit to a lower level than after the second. In 2022, when the Omicron variant became dominant, familial transmission occurred even among vaccinated people. In infected individuals, the levels of serum anti-RBD IgG antibodies increased later, while anti-N IgG peaked earlier. The N-specific activated T cells expressing IFN- or CD107a were detected early. In saliva, SARS-CoV-2-specific IgG but not IgA was detected. Interestingly, two individuals showed a temporary peak in RBD- and N-specific IgA antibodies in their saliva on the second day after infection. Thus, SARS-CoV-2 infection triggers typical immune responses in humans against acute viral infections, but mucosal immune responses, which are temporarily induced early during infection, may be more important for protection than current intramuscular vaccines.

The determinants of enterprises providing ICT training in Europe are analyzed in this article. Data are collected from the European Innovation Scoreboard-EIS of the European Commission for 36 European countries in the period 2000-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. Results show that the number of enterprises providing ICT training in Europe is positively associate with “Innovation Index”, “Innovators”, “New Doctorate Graduates”, “Tertiary Education” and negatively associated with “Government Procurement of Advanced Technology Products”, “Human Resources”, and “Marketing or Organisational Innovators”. In adjunct a cluster analysis is performed by using k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of four clusters. Finally, we use eight different machine learning algorithms to predict the value of the enterprises providing ICT training in Europe. We found that the Simple Tree Regression is the best predictor and that the number of enterprises providing ICT training in Europe is expected to growth of the 5,02%.

Prefabricated forms of construction have led to the rapid onsite assembly of buildings however there are still on-site tasks and processes which can be reevaluated and redone specifically in keeping with the principles of prefabrication instead being adapted to fit its purpose. One such process is that of waterproofing between prefabricated panels and modules which come from the factory fully complete façade and all. Conventional means of waterproofing can be used however it results in more work done on site, potential delays and generally requires access from the external face of the building. This paper presents the Modelling, Implementation and Evaluation of purpose developed weatherproof seals specific for Prefabricated Construction. An overview is provided of the entire development process and specific focus is given to the modeling using FEA computer simulations, manufacturing and testing which then resulted in the implementation in a prefabricated panelised building which is used as a case study and the means of further evaluation. These strategies have enabled an efficient and robust prefabricated waterproofing solution specific for this form of construction to be understood and implemented. The resulting case study has successfully verified the time and cost savings when compared to conventional techniques whilst still providing a durable and effective weatherproof seal for prefabricated panelised and modular systems.

Coating of suitable materials having thickness of few atoms to several microns on a substrate is of great interest to the scientific community. Hard coatings develop under the significant composition of suitable-natured atoms where their force-energy behaviors when in certain transition state favour binding. In the binding mechanism of suitable atoms, electron belonging to outer ring filled state of gas-atom undertakes another clamp of energy knot belonging to outer ring unfilled state of solid-atom. Set process conditions develop the binding of different-natured atoms when processing their suitable composition in a system. Atoms of different nature develop structure in the form of hard coating by locating their ground points between the original ones. Here, gas-natured atoms increase the potential energy under decreasing levitational force of electrons, whereas, solid-natured atoms decrease the potential energy under decreasing gravitational force of electrons. In TiN coating, Ti–Ti atoms bind under the difference of expansion of their lattices, called nets of energy knots, where one atom just lands on the already landed atom. An adhered N-atom to a Ti-atom forms its position among four Ti-atoms where N-atom occupies the interstitial site of Ti-atoms. Two oppositely working force-energy behavior atoms deposit in the form of coating at substrate surface as per set conditions of the process. The rate of ejecting (or dissociating) solid-natured atoms depend on the nature of their source (target), process parameters and processing technique. In random arc-based vapor deposition system, depositing differently natured atoms at substrate surface depends on the input power. In addition to intrinsic nature of atoms, different properties and characteristics of coatings emerge as per engaged forces under their involved energy. The present study sets new trends in the field of coatings involving the diversified class of materials and their counterparts.

Employing data supplied by the Oxford-based UK Childhood Cancer Research Group in 2003 it is shown that after the Chernobyl accident, childhood leukemia by single age and year of birth in the 0-4y cohort increased significantly in Wales and Scotland combined in the period 1986-1990 compared with controls born 1970-1985 and 1991-1994. Relative risk RR = 1.41; 95% CI 1.20<RR<1.65; p = 0.00004. These exposure periods were chosen because whole body Caesium-137 monitoring had demonstrated that internal exposures persisted for more than 4 years. The dose-response exhibits saturation and reversal, interpreted as biological censoring effects in the developing individual.

This paper presents a two-way factor design incorporating both spatial and temporal variation in the prediction of COVID 19 in Africa. In line with this, the impact of COVID-19on the GDP in Africa is well scrutinized. In contrast to the existing works [1–3], this work also extends the two-factor design into the one-way factor design through incorporating covariates into spatial effects. The data rely on the spatial and temporal obtained from WHO datasets [4, 5]. The one-factor design with more covariates is taken into consideration to identify the major potential predictor variables responsible for the deaths and confirmed cases due to COVID 19 in Africa. The MANCOVA considered population density, temperature, humidity; perception, and wind are all considered as co-variates. Simulations show that the two-way analysis of variance has shown that there is a statistically significant difference between the spatial (Fcal= 8.2704, Pvalue= 3.099∗10−6)and temporal (Fcal= 48.7964, Pvalue= 9.147∗10−16) effects. South Africa and Nigeria are highly influencing due to the pandemic where their GDP also relatively mostly declined. A significant economic change is observed before the pandemic and after the outbreak of the pandemic(tcal= 2.9548, Pvalue= 0.01805). COVID 19 negatively influenced the economy of1 most of the African countries. The population density, temperature, and wind are found to be statistically significantly associated with COVID 19 cases and deaths.

Textile and clothing is one of the most important industrial sectors, not only due to the significant number of jobs generated, but also because it addresses one of the people’s fundamental needs (clothing). It is, however, a sector with a huge environmental impact, all over the world, and also an important social impact, especially in developing countries. Sustainability in the Textile &amp; Clothing value chain is a known issue, concerning both environmental, and economical-social facets of sustainability. One way to improve sustainability in this sector is by measuring the environmental, economic and social impacts of value chain activities and, ultimately, computing an Environmental and Circular score for each batch of textile and clothing product, and an Economical and Social score for each involved firm, reflected in their products. The consumer will then have the opportunity and responsibility for selecting products with the least negative environmental, economical and social impact. This article presents the results of STVgoDigital project - PPS1, developed in Portugal with the aim of implementing the traceability of textile and clothing products, boosting sustainability in this sector, and preparing the ground for the implementation of the circular economy. More exactly, a blockchain-based textile and clothing value-chain traceability platform is presented, for tracing textile product lots and activities, along the value chain, classifying them with a score, which measures their environmental and social impact. The environmental, economic and social impact scores are based on a set of proposed indicators. The results are assessed through the presentation of a case study of a face towel (home textile) and a case study of a T-shirt (clothing).

Identification of Dengue drivers is crucial for pro-active prevention strategies. In semi-arid regions, the relationship between meteorological variables, particularly rainfall, and the dengue vector is complex. This study analyzes associations between the number of dengue cases and rainfall categories in six semi-arid locations in India. Focusing on official website data, we find significant correlations only with heavy rainfall (R>10 mm/day). The findings underscore the importance of heavy rainfall in Dengue incidence and offer insights for pro-active prevention. The study methodology involves rainfall and dengue occurrence over Indian region. This research contributes to the growing body of knowledge on Dengue prevention, emphasizing the need for targeted interventions during periods of heavy rainfall.

Political and legal debate about freedom of religion and belief (FoRB) in Australia has intensified since the Same-sex marriage postal survey in 2017. Central to this debate has been children, their parents and institutions (Schools). This paper outlines the place of children in the Australian FoRB since 2017, focusing on the Same-sex marriage postal survey debate and subsequent reviews into freedom of religion. In particular it highlights the links drawn between same-sex marriage or marriage equality and the Safe School Coalition Australia campaign, the emphasis on parental rights in relation to education about marriage in schools and the ongoing debate about potential reform to Australia’s suit of anti-discrimination laws

Orthogonal operators can successfully be used to calculate eigenvalues and eigenvector compositions in complex spectra. Orthogonality ensures least correlation between the operators and thereby more stability in the fit, even for small interactions. The resulting eigenvectors are used to transform the pure transition matrix into realistic intermediate coupling transition probabilities. Calculated transition probabilities for close lying levels illustrate the power of the complete orthogonal operator approach.

Epistemological naturalism dismisses the notion that epistemology is a basis for the empirical sciences. In particular, it rejects the demand for a general justification of induction. Making inductive generalisations is a basic habit among humans. There is no such thing as a logic of inductive inference. The role of induction in science is heuristic; it is our way of inventing new theoretical predicates and developing theories. We discover new laws by applying inductive thinking; but this is not any kind of inference which can be evaluated as more or less rational.

Background: This research examines how market knowledge and artificial intelligence (AI) interact in different market designs such as business-to-business (B2B) settings while taking emerging technologies and the changing digitalization landscape into account. Objective: The main goal is to understand how AI affects market knowledge in different market designs such as business-to-business (B2B) contexts, taking into account language barriers, practical difficulties, and the revolutionary effects on decision-making and customer interactions. Result: They underscore the transformative potential of artificial intelligence (AI) by highlighting how it shapes market knowledge, encourages customized approaches, and improves marketing efficacy in the business-to-business (B2B) space. Conclusion: In order to create a path for responsible AI integration in B2B marketing, the study concludes with recommendations for standardized terminology related to AI, practical insights into implementation challenges, and ethical issues.

The concept of {\it quantum ratio} emerged in the recent efforts to understand how Newton's equations appear for the center of mass (CM) of an isolated macroscopic body at finite body-temperatures, as the first approximation to quantum-mechanical equations. It is defined as $Q\equiv R_q/L_0$, where the quantum fluctuation range $R_q$ is the spatial extension of the pure-state CM wave function, whereas $L_0$ stands for the body's linear size (the space support of the internal, bound-state wave function). The two cases $R_q /L_0 \lesssim 1$ or $R_q/ L_0 \gg 1$, roughly correspond to the body's CM behaving classically or quantum mechanically, respectively. In the present note we elaborate more on this concept, illustrating it in several examples. An important notion following from introduction of the quantum ratio is that the elementary particles (thus the electron and the photon) are quantum mechanical, even when the environment-induced decoherence turns them into a mixed state. Decoherence and classical state should not be identified. This simple observation, further illustrationed by the consideration of a few atomic or molecular processes, may have significant implications on the way quantum mechanics works in biological systems.

The use of artificial intelligence (AI) is becoming more prevalent across industries as diverse as healthcare, finance, and transportation. Artificial intelligence is based on the analysis of large data sets and requires a continuous supply of high-quality data. However, using data for AI is not without its challenges. This paper comprehensively reviews and critically examine the challenges of using data for AI, including data quality, data volume, privacy and security, bias and fairness, interpretability and explainability, ethical concern, and technical expertise and skills. This paper examines e these challenges in details and offers advices on how companies can address them. By understanding and addressing these challenges, organizations can harness the power of AI to make smarter decisions and gain a competitive advantage in the digital age.

NACA 0015 and NACA 4415 aerofoil are most common four digits and broadly used aerodynamic shape. Both of the shapes are extensively used for various kind of applications including turbine blade, aircraft wing and so on. NACA 0015 is symmetrical and NACA 4415 is unsymmetrical in shape. Consequently, they have big one-of-a-kind in aerodynamic traits at the side of widespread differences of their utility and performance. Both of them undergo the same fluid principle while applied in any fluid medium giving dissimilar outcomes in aerodynamics behavior. On this work, experimental and numerical investigation of each NACA 0015 and NACA 4415 is done to decide their performance. For this purpose, aerofoil section is tested for a prevalence range attack of angle (AOA). The study addresses the performance of NACA 0015 and NACA 4415 and evaluates the dynamics of flow separation, lift, drag, pressure and velocity contour and so on. This additionally enables to layout new optimistic aerofoil, which is critical to enhance the efficiency and performance of an aircraft in terms of lift enhancement and drag reduction.

We investigate the innovational determinants of “Patent Applications” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS and Dynamic Panel. We found that the variables that have a deeper positive association with “Patent Applications” are “Human Resources” and “Intellectual Assets”, while the variables that show a more intense negative relation with Patent Applications are “Employment Share in Manufacturing” and “Total Entrepreneurial Activity”. A cluster analysis with the k-Means algorithm optimized with the Silhouette Coefficient has been realized. The results show the presence of two clusters. A network analysis with the distance of Manhattan has been performed and we find three different complex network structures. Finally, a comparison is made among eight machine learning algorithms for the prediction of the future value of the “Patent Applications”. We found that PNN-Probabilistic Neural Network is the best performing algorithm. Using PNN the results show that the mean future value of “Patent Applications” in the estimated countries is expected to decrease of -0.1%.

In this article we have estimated the value of “Opportunity Driven Entrepreneurship” in Europe. We use data from European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, Pooled OLS, and Dynamic Panel. Our results show that “Opportunity Driven Entrepreneurship” is positively associated, among others, to “Innovation Friendly Environment” and “Turnover Share Large Enterprises”, while it is negatively associated, among others, to “Sales Impacts” and “R&D Expenditure Business Sectors”.

In this article we estimate the value of “Non-R&D Innovation Expenditures” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission from the period 2010-2019. We test data with the following econometric models i.e.: Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. We found that “Non-R&D Innovation Expenditures” is positively associated among others to “Innovation Index” and “Firm Investments” and negatively associated among others to “Human Resources” and “Government Procurement of Advanced Technology Products”. We use the k-Means algorithm with either the Silhouette Coefficient and the Elbow Method in a confrontation with the network analysis optimized with the Distance of Manhattan and we find that the optimal number of clusters is four. Furthermore, we propose a confrontation among eight machine learning algorithms to predict the level of “Non-R&D Innovation Expenditures” either with Original Data-OD either with Augmented Data-AD. We found that Gradient Boost Trees Regression is the best predictor for OD while Tree Ensemble Regression is the best Predictor for AD. Finally, we verify that the prediction with AD is more efficient of that with OD with a reduction in the average value of statistical errors equal to 40,50%.

In this article we investigate the determinants of “New Doctorate Graduates” in Europe. We use data from the EIS-European Innovation Scoreboard of the European Commission for 36 countries in the period 2010-2019 with Pooled OLS, Dynamic Panel, WLS, Panel Data with Fixed Effects and Panel Data with Random Effects. We found that “New Doctorate Graduates” is positively associated, among others, with “Human Resources” and “Government Procurement of Advanced Technology Products” and negatively, associated among others, with “Total Entrepreneurial Activity” and “Innovation Index”. We apply a clusterization with k-Means algorithm either with the Silhouette Coefficient either with the Elbow Method and we found that in both cases the optimal number of clusters is three. Furthermore, we use the Network Analysis with the Distance of Manhattan, and we find the presence of seven network structures. Finally, we propose a confrontation among ten machine learning algorithms to predict the value of “New Doctorate Graduates” either with Original Data-OD either with Augmented Data-AD. Results show that SGD-Stochastic Gradient Descendent is the best predictor for OD while Linear Regression performs better for AD.

In this article we investigate the determinants of the European “Most Cited Publications”. We use data from the European Innovation Scoreboard-EIS of the European Commission for the period 2010-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Results show that the level of “Most Cited Publications” is positively associated, among others, to “Innovation Index” and “Enterprise Birth” and negatively associated, among others, to “Government Procurement of Advanced Technology Products” and “Human Resources”. Furthermore, we perform a cluster analysis with the k-Means algorithm either with the Silhouette Coefficient and the Elbow Method. We find that the Elbow Method shows better results than the Silhouette Coefficient with a number of clusters equal to 3. In adjunct we perform a network analysis with the Manhattan distance, and we find the presence of 4 complex and 2 simplified network structures. Finally, we present a confrontation among 10 machine learning algorithms to predict the level of “Most Cited Publication” either with Original Data-OD either with Augmented Data-AD. Results show that the best machine learning algorithm to predict the level of “Most Cited Publication” with Original Data-OD is SGD, while Linear Regression is the best machine learning algorithm for the prediction of “Most Cited Publications” with Augmented Data-AD.

In this article we analyze the determinants and the export trend of European countries of medium and high technology products. The data were analyzed using various econometric models, namely WLS, Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects. The results show that exports of medium and high-tech products are positively associated, among other variables, with the value of “Average Annual GDP Growth”, “Total Entrepreneurial Activity” and “Sales Impacts”, and negatively associated with, among other variables, “Human Resources”, “Government and Procurement of Advanced Technology Products” and “Buyer Sophistication”. A cluster analysis was realized with the k-Means algorithm optimized with the Silhouette coefficient. The result showed the presence of only two clusters. Since this result was considered poorly representative of the industrial complexity of the European Union countries, a further analysis was carried out with the Elbow method. The result showed the presence of 6 clusters with the dominance of Germany and the economies connected to the German economy. In addition, a network analysis was carried out using the distance to Manhattan. Four complex network structures and two simplified network structures were detected. A comparison was then made between 10 machine learning algorithms for predicting the value of exports of medium and high-tech products. The result shows that the best performing algorithm is the SGD. An analysis with Augmented Data-AD was implemented with a comparison between 10 machine learning algorithms for prediction and the result shows that the Linear Regression algorithm is the best predictor. The prediction with the Augmented Data-AD allows to reduce the MAE by about 0.0022131 compared to the prediction with the Original Data-OD.

The article affords the question of lifelong learning in Europe using data from the European Innovation Scoreboard-EIS in the period 2010-2019 for 36 countries. The econometric analysis is realized using WLS, Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects and Random Effects. The results show that lifelong learning is, among other variables, positively associated to “Human Resources” and “Government procurement of advanced technology products” and is negatively associated, among others, to “Average annual GDP growth” and “Innovation Index”. A clusterization is realized using the k-Means algorithm with a confrontation between the Elbow Method and the Silhouette Coefficient. Subsequently, a Network Analysis was applied with the distance of Manhattan. The results show the presence of 4 complex and 2 simplified network structures. Finally, a comparison was made among eight machine learning algorithms for the prediction of the value of lifelong learning. The results show that the linear regression is the best predictor algorithm and that the level of lifelong learning is expected to growth on average by 1.12%.

In this article we investigate the determinants of marketing or organizational innovators in Europe for 36 countries in the period 2010-2019. We have used data from the European Innovation Scoreboard-EIS of the European Commission. We perform different econometric models i.e. Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. Results show that the level of marketing or organizational innovators in positively associated, among others variables to “Innovation Index”, “Innovators” and “Knowledge Intensive Service Exports”, while is negatively associated with “Sales Impacts”, “Foreign Controlled Enterprises Share of Value Added” and “Government procurement of advanced technology products”.

In the following article, the value of the "Knowledge Intensive Services Exports in Europe" in 36 European countries is estimated. The data were analyzed through a set of econometric models or: Poled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. The results show that “Knowledge Intensive Services Exports” is negatively associated, among others, with "Buyer Sophistication", "Government Procurement of Advanced Technology Products", and positively associated with the following variables i.e. "Innovation Index", "Sales Impacts" and "Total Entrepreneurial Activity". Then a clusterization with k-Means algorithm was made with the Elbow method. The results show the presence of 3 clusters. A network analysis was later built and 4 complex network structures and three structures with simplified networks were detected. To predict the future trend of the variable, a comparison was made with eight different machine learning algorithms. The results show that prediction with Augmented Data-AD is more efficient than prediction with Original Data-AD with a reduction of the mean of statistical errors equal to 55,94%.

The following article indicates the determinants of “Internet User Skills” among European countries based on the application of the database deriving from the DESI-Index. The data were analyzed using the following econometric models, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS, WLS corrected for heteroskedasticity. The Elbow method and the Silouette coefficient method were compared for the optimization of the number of clusters obtained by the k-Means algorithm. The result shows the presence of 5 clusters. A network analysis was carried out using the Euclidean distance with the result of identifying two network structures between some analyzed countries. subsequently a comparison was made between six different machine learning algorithms for the prediction of the future value of the variable of interest. The result shows that the best predictor algorithm is Gradient Boosted Tree Regression with an expected value of the predicted variable increasing by a value of 1.75%. Later a further comparison was made by comparing 6 algorithms with the increased data. The result shows that the best predictor is Simple Regression Tree. The interest variable is predicted to decrease by an amount equal to -6.099%. Statistical errors improve on average by 32.43% in the transition between the original data and the increased data.

The following article analyzes the determinants of the innovation index in Europe. The data refer to the European Innovation Scoreboard-EIS of the European Commission for the period between 2010 and 2019 for 36 countries. The data are analyzed using the following econometric techniques: Panel Data with Random Effects, Panel Data with Fixed Effects, Dynamic Panel Data, Pooled OLS, WLS. The results show that the Innovation Index is negatively connected to some variables, among which the most significant are "GDP per capita", "R&D expenditure public sector", "Venture capital", "Tertiary education", and positively connected to some variables among which the most relevant are: "Government procurement of advanced technology products", "Average annual population growth", "Finance and support", "Human resources", "Marketing or organisational innovators", "Linkages". A clustering was then carried out using the unsupervised k-Means algorithm optimized with the Silhouette coefficient which shows the presence of 2 clusters per value of the Innovation Index. Eight machine learning algorithms has been used for prediction with real data. The Tree Ensemble Regression algorithm has been chosen as best performer. A further prediction has been made with the augmented data. The result shows that the best performing algorithm is Linear Regression with an innovation index value predicted to grow by approximately 3.38%.

The following article estimates the value of ICT Specialists in Europe between 2016 and 2021 for 28 European countries. The data were analyzed using the following econometric techniques, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, WLS and Pooled OLS. The results show that the value of ICT Specialists in Europe is positively associated with the following variables: "Desi Index", "SMEs with at least a basic level of digital intensity", "At least 100 Mbps fixed BB take-up" and negatively associated with the following variables: "4G Coverage","5G Coverage", "5G Readiness", "Fixed broadband coverage", "e-Government", "At least Basic Digital Skills", "Fixed broadband take-up", "Broadband price index", "Integration of Digital Technology". Subsequently, two European clusters were found by value of "ICTG Specialists" using the k-Means clustering algorithm optimized by using the Silhouette coefficient. Finally, eight different machine learning algorithms were compared to predict the value of "ICT Specialists" in Europe. The results show that the best prediction algorithm is ANN-Artificial Neural Network with an estimated growth value of 12.53%. Finally, "augmented data" were obtained through the use of the ANN-Artificial Neural Network, through which a new prediction was made which estimated a growing value of the estimated variable equal to 3.18%.

The following article analyzes the determinants of e-government in 28 European countries between 2016 and 2021. The DESI-Digital Economy and Society Index database was used. The econometric analysis involved the use of the Panel Data with Fixed Effects and Panel Data with Variable Effects methods. The results show that the value of “e-Government” is negatively associated with “Fast BB (NGA) coverage”, “Female ICT specialists”, “e-Invoices”, “Big data” and positively associated with “Open Data”, “e-Government Users”, “ICT for environmental sustainability”, “Artificial intelligence”, “Cloud”, “SMEs with at least a basic level of digital intensity”, “ICT Specialists”, “At least 1 Gbps take-up”, “At least 100 Mbps fixed BB take-up”, “Fixed Very High Capacity Network (VHCN) coverage”. A cluster analysis was carried out below using the unsupervised k-Means algorithm optimized with the Silhouette coefficient with the identification of 4 clusters. Finally, a comparison was made between eight different machine learning algorithms using "augmented data". The most efficient algorithm in predicting the value of e-government both in the historical series and with augmented data is the ANN-Artificial Neural Network.

This article analyzes the determinants of the "Broadband Price Index" in Europe. The data used refer to 28 European countries between 2016 and 2021. The database used is the Digital, Economy and Society Index-DESI of the European Commission. The data were analyzed using the following econometric techniques, namely Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS and Dynamic Panel. The value of the "Broadband Price Index" is positively associated with the DESI Index, and "Connectivity" while it is negatively associated with "Fixed Broadband Take Up", "Fixed Broadband Coverage", "Mobile Broadband", "e-Government", "Advanced Skills and Development", "Integration of Digital Technology", "At Least Basic Digital Skills ", "Above Basic Digital Skills "," At Least Basic Software Skills ". A cluster analysis was carried out below using the k-Means algorithm optimized with the Silhouette coefficient. The analysis revealed the existence of three clusters. Finally, an analysis of the machine learning algorithms was carried out to predict the future value of the "Broadband Price Index". The result shows that the most useful algorithm for prediction is the Artificial Neural Network-ANN with an estimated value equal to an amount of 9.21%.

The determinants of the presence of “Foreign Doctorate Students” among 36 European Countries for the period 2010-2019 are analyzed in this article. Panel Data with Fixed Effects, Random Effects, WLS, Pooled OLS, and Dynamic Panel are used to investigate the data. We found that the presence of Foreign Doctorate Students is positively associated to “Attractive Research Systems”, “Finance and Support”, “Rule of Law”, “Sales Impacts”, “New Doctorate Graduates”, “Basic School Entrepreneurial Education and Training”, “Tertiary Education” and negatively associated to “Innovative Sales Share”, “Innovation Friendly Environment”, “Linkages”, “Trademark Applications”, “Government Procurement of Advanced Technology Products”, “R&D Expenditure Public Sectors”. A cluster analysis was then carried out through the application of the unsupervised k-Means algorithm optimized using the Silhouette coefficient with the identification of 5 clusters. Finally, eight different machine learning algorithms were used to predict the value of the "Foreign Doctorate Students" variable. The results show that the best predictor algorithm is the "Tree Ensemble Regression" with a predicted value growing at a rate of 114.03%.

Research into professionalization in health and safety has recently gained in interest. Graduate training is one of the factors that determines or conditions the role of the safety professional, thus intervene in the professionalization process. This article is the result of a workshop and the discussions of nine academic directors of safety education programs about quality evaluation. This article introduces the issue with a historic overview of safety education, presents a synthesis of nine selected education programs, discusses quality evaluation of health and safety education programs, propose a quality evaluation frame and finally, proposes a process for designing a quality safety education program with an associated model of the learning objectives. The outcomes are interesting for everyone who is interested in health and safety education and quality evaluation and will give insights into how safety professionals are educated.

In Low and Lower-Middle-Income countries, the prevalence of anemia in infancy remains high. In early childhood anemia cause irreversible cognitive deficits and represents a higher risk of child mortality. The consequences of anemia in infancy are a major barrier to overcome poverty traps. The aim of this study was to analyze based on a multi-level approach, different factors associated with anemia in children 6–23 m old based on recent available Standard Demographic Health Surveys (S-DHS). We identified 52 S-DHS that had complete information in all covariates of interest in our analysis between 2005 and 2015. We performed traditional logistic regressions and multilevel logistic regression analyses to study the association between hemoglobin concentrations and household, child, maternal, socio-demographic variables. In our sample, 70 % of the 6–23 m old children were anemic. Child anemia was strongly associated with maternal anemia, household wealth, maternal education and low birth weight. Children fed with fortified foods, potatoes and other tubers had significantly lower rates of anemia. Improving overall household living conditions, increasing maternal education, delaying childbearing and introducing iron rich foods at six months of age may reduce the likelihood of anemia at in toddlerhood.