Artificial intelligence (AI) is a versatile term that is a conclusive remedy to solve the problem using past rational data after deep contemplation using these terms i-e basic statistics, carving data, familiarity with common AI algorithms. Seafood especially tiger prawn export as a busi-ness will provide enormous foreign exchange to any country if the farmers overcome the corre-lated vulnerabilities in prawn farming. This research is elucidating lacking in Tiger prawn (TP) farming like curbing of Oxygen, pH, water temperature, and nutrients, etc. Moreover, hatchery statistics in terms of juveniles will depict this study's clear picture of curbed aquaculture. For normative decisions, the Analytical Hierarchical Process (AHP) is used. The problem which has been faced by local prawn farmers that there is a stagnant TP growth in ponds, the reason is the predominant sensitivity factor in TP. For this reason, they need indemnification of thirteen fac-tors with natural resources to get the plausible results to get calmness in their lives. This study will solely focus on the TP growth model, and the monitoring effect will be established by the Artificial Intelligence algorithm. This study will employ the AHP, 0-1 scaling method, data cura-tion techniques, and ecological statistics. The life of Tiger Prawn (TP) depends upon these factors mainly, a) Physical and b) Chemical parameters. Physical parameters contain environment (E) provided to TP like season (S) and temperature (T) etc. whereas the quality of Ammonia NH3 (N) from fish waste, Oxygen level (O), and water quality hard & soft (W) lies in chemicals do-main. This research will Elucidate the factors which cause conceptual muddles in the aquamarine life of TP, for this reason, Statistical tools will assess the current result, forecast the gap. AHP will analyze the domain inputs, circumspect ramification which will depict visceral factors, later results depict which pond suits the TP. In curtail, these factors will be curbed to improve the growth of TP in a control conditioned environment.

Financial statements depict the condition of a company and need to be analyzed and evaluated to assess its performance. This research aims to analyze financial statements to describe the financial condition, measure business development over time, and evaluate the achievement of the com-pany's objectives. An optimization analysis of financial ratios is performed using the Weighted Goal Programming (WGP) model, which addresses multiple objectives by applying weights based on their priorities. The Analytical Hierarchy Process was used to determine the priority weights of deviation variables from each financial ratio target. Financial ratios were selected based on their impact on profit using factor analysis. The constructed WGP model aims to minimize deviations in Return on Assets, Operating Ratios, Operating Income Ratio, Total Assets Turnover, and Current Ratio. Computational calculations to solve the WGP model are per-formed using Python, with pseudocode provided. A case study on a company in the garment and textile sector was conducted and found that the Operating Ratio, Return on Assets, Operating Income Ratio, and Current Ratio still need improvement by developing strategies to achieve the targets. Sensitivity analysis was also employed to assess the resilience of the model in response to alterations in data.

This study addresses the critical issue of cardiovascular diseases (CVD) as the leading cause of death globally, emphasizing the importance of stent delivery catheter manufacturing. Traditional manufacturing processes, reliant on destructive end-of-batch sampling, present significant financial and quality challenges. The research highlights the need for non-destructive Process Analytical Technologies (PAT) to meet the increasing demand for these life-saving devices. The study employs a mixed-method approach, combining qualitative literature review and quantitative artefact development, to propose a closed-loop Cyber Physical Production System (CPPS). The proposed system aims to enhance real-time quality control, minimize costs, and improve manufacturing efficiency. Initial results demonstrate the system's effectiveness in reducing cycle times, improving stability, and significantly decreasing production misses. The findings suggest substantial financial savings and quality improvements, underscoring the potential of advanced control strategies in regulated medical device manufacturing. This study proposes a generalized CPPS framework to be applicable across diverse regulated manufacturing environments, ensuring optimal processing conditions and adherence to regulatory standards. The research concludes with the successful demonstration of innovative approaches and technologies, leading to improved product quality, patient safety, and operational efficiency in the medical device industry.

This paper proposes a method for monitoring the structural health of concrete bridges in Iran. In this method, the bridge condition index (BCI) of bridges is determined by the analytical hierarchy process. BCI constitutes eight indices that are scored based on the experts' views, including structural, hydrology and climate, safety, load impact, geotechnical and seismicity, strategic importance, facilities, and traffic and pavement. Experts' views were analyzed by Expert Choice software, and the relative importance (weight) of indices were determined using the analytical hierarchy process (AHP). Then, the gave scores of experts were assigned to indices for various conditions. Bridge inspectors can examine the bridge, determine the scores of indices, and compute BCI. Higher values of BCI ​​indicate better conditions. Therefore, bridges with lower BCI take priority in maintenance activities. Five bridges in Iran, Semnan province, were selected as the case studies, and BCI calculation of these bridges was conducted.

Landslides in the hilly regions of Al‐Madinah Al‐Munawarah are a natural hazard that endangers both infrastructure and human lives. The objective of this work is to create maps that show the likelihood of landslides occurring on the Al Figrah Road, which is a vital road connects the cities of Al‐Madinah and Yanbu. This will be done using the analytical hierarchy process (AHP) approach. The landslide susceptibility maps have been created by taking into account various parameters such as elevation, slope, aspect, drainage density, lithology, soil, and precipitation. Assess the significance of these thematic layers in relation to the frequency of landslides in the research area based on historical landslide data and field verification, in order to allocate suitable weights. The sensitivity maps of the study region delineated areas with low risk (93,552,333 m2), moderate risk (271,180,722 m2), and high risk (33,053,839 m2). 28.63% of the Al Figrah total Road is classified as low risk, 48.09% as moderate risk, and 23.28% as high risk. A total of 10 landslides were identified in areas with steep slopes and denudational hills, confirming the findings of the AHP analysis conducted in high‐risk zones. The integrity of these slide zones was greatly impacted by the presence of joints, faults, foliation, and shear zones within igneous and metamorphic rocks. Examining the susceptibility of landslides in this region enhances our understanding of landslides on other steep routes in Saudi Arabia.

The key to building a strong bridge country lies in talent, and the foundation lies in education. The cultivation of bridge engineering talents is related to the future and destiny of building a strong bridge country. This course adopts the educational philosophy of "holographic teaching method" centered on the comprehensive development of students, cultivating "engineering thinking" guided by engineering education certification, enhancing "abilities and qualities" through professional knowledge, reconstructing the course knowledge content system through engineering philosophy thinking, and implementing the ideological and political construction of the course in a multi-level unified manner of "explicit + implicit". Based on restructuring the course content system, we will strengthen the construction of diversified course resources, integrate theory with practice throughout the entire process of the course, practice the concept of "bridge architects + bridge engineers" parallel development, and cultivate cross-border and compound talents with comprehensive qualities of "engineering + art + humanities".

This paper proposes a method for determining the bridge condition index (BCI) in concrete bridges, which is based on the views of bridge experts. First, eight indices were defined for a concrete bridge including structure, hydrology, safety, load impact, geotechnical and seismicity, strategic importance, facilities, and finally traffic and pavement. Each index consists of several sub-indices. Next, a series of questionnaires about the relative importance of indices and their sub-indices were prepared and distributed among bridge experts. Experts’ views were analyzed by Expert Choice software and the relative importance (weight) of each index and each sub-index was determined using the analytical hierarchy process (AHP). Then, based on experts’ views, an average score was assigned to each sub-index for any condition. Now the bridge inspectors can examine the bridge and determine the scores of sub-indices. Each index’s score is the sum of the weighted score assigned to its’ sub-indices and BCI is the sum of weighted scores assigned to indices. Higher values of BCI indicate a better condition. Therefore, bridges with lower BCI take priority in maintenance activities. To apply the proposed method, five bridges were selected in Semnan province, Iran, and BCI calculation of these bridges were conducted.

Today project management in every field of life is prerequisite for the success of project by increasing quality reduces cost and schedule. But selecting tools and techniques to achieve our objectives and implement our plan fully is very difficult task because choice creates complexity. So, we discuss AHP to make decision simple. Ranking critical success factor, cloud computing services, risk prioritization, selection of right ETL software and many other systems AHP plays its important role. For the improvement of today’s complex systems it is very important to prioritize and select projects to remove the root cause of the problem. To attain the right selection of construction equipment for carrying out schedule tasks with high efficiency, production and financial capability is the main purpose of procurement of construction equipment process. Certain conflicts can occur due to the construction of UML models in a collaborative way. AHP is used to remove these conflicts and for establishing and evaluating modelers judgments. Nowadays it is very important and critical decision to choose the best option from multiple alternatives for a successful career after passing 12th standard and also it affects our future. “AHP and TOPSIS” methods are used for this purpose. In this paper, an “AHP and Fuzzy AHP” based hierarchical trust model has been used to rate the service providers and their various plans for infrastructure as a service.

Sesquiterpene lactones (STLs) are a large group of terpenoids most commonly found in plants of the Asteraceae family, e. g. in chicory plants, displaying a wide range of interesting biological activities. However, further studies on the biological potential of chicory derived STLs and analogues are challenging as only four of these molecules are commercially available (as analytical standards), and to date there are no published or patented simple extraction-purification processes capable of large scale STLs isolation. In this work we describe a novel three-step large scale extraction and purification method for the simultaneous purification of 11,13-dihydrolactucin (DHLc) and lactucin (Lc) starting from a chicory genotype rich in these STLs and in the corresponding glycosyl and oxalyl conjugated forms. After a small-scale screening on 100 mg of freeze-dried chicory root powder, the best results were achieved with a 17 h water maceration at 30°C. With these conditions we managed to increase the content of DHLc and Lc, at the same time favouring the hydrolysis of their conjugated forms. On a larger scale, the extraction of 750 g of freeze-dried chicory root powder, followed by a liquid-liquid extraction step and a reversed-phase chromatography, allowed the recovery of 642.3 ± 76.3 mg of DHLc and 175.3 ± 32.9 mg of Lc. The two pure STLs were subsequently used in the context of semi-synthesis to generate analogues for biological evaluation as antibacterial agents. In addition, other described chicory STLs that are not commercially available were also synthesized or extracted to serve as analytical standards for the study. In particular, lactucin-oxalate and 11,13-dihydrolactucin-oxalate were synthesized in two steps starting from Lc and DHLc, respectively. On the other hand, 11β,13-dihydrolactucin-glycoside was obtained after a MeOH/H₂O (70/30) extraction, followed by a liquid-liquid extraction step and a reversed-phase chromatography. Together, this work will help facilitate the evaluation of the biological potential of chicory derived STLs and their semisynthetic analogues.

This review is dedicated to sustainable practices in liquid chromatography. HPLC and UHPLC methods contribute significantly to routine analytical techniques. Therefore, the transfer of classical liquid chromatographic methods into sustainable ones is of utmost importance in moving toward sustainable development goals. Among other principles to render a liquid chromatographic method green, substitution of the organic solvent component in the mobile phase with a greener one received great attention. This review concentrates on choosing the best alternative green organic solvent to replace the classical solvent in the mobile phase for easy rapid transfer to a more sustainable normal phase or reversed-phase liquid chromatography. The main focus of this review will be on describing the transfer of non-green to green and white chromatographic methods in an effort to elevate the sustainability best practice in analytical chemistry. The greenness properties and greenness ranking in addition to the chromatographic suitability of seventeen organic solvents for liquid chromatography are mentioned to have a clear insight into the issue of rapidly choosing the appropriate solvent to transfer a classical HPLC or UHPLC method into a more sustainable one. A simple guide is proposed for making the liquid chromatographic method more sustainable.

We analyze the transformation of a very broad class of metrics that can be put in terms of static coordinates. Starting from a general ansatz, we obtain a relation for the parameters in which one can impose further symmetries, or restrictions. One of the simplest restrictions leads to FLRW cases, while transforming from the initial static to other static-type coordinates can lead to near horizon coordinates, Wheeler-Regge, isotropic coordinates, among others. As less restrictive cases, we show an indirect route for obtaining Kruskal-Szekeres within this approach, as well as Lema\^{\i}tre coordinates. We use Schwarzschild spacetime as prototype for testing the procedure in individual cases. However, application to other spacetimes, such as de-Sitter, Reissner-Nordstr\"{o}m or Schwarzschild de Sitter, can be readily generalized.

In this paper, an analytical form of Rump Function is presented. This seminal function constitutes a fundamental concept of digital signal processing theory and is also involved in many other areas of applied mathematics. In particular, Rump Function is performed in a simple manner as the limit of a sequence of real functions letting ? tend to infinity. This limit is zero for strictly negative values of the real variable ? whereas it coincides with the independent variable ? for strictly positive values of the variable ?. The novelty of this work compared to other research studies concerning analytical expressions of the Ramp Function, is that the proposed formula is not exhibited in terms of miscellaneous special functions, e.g. Gamma Function, Biexponential Function or any other special functions such as Error Function, Hyperbolic Function, Orthogonal polynomials etc. Hence, this formula may be much more practical, flexible and useful in the computational procedures which are inserted into digital signal processing techniques and other engineering practices.

This publication investigates the potential application of bark extractives as a biopolyol and extracted bark residues as a filler for producing polyurethane materials. The aim is to enhance the properties of polymeric composites while reducing the environmental impact associated with the complex utilization of bark.The comprehensive study of compositions of extractives isolated from black alder (Alnus glutinosa) and Baltic pine (Pinus silvestris) barks was performed using microwave-assisted water extraction. The yield of the extracts obtained under different extraction conditions, as well as the total phenolic and monomeric carbohydrate content in the extractives, were studied. Furthermore, UHPLC-HRMS analysis was conducted to study the detailed composition of the bark extracts.The total content of hydroxyl groups and the relative portion of aliphatic and phenolic groups in the isolated extracts were determined depending on the extraction regimes and bark origination. The dominant compounds in black alder bark extracts isolated at 70-90⁰C were identified as diarylheptanoids and their derivatives bearing sugar units, with oregonin being the main compound. Pine bark extracts isolated at the same temperature were found to be rich in oligomeric proanthocyanidins. Extracts from both black alder and pine barks obtained at different times of isothermal heating between 130-150°C were rich in carbohydrates and showed an increased proportion of aliphatic OH groups.The study also focused on the composition of residual biomass. It was indicated by Py-GC/MS/FID and wet chemistry methods that residues of both black alder and pine bark are enriched with lignin in comparison with initial barks. Therefore, it can be proposed that extracted bark residues introduced into polyurethane compositions will act as a charcoal formation promoter, thus increasing the flame resistance of materials.Overall, the study provides valuable insights into the chemical composition of bark extractives and extracted bark residues for their potential application as biopolyol and fillers of polyurethane materials, contributing to a more sustainable approach in polymer composite production.

Paper-based analytical devices have been substantially developed in recent decades. Many fabrication techniques for paper-based analytical devices have been demonstrated and reported. Herein we report a relatively rapid, simple, and inexpensive method for fabricating paper-based analytical devices using parafilm hot pressing. We studied and optimized the effect of the key fabrication parameters, namely pressure, temperature, and pressing time. We discerned the optimal conditions, including pressure of 3.8 MPa (3 tons), temperature of 80oC, and 3 minutes of pressing time, with the smallest hydrophobic barrier size (821 µm) being governed by laminate mask and parafilm dispersal from pressure and heat. Physical and biochemical properties were evaluated to substantiate the paper functionality for analytical devices. Wicking speed in the fabricated paper strips was slightly slower than that of non-processed paper, resulting from reducing paper pore size. A colorimetric immunological assay was performed to demonstrate the protein binding capacity of the paper-based device after exposure to pressure and heat from the fabrication. Moreover, mixing in two-dimensional paper-based device and flowing in a three-dimensional counterpart were thoroughly investigated, demonstrating that the paper device from this fabrication process is potentially applicable as analytical devices for biomolecule detection. Fast, easy, and inexpensive parafilm hot press fabrication presents an opportunity for researchers to develop paper-based analytical devices in resource-limited environments.

While there are many models of epidemic evolution perhaps the basis for such models finds itself in the lumped behavior expressed through the so-called SIR model (Susceptible, Infectious, Recovered) from which spring many related models. This paper discusses multiple analytic solutions to that equation including those that are available in closed analytic form and those for which at least one final integral has to be done numerically, so-called quasi-analytic solutions. The solutions are intrinsically time-dependent of course. The hope is that such an investigation will lead to a better understanding of when and how models can be of use in studying the dynamical evolution of diseases including, perhaps, the great influenza pandemic of 1918 together with later pandemics and epidemics not excluding the Covid-19 pandemic of the present day.

Recently, we have applied the generalized Littlewood theorem concerning contour integrals of the logarithm of analytical function to find the sums over inverse powers of zeroes for the incomplete Gamma- and Riemann zeta- functions, polygamma functions, and elliptical functions. Here, the same theorem is applied to study such sums for the zeroes of the Hurwitz zeta-function , including the sum over the inverse first power of its appropriately defined non-trivial zeroes. We also study some related properties of the Hurwitz zeta-function zeroes. In particular, we show that for any natural N and small real epsilon, when z tends to n=0, -1, -2… we can find at least N zeroes of zeta in the - vicinity of 0 for sufficiently small epsilon, as well as one simple zero tending to 1, etc.

The present paper is aimed at presenting an updated review of prediction methods for the aerodynamic noise of ducted rotor-stator stages. Indeed, ducted rotating-blade technologies are in continuous evolution and increasingly used, for both aeronautical propulsion units, power generation and air conditioning systems. Different needs are faced, from the early design stage to the final definition of a machine. Fast-running, approximate analytical approaches and high-fidelity numerical simulations are considered as the best suited tools for each, respectively. Recent advances are discussed, with emphasis on their pros and cons.

Stabilization of planar premixed flame front on a lattice (porous) burner is considered. It is rigorously mathematically proved that there exist two different stabilization regimes: one with flame front located nearby the surface of the burner, and another with flame front located inside the lattice. These two regimes result in qualitatively different gas temperature profiles along the flow, that is monotonic and non-monotonic, respectively. Boundary between the two regimes is described in terms of dependence of the lattice solid material temperature on flow Peclet number. Likewise temperature profiles, such dependencies may be both monotonic and non-monotonic. Transition between the two types of dependencies is controlled by Arrhenius number. Conclusions of the study are supported by numerical analysis. They also compare favourably with available experimental data. Novelty of the present approach is fundamentally rigorous analytical analysis of the problem.

We have conducted a comprehensive year-long sampling campaign for particulate matter (PM) pollutants at a site near a major highway, following standard protocols. Total mass, and elemental and chemical composition of the fine fractions (PM2.5) of traffic-related pollutants are determined utilizing several complementary techniques. These complementary techniques included gravimetric analysis, X-ray fluorescence (XRF), scanning electron microscopy and energy dispersive spectroscopy, X-ray diffraction (XRD) and black carbon multi-wavelength absorption. The results show that the PM2.5 mass concentrations are within or slightly above international standards and include natural dust and anthropogenic pollutants such as black carbon, sulfates and other traffic-related elements. Anthropogenic sources include the secondary pollutants Mascagnite and Koktaite, traffic emissions such as exhaust emissions and tires, brakes and road erosions. It was found that the sulfates are the highest contributors to PM2.5 (~40%), as evident from XRD results and the S content in the XRF analysis.

Chlorogenic acid or 5-Caffeoylquinic acid is a polyphenolic component present in coffee and its by-products. Chlorogenic acid has been shown to exert biological properties, particularly in relation to glucose and lipid metabolism, including antibacterial, antioxidant, anti-inflammatory activities, among others. Due to its importance, it is necessary to evaluate the reliability of the analytical method for its determination in complex matrices such as food. In this work, different methods of chlorogenic acid extraction in coffee Silverskin were studied, as well as its quantification by HPLC. The results showed that the method of extraction with a mixture of methanol:water (3:1 v/v) in an ultrasonic bath, favored the recovery of chlorogenic acid with a recovery of 77.44%. The instrument detection limit for chlorogenic acid was 3.311 µg/mL and the quantification limit was 11.037 µg/mL. For coffee Silverskin, the concentration obtained of chlorogenic acid by the three extraction methods evaluated was in the range of 57 to 224 mg/kg of coffee silverskin (dry basis).

This paper reviews the current research on the speciation and determination of mercury by various analytical instruments such as, atomic absorption spectrometer (AAS), voltammeter, inductively coupled plasma optical emission spectrometer (ICP-OES), ICP-atomic emission spectrometer (AES), ICP-mass spectrometer (MS), atomic fluorescence spectrometer (AFS), spectrophotometer, spectrofluorometer, and high performance liquid chromatography (HPLC). Approximately 126 research papers on the speciation and determination of mercury by various analytical instruments published in international journals since 2015 are reviewed. All the analytical parameters, such as limit of detection, linearity range, quality assurance and quality control studies, applicability, and interfering ions studies evaluated in the reviewed articles are tabulated. This review find outs the lack of information on speciation studies of mercury in recent years. Another important prediction from this review is authors are not much studied about the concentrations of mercury in the atmosphere.

A sustainable reversed-phase chromatographic method has been developed and validated for the simultaneous determination of three active pharmaceutical ingredients, dorzolamide, brinzolamide, and timolol, used to treat glaucoma. The eco-friendly solvent isopropanol has been used as an organic mobile phase constituent. According to the Hansen space green solvent selection tool, isopropanol has a G score of 6.5, comparable to ethanol, which has a G score of 6.6. The mobile phase consists of isopropanol: aqueous sodium acetate buffer (0.1 M, pH 4.25) in the ratio of 10:90 (v/v). The flow rate was maintained at 1 mL/min. Dorzolamide and brinzolamide were detected at 254 nm, and timolol was detected at 295 nm. A high-purity silica with a polymeric C18 modification column (5 µm,150 x 4.6 mm) was used for this separation. The three compounds were eluted within 8 min. The method was validated according to ICH guidelines. The calibration curves were linear in the range of 20-70 µg/mL, 40-140 µg/mL, and 20-70 µg/mL for dorzolamide, brinzolamide, and timolol, respectively. The LODs were found to be 1.61 µg/mL, 1.60 µg/mL, and 3.16 µg/mL for dorzolamide, brinzolamide, and timolol, respectively. Good accuracy and precision were obtained for the three compounds. The greenness and whiteness of the method were indicated using the AGREE and RGB12 tools, respectively.

Despite the fact that strong routine separation methodologies can give reliable specificity and validity at usual working pharmaceuticals concentrations, they may fail at very low concentration levels. This poses considerable challenges for researchers inves-tigating product purity and therapeutic drug monitoring. Sensitivity enhancement pro-cedures are thus required to maximize the performance of separation techniques. Large volume injection, solid phase extraction/solid phase enrichment (SPE/SPEn), pre-, post-, and in-column derivatization, as well as the use of sensitive detection devices are the simplest strategies for improving sensitivity of the separation-based analytical techniques. Large volume injection of samples with online SPE/SPEn coupled with separation techniques increased sensitivity and improved detection as well as quantification limits without affecting peak shape and system performance. Although the primary purpose of derivatization is to improve sensitivity and selectivity, greener derivatization is growing in popularity and should be considered in analytical chemistry. In general, two strategies are essential for accomplishing greener derivatization goals. The first is the search for and use of ecologically acceptable derivatizing reagents, solvents, and reaction conditions. The second is miniaturization and automation of analytical methods. This review discusses significant advances in separation-based analytical techniques, specifically enrichment approaches and detector signal improvement for pharmaceutical quantification in various matrices at very low concentration levels. As a result of improved analytical systems setup in drug assays, the possibility of high-throughput analyses was also highlighted.

Cyrene was evaluated for the first time as a potential sustainable mobile phase solvent in re-versed-phase chromatography. As a benign biodegradable solvent, Cyrene is an attractive re-placement to classical non-green organic chromatographic solvents such as acetonitrile and a modifier, co-eluent to known green solvents such as ethanol. Compared to ethanol, Cyrene is less toxic, non-flammable, bio-based, biodegradable and cheaper solvent. A fire safety spider Chart was generated to compare the properties of Cyrene to ethanol and show its superiority as a greener solvent. Cyrene's behaviour, advantages, and drawbacks in reversed-phase chromatography, including cut-off value, elution power, selectivity, and effect on the column, were investigated using a model drug mixture of moxifloxacin and metronidazole. A monolithic C18 (10 x 4.6 mm) column was used as a stationary phase. Different ratios of Cyrene: ethanol with an aqueous portion of sodium acetate buffer mobile phases were tested. A mobile phase consisting of Cyrene: ethanol: 0.1 M sodium acetate buffer pH 4.25 (8:13:79, v/v) was selected as most suitable mobile phase system for separating and simultaneously determining metronidazole and moxifloxacin. The greenness and whiteness of the method were evaluated using the qualitative green assessment tool AGREE and the white analytical chemistry assessment tool RGB12. Further potentials of Cyrene as a solvent or modifier in normal phase chromatography, liquid chromatography-mass spectrometry, and supercritical fluid chromatography are discussed.

One of the most common solutions to access underground is through the construction of circular shafts. At preliminary design stage analytical expressions are often used to estimate the horizontal earth pressure acting on the lining. However, most of these solutions are based on active state conditions and do not consider the restrictions imposed on the shaft lateral displacements by the rigidity of its lining or by the construction method employed. To overcome this limitation a new methodology to account with the shaft lateral displacements in the determination of the horizontal earth pressure acting on circular shafts is developed and validated against the results of relevant physical scale models. The obtained results show good agreement with the measured data, reproducing adequately the reduction of the horizontal earth pressure from its initial value to an active state condition with the increase of the shaft lateral displacement. Following this approach more realistic predictions of the earth pressure acting on the lining of circular shafts can be performed.

Solifenacin (SFC) is a potent muscarinic antagonist that effectively reduces bladder muscle contraction, thereby alleviating symptoms such as frequency of micturition and urgency. Oxidation of SFC leads to the formation of impurities like Impurity K. Effective analysis and control of this impurity is crucial for ensuring compliance with regulatory standards and safeguarding patient health. To address these challenges, we propose a novel one-step synthesis of Impurity K from SFC. Impurity K was synthesized using cerium ammonium (IV) nitrate (CAN) in water/acetonitrile as the solvent. Additionally, we describe a new HPLC-MS method for the detection of Impurity K in solifenacin succinate tablets.

Carbon nanotubes have sparked a substantial amount of scientific and technological research due to their exceptional mechanical, physical and electrical characteristics compared to conventional materials. As a result, detailed studies on their mechanical properties have been conducted, and static and dynamic behavior of single-walled and multi-walled carbon nanotubes have been proposed using Euler-Bernoulli and Timoshenko beam models. The main objective of this paper is to study the free vibration of a Timoshenko-Ehrenfest single-walled carbon nanotube based on the nonlocal theory and taking surface effects into account. To model these effects on frequency response of nanotubes, we use Eringen’s nonlocal elastic theory and surface elastic theory proposed by Gurtin and Murdoch to modify the governing equation. A modified version of Timoshenko nonlocal elasticity theory - known as the nonlocal truncated Timoshenko beam theory - is put forth to investigate the free vibration behavior of single-walled carbon nanotubes (SWCNT). Using the Hamilton’s principle, the governing equations and the corresponding boundary conditions are derived. Finally, to check the accuracy and validity of the proposed method, some numerical examples are carried out. The impacts of the nonlocal coefficient, surface effects and nanotube length on the free vibration of single-walled carbon nanotube (SWCNT) are evaluated and the results are compared with those found in the literature. The findings indicate that the length of the nanotube, the nonlocal parameter and the surface effect all play important roles and should not be disregarded in the vibrational analysis of nanotubes. Finally, the results show how effective and successful the current formulation is at explaining the behavior of nanobeams.

The identification and quantitative determination of wool and fine animal fibers are of great interest in the textile field because of significant price differences between them and common adulterations in raw and processed textiles. Since animal fibers have remarkable similarities in their chemical and physical characteristics, specific identification methods have been studied and proposed following advances in analytical technologies. The identification methods of wool and fine animal fibers are reviewed in this paper and the results of relevant studies are listed and summarized, starting from classical microscopy methods which are still used today not only in Small to Medium Enterprises but also in large industries, research studies and quality control laboratories. Particular attention has been paid to image analysis, Nir spectroscopy and proteomics which constitute the most promising technologies of quality control in the manufacturing and trading of luxury textiles and can find application in forensic science and archeology.

Fiber aggregation in nanocomposites has an important effect on the macroscopic electrical performance. To quantitatively evaluate its effect, an index to characterize the degree of aggregation is imperative, and ideally it should have three features simultaneously, i.e., single-parametric, dimensionless and physically meaningful, applicable to different aggregation topologies, and one-to-one corresponding to material electrical properties. To this end, a new aggregation degree is proposed, which is defined as the average increased number of fibers that connect with each one when fibers aggregate from a uniformly distributed state. This index is applicable to different aggregation topologies from lump-like aggregating clusters to network-like aggregating clusters. This index is proven to only depend on the local features of aggregating clusters, and can be concisely expressed by the characteristic parameters of local structure, via geometric probability analysis and numerical validations. Further, a one-to-one linear relation between the aggregation degree and percolation threshold is established by Monte Carlo simulations, which is independent of the distribution law of the fibers. This work provides a guide to the property characterization, performance prediction and material design of nanocomposites, and also gives a physical insight into the understanding of systems with similar non-uniform distributions.

This paper extends the Stochastic Method of Cuts (SMoC) to approximate of the Macroscopic Fundamental Diagram (MFD) of urban networks and uses Maximum Likelihood Estimation (MLE) method to estimate the model parameters based on empirical data from a corridor and 30 cities around the world. For the corridor case, the estimated values are in good agreement with the measured values of the parameters. For the network datasets, the results indicate that the method yields satisfactory parameter estimates and graphical fits for roughly 50\% of the studied networks, where estimations fall within the expected range of the parameter values. The satisfactory estimates are mostly for the datasets which (i) cover a relatively wider range of densities and (ii) the average flow values at different densities are approximately normally distributed similar to the probability density function of the SMoC. The estimated parameter values are compared to the real or expected values and any discrepancies and their potential causes are discussed in depth to identify the challenges in the MFD estimation both analytically and empirically. In particular, we find that the most important issues needing further investigation are: (i) the distribution of loop detectors within the links, (ii) the distribution of loop detectors across the network, and (iii) the treatment of unsignalized intersections and their impact on the block length.

Pathogens and adulterants in human feeding consumables can be readily identified according to their electrical properties. Electrical bioimpedance analysis (BIA) has been widely used for body contents characterization, such as blood, urine, lactate and sweat. If the blood glucose concentration alters the electrical properties of the blood medium, then the impedance spectrum obtained by BIA can be used to measure glycemia. In some applications, artificial neural networks allows the correlation of these parameters (impedance and glucose concentration) by means of symbolic and statistical rules. According to our literature review, there is any physical model that allows the interpretation of the relationship between blood’s electrical properties, obtained by BIA, and the concentration of glucose in the blood plasma. This article proposes a simplified physical model for blood electrical conductivity as a function of glucose concentration, based on Bruggeman’s effective medium theory. The equations of this model were obtained considering an insulating phase distribution diffused in a conductive matrix, in which red blood cells are represented by macroscopic insulating nuclei and glucose molecules by microscopic insulating particles. The impedance spectrum for different glucose concentrations (4.0 to 6.8 mmol/L) in a blood sample, published by Kamat Bagul (2014), were compared with the proposed model. The results showed a significant correlation with the experimental data, showing a maximum error of 5.2%. The proposed model might be useful in the design of noninvasive blood glucose monitoring systems.

It has been known since the 1930’s that all immunoglobulins carry a weak negative charge in physiological solvents. However, there has been no systematic exploration of this fundamental property. Accurate charge measurements have been made using membrane confined electrophoresis in two solvents (pH 5.0 and pH 7.4) on a panel of twelve mAb IgGs, as well as their F(ab’)₂ and Fc fragments. The following observations were made at pH 5.0: 1) the measured charge differs from the calculated charge by ~40 for the intact IgGs, and by ~20 for the Fcs; 2) the intact IgG charge depends on both Fv and Fc sequences, but does not equal the sum of the F(ab)’₂ and Fc charge; 3) the Fc charge is consistent within a class. In phosphate buffered saline, pH 7.4: 1) the intact IgG charges ranged from 0 to -13; 2) the F(ab’)₂ fragments are nearly neutral for IgG1s and IgG2s, and about -5 for some of the IgG4s; 3) all Fc fragments are weakly anionic, with IgG1 < IgG2 < IgG4; 4) the charge on the intact IgGs does not equal the sum of the F(ab’)₂ and Fc charge. In no case is the calculated charge, based on H⁺ binding, remotely close to the measured charge. The charge on IgGs in physiological solvent is sufficiently small to minimize its contribution to thermodynamic nonideality. Some of the mAbs carried a charge in physiological salt that was outside the range observed for serum-purified human poly IgG. To best match physiological properties, a therapeutic mAb should have a measured charge that falls within the range observed for serum-derived human IgGs.

This paper investigates the tank drainage problem of an isothermal, unsteady, incompressible electrically conducting Power law fluid. Analytic solution have been obtained from governing continuity and momentum equations subject to appropriate boundary conditions by using Perturbation method. The Power law fluid model solution without MHD is retrieved from this proposed model on substitution . Declaration on behalf of velocity profile, volume flux, average velocity, connection of time with respect to length of the tank and requirement of time for whole drainage of fluid are acquired. Special effects of numerous emerging parameter’s on velocity profile vz and depth of the fluid in the tank are graphically presented. Keywords: Tank drainage, Power law MHD fluid, Analytical solution.

Textile heaters are made of knitted conductive yarns integrated into the fabric, making them stretchable, washable, breathable, and suitable for close-to-skin wear. The non-zero resistance in the lead wires, however, causes non-uniform power distribution, presenting a design challenge. To address this, the electrical performance of the heaters is modelled as an n-ladder resistor network. Using the finite difference method, simple, closed-form expressions are derived for networks with the power source connected to input terminals A1B1 and A1Bn, respectively. The results are exact and are used to derive approximations and design criteria. Solutions for ladder networks as presented in this paper apply to a wider class of physical problems, such as irrigation systems, transformer windings, and cooling fins.

Nuclear magnetic resonance (NMR) is a technique used for many years by chemists for elucidation of molecular structure. Technological progress over the years has enabled this technique, making it easier to use. Thus, the LF-NMR (low-field NMR) was introduced as side technique, characterized by low man-agement costs and shorter analysis time than its main counterpart. The application of 1H LF-NMR for the quantification of ethyl alcohol in different alcoholic matrices is herein described, comparing results ob-tained with this technique with those determined by a reference gascromatographic method.

In this paper is proposed an analytical technique which can be used to obtain the forced response of a cantilevered tube conveying fluid. Considering the pipe subjected to an arbitrary harmonic force either distributed or concentrated, an analytical solution is found using Green’s function method. The solution obtained of the closed form satisfies the differential equations in a classical sense. The presented method giving the exact solutions is more precise than the classical eigenfunction expansion or Galerkin’s method with no need to the eigenfunctions or eigenvalues.

The valve controlled cylinder drive system is the most common type among hydraulic applications. The nonlinear behaviour in such system is inevitable when the valve spool around its null position [1] , Leaney [2] utilised component linking method to investigate the nonlinearities in a Moog valve controlled asymmetric cylinder drive system by simulation in Fortran, in which a generalised concept is introduced and validated by comparing to the experimental results. An factor is proposed in the generalised concepts to describe the asymmetric cylinder state, which is a constant when the cylinder in extending or retracting, but numerically calculated when the valve spool in the underlap region [2]. This paper utilises the component linking method to simulate the Moog valve controlled asymmetric cylinder drive system in Matlab Simulink, and proposed an analytical solution for factor when the valve spool in the underlap region.

Compton cameras detect scattered gamma rays and estimate the distribution of gamma-ray sources. Nonetheless, crafting a camera tailored to a specific application presents formidable challenges, often necessitating the implementation of diverse image reconstruction techniques. Delving into the factors influencing these cameras can pave the way for design optimization and performance enhancement. This study introduces an inventive detector design for Compton imaging systems, building upon the achievements of prior designs. The proposed system contains eight scatterer detectors and a semiconductor absorber detector, spaced at 1 mm and 30 mm intervals, respectively. The source-to-first-scatterer-detector distance is 5 mm, with scatterer and absorber detector plates measuring 70× 70× 2.125 mm³ and 70× 70× 10 mm³, respectively. Geant4 simulation toolkit models the Compton imaging system, and an analytical method reconstructs Compton camera images. Unlike more straightforward techniques, the analytical method directly reconstructs Compton camera images by solving the equation relating to the reflected image data. This approach is implemented in the C++ programming language. The study's findings reveal that the analytical method discerns optimal conditions and parameters that significantly influence efficiency, yielding a full width at half maximum (FWHM) of 3.7 mm with an angular uncertainty of approximately 2.7 degrees at an energy level of 0.662 MeV. Compared to another experimental design employing the analytical image reconstruction approach, the FWHM value decreased by 0.7 mm. This study presents an innovative detector design and an analytical reconstruction method for Compton imaging systems, showcasing improved efficiency and accuracy.

This article presents the impact analysis of space harmonics (SH) presence on a single-sided three-phase linear induction motor, along with a comprehensive parametric investigation. The presence of SH often reduces the LIM performances. The electromagnetic phenomena are governed by Maxwell's equations associated with equivalent circuit modelling. The chosen mathematical model uses 2D formulation with magnetic vector potential A. The model implementation is performed with finite element method on Gmsh-GetDP free platform. The electromagnetic thrust is calculated in current excitation case by a numerical model (FEM) with and without term generating SH in order to highlight the effect of SH. The adaptation to voltage supply operation is obtained by equivalent electric circuits (EEC), through calculation of the operational impedance. The main objective of the study consists in a comparative exploration of SH presence using two numerical models (single and multi-harmonics), and an assessment of parameters effect on space harmonic presence and various machine characteristics such as thrust, efficiency, and power factor. The motor’s characteristics (ie: thrust, efficiency and power factor) strongly depend on parameters such as the pole pair number and conductivity. Improving the operation and maximizing the performances of such a machine for a given specification requires the use of optimization algorithms.

The determination of critical ventilation flow rate is significant for the risk control and the standard development during accidental hydrogen leakage in a confined space with hydrogen-related equipment. In this paper, an analytical model for calculating critical ventilation flow rate was proposed through the quantification and constraint solution of ventilation effect and ventilation cost. The experimental method was used to investigate the effects of nozzle diameter and stagnation pressure on diffusion and ventilation for horizontal hydrogen leakage in a cuboid chamber. Ventilations from 30m3/h to 180m3/h were carried out through the rectangular vent. It was shown that the peak concentration of the measuring point is positively correlated with the stagnation pressure and the nozzle diameter. The experimental data are used to verify the analytical model by calculating the effective ventilation time. The study demonstrates that the critical ventilation flow rate can be increased significantly at higher stagnation pressures and larger nozzle diameters. And the discrepancy of critical ventilation flow rates under different nozzle diameters will be enhanced with the increase of stagnation pressure. For the stagnation pressure of 0.4MPa, the critical ventilation flow rate under 4mm nozzle even increases by 52% relative to the 2mm nozzle.

The production of polyurethane films from bark-derived polyols requires the complete solubility of all components in the polyurethane synthesis media. In this study, a comprehensive investigation was conducted to achieve the copolymerization of black alder bark water extract-derived polyol with isocyanate for polyurethane film synthesis in THF solution. A fractionation approach using tetrahydrofuran (THF) as a solvent was employed to dissolve the extract, followed by filtration and removal of the solvent. The resulting THF-soluble fraction comprised 62±1% of the dry weight of the alder bark extract, mainly consisting of the xyloside form of the diarylheptanoid compound oregonin, along with oligomeric flavonoids and carbohydrates. The THF-insoluble fraction was the most enriched with carbohydrate compounds, followed by the crude extract and THF-soluble fraction. Another approach was aimed at obtaining bark extractives based liquid polyols suitable for producing rigid PU foams. For this purpose, oven-dried crude black alder bark water extract was liquefied with polyethylene glycol (PEG 400). The liquefaction of black alder bark and pine bark extractives was studied under different conditions, including varying temperature ranges (130-170⁰C), catalyst concentrations (0-1,5%), and bark extract content in the mixture (15-30%). The results showed that the use of sulphuric acid as a catalyst (1-1.5%) significantly improved the solubility of both extractives, enabling the attainment of extract concentrations up to 25% at 170⁰C. However, increasing the extract content beyond a certain threshold led to incomplete solubility. It was shown that the PEG-insoluble fractions consist mainly of carbohydrate components. To increase the content of biomass in liquid polyols, the effect of glycerol additions into the liquefaction agent is under study. The findings provide insights into tailoring bark-sourced polyols for polyurethane foam production through appropriate liquefaction conditions.

Analytical mechanics is the most basic discipline. The basic principles of analytical mechanics should also be applicable to general deformed objects. However, the virtual displacement principle proposed by analytical mechanics is only applicable to particle systems and rigid body systems, but not to general deformed objects. In this paper, the generalized virtual displacement principle of general deformed objects (such as, elastic objects, plastic objects, elasto-platic objects and flexible objects etc ) is derived by the method of analytical mechanics, which is also applicable to particle systems and rigid body systems. First of all, according to the method of analytical mechanics, the external force, internal force, constraint reaction force and elastic recovery force of the deformed object system under the equilibrium state are analyzed, and the concepts of virtual displacement, ideal constraint and virtual work are introduced, and the generalized virtual displacement principle (also called generalized virtual work principle) of deformed objects is proposed; secondly, vector form, coordinate component form and generalized coordinate form of generalized virtual displacement principle of deformed object are given; thirdly, as the application of the principle, the virtual displacement principle of deformed objects in plane polar coordinate system, space cylindrical coordinate system and spherical coordinate system is given; finally, a brief conclusion is drawn. This work unifies the virtual displacement principle of elastic object, plastic, elastoplastic etc deformed object systems and rigid object systems with the basic method of analytical mechanics. It is a basic principle for dealing with the static problems of deformed objects. This work also lays a foundation for the further study of the dynamics of deformed object systems.

Digital medicine based on the integration of all medical data of a particular patient, has become a reality today, thanks to information technology. Traditional medical examinations can be supple-mented by assessment results of the oxidative-anti-oxidative (OAO) status of the body [1]. Elec-trochemical sensors are able to not only determine the integral indicators of the OAO system of the body, but also to depict details of the processes occurring in the system. The main obstacle to the widespread use of electrochemical sensors in medical diagnostics is the extremely small amount of the received information in comparison with tens of thousands of known human dis-eases. The problem can be eliminated only by rethinking the purpose of electrochemical measure-ment within the framework of thermodynamics of information processes and information theory. In the information paradigm of electrochemical analysis of biological fluids, a sample is considered as an electrochemical message created by a sensor. The purpose of electrochemical measurement is to obtain information in a volume sufficient to identify the sample composition within the range of possible concentrations of its components. The fundamentals of the thermodynamics of infor-mation processes are considered and conclusions that are of practical importance for the devel-opment of electrochemical sensors and analyzers are derived. It is shown that potentiostatic con-trol of the sensor is physically impacted by the electromechanical instability of the electrical double layer, which is the main source of sensor signal noise. Estimates are of a minimum amount of an-alytical signal information required for identification of a sample of a known composition, such as a biological fluid, are provided. Examples of highly informative analytical signals for flowing and stationary samples are presented. Problems related to the visualization of such signals are noted.

The role that Colombia will play in terms of food supply in the coming years has generated a discussion on the agricultural practices implemented, specifically in the use of pesticides. Therefore, this article aims to provide a comprehensive and complete review of the status of pesticide use in the agricultural sector, highlighting the agri-food industry in Colombia. Currently, the use of pesticides has intensified throughout the world, generating a call for attention by governmental entities in terms of regulation. Colombia for the year 2019 presented a rate of use of 7.8 kg/ha of pesticides, placing it among the twenty countries with the highest rate. On the other hand, the quantities and economic benefits of exports and imports are growing steadily. Several organizations have focused their efforts on determining the health consequences that people exposed to chronic and/or acute intoxication may suffer. This has led to cases of cytogenetic, neurocognitive and physical effects, prompting governmental organizations to regulate the use of pesticides. Finally, the need to design pesticide management and handling systems that respond to the needs of producers and the sector, integrating international food safety guidelines, is identified.

The Gol'denveizer problem of a torus was studied analytically by Audoly and Pomeau (2002), and the accuracy of the Audoly and Pomeau linear law was confirmed numerically by Sun (2021). However, the law does not include the major radius R of the torus. To find the influence of the major radius, we used finite element numerical simulation to simulate different cases, and we propose a modified Audoly and Pomeau linear law for vertical deformation, which includes R. A linear law of horizontal deformation is presented as well. Our studies show that the Audoly and Pomeau linear law has high accuracy. With modified vertical and horizontal deformation, a displacement-compatible relation between them is formulated.

This study aimed at the investigation of the effect of substrate preheating on residual stress in laser powder bed fusion using a physics-based analytical model. In this study, an analytical model is proposed to predict the residual stress through the calculation of preheating affected temperature profile and thermal stress. The effect of preheating is super-positioned with initial temperature in the modeling of temperature profile using a moving heat source approach; the resultant temperature gradient is then employed to predict the thermal stress from a point body load approach. If the thermal stress exceeds the yield strength of the material, then the residual stress under cyclic heating and cooling will be calculated based on the incremental plasticity and kinematic hardening behavior of metal. IN718 is used as a material example to pursue this investigation. To validate the predicted residual stress, experimental measurements are conducted using X-ray diffraction on IN718 samples manufactured via laser powder bed fusion under different process conditions. Results showed that preheating of the substrate could reduce the residual stress in an additively manufactured part due to the reduction in temperature gradient and resultant shrinkage stresses. However, the excessive preheating could have an opposite impact on residual stress accumulation. Moreover, the results confirm that the proposed model is a valuable tool for the prediction of residual stress- eliminating the costly experiments and time-consuming finite element simulations.

Heat emitters constitute the primary devices used in space heating and cover a fundamental role in the energy efficient use of buildings. In the search for an optimized design, heating devices should be compared with a benchmark emitter with maximum heat emission efficiency. However, such an ideal heater still needs to be defined. In this paper we perform an analysis of heat transfer in a European reference room, considering room side effects of thermal radiation and computing the induced operative temperature both analytically and numerically. By means of functional optimization, we analyse trends such as the variation of operative temperature with radiator panel dimensions, finding optimal configurations. In order to make our definitions as general as possible, we address panel radiators, convectors, underfloor (UFH) and ceiling heater. We obtain analytical formulas for the operative temperature induced by panel radiators and identify the 10-type as our ideal radiator, while the UFH provides the best performance overall. Regarding specifically UFH and ceiling heaters, we find optimal sizes that identify the according ideal emitters. The analytical method and quantitative results reported in this paper can be generalized and adopted in most studies concerning the efficiency of different heat emitter types in building enclosures.

In this paper, we tackle air quality forecasting by using machine learning approaches to predict the hourly concentration of air pollutants (e.g., Ozone, PM_2.5 and Sulfur Dioxide). Machine learning, as one of the most popular techniques, is able to efficiently train a model on big data by using large-scale optimization algorithms. Although there exists some works applying machine learning to air quality prediction, most of the prior studies are restricted to small scale data and simply train standard regression models (linear or non-linear) to predict the hourly air pollution concentration. In this work, we propose refined models to predict the hourly air pollution concentration based on meteorological data of previous days by formulating the prediction of 24 hours as a multi-task learning problem. It enables us to select a good model with different regularization techniques. We propose a useful regularization by enforcing the prediction models of consecutive hours to be close to each other, and compare with several typical regularizations for multi-task learning including standard Frobenius norm regularization, nuclear norm regularization, ℓ_2,1 norm regularization. Our experiments show the proposed formulations and regularization achieve better performance than existing standard regression models and existing regularizations.

Starting with a hypothetical geostrophic zonal current in an unbounded ocean, the investigation points out the response of this simple system to a thermal forcing, applied to the free surface and consistent with the maintenance of the geostrophic balance. The main result is the formation of a meridional component of the current, according to the Sverdrup relation, such that the full velocity vector rotates clockwise for heating and anticlockwise for cooling to adjust eventually in the initial zonal direction for large depths.

In this study, we have designed a promising platform based on metal-organic frameworks (MOFs) to develop paper-based analytical devices (PADs) to immobilize biomolecules for application in biosensors. PADs have become increasingly popular in sensing applications in recent years due to their portability, low cost, simplicity, efficiency, fast detection capability, excellent sensitivity, and selectivity. In addition, MOFs are an excellent choice for developing highly sensitive and selective sensors. Their ability to reversibly and reproducibly adsorb and desorb specific molecules allows using these materials as sensors for various applications. They also offer the possibility to modify their structure and properties, making them highly versatile and adaptable to different environments and sensing needs. In this research, we synthesized and characterized three different amino-functionalized MOFs: UiO66-NH2 (Zr), MIL125-NH2 (Ti), and MIL101-NH2 (Fe). These MOFs were used to fabricate PADs capable of sensitive and portable monitoring of alkaline phosphatase (ALP) enzyme activity by laser-induced fluorescence (LIF). Overall, amino-derivated MOF platforms demonstrate significant potential for integration into biosensor PADs, offering key properties that enhance their performance and applicability in analytical chemistry and diagnostics.

We describe the development and validation of a HPLC-MS/MS method to assess the pharmacokinetics and tumour distribution of fenretinide, a synthetic retinoid chemically related to all-trans-retinoic acid, after administration of a novel oral nanoformulation of fenretinide, called bionanofenretinide (BNF). BNF was developed to overcome the major limitation of fenretinide: its poor aqueous solubility and bioavailability due to its hydrophobic nature. The method proved to be reproducible, precise, and highly accurate for the measurement of the drug and the mains metabolites. The lower limit of quantification resulted 1 ng/mL. The curve range of 1-500 ng/mL and 50-2000 ng/mL, for plasma and tumor homogenate respectively, was appropriate for the analysis, as demonstrated by the accuracy between 96.8% and 102.4% for plasma and 96.6-102.3% for tumor. The inter-days precision and accuracy determined on quality controls at 3 different levels were in ranges of 6.9%-7.5% and 99.3-101.0% and 0.96-1.91% and 102.3-105.8% for plasma and tumour, respectively.

As a new type of gear, bevoloid gears have the advantages of compensating axial error, smooth transmission, and eliminating turning error, and they are widely used in applications requiring high transmission accuracy and stability. However, research on calculating the time-varying mesh stiffness of bevoloid gears is still limited, and there is an urgent need to propose a method that can calculate the stiffness of bevoloid gears quickly and accurately. This paper first establishes the bevoloid gear tooth profile expressions, then assumes a pair of bevoloid gears meshing with the same rack and derives the contact line equations of parallel axis bevoloid gear pairs, and analyze the contact process of bevoloid gears. We propose an analytical algorithm that uses the slicing method to calculate the stiffness of helical gears, straight bevoloid gears, and helical bevoloid gears, change the parameters of helical bevoloid gears respectively, and analyze the influence of different parameters on stiffness. Finally, the finite element method is used to verify the analytical method, and the correctness of the analytical calculation results is verified, and the errors are analyzed.

The late universe contains a wealth of information about fundamental physics and gravity, wrapped up in non-Gaussian fields. To make use of as much information as possible it is necessary to go beyond two-point statistics. Rather than going to higher order N-point correlation functions, we demonstrate that the probability distribution function (PDF) of spheres in the matter field (a one-point function) already contains a significant amount of this non-Gaussian information. The matter PDF dissects different density environments which are lumped together in two-point statistics, making it particularly useful for probing modifications of gravity or expansion history. Our approach in Cataneo et. al. 2021 extends the success of Large Deviation Theory for predicting the matter PDF in ΛCDM in these “extended” cosmologies. A Fisher forecast demonstrates the information content in the matter PDF via constraints for a Euclid-like survey volume combining the 3D matter PDF with the 3D matter power spectrum. Adding the matter PDF halves the uncertainties on parameters in an evolving dark energy model, relative to the power spectrum alone. Additionally, the matter PDF contains enough non-linear information to substantially increase the detection significance of departures from General Relativity, with improvements up to six times the power spectrum alone. This analysis demonstrates that the matter PDF is a promising non-Gaussian statistic for extracting cosmological information, particularly for beyond ΛCDM models.

The conventional rolled-up model for carbon nanocones assumes that the cone is constructed from a rolled-up graphene sheet joined seamlessly, which predicts five distinct vertex angles. This model completely ignores any effects due to the changing curvature and all bond lengths and bond angles are assumed to be those for the planar graphene sheet. Clearly curvature effects will become more important closest to the cone vertex, and especially so for the cones with the smaller apex angles. Here we construct carbon nanocones which in the assembled cone are assumed to comprise bond lengths and bond angles which are, as far as possible, equal throughout the structure at the same distance from the conical apex. Predicted bond angles and bond lengths are shown to agree well with those obtained by relaxing the conventional rolled-up model using the LAMMPS software. The major objective here is not simply to model physically realisable carbon nanocones for which numerical procedures are far superior, but rather to produce an improved model that takes into account curvature effects close to the vertex, and from which we may determine an analytical formula which represents an improvement on that for the conventional rolled-up model.

For advancing manufacturing, arising AM, with an inverse philosophical approach compared to conventional procedures, has benefits that include intricate fabrication, reduced material waste, flexible design, and more. Regardless of its potential, AM must overcome several challenges due to multi-physical processes with miscellaneous physical stimuli in diverse materials systems and situations, such as anisotropic microstructure and mechanical properties, a restricted choice of materials, defects, and high cost. Unlike conventional experimental work that requires extensive trial and error resources and FEM, which generally consumes substantial computational power, the analytical approach based on physics is an exceptional choice. Understanding the relationship between the microstructure and material properties of the fabricated parts is a crucial focus in AM research. Texture is a vital factor in almost every modern industry. This study first proposed a physics-based model to foreshadow the multi-phase crystallographic orientation distribution in Ti-6Al-4V LPBF while considering the part boundary conditions due to the importance of part geometry in real industry. The thermal distribution obtained from this function operates as the information for the single-phase crystallographic texture model. In this model, we forerun and validate the orientations of single-phase materials utilizing three Euler Angles with the principles of CET and thermodynamics, as well as the intensity of the texture by approximating them with published results. Then, we transform the single-phase texture into a dual-phase texture in Bunge calculation, illustrating visualized by pole figures of both BCC and HCP phases. This texture evolution model provides a new paradigm for future researchers to model the texture or microstructure evolution semi-analytically and save many computational resources in a real-world perspective. Others have not yet done this work about simulating the multi-phase texture in an analytical approach, so this work bridges the gap in this field. Furthermore, this paper establishes the foundation for future research on materials properties affected by microstructure or texture in academic and industrial environments. The precision and dependability of the results obtained through this method make it a valuable tool for ongoing research and advancement.

This study examines stress distributions in adhesive joints under various loading and temperature conditions. Finite element analysis (FEA) was employed to compute the peel and shear stresses at the adhesive interface and bondline mid-section. Dependency analysis shows that mid-section peel stress significantly impacts the experimental shear strength of SLJs more than shear stress. This insight highlights the need to carefully analyze peel stress and bending moment factors. The analytical solutions proposed by Goland and Reissner were analyzed with modifications by Hart-Smith and Zhao. Hart-Smith’s approach performed more effectively, especially when the adhesive layer thickness (t_a) is 0.5 mm and the overlap length to thickness ratio (c/t_a) is ≥20. FEA revealed stress distributions at the adhesive/adherend interface and bondline mid-section. DP490 adhesive joints exhibited lower stresses than EA9696. Temperature variations significantly affected joint behavior, particularly above the adhesive’s glass transition temperature (T_g). Both EA9696 and DP490 adhesive joints displayed distinct responses to stress and temperature changes. The parabolic and biquadratic solutions for functionally graded adhesive (FGA) joints were compared. The biquadratic solution consistently yielded higher shear and peel stress values, with an increase ranging from 15% to 71% compared to the parabolic solution at various temperatures because of larger gradient of the Young's modulus distribution near the overlap ends. The ratio of peak peel stress to peak shear stress suggests selecting an adhesive with a superior peel strength or primarily reducing the peak peel stress by functionally grading is advisable, particularly if the adhesive is brittle. Comparison of stress distributions emphasize the importance of selecting adhesives based on stress type, temperature, and solution methods in optimizing adhesive bonding applications. These findings provide valuable insights for thermomechanical applications where thermal stimuli may be used for controlled debonding.

Leak of carbon dioxide (CO2) from conventional underground carbon storage reservoirs is an increasing concern. It is highly desirable to inject CO2 into low-temperature reservoirs so that CO2 can be locked inside the reservoir in solid state as CO2-hydrates. Marine gas hydrate reservoirs and surrounding water aquifers are attractive candidates for this purpose. However, the nature of low-permeability of these marine sediments hinders injection of CO2 in commercial scale due to the low-injectivity of wells with conventional completions. This study investigates injection of CO2 into the low-permeability marine reservoirs using a new type of well namely radial-lateral wells (RLW). An analytical model was developed for predicting CO2 injectivity of the RLW to assess well injectivity improvement. A case study and sensitivity analysis were performed with field data from the South China Sea. Result of analysis reveals that the injectivity of the RLW is nearly proportional to reservoir permeability, lateral wellbore length, and number of laterals. CO2 injection rate is predicted to be 19 tons/day to 250 tons/day, which is 3 to 15 times higher than the injectivity of frac-packed wells. It is feasible to inject CO2 into the low-permeability-low-temperature marine reservoirs at commercial flow rates. This work provides an analytical tool to predict CO2-injectivity of RLW in low-temperature marine reservoirs for leak-free CO2 storage.

Pressure-sensitive paint (PSP) has received significant attention for capturing surface pressure in recent years. One major source of uncertainty in PSP measurements, temperature dependency, stems from the fundamental photophysical process that allows PSP to extract pressure information. The motion-capturing PSP method, which involves two luminophores, is introduced as a method to reduce the measurement uncertainty due to temperature dependency. A theoretical model for the pressure uncertainty due to temperature dependency is proposed and demonstrated using a static pressure measurement with an applied temperature gradient. The experimental validation of the proposed model shows that the motion-capturing PSP method reduces the temperature dependency by 37.7% compared to the conventional PSP method. The proposed model also proves that a PSP with zero temperature dependency is theoretically possible.

The formulation and analytic solution of a new mathematical model with constitutive curvature for analysis of tunnel ventilation shaft wall is proposed. Based on the Mindlin-Reissner theory for thick shells, this model also takes into account the shell constitutive curvature and considers an expression of the shear correction factor variable (αn) in terms of the thickness (h) and the radius of curvature (R). The main advantage of the proposed model is that it has the possibility to analyze thin, medium and thick tunnel ventilation shafts. As a result, two comparisons were made: the first one, between the new model and the Mindlin-Reissner model without constitutive curvature with the shear correction factor (α_n=6/5) as a constant, and the other, between the new model and the tridimensional numerical models (solids and shells) obtained by finite element method for different slenderness ratios (h/R). The limitation of the proposed model is that it is to be formulated for a general linear-elastic and axial-symmetrical state with continuous distribution of the mass.

A hand-held laser-induced breakdown spectroscopy device was used to acquire spectral emission data from laser-induced plasmas created on the surface of cerium-gallium alloy samples with Ga concentrations ranging from 0 to 3 weight percent. Ionic and neutral emission lines of the two constituent elements were then extracted and used to generate calibration curves relating the emission line intensity ratios to the gallium concentration of the alloy. The Ga I 287.4 nm emission line was determined to be superior for the purposes of Ga detection and concentration determination.A limit of detection below 0.25% was achieved using a multivariate regression model of the Ga I287.4 nm line ratio versus two separate Ce II emission lines. This LOD is considered a conservative estimation of technique’s capability given the type of the calibration samples available and low power( 5 mJ per 1 ns pulse) and resolving power (λ/∆λ= 4000) of this handheld device. Nonetheless, the utility of the technique is demonstrated via a detailed mapping analysis of the surface Ga distribution of a Ce-Ga sample which reveals significant heterogeneity resulting from the sample production process.

In this paper we study the class of mixed-index time fractional differential equations in which different components of the problem have different time fractional derivatives on the left hand side. We prove a theorem on the solution of the linear system of equations, which collapses to the well-known Mittag-Leffler solution in the case the indices are the same, and also generalises the solution of the so-called linear sequential class of time fractional problems. We also investigate the asymptotic stability properties of this class of problems using Laplace transforms and show how Laplace transforms can be used to write solutions as linear combinations of generalisedMittag-Leffler functions in some cases. Finally we illustrate our results with some numerical simulations.

Disabled people have been all but invisible in refugee research. The same can be said of refugees in disability studies. We propose an analytical framework that integrates critical and trauma approaches to inform studies of the experiences of disabled refugees as they express their agency and engage in their communities. Critical disability theory questions the assumptions undergirding the social model that have led to “fixed” conceptions of disabled people and ignored their innate agency. By equating disability with oppression, social model proponents have argued that the emancipation of disabled people may only be achieved through shifts in oppressive structures. On the other hand, understanding how trauma affects disabled refugees helps avoid defining them simply as dependent victims and omitting or overlooking their resilience. We contend that a sociocultural understanding of trauma allows for a dynamic and contextual perspective on agency and resilience; one that challenges the “traumatized refugee” narrative. The principal claim underpinning the framework is that disabled refugees should be regarded as capable agents of change confronting contexts of continuing trauma, displacement and vulnerability. This article offers an integrative and interpretive understanding of the lived experiences of disabled refugees that highlights the possibilities inherent in their human agency.

In metropolitan regions, which are particularly vulnerable to seismic damage, numerous reinforced concrete (RC) buildings are being constructed. Public safety has been an important consideration to safeguard and protect people, buildings, and infrastructure from the potential effects of earthquakes. The assessment of seismic vulnerability within urban areas encompassed an analysis of both building vulnerability and the scale of seismic hazards prevalent in the locality. This assessment aimed to ascertain the likelihood of building damage resulting from ground motion induced by an earthquake of a specific magnitude. In recent decades, considerable efforts have been made to develop and improve methods for assessing earthquake damage to reinforced concrete (RC) buildings. These efforts included the creation of seismic hazard and seismic risk indices that were used to quantify the potential destruction of individual building components or the entire building. This scholarly review article presents an in-depth analysis and concise summary of the primary techniques (including qualitative or empirical, quantitative, analytical, and experimental test methods) devised for appraising the seismic vulnerability of reinforced concrete frame buildings, pre- and post-earthquake occurrences. It is a valuable reference for policymakers, engineers, researchers, and specialists engaged in earthquake risk mitigation efforts.

The fundamental period is one of the most important parameters for the design of new structures , as well as the estimation of the capacity of existing ones. However, its calculation requires the solution of an eigenvalue problem. Especially for new buildings, this can involve material and geometric parameters that are not known beforehand. Thus, to estimate it, various design codes and researchers have adopted a several approximate analytical equations based on a number of key structural parameters. To this end, the present study introduces a novel methodology for the derivation of analytical equations for the fundamental period of Reinforced Concrete (RC) structures. The methodology is based on Machine Learning (ML) explainability techniques and specifically the so-called SHapley Additive exPlanations (SHAP) values. The novel methodology allows these equations to be constructed sequentially and in an informed manner, controlling the balance between accuracy and complexity. An extended dataset comprised of 4026 data points is employed. The results showed excellent accuracy, with a coefficient of determination R2≈0.95. This demonstrates the potential applicability of the proposed methodology in a wide array of similar engineering challenges.

This review paper presents a comprehensive synthesis of current knowledge on the contamination of water systems by polycyclic aromatic hydrocarbons (PAHs). PAHs, organic contaminants characterized by two or more fused aromatic rings, are notably problematic due to their persistence, bioaccumulation, and significant health risks. The review commences with an examination of various sources of PAHs in aquatic environments, encompassing both anthropogenic activities, such as industrial discharges, urban runoff, and oil spills, and natural phenomena including volcanic eruptions and wildfires. Subsequently, the discussion shifts to the distribution patterns of PAHs within different aquatic ecosystems, with an analysis of factors that influence their transport. Considerable focus is placed on the entry mechanisms of PAHs into water systems and their interactions with diverse environmental matrices. Additionally, the ecotoxicological effects of PAHs on aquatic life are scrutinized, with particular emphasis on molecular, individual, and ecosystemic impacts. This includes an exploration of PAH bioaccumulation in aquatic organisms and their potential mutagenic and carcinogenic consequences. The review further addresses the challenges associated with detecting and quantifying PAHs in aquatic settings, reflecting on the advancements in analytical methodologies and the complexities introduced by their varied physicochemical properties. The paper concludes with a summary of existing regulatory frameworks and guidelines governing PAH contamination in water systems, underscoring the imperative for global collaboration in the monitoring and management of PAH pollution.

The mass of a direct-drive generator is often defined by the requirements for structural stiffness to meet the magnetic stiffness between the rotor and stator surfaces. This paper analyses this magnetic stiffness and estimates the structural stiffness of direct-drive generators for different modes of deflection. The magnetic stiffness modelling is based on an analytical model of the airgap closing forces. The final models are verified using Finite Element analysis and carried out for both permanent magnet and wound rotor generators. It shows that wound rotor machines have higher stiffness requirements than permanent magnet machines. The structural stiffness of the generator rotor and stator are evaluated for different modes by applying spatially-varying forces and finding the associated deflections. Structural stiffnesses for the rotor, stator and bearing are then combined. Finally, the magnetic and structural stiffnesses are combined and a stiffness margin can be found. For the airgap not to close, this combined stiffness must be greater than 0. This method is applied to a relatively stiff and a relatively compliant set of generator structures in a case study in order to find the optimum and more sustainable configuration.

A new approach for predicting the geometrical characteristics of the mixing behavior of an inclined dense jet for angles ranging from 15° to 85° is proposed in this study. This approach is called group method of data handling (GMDH) which is based on the artificial neural network (ANN) technique. The proposed model was trained and tested using existing experimental data reported in literature. The model was then evaluated using statistical indices as well as compared with analytical models from previous studies. The results of the coefficient of determination (R2) indicate a high accuracy of the proposed model with values of 0.9719 and 0.9513 for training and testing for the dimensionless of the distance from the nozzle to the return point xr/D, and 0.9454 and 0.9565 for training and testing for the dimensionless of the terminal rise height yt/D . Moreover, four previous analytical models were used to evaluate the GMDH model. The results showed the superiority of the proposed model in predicting the geometrical characteristics of the inclined dense jet for all tested angles. Finally, the standard error of estimate (SEE) was applied to demonstrate which model performed the best in terms of getting closer to the actual data. The results illustrate that all fitting lines of the GMDH model performed very well for all geometrical parameter predictions and was the best model with approximately 10% error, which was the lowest value of error among the models. Therefore, this study confirms that the GMDH model can be used to predict the geometrical properties of the inclined negatively buoyant jet with high performance and accuracy.

In this paper we overview all analytical engineering solutions for corrosion problems in pressure vessels delivered over the past 60 years. We briefly detail strengths and weaknesses of existing approaches, thus demonstrating the need for novel uniform corrosion analysis methods for both current and new applications. To complement the review, we also present a new analytical model allowing to estimate the lifetime of pressured elastic vessels with mechanically assisted corrosion. Both internal/external pressure and internal/external corrosion are captured and dissolution driven corrosion is also considered. The readily implemented method improves existing analytical approaches and is shown to be effective for thin and thick shells, as well as various loading and corrosion intensity and geometrical conditions.

Anti-microbial drugs and coccidiostat compounds are commonly used in poultry farming. These compounds are subsequently excreted and released into the environment via broiler litter (BL) and can re-enter the food chain as fertilizer and/or animal feed. Residues of such drugs can encourage the appearance of antibiotic-resistant bacteria (ARB), as well as toxicity, when found in animal feed. The aim of this study was to develop a multi-residue analytic method for assessing 30 an-ti-microbial drugs and coccidiostats associated with BL and investigate the effects of stacking treatment on anti-microbial and coccidiostat residue degradation in BL used for ruminant feed at the lab-scale. Today, most analytical methods used to identify and quantitate these drug residues are traditional, and may be specific to some antimicrobials. All call for lengthy sample preparation and may present limitations in assessing broiler litter. Such conventional mul-ti-anti-microbial/coccidiostat residue detection assays employ liquid-liquid extraction (LLE) and solid phase extraction (SPE) for sample purification. In our research, LLE and SPE were replaced by Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) clean-up steps for 30 an-ti-microbials and coccidiostats used in broiler farming and detection by liquid chromatography mass spectrometry (LC/MS/ MS). Using this method, recoveries were 70-120%, with the exception of norfloxacin and narasin, which showed recoveries of 67 and 68%, respectively. This analytical meth-od results show that eight samples were not detected in 42 samples, while in 34 samples, one or more drugs were present. Eighteen anti-microbial and coccidiostat residues were detected dur-ing one year sample collaction. The most frequently detected residues were narasin, nicarbazin, monensin, robenidine, oxytetracycline, chlortetracycline, norfloxacin and sulfachloropyridazine, seen at levels from 0.4 to 8.9 mg•kg-1 (ppm). Nineteen anti-microbials and one coccidiostat were degraded to 95% by the stacking treatment. However, tilmicosin and eight coccidiostats persisted in litter (26-100%). The use of antimicrobials and coccidiostats in animal farming is of paramount concern with respect to human, animal and environmental contamination issues and as a source of resistant pathogenic bacteria. Still, most farmers use BL as ruminant feed and fertilizer without processing. Even though the effects of the stacking treatments on degradation of antimicrobials were significantly high, the degradation of coccidiostats and tilmicosin was limited. Clearly, BL should be treated and supervised before use as feed supplement or for land application. Hence, the present method, designed to support these goals, was optimized in terms of sensitivity and se-lectivity for the analytes addressed.

This study investigates the application of Unmanned Aerial Vehicles (UAVs) equipped with a Micasense RedEdge-MX multispectral camera for the estimation of Secchi Depth (SD) in inland water bodies. The research analyzed and compared five sun-glint correction methodologies — Hedley, Goodman, Lyzenga, Joyce, and threshold removed glint to model the SD values derived from UAV multispectral imagery, highlighting the role of reflectance accuracy and algorithmic precision in SD modeling. While Goodman's method showed a higher correlation (0.92) with in situ SD measurements, Hedley's method exhibited the smallest average deviation (0.65 m), suggesting its potential in water resource management, environmental monitoring, and ecological modeling. The study also underscored the Quasi-Analytical Algorithm (QAA) potential in estimating SD due to its flexibility to process data from various sensors without requiring in situ measurements, offering scalability for large-scale water quality surveys. The accuracy of SD measures, calculated using QAA, was related to variability in water constituents of coloured dissolved organic matter and the solar zenith angle. A practical workflow for SD acquisition using UAVs and multispectral data was proposed for monitoring inland water bodies.

Chipless radio frequency identification (RFID) technology is expected to replace barcode technology due to its ability to read in non-line-of-sight (NLOS) situations, long reading range, and low cost. Currently, there is extensive research being conducted on frequency-coded (FC) co-polarized radar cross-section (RCS)-based tags, which are widely used. However, detecting co-polarized chipless RFID tags in cluttered environments is still a challenge, as confirmed by measuring two co-polarized tags in front of a perfect metal reflector (30.5cm×22.5cm). To address this challenge, a realistic mathematical model for a chipless RFID system has been developed that takes into account the characteristics of the reader and the tag, as well as reflections from cluttered objects. This model has been simulated and verified with measurement results by placing a single flat metal reflector behind two co-polarized one-bit designs: a dipole array tag and a square patch tag. The results showed that the interfering signal completely overlaps the ID of the co-polarized tag, severely limiting its detectability. To solve this issue, the proposed solution involves reading the tag in cross-polarization mode by etching a diagonal slot in the square patch tag. This proposed tag provides high immunity to the environment and can be detected in front of both dielectric and metallic objects.

Understanding how the public perceives various risks and hazards associated with our well-being and health is crucial for government and policymakers. The present research aimed to assess the public's perception of various risks and hazards associated with their well-being and health. The study combined two well-known approaches to risk assessment, namely, the analytical hierarchical process (AHP) and the psychometric paradigm. Seven risk attributes were chosen from the risk perception literature to evaluate 27 risks and hazard activities using a survey questionnaire developed based on the psychometric paradigm literature. The collected data was then analyzed using AHP to determine the priority weight for each risk attribute. The results showed that the most important risk attribute was voluntariness of risk, followed by chronic-catastrophic and newness of risk. Furthermore, the study found that natural hazards were ranked the highest, followed by refugee influx and fire hazards. In contrast, the mobile phone was perceived as the lowest type of risk. The findings can be used by policymakers to develop effective and sustainable risk communication strategies. Policymakers can use the research findings to create effective and sustainable risk communication strategies that help the government to inform and educate the public about potential risks, improve coordination among agencies and stakeholders, and enhance public trust in government decision-making.

A large variety of fermentation products are used in food and feed production, but also in other industries, and many of these products are produced with genetically modified microorganisms (GMMs). In food and feed production, prominent examples are amino acids, vitamins, food and feed enzymes, colorants, non-caloric sweeteners and human milk oligosaccharides. From a regulatory perspective, fermentation products are typically produced under containment. This means that premises, equipment and work processes need to be designed to prevent or at least minimize release of GMMs into the environment. The fermentation products themselves should not contain any live cells of the GMM. Over the past years, there have been concerning developments, particularly in the European Union, stipulating that also absence of recombinant DNA might be interpreted as a regulatory requirement for fermentation products produced with GMMs. In this paper, we (i) attempt to place these developments into the historical context, (ii) sketch the potential negative repercussions for the food and feed industries, (iii) elaborate on the safety of recombinant DNA, and (iv) postulate that recombinant DNA should remain an integral part of the safety assessment of fermentation products but should not be misconstrued as a criterion for regulatory classification of products of biotechnology.

Efficient and uninterrupted energy supply plays crucial role in the quality of the modern daily life, while it is obvious that the efficiency and performance of energy supply companies has significant impact on energy supply itself, and on determining and finetuning the future roadmap of the sector. In this study, the performance and efficiency of energy supply companies with respect to productivity is investigated over a case study of an electricity distribution company in Turkey. The factors affecting the company’s performance and their corresponding weights have been determined and elicited using analytical hierarchy process (AHP) and the Fuzzy AHP methods, as two well-known multi-criteria decision-making methods, which are two well-known prominent methods widely used in the literature. The results help demonstrate that the criteria elicited to evaluate the company’s energy supply performance plan a crucial role in developing strategies, policies and action plans to achieve continuous improvement and consistent development.

The energy efficiency of ice hockey arenas is a central concern for the administrations, as these buildings are well known to consume a large amount of energy. Since they are composite, complex systems, solutions to such a problem can be approached from many different areas, from managerial to technological to more strictly physical. In this paper we consider heat transfer processes in an ice hockey hall, during operating conditions, with a bottom-up approach based upon on-site measurements. Detailed heat flux, relative humidity and temperature data for the ice pad and the indoor air are used for a heat balance calculation in the steady-state regime, which quantifies the impact of each single heat source. We then solve the heat conduction equation for the ice pad in transient regime, and obtain a generic analytical formula for the temperature profile that can be used in practical applications. We then apply this formula to the resurfacing process for validation, and find good agreement with an analogous numerical solution. Since it is given with implicit initial condition and boundary conditions, it can be used not only in ice hockey halls, but in a large variety of engineering applications.

Biophoton emission has been experimented for decades. The photo-genic origin of biophoton has also been attributed to the oxidative stress or free radical production. However, there are considerable gaps in quantitative understanding of biophoton emission. In this work, I propose an analytical hypothesis for interpreting a few patterns of steady-state biophoton emission of human, including the dependency on age, the diurnal variation, and the geometric asymmetry associated with serious asymmetrical pathological conditions. The hypothesis is based on an alternative form of energy state, termed vivo-nergy, which is associated with only metabolically active organisms that are also under neuronal control. The hypothesis projects a decrease of the vivo-nergy in human during growth beyond puberty. The hypothesis also proposes a modification of the vivo-nergy by the phases of systematic or homeostatic physiology. The hypothesis further postulates that the deviation of the physiology-modified vivo-nergy from the pre-puberty level is deteriorated by acquired organ-specific pathological conditions. A temporal differential change of vivo-nergy is hypothesized to proportionally modulate oxidative stress that functions as the physical source of biophoton emission. The resulted steady-state diffusion of the photon emitted from a photo-genic source in a human geometry simplified as a homogeneous spherical domain is modeled by photon diffusion principles incorporating an extrapolated zero-boundary condition. The age and systematic physiology combined determines the intensity of the centered physiological steady-state photo-genic source. An acquired pathology sets both the intensity and the off-center position of the pathological steady-state photo-genic source. When the age-commemorated, physiology-commanded, and pathology-controlled modifications of the steady-state photo-genetic sources are implemented in the photon diffusion model, the photon fluence rate at the surface of the human-representing spherical domain reveals the patterns on age, the temporal variation corresponding to systematic physiology, and the geometric asymmetry associated with significant asymmetric pathological condition as reported for spontaneous biophoton emission. The hypothesis, as it provides conveniences for quantitative estimation of biophoton emission patterns, will be extended in future works towards interpreting the temporal characteristics of biophoton emission under stimulation.

The electric vehicle market is constantly evolving, with research and development efforts to improve motor technologies and address current challenges to meet the growing demand for sustainable transportation solutions well underway. Electric vehicles are crucial to the global initiative to reduce carbon emissions. The core component of an electric vehicle is its motor drive technology, which has seen significant advancements and diversification in recent years. Although alternating-current motors, particularly induction and synchronous motors, are widely used for their efficiency and low maintenance, direct-current motors provide high torque and cost-effectiveness advantages. This study examines various electric motor technologies used in electric vehicles and compares them using several parameters such as reliability, cost, and efficiency. This study presents a multi-criteria comparison of the various electric motors used in the electric traction system to provide a picture that enables selecting the appropriate electrical motor for the intended application. Although the permanent magnet synchronous motor appears to be the popular choice among electric car makers, the proposed comparative study demonstrates that the induction motor matches the essential requirements of electric vehicles.

The dynamic beam equations provide an analytical model and a generic solution for continuous systems. The constants for amplitudes and frequencies are given by the boundary conditions, which are here considered looped, in order to represent a closed element, by topological closure. This type of model is applied to the representation of a semicircular canal. This approach addresses the deformability of this anatomical element, both in Lagrangian solid parts (bone, membranes, intermediate materials) and in fluids (Eulerian pressure waves). The model is proposed for both physiological representation and pathology modeling. The latter is represented by a passive or retroactive singularity. An original analytical approach is thus developed for each segment, representing physiological modes – nodes and bellies - and possible disturbances. The damping entropy is also the subject of a special segmented treatment, to take account of fluid-solid interactions, providing a coherent model. The result is a simplified but robust model that both reproduces the vibro-acoustic modes of the semicircular canal and anticipates the effects of a singular pathology, such as a third window or neuritis. Mathematically, this model opens the way to structural analytical models of the inner ear, and to possible dynamic couplings between equilibration and acoustics.

The development of one technology can be portrayed by common methods like Gartner’s hype cycle or S-curve, however, there is no method to characterize the feature distributions of multiple technologies within a specific domain. This study proposes a big data-based method in terms of four proposed features, namely versatility, significance, commerciality, and disruptiveness, to characterize the technologies within a given domain. The features of technologies are quantitively portrayed using the representative keywords and volumes of returned search results from Google and Google Scholar in two-dimensional analytical spaces of technique and application. We demonstrate the applicability of this method using 452 technologies in the domain of intelligent robotics. The results of our assessment indicate that the versatility values are normally distributed, while the values of significance, commerciality, and disruptiveness follow power-law distributions, in which few technologies possess higher feature values. We also show that significant technologies are more likely to be commercialized or causing potential disruption, as such technologies have higher scores in these features. Further, we validly prove the robustness of our approach via comparing historical trends with literature and characterizing technologies in reduced analytical spaces. Our method can be widely applied in analyzing feature distributions of technologies in different domains, and it can potentially be exploited in decisions like investment, trade, and science policy.

Natural risks encompass a range of disasters and dangers, requiring comprehensive management through assessments, anticipations, and advanced alert systems. Our specific focus is on landslides in challenging terrains. The evaluation of landslide risks employs sophisticated multicriteria models, such as the weighted sum approach, integrating qualitative parameters. Despite the challenges of the rugged terrain in Northern Algeria, it paradoxically hosts a dense population attracted by valuable hydro-agricultural resources. Our research is dedicated to studying landslide risks in these areas, particularly in the Mila region, with the aim of constructing a statistical model integrating considerations of both danger and vulnerability. This complex process identifies threats and their determining factors, including geomorphology and socio-economic conditions. The result is a valuable tool for effective risk management, strengthening safety and resilience against natural disasters. By understanding the intricate interplay of geological, environmental, and social elements, our research can contribute to the development of targeted interventions, fostering a more resilient community in the face of natural adversities.

Although the empirical Kepler’s laws can be proven by applying Newton’s laws to the dynamics of two particles attracted due to the gravitational interaction, there is no explicit formula for the motion as a function of time. In this paper, a quasi-analytical solution for this problem is proposed. It approximates the real behavior of celestial bodies with an acceptable degree of accuracy. All calculations involved require a low computational cost. This problem is closely related to Kepler’s equation, since, the solution for the equations of motion as a function of time gives us the solution to Kepler’s equation as well. The results are presented for each planet of the solar system (including Pluto), and the solution is compared against the real orbits.

The presence of antibiotic residues in honey has recently become a growing public health concern due to the overuse of these products in beekeeping and their transfer to the food industry. The aim of this study was to develop and validate a simple, selective and sensitive method for the simultaneous identification and quantification of residues of twenty-two sulfonamides, trimethoprim and dapsone in honey using a rapid and reliable liquid chromatography–tandem mass spectrometry (LC–MS/MS) method. The developed method showed good linearity, specificity, precision (repeatability and intra-laboratory reproducibility) and recovery. The decision limit (CCalpha) ranged between 2.16-22.12 µg/kg for CCα, while the detection capability (CCbeta) was between 2.16- 2.67-27.36 µg/kg. The method proved to be rapid, reliable and effective for the determination of sulfonamides, trimethoprim and dapsone from honey samples. The average recoveries were estimated to be between 70 and 106%. The relative standard deviations (RSDs) were between 6-18%. In practice, the method is essential to check the honey sold on the market and ensure its safety before it reaches the consumer.

The research object was the stress-strain state of shear stud bonds in the contact joint of steel-concrete beams. The work diagrams for three types of anchors are given. Based on the analysis of numerical and full-scale experiments, analytical dependencies are proposed that reflect the actual operation of anchor ties. Comparisons of the calculation results by analytical formulas and comparisons with numerical and full-scale experiment data are given. Numerical studies have revealed the pattern of the stress-strain state of the contact joint, the stages of development of cracks in the concrete flange, and the sequence of development of deformations in anchor ties. It was revealed that vertical shear studs bonds have an increased bearing capacity, although displacements are 1.5-2 times greater than those of loop-shaped anchor ties.

In this paper, we present a new parametric class of optimal fourth-order iterative methods to estimate the solutions of nonlinear equations. After the convergence analysis, we study the stability of this class by using the tools of complex discrete dynamics. This allows us to select those elements of the class with lower dependence on initial estimations. We verify by means of numerical tests that the stable members on quadratic polynomials perform better than the unstable ones, when applied to other non-polynomial functions. We also compare the performance of the best elements of the family with known methods, such as the schemes by Newton or Chun, among others, showing robust and stable behaviour.

Scientific, technical and bioinformatics advances have made it possible to establish analytics-based molecular biosimilarity for the approval of biosimilars. If the molecular structure and other product- and process-related attributes are comparable within the limits of testing then a biosimilar candidate would have safe safety and efficacy as its reference products. The current model of animal and human testing becomes redundant since all of these studies have much lower sensitivity and reproducibility in confirming biosimilarity. The recent AI-based protein structure prediction model has confirmed that the 3D structure can be predicted from the amino acid sequence, reducing the need for structural analysis; however, the new test methods based on MS are millions of times more sensitive and accurate. While the regulatory agencies have begun waiving animal testing and, in some cases, clinical efficacy testing, removing clinical pharmacology profiling brings a dramatic paradigm shift, reducing development costs without compromising safety and efficacy. Also shared is a list of 160+ products ready to enter as biosimilars. Major actions from regulatory agencies and developers are required to make this paradigm shift.

Is it possible to quantify in General Relativity, GR, the entropy generated by supermassive black holes, BHs, during its evaporation time, since the intrinsic Hawking radiation in the infinity that, although insignificant, is important in the effects on the thermal quantum atmosphere?The purpose was to develop a formula that allows us to measure the entropy generated during the evaporation time of different types of BHs of: i. remnant BH of the binary black holes’ merger, BBH: GW150914, GW151226 and LTV151012 detected by the Laser Interferometer Gravitational-Wave Observatory (LIGO), and ii. Schwarzschild, Reissner-Nordström, Kerr and Kerr-Newman, and thus quantify in GR the “insignificant” quantum effects involved, in order to contribute to the validity of the generalized second law (GSL) that directly links the laws of black hole mechanics to the ordinary laws of thermodynamics, as a starting point for unifying quantum effects with GR. This formula could have some relationship with the detection of the shadow’s image of the event horizon of a BH.This formula was developed in dimensional analysis, using the constants of nature and the possible evaporation time of a black hole, to quantify the entropy generated during that time. The energy-stress tensor was calculated with the 4 metrics to obtain the material content and apply the proposed formula.The entropy of the evaporation time of BHs proved to be insignificant, its temperature is barely above absolute zero, however, the calculation of this type of entropy allows us to argue about the importance of the quantum effects of Hawking radiation mentioned by authors who have studied the quantum effects with arguments that are fundamentally based on the presence of the surrounding thermal atmosphere of the black hole.

Large office buildings are responsible for a substantial portion of energy consumption in urban districts. However, thorough assessments regarding the Nordic countries are still lacking. In this paper we analyse the largest dataset to date for a Nordic office building, by considering a case study located in Stockholm, Sweden, that is occupied by nearly a thousand employees.Distinguishing the lighting and occupants’ appliances energy use from heating and cooling, we can estimate the impact of occupancy without any schedule data. A standard frequentist analysis is compared with Bayesian inference, and the according regression formulas are listed in tables that are easy to implement into building performance simulations (BPS). Monthly as well as seasonal correlations are addressed, showing the critical importance of occupancy.A simple method, grounded on the power drain measurements aimed at generating boundary conditions for the BPS, is also introduced; it shows how, for this type of data and number of occupants, no more complexities are needed in order to obtain reliable predictions. For an average year, we overestimate the measured cumulative consumption by only 4.7%. The model can be easily generalised to a variety of datasets.

Land suitability analysis is a basic premise for allocating specific land for specific purpose. The objective of this study was to predict the suitable sites for cultivating Moringa oleifera tree in Ethiopia using Spatial Analytic Hierarchy Process. Findings of this study will have paramount significance in supporting decision making in the agroforestry development sector. This study employs Spatial Analytic Hierarchy Process and Geographic Information System to generate valuable information in land allocation for moringa oleifera tree production. Climate, topography, soil type and land use parameters were evaluated for suitability analysis. The results of the study revealed that most of the central part of the country are categorized as moderately suitable for the production of moringa oleifera tree. Areas classified as highly suitable are distributed along the borders of southern and western part of the country. However, some of the central part was classified as not suitable for Moringa oleifera tree production. This paper tried to investigate analysis of spatial data to predict suitable site for moringa tree production at national level. At national level, highly suitable, moderately suitable, and not suitable class covers an area of 308,508.2, 1,628,930.8 and 59891.3 Square Kilometer respectively.

Failaka Island, located in the far east of Kuwait Bay, is about 20 km from the State of Kuwait’s coast, and represents a focal point for regional geography and history, with pristine beaches and archaeological sites dating to the Bronze, Iron, Hellenistic, Christian and Islamic periods. According to environmental data and in coordination with local authorities to develop an urban plan, the island is set to become the first tourist destination for the State of Kuwait. To achieve the Vision of Kuwait 2035, one of the planning objectives focuses around Urban Planning for the Establishment of Environmental Cities that Achieve (UPEECA) environmental sustainability criteria. The paper then, aims to propose the environmental urban plan for Failaka Island. Based around Environmental Analytical Hierarchical Processes (EAHP), and using the Field Calculator and ModelBuilder functions in ArcGIS, this research centres on the feasibility of carrying out an urban plan using suitability modelling that includes four factors and 13 criteria covering the island’s ecological and human composition. This study utilizes both remote sensing (UAVs for 3D imaging) and field study (ground truthing) to identify changes in land use and land cover – such as using sample analysis of the historical sites and soils for tracing evidence and creating/updating a soil map – and create the first GIS database for the island that can lead to generating a suitability model.

This paper is concerned about the novel exact solitons to the truncated M-fractional (1+1)-dimensional non-linear generalized Bretherton model with arbitrary constants . This model is used to explain the resonant nonlinear interaction between the waves in different phenomenon, including fluid dynamics, plasma physics, ocean waves, and many others. A series of exact solitons, including bright, dark, periodic, singular, singular-bright, singular-dark, and other solitons are obtained by applying the extended sinh-Gordon equation expansion (EShGEE), and the modified (G′/G2)-expansion tech- niques. A novel definition of Fractional derivative provides the solutions distinct from the present solutions. Mathematica software is used to obtain, and verify the solutions. The solutions are shown through 2-D, 3-D, and density plots. The stability process is performed to verify that the solutions are exact and accurate. The modulation instability is used to determine the steady-state stable results to the corresponding equation.

Today, with the increase in population, technological developments, industrialization and urbanization, the problems related to waste management (WM) have become increasingly important to sustainably global clean environment. The gradual change in the quality of the elements that make up the environment, increasing environmental problems, and gaining global quality have caused societies to focus more on environmental problems. Waste management is a form of management that includes the prevention, non-prevention, reuse, recovery, and disposal of domestic, medical, hazardous, and non-hazardous wastes. In this study, it is aimed to prioritize critical success factors with the Analytical Hierarchy Process (AHP) in industrial waste management and to determine the most important critical success factor. The four main criteria and 23 sub-criteria were scored by the AHP method by five expert environmental engineers. Accordingly, after critical success factors were determined, survey questions were prepared to make employees rank these factors. While "national/local waste management strategies and policies" factor was the most important critical success factor according to experts, the most important critical success factor for employees was "enterprise waste management strategies and policies". In addition, differences in the priorities of CSFs were found in the opinions of employees in different sectors.

The chiral recognition of enantiomers is a topic of great importance. In this study, a straightforward and effective chiral detection strategy was developed for distinguishing between tryptophan (TRP) enantiomers. The approach involved the preparation of a magnetic molecularly imprinted chitosan (MMIC) for the sample preparation, which was combined with a nitrocellulose membrane (paper-based analytical device, PAD) integrated with D-TRP covalently-grafted polymethacrylic acid (PAD_PMA_D-TRP). The discrimination between TRP enantiomers was achieved using AuNPs as a colorimetric probe. Indeed, the presence of D-TRP rapidly induced the aggregation of AuNPs due to its strong affinity to PAD-PMA_D-TRP, resulting in a noticeable color change of the AuNPs from red to purple. On the other hand, L-TRP did not induce any color change. The chiral analysis could be easily performed with the naked eye and/or a smartphone. The developed method exhibited a detection limit of 3.3 µM and it was successfully applied to detect D-TRP in serum samples, demonstrating good recovery rates. The proposed procedure is characterized by its simplicity, cost-effectiveness, rapidity, and ease of operation.

This paper presents some results from a computational fluid dynamics (CFD) model of a multi-megawatt crosswind kite spinning on a circular path in a straight downwind configuration. The unsteady Reynolds averaged Navier-Stokes equations closed by the k−ω SST turbulence model are solved in the three-dimensional space using ANSYS Fluent. The flow behaviour is examined at the rotation plane, and the overall (or global) induction factor is obtained by getting the weighted average of induction factors on multiple annuli over the swept area. The wake flow behaviour is also discussed in some details using velocity and pressure contour plots. In addition to the CFD model, an analytical model for calculating the average flow velocity and radii of the annular wake downstream of the kite is developed. The model is formulated based on the widely-used Jensen’s model (Technical Report Risø-M; No. 2411, 1983), which was developed for conventional wind turbines, and thus has a simple form. Expressions for the dimensionless wake flow velocity and wake radii are obtained by assuming self-similarity of flow velocity and linear wake expansion. Comparisons are made between numerical results from the analytical model and those from the CFD simulation. The level of agreement was found to be reasonably good. Such computational and analytical models are indispensable for kite farm layout design and optimization, where aerodynamic interactions between kites should be considered.

Introduction: Heat is a kinetic process whereby energy flows from between two systems; hot-to-cold objects. In oro-dental implantology, conductive heat transfer/(or thermal stress) is a complex physical phenomenon to analyze and consider in treatment planning. Hence, ample research has attempted to measure heat-production to avoid over-heating during bone-cutting and -drilling for titanium (Ti) implant-site preparation and insertion, thereby preventing/minimizing early (as well as delayed) implant-related complications and failure. Objective: Given the low bone-thermal conductivity whereby heat generated by osteotomies is not effectively dissipated and tends to remain within the surrounding tissue (peri-implant), increasing the possibility of thermal-injury; this work attempts to obtain an exact analytical solution of the heat equation under exponential thermal-stress, modeling transient heat transfer and temperature changes in Ti implants upon hot-liquid intake. Materials and Methods: We investigate the impact of the material, the location point along implant length, and the exposure time of the thermal load on temperature changes. Results: Despite its simplicity, the presented solution contains all the physics and reproduces the key features obtained in previous numerical analyses studies. To the best of knowledge, this is the first introduction of the intrinsic time, a “proper” time that characterizes the geometry of the dental implant, where we show, mathematically and graphically, how the interplay between “proper” time and exposure time influences temperature changes in Ti implants, under the suitable initial and boundary conditions. Conclusions: This work aspires to accurately complement the overall clinical diagnostic and treatment plan for enhanced bone-implant interface, implant stability and success rates, whether for immediate or delayed loading strategies.

Socio-demography of statuses reflects the demographic and social roles and achievements of an individual(s) in a population. In the theoretical frameworks, little was known about the theory, analytical measures, and evolutionary mechanism of the socio-demographics of statuses of an individual(s). In this paper, three (3) methodological issues regarding the concept of socio-demographics were proposed, these are: (a) identified the basic features that clarify our understanding about the conception of the socio-demographic statuses of an individual(s) as common, universal, and desirable positions, achievements, and advantages every individual strives and competes to attain, achieve, maintain, update, and upgrade which are determined by biological and social environments, driven and regulated by a continuum of competitions and natural selections; (b) presented a new paradigm of analytical measures of an individual’s socio-demographic statuses and the established hierarchical transitions; (c) proposed theoretical assumptions for the evolution of a socio-demographically unique population. Seven (7) factors (the driving forces) and eight (8) conditions responsible for the evolution of socio-demographically unique populations were identified and explained. The evolutionary transitions were organized into six (6) socio-demographic ranks.

The implementation of green roofs as sustainable urban drainage systems provides benefits for stormwater control and the environment and is always more encouraged. In this paper, the estimation of the probability of vegetation survival without irrigation has been proposed as a guide to choose the proper values for the design parameters; in particular the growing medium thickness has been related to the average return interval of the water content at the end of the dry period. Moreover the study represents an improvement of the analytical probabilistic approach since a chain of consecutive rainfall events has been considered, in order to take into account the possibility that the storage capacity is not completely available at the beginning of each event because of the pre-filling from more than one previous rainfall as typically happens for green roofs. Finally, developed equations have been validated by means of their application to two case studies, respectively in northern and southern Italy.

Residual stress (RS) is the most challenging problem in metal additive manufacturing (AM) since the build-up of high tensile RS may influence the fatigue life, corrosion resistance, crack initiation, and failure of the additively manufactured components. While tensile RS is inherent in all the AM processes, fast and accurate prediction of stress state within the part is extremely valuable and would result in optimization of the process parameters in achieving a desired RS and control of the build process. This paper proposes a physics-based analytical model to rapidly and accurately predict the RS within the additively manufactured part. In this model, a transient moving point heat source (HS) is utilized to determine the temperature field. Due to the high temperature gradient within the proximity of the melt pool area, material experience high thermal stress. Thermal stress is calculated by combining three sources of stresses known as stresses due to the body forces, normal tension, and hydrostatic stress in a homogeneous semi-infinite medium. The thermal stress determines the RS state within the part. Consequently, by taking the thermal stress history as an input, both the in-plane and out of plane RS distributions are found from incremental plasticity and kinematic hardening behavior of the metal by considering volume conservation in plastic deformation in coupling with the equilibrium and compatibility conditions. In this modeling, material properties are temperature-sensitive since the steep temperature gradient varies the properties significantly. Moreover, the energy needed for the solid-state phase transition is reflected by modifying the specific heat employing the latent heat of fusion. Furthermore, the multi-layer and multi-scan aspects of metal AM are considered by including the temperature history from previous layers and scans. Results from the analytical RS model presented excellent agreement with XRD measurements employed to determine the RS in the Ti-6Al-4V specimens.

Residual stress (RS) is the most challenging problem in metal additive manufacturing (AM) since the build-up of high tensile RS may influence the fatigue life, corrosion resistance, crack initiation, and failure of the additively manufactured components. While tensile RS is inherent in all the AM processes, fast and accurate prediction of stress state within the part is extremely valuable and would result in optimization of the process parameters in achieving a desired RS and control of the build process. This paper proposes a physics-based analytical model to rapidly and accurately predict the RS within the additively manufactured part. In this model, a transient moving point heat source (HS) is utilized to determine the temperature field. Due to the high temperature gradient within the proximity of the melt pool area, material experience high thermal stress. Thermal stress is calculated by combining three sources of stresses known as stresses due to the body forces, normal tension, and hydrostatic stress in a homogeneous semi-infinite medium. The thermal stress determines the RS state within the part. Consequently, by taking the thermal stress history as an input, both the in-plane and out of plane RS distributions are found from incremental plasticity and kinematic hardening behavior of the metal by considering volume conservation in plastic deformation in coupling with the equilibrium and compatibility conditions. In this modeling, material properties are temperature-sensitive since the steep temperature gradient varies the properties significantly. Moreover, the energy needed for the solid-state phase transition is reflected by modifying the specific heat employing the latent heat of fusion. Furthermore, the multi-layer and multi-scan aspects of metal AM are considered by including the temperature history from previous layers and scans. Results from the analytical RS model presented excellent agreement with XRD measurements employed to determine the RS in the Ti-6Al-4V specimens.

Selective laser melting (SLM) is one of the widely used techniques in metallic additive manufacturing, in which high-density laser powder is utilized to selectively melting layers of powders to create geometrically complex parts. Temperature distribution and molten pool geometry directly determine the balling effect, and concentrated balling phenomenon significantly deteriorates surface integrity and mechanical properties of the part. Finite element models have been developed to predict temperature distribution and molten pool geometry, but they were computationally expensive. In this paper, the three-dimensional temperature distributions are predicted by analytical models using point moving heat source and semi-ellipsoidal moving source respectively. The molten pool dimensions under various process conditions are obtained from the three-dimensional temperature predictions and experimentally validated. Ti-6Al-4V alloy is chosen for the investigation. Good agreements between the predictions and the measurements are observed. The presented models are also suitable for other metallic materials in the SLM process.

This study explores integrating Building Information Modeling (BIM) technology into risk management practices for construction projects, aiming to enhance project performance through improved risk identification, assessment, and mitigation. The research employs the Analytical Hierarchy Process (AHP) to prioritize BIM-based strategies across multiple risk management dimensions, including technical, financial, sustainability, and time management. The findings demonstrate that BIM-financial strategies rank most among BIM-driven risk management, followed by sustainability and time. In contrast, Technical, Operation, and maintenance capabilities have the lowest rank. Given the high priority of BIM financial strategies, it has been applied to conduct sensitivity analysis; the sensitivity analysis results demonstrate the dynamic nature of BIM sub-criteria strategy in response to changes in the weight of financial considerations. As financial concerns diminish, the shift towards sustainability, health, safety, and time efficiency underscores the importance of a more balanced approach in BIM strategy prioritization. BIM- risk management improves project outcomes by enabling real-time data-driven decision-making, enhancing stakeholder collaboration, and optimizing resource use, cost control, and sustainability. This research contributes to theoretical and practical advancements in construction risk management, suggesting that BIM can be a transformative tool for optimizing project performance while addressing the complexities and uncertainties inherent in the construction industry.