A microwave-photonics method has been developed for measuring distributed acoustic signals. This method uses microwave-modulated low coherence light as a probe to interrogate distributed in-fiber interferometers, which are used to measure acoustic-induced strain. By sweeping the microwave frequency at a constant rate, the acoustic signals are encoded into the complex microwave spectrum. The microwave spectrum is transformed into the joint time-frequency domain and further processed to obtain the distributed acoustic signals. The method is first evaluated using an intrinsic Fabry Perot interferometer (IFPI). Acoustic signals of frequency up to 15.6 kHz were detected. The method was further demonstrated using an array of in-fiber weak reflectors and an external Michelson interferometer. Two piezo-ceramic cylinders (PCCs) driven at frequencies of 1700 Hz and 3430 Hz were used as acoustic sources. The experiment results show that the sensing system can locate multiple acoustic sources. The system resolves 20 nε when the spatial resolution is 5 cm. The recovered acoustic signals match the excitation signals in frequency, amplitude, and phase, indicating an excellent potential for distributed acoustic sensing (DAS).

The aim of this study was to develop a basic model to predict enteric methane emission from dairy cows and to update operational calculations for the national inventory in Norway. Basic models were developed using a database with 63 treatment means from 19 studies. The database included records for enteric CH4 production (MJ/day), dry matter intake (DMI), and dietary nutrient composition. The basic models were evaluated against an external database (n=36, from ten studies) along with other extant models. When evaluated by low root mean square prediction errors and high concordance correlation coefficients, the developed basic models that included DMI, dietary concentrations of fatty acids and neutral detergent fiber performed slightly better in predicting CH4 emissions than extant models. In order to propose country-specific values for the CH4 conversion factor Ym (% of gross energy intake partitioned into CH4) and thus to carry out the national inventory for Norway, the existing operational model was updated for the prediction of Ym over a wide range of feeding situations using energy corrected milk and dietary concentrate share as predictor variables. Input values of Ym were updated based on the results from the basic models. The predicted Ym ranged from 6.22 to 6.72%. In conclusion, the prediction of CH4 production from dairy cows was improved with the help of newly published data, which enabled an update of the operational model for calculating the national inventory of CH4 in Norway.

After a Century it is time to turn the page on understanding of lactate metabolism and appreciate that lactate shuttling as an important component of intermediary metabolism in vivo. Cell-Cell and intracellular Lactate Shuttles fulfill purposes of energy substrate production and distribution as well as cell signaling under fully aerobic conditions. Recognition of lactate shuttling came first in studies of physical exercise where roles of driver and recipient cells and tissues were obvious. Moreover, the presence of lactate shuttling as part of postprandial glucose disposal has been recognized. Mitochondrial respiration creates the physiological sink for lactate disposal in vivo. Repeated lactate exposure from regular exercise results in adaptive processes such as mitochondrial biogenesis and other healthful circulatory and neurological characteristic such as improved physical work capacity, metabolic flexibility and cognition. The importance of lactate and lactate shuttling in healthful living is further emphasized when lactate signaling and shuttling are dysregulated as occur in illness and injury. Like a Phoenix, lactate rises again in importance in 21^st Century Biology.

It is shown that the termination of the channeling of the fundamental radiation mode in the waveguide can be observed upon heating of an optical integrated circuit based on proton exchange channel waveguides formed in a lithium niobate single crystal. This process is reversible, but restoration of waveguide performance takes tens of minutes. The effect of the waveguide disappearance is observed upon rapid heating (5 °C/min) from a low temperature (minus 40 °C). This effect can lead to a temporary failure of navigation systems using fiber optic gyroscopes with modulators based on a lithium niobate crystal

Prestress loss evaluation in prestressed strand is essential for prestressed structures. However, the sensors installed outside the duct can only measure the total prestress loss. The sensors attached on strand inside the duct also have several problems, such as inadequate durability in an aggressive environment, vulnerable damage at tensioning and so on. This paper proposes a new installation method for long-gauge fiber Bragg grating (LFBG) sensor to prevent accidental damage. Then the itemized prestress losses were determined in each stage of the pre-tensioning and post-tensioning according to the LFBG measurements. We verified the applicability of the LFBG sensors for prestress monitoring and the accuracy of the proposed prestress loss calculation method during pre-tensioning and post-tensioning. In the pre-tensioning case, the calculated prestress losses had less deviation from the true losses than those obtained from foil-strain gauges, and the durability of the LFBG sensors was better than foil-strain gauges, whereas in post-tensioning case, the calculated prestress losses were close to those derived from theoretical predictions. Finally, we monitored prestress variation in the strand for 90 days. The itemized prestress losses at each stages of post-tensioning were obtained by the proposed calculation method to show the prospect of the LFBG sensors in practical evaluation.

Rigid-hulled inflatable boats are extremely practical and popular nowadays. They offer a effective conciliation among usability and costs. Their stable and seaworthy behaviour is guaranteed by performing hydroplaning hulls coupled with unsinkable inflated tubes. At the same time, their design is often based on tradition and preconceptions. Rarely, the design assumptions are validated by the reality or, even, by deeper investigations. In this article, both numerical methods and experimental mechanics techniques are proposed as an essential way for supporting the designers in their decisive tasks. Three different situations are detailed where a numerical or an experimental approach shows its benefit inside the engineering design process: firstly permitting to investigate the behaviour of materials driving the fiberglass selection; then measuring the levels of stress and strain in the hull during sailing; finally, using all available information as a base for developing numerical models of the hull slamming in waves. Even if the discussion is focused on a rigid inflatable boat, large part of its considerations is relevant beyond this special case.

A novel fiber optic sensing technology for high frequency dynamics detection is proposed in this paper, specifically tailored for structural health monitoring applications based on strain wave analysis, including both passive impact identification and active Lamb wave monitoring. The sensing solution relies on a fiber optic-based interferometric architecture associated to an innovative coherent detection scheme, which retrieves in a completely passive way the high-frequency phase information of the received optical signal. The optical fiber can be arranged into different configurations in order to meet the requirement of the specific application, the sensor sensitivity being maximized while still ensuring a limited gauge length if a local measure is required. For the active Lamb wave monitoring, this results in a sensing fiber arranged in multiple loops glued on an aluminum thin panel in order to increase the phase signal relative only to the sensing points of interest. Instead, for passive impact identification, the sensitivity is simply increased by exploiting a longer gauge length glued to the structure. The fiber optic coherent (FOC) sensor detects the strain waves emitted by a piezoelectric transducer placed on the aluminum panel or generated by an impulse hammer, respectively. The FOC sensor measurements have been compared with both a numerical model based on Finite Elements and traditional piezoelectric sensors, confirming a very good agreement between experimental and simulated results for both the active and passive impact monitoring scenarios.

Mode locked pulse generation has been reported using both active and passive mode locking schemes. Active mode locking technique has been proven to be an effective way to generate high-repetition-rate pulses by incorporating a modulator inside the laser cavity. Compared to actively mode locked lasers, passively mode locked lasers can generate pulse train at ultrashort pulse width but with relatively lower repetition rate. Thus, it is a brilliant idea to build a hybrid mode locked system combining both active and passive mode lockers. In this review, several hybrid mode locked fiber ring laser systems are discussed and summarized. Hybrid mode locking is a promising method to generate high speed ultrashort optical pulses for fiber-optic telecommunication system.

The objective of the this study was to reduce the benzo[a]pyrene-induced hepatotoxicity method in herbal medicine products and to give proof that neferine, daidzein, genistein possess antihepa-totoxic effects. B[a]P which classified as a group 1 carcinogen and metabolized to B[a]P-7,8-dihydrodiol-9,10-epoxide (BPDE) causes mutagenic DNA addition products. The reduc-tion of BPDE-DNA adduct formation by B[a]P-7,8-dihydrodiol-9,10-epoxide (BPDE) was derived by benzo[a]pyrene (B[a]P). In HepG2 cells, B[a]P exhibited toxicity and substance treatment of the cells with B[a]P with neferine in lotus and daidzein, genistein in soybean reduced the BPDE-DNA ad-ducts level. The level of B[a]P-metabolites in the substance treatment of the cells was presented that BPDE levels were reduced by neferine in lotus and daidzein, genisten in soybean. These results suggest that neferine in lotus and daidzein, genistein in soybean prevent B[a]P-induced hepato-toxicity for BPDE-DNA adduct formation.

BackgroundThe use of antimicrobials to treat food animals may result in antimicrobial residues in foodstuffs of animal origin. The European Medicines Association (EMA) and World Health Organization (WHO) define safe antimicrobial concentrations in food based on acceptable daily intakes (ADIs). It is unknown if ADI doses of antimicrobials in food could influence the antimicrobial susceptibility of human-associated bacteria. ObjectivesThis aim of this study was to evaluate if the consumption of ADI doses of erythromycin could select for erythromycin resistance in a Galleria mellonella model of Streptococcus pneumoniae infection. Methods A chronic model of S. pneumoniae infection in G. mellonella larvae was used for the experiment. Inoculation of larvae with S. pneumoniae was followed by injections of EMA (0.0875 μg/ml) and WHO (0.012 μg/ml) ADI doses of erythromycin proceeded by isolation of S. pneumoniae colonies on selective agar plates. Minimum inhibitory concentrations (MICs) of resistant colonies were measured, and whole genome sequencing (WGS) was performed followed by variant calling to determine the genetic modifications.   Results Exposure to single doses of both EMA and WHO ADI doses of erythromycin resulted in the emergence of erythromycin resistance in S. pneumoniae. Emergent resistance to erythromycin was associated with a mutation in rplA. Conclusion In our in vivo model, even single dose of erythromycin that are classified as acceptable by the WHO and EMA induced significant increases in erythromycin MICs in S. pneumoniae. These results suggest the need to include the induction of antimicrobial resistance (AMR) as a significant criterion for determining ADIs.

Monitoring the integrity of aeronautical structures is fundamental for safety. Structural Health Monitoring Systems (SHMS) perform real-time monitoring functions, but their performances must be carefully assessed. In this work the damage detection performances of a strain-based SHMS, were evaluated on a composite helicopter rotor blade root. The SHMS monitored the bonding between the central core and the surrounding antitorsional layer. A damage detection algorithm was trained through Finite Element analyses performed on the component. The effects of the loads variability and of damages were decoupled by including a load recognition step in the algorithm. Load recognition was accomplished in different ways: version#1 adopted an Artificial Neural Network (ANN) trained on blades in pristine condition; version#2 was trained also on damaged blades; version#3 adopted a calibration matrix method. Anomaly detection, damage assessment, and localization were performed by using an ANN. Results showed a higher load identification and anomaly detection accuracy for version#1 and version#2 compared to version#3. Gaussian noise reduced anomaly detection and damage assessment performances, and reduced damage localization accuracy for bigger damages. The damage detection performance were obtained for a fibre optic based-SHMS, including the trade-off between probability of detection and false alarm rate for different damage sizes.

The gastrointestinal tract is colonized by trillions of different microorganisms, named the gut microbiota, which is key to degrade undigested food such as dietary fibers. The fermentation of these food components leads to the production of short-chain fatty acids (SCFA) acetate, propionate, and butyrate, which exploit several beneficial roles for the host’s health. Their production and absorption happen in different ways in the human intestine and depend on the type of dietary fiber reaching the gut and the microorganisms involved in the fermentation. The supplementation of SCFAs, mostly butyrate, in treating gastrointestinal, metabolic, cardiovascular, and gut-brain-related diseases has been reported in the medical literature. This review aims to give an overview of the production and absorption dynamics of acetate, propionate, and butyrate in the human gut, with a final focus on the role played by these SCFAs on gastrointestinal and metabolic health and the present therapeutic implications.

A micro-ring resonator structure was fabricated via two-photon polymerization (2PP) technique directly on a single-mode fiber tip and tested for refractive index sensing application. The micro-ring structure was used to excite whispering gallery modes (WGMs) and observations of the changes in resonance spectrum introduced by changes in refractive index of the environment served as the sensing principle. The proposed structure has the advantages of a very simple design, allowing for measurements in reflection mode, relatively easy and fast fabrication and integration with a single tip of a standard single-mode fiber, which allowed for quick and convenient measurements in the optical setup. The performance of structure was characterized, resonant spectrum giving high potential for refractive index sensing was measured. Future perspectives of the research are discussed.

The use of additive manufacturing in fabricating composite components has been gaining traction in the past decade. However, some issues with mechanical perfor-mance still need to be resolved. The issue of material porosity remains a pertinent one that needs more understanding to be able to determine viable solutions. Different re-searchers have examined the subject of porosity issues in AM-fabricated CFRP compo-sites. However, more research to quantitatively determine the effects of fabrication temperatures at the micro-scale is still needed. This study employed micro CT scan analysis to quantitatively compare the effects of fabrication temperatures at 230°C, 250°C, 270°C, and 290°C for CF-PA and CF-ABS composites. This followed an SEM evaluation which was used to determine the effects of the temperatures on interlayer and intralayer porosity generation. The porosity volume was related to the mechanical properties results in which it was determined how deposition temperatures affect the porosity volumes. It was also determined that semicrystalline composites are generally more affected by fabrication temperatures than amorphous composites, with the rela-tionship between porosity and mechanical properties also established. The overall po-rosity volume from the interlayer and intralayer voids was also determined, with the interlayer voids found to play a more determinant role in influencing the mechanical properties.

Environmental monitoring is an important topic and serves a vibrant scientific role by revealing long-term trends that can lead to new knowledge and understanding. Globally, there is active development of photonic sensors incorporating multidisciplinary research. The ultimate objective is to develop small, low-cost, sensitive, selective, quick, durable, remote-controllable sensors that are resistant to electromagnetic interference. Different photonic sensor designs and advances in photonic frameworks have shown the possibility to realize these capabilities. In this review paper, the latest developments in the field of optical waveguide and fiber-based sensors which can serve for environmental monitoring are discussed. Several important topics such as toxic gas, water quality, indoor environment, and natural disaster monitoring are reviewed.

Residual stresses in fiber metal laminates (FML) inevitably develop during the manufacturing process. The main contributor to these stresses is the difference in the coefficients of thermal expansion (CTE) between fibers and metal in combination with high process temperatures. To quantify these stresses, the use of specimens with an asymmetric layup is an easily adaptable method. The curvature that develops after the manufacturing of flat laminates with an asymmetrical layer stack is a measure of the level of residual stresses evolving during cure. However, the accuracy of the curvature evaluation is highly dependent on specimen design and other influencing parameters. In this work a large set of FML specimens is investigated to identify relevant influencing parameters and derive conclusions about specimen design and evaluation techniques. For certain layups and process parameters, there is a good correlation between the curvature and the stress-free temperature, which is further covered by analytical solutions for bimetals. This correlation is the basis to transfer curvature into a stress-free temperature that can consequently be used for the quantification of residual stress levels in more complex FMLs. The transfer is validated by in-situ strain measurements during cure using a strain gage technique. Based on the results, the application of asymmetric specimens for residual stress characterization in more complex laminates is presented in the form of a workflow.

Structural health monitoring of lightweight constructions made of composite materials can be performed using guided ultrasonic waves. If modern fiber metal laminates are used, this requires integrated sensors that can record the inner displacement oscillations caused by the propagating guided ultrasonic waves. Therefore, we have developed a robust MEMS vibrometer that can be integrated with structural and functional compliance. This vibrometer is directly sensitive to the high-frequency displacements from structure-borne ultrasound when excited between its first and second natural frequency. The vibrometer is mostly realized by processes earlier developed for a pressure sensor but with additional femtosecond laser ablation and wafer bonding. The piezoresistive transducer made from silicon is encapsulated between top and bottom glass lids. The natural frequencies are experimentally determined using an optical micro vibrometer setup. The vibrometer functionality and usability for structural health monitoring are demonstrated on a customized test rig by recording application-relevant guided ultrasonic wave packages with a central frequency of 100 kHz at a distance of 200 mm from the exciting ultrasound transducer.

The work presents an approach to instrument the load sensing bearings for automotive applications for estimation of the loads acting on the wheels. The system comprises fiber-optic sensors based on addressed fiber Bragg structures (AFBS) with two symmetrical phase shifts. A mathematical model for load-deformation relation is presented, and the AFBS interrogation principle is described. The simulation includes (i) modeling of vehicle dynamics in a split-mu braking test, during which the longitudinal wheel loads are obtained, (ii) the subsequent estimation of bearing outer ring deformation using a beam model with simply supported boundary conditions, (iii) the conversion of strain into central wavelength shift of AFBS, and (iv) modeling of the beating signal at the photodetector. The simulation results show that the estimation error of the longitudinal wheel force from the strain data acquired from a single measurement point was 5.44% with root-mean-square error of 113.64 N. A prototype load sensing bearing was instrumented with a single AFBS sensor and mounted in a front right wheel hub of an experimental vehicle. The experimental setup demonstrated comparable results with the simulation during the braking test. The proposed system with load-sensing bearings is aimed at estimation of the loads acting on the wheels, which serve as input parameters for active safety systems, such as automatic braking, adaptive cruise control, or fully automated driving, in order to enhance their effectiveness and safety of the vehicle.

In this article, we prove an orthogonal decomposition theorem for real inner product gyrogroups, which unify some well-known gyrogroups in the literature: Einstein, M\"{o}bius, Proper Velocity, and Chen's gyrogroups. This leads to the study of left (right) coset partition of a real inner product gyrogroup induced from a subgyrogroup that is a finite-dimensional subspace. As a result, we obtain gyroprojectors onto the subgyrogroup and its orthogonal complement. We construct also quotient spaces and prove an associated isomorphism theorem. The left (right) cosets are characterized using gyrolines (cogyrolines) together with automorphisms of the subgyrogroup. With the algebraic structure of the decompositions, we study fiber bundles and sections inherited by the gyroprojectors. Finally, the general theory is exemplified for the aforementioned gyrogroups.

The enormous diversity of hair fibers found in human population is striking, while the basic structure of human fibers is often the same! But why do some fibers curl? Curling is related to the machinery and processes that produce different keratin filament orientation in relation to the axis of hair growth, influenced by developmental and molecular control. It is established that a curly hair shaft is produced by a curved hair follicle that have an angulated dermal implantation, with a bulb bent in the shape of golf club, while the outer root sheath is dissymmetrical; have an outer side that is convex bulging and thin and a concave side in which the cells express alpha-smooth muscle protein reflecting internal mechanical force. Yet, the exact cause of hair curling is not known. All the previous studies were short of impacting curly hair treatment. My hypothesis is that the curling mechanical force is generated by a hypersensitive contracted Arrector Pili muscle (APM) of the hair follicle. In curly hair, each APM fiber is shortened; pulling its attachment spot upward towards the epidermis and obliquely or laterally; curling the outer root sheath to produce the curved follicle described above. This contraction has the influence at a time when the young hair root is being formed and keratin microfibrils are being oriented and packed. APM is a multi-unit muscle wherein each fiber contracts independently to create the enormous diversity of curly hair types. APM contraction can be modulated by oral administration of selective smooth muscle relaxing treatment that relax the curved follicle from within. Further studies are needed to confirm the role of APM in shaping curly hair follicle including AI studies, i.e., computer-aided target identification to demonstrate APM active site that can interact with herbal small molecules.

Maritime surveillance technology faces challenges of astronomical size in this vast ocean world—challenges vital to global security and environmental protection alike. Such as these may be reversible or not. Remotely sensed monitoring also uses photos taken from satellites, synthetic aperture radar (SAR) equipment, and unmanned aerial vehicles (UAVs) to fully monitor maritime activities but also ferret out suspicious behaviour like piracy, bootleg shipments, and illegal fishing. This mixed-method approach--quantitatively and qualitatively——measures the efficiency of difficulties associated with, and legal implications behind aerospace-monitored maritime surveillance. The results show that remote sensing provides a great deal of sea-level situational awareness; however, there are also many complex technical, operational, and legal issues, including information overcrowding, complications in integration, privacy issues, as well as the need for worldwide legal harmonisation. It ends with recommendations on ways to ultimately increase capacity, how to write standard procedures for secondary development and proposals for revising laws to absorb these new technologies. Its goal, therefore, is to benefit the global anti-maritime crime effort. Ultimately, though, it dreams that we might construct an entirely marine environment where all marine activities are conducted both safely and freely, without fear.

Recently, Gohar et al. introduced a novel, local, and well-behaved fractional calculus. It possesses all the classical properties, and Its locality imposes simplicity and accuracy in modeling fractional order systems. In this article, we further develop the definitions and extend the classical properties of Gohar fractional calculus to address some of the open problems in Calculus. The fractional Gronwall's integral inequality, Taylor power series expansion, and Laplace transform are defined and applied to overcome some of the limitations in the classical integer-order calculus. The fractional Laplace transform is applied to solve Bernoulli-type logistic and Bertalanffy nonlinear fractional differential equations, and the criteria under which it can be applied to solve linear differential equations are investigated.

Obesity is a complex disease increasing risk of other pathologies. Its prevention or long-term weight loss maintenance is problematic. Gut microbiome is considered a potential obesity modulator. The objective of the present study was to summarize recent findings regarding relationships between obesity, gut microbiota and diet, with emphasis on dietary fiber and resistant starch. Composition of the human gut microbiome and methods of its quantification are described. Products of the gut microbiome metabolism, such as short-chain fatty acids and secondary bile acids including their effects on the gut microbiota, intestinal barrier function and immune homeostasis are discussed in the context of obesity. Importance of dietary fiber and resistant starch is emphasized as far as effects of the host diet on the composition and function of the gut microbiome are concerned. Complex relationships between human gut microbiome and obesity are finally summarized.

Rapidly digestible starch can be obtained by gelatinization (cooking), cooking extrusion, use of small granule starch, breaking down starch granules, or by hydrolysis to maltodextrins. Resistant starch includes five groups: the first group is physically encapsulated starch within a food/polymer matrix, the second one is some native starch, the third one is recrystallized starch, the fourth one is chemically modified starch, and the fifth one is starch-lipid complexes. Starch digestion in the human body is also influenced by the degree of chewing, activity of α-amylase in the intestine, and transit time through the stomach and small intestine. Resistant starch or dietary fiber (DF) enriches specific bacterial groups located in the large intes-tine. They produce short chain fatty acids (SCFAs) and gases, causes the lowering of the pH, and inhibits pathogens. SCFAs are considered endogenous signaling molecules, acting through their free fatty-acid receptors 2 and 3 which can trigger the secretion of glucagon-like peptide-1 and peptide PYY, being released together following a meal to mediate postprandial satiety. A sufficient intake of DF reduces the risk of cardiovascular disease, coronary heart disease, stroke, hyperten-sion, colorectal cancer, and type 2 diabetes. Gluten matrix or phenolic compounds can lead to a low digestion rate of starch.

The global textile sector, pivotal to economic development, significantly contributes to environmental degradation, prompting a shift towards sustainable raw material sources. Embracing circular economy principles, this industry is exploring the valorization of agricultural by-products. This study introduces an innovative approach to repurposing mango waste into valuable textile fibers, a byproduct of the fruit processing industry, predominantly generated during juice and jam production. The focus is on the lignocellulosic constituents of mango waste, specifically the peel, seed, and fibrous material, traditionally considered as refuse. Previous research has predominantly utilized mango peel in pectin extraction for food applications, whereas the potential of seed and fibrous content remains underexplored. This investigation endeavors to transform these fibrous by-products into high-value materials suitable for textile manufacturing. The process involved washing, drying, and comprehensive physicochemical characterization of mango fibers, emphasizing lignin quantification, revealing a composition of 12.2% lignin. An experimental design was employed to elucidate the impact of variables such as liquid-to-solid ratio, reaction duration, and sodium hydroxide concentration on lignin dissolution through alkaline hydrolysis. Optimal conditions—10% NaOH concentration, 30 mL/g liquid-to-solid ratio over six hours—achieved an 83% reduction in lignin content. The resulting fibers exhibited properties akin to conventional natural fibers, including a favorable aspect ratio indicative of their suitability for textile applications. A subsequent softening process using propylene glycol enhanced the fibers' spinability, producing a durable, textured fabric ideal for eco-conscious fashion applications, including bags, footwear, and accessories. This research demonstrates the feasibility of converting mango waste into a textile-worthy material and underscores the importance of waste revalorization in promoting sustainability within the circular economy framework.

In the process of use and manufacture, carbon fiber foam sandwich structures were often damaged by low-energy impact, resulting in performance degradation. Therefore, it was necessary to study the damage caused by low-speed impact of composite sandwich structures. In this paper, based on Hashin failure criterion, an equivalent finite element model of carbon fiber foam sandwich panel under low velocity impact was established. The model was used to simulate the damage of foam sandwich panel with [±45°/±45°/ (core) /±45°/±45°] ply structure under the impact energy of 10.58J, 21.17J, 31.75J and 42.34J. The simulation results of impact damage depth were compared with the experimental results. The error was less than 10%, which proved the rationality of the impact equivalent model. The model was used to predict and analyze the damage of foam sandwich panels with [±45°/ (core) /±45°], [±45°/ (0°, 90°) / (core) /±45°] and [±45°/ (0°, 90°) (core) / (0°, 90°) /±45°] ply structures under 21.17J impact energy. By comparing and analyzing the damage situation, impact force response time and impact velocity response time, the low energy impact resistance was analyzed. The results showed that increasing the number of ply structure of [±45°] can reduce the impact damage degree and improve the bearing capacity of sandwich panels.

Abstract: In recent years, the construction engineering sector has undergone a transformative shift towards the integration of machine learning (ML) techniques, particularly in predicting the properties of steel fiber-reinforced concrete (SFRC). Despite the theoretical sophistication of existing models, a persistent challenge remains – their opacity, lacking transparency and real-world relevance for practi-tioners. To address this gap and advance our current understanding, this study employs the extra gradient (XG) Boosting algorithm, crafting a comprehensive ap-proach. Grounded in a meticulously curated database drawn from 43 seminal pub-lications, encompassing 420 distinct records, this research focuses predominantly on three primary fiber types: crimped, hooked, and mil-cut. Complemented by hands-on experimentation involving 20 diverse SFRC mixtures, this empirical campaign is further illuminated through the strategic use of Partial Dependence Plots (PDPs), revealing intricate relationships between input parameters and con-sequent compressive strength. A pivotal revelation of this research lies in the identification of optimal SFRC formulations, offering tangible insights for real-world applications. The developed ML model stands out not only for its sophistication but also its tangible accuracy, evidenced by exemplary performance against inde-pendent datasets, boasting a commendable mean target-prediction ratio of 99%. To bridge the theory-practice gap, we introduce a user-friendly digital interface, thri-ughly designed to guide professionals in optimizing and accurately predicting the compressive strength of SFRC. This research thus contributes to the construction and civil engineering sectors by enhancing predictive capabilities and refining mix designs, fostering innovation, and addressing the evolving needs of the industry.

The wavelet spectral characteristics of three respiratory muscle signals (Scalenus (SC), Parasternal intercostal (IC) and Rectus abdominis (RA)) and one locomotor muscle Brachioradialis (BR) were analyzed in the time-frequency (T-F) domain during breath-holding (BH). Study was performed for an end-expiratory BH maneuver on twelve healthy, physically active, naive apneists (6 professional athletes; 6 recreational athletes, two in the post-COVID-19 period) using surface electromyography (sEMG). We observe individual effects dependent on muscle oxygenation and person’s fitness, consistent with the mechanism of motor unit (MU) recruitment and the transition of slow-twitch oxidative (type 1) to fast-twitch (oxidative) glycolytic (type 2) muscle fibers. Professional athletes had longer BH duration (BHD) and strong hypercapnic response on expiratory RA, which is activated abruptly at higher BHDs in a person-specific range below 250 Hz and dependent on BHD. This is in contrast with recreational athletes, who had strong hypoxic response on inspiratory IC, which is activated faster and gradually in the frequency range of 250-450 Hz (independent of the apneist and BHD). This pilot study preliminarily indicates that it is possible to non-invasively assess the physiological characteristics of skeletal muscles, especially oxygenation, and improve physical fitness tests by determining T-F features of elevated myoelectric IC and RA activity during BH.

The utilization of Fiber Bragg Grating (FBG) sensors in innovative optical sensor networks has displayed remarkable potential in providing precise and dependable thermal measurements in hostile environments on Earth. Multi-Layer Insulation (MLI) blankets serve as critical components of spacecraft and are employed to regulate the temperature of sensitive components by reflecting or absorbing thermal radiation. To enable accurate and continuous monitoring of temperature along the length of the insulative barrier without compromising its flexibility and lightweight, FBG sensors can be embedded within the thermal blanket, thereby enabling distributed temperature sensing. This capability can aid in optimizing the thermal regulation of the spacecraft and ensuring the reliable and safe operation of vital components. Furthermore, FBG sensors offer several advantages over traditional temperature sensors, including high sensitivity, immunity to electromagnetic interference, and the ability to operate in harsh environments. These properties make FBG sensors an excellent option for thermal blankets in space applications, where precise temperature regulation is crucial for mission success. Nevertheless, the calibration of temperature sensors in vacuum conditions poses a significant challenge due to the lack of an appropriate calibration reference. Therefore, this paper aims to investigate innovative solutions for calibrating temperature sensors in vacuum conditions. The proposed solutions have the potential to enhance the accuracy and reliability of temperature measurements in space applications, which can enable engineers to develop more resilient and dependable spacecraft systems.

The new climate law introduces a policy of sustainable construction, the assumption of which is the reduction of CO2 by the construction industry and the use of environmentally friendly materials, such as agricultural, mineral, and recycled waste, while limiting the consumption of natural resources. The article is a literature review that analyzes selected waste materials from various sectors of the economy that can be used as additives or partial substitutes for natural resources in the production of cement and in and cement building materials, the production of which reduces CO2 emissions, producing materials with high mechanical strength and environmentally friendly.

Retinal findings may change in patients with obstructive sleep apnea syndrome (OSAS). The present study aims to evaluate several retinal findings such as macula layer thickness, peripapillary retinal nerve fiber layer, and the optic nerve head in patients with OSAS using optical coherence tomography (OCT) and monitor the result of several types of treatment of OSAS with OCT. A prospective comparative study was designed. Patients were recruited at a Sleep Unit of a University Hospital and underwent comprehensive ophthalmological examinations. Following exclusion criteria, fifty-two patients with OSAS were finally included. Patients were examined by OCT twice: first, before treatment; secondly, after six months of treatment. In mild-moderate patients, where retinal swelling has been demonstrated, retinal thicknesses decreased [fovea (p=0.026), as well as inner ring macula (p=0.007), outer ring macula (p=0.015), and macular volume (p=0.015)]. In severe patients, where retinal atrophy had been observed, retinal thickness increased [fovea (p<0.001)]. No statistically significant differences in efficacy between treatments were demonstrated. In conclusion, OCT can evaluate the retina in patients with OSAS and help monitor results after treatment. In severe OSAS, retinal thickness increased six months after treatment.

This paper focuses on parametric model order reduction (PMOR) of guided ultrasonic wave propagation and its interaction with damage in a fiber metal laminate (FML). Structural health monitoring in FML seeks to detect, localize and characterize the damage with high accuracy and minimal use of sensors. This can be achieved by the inverse problem analysis approach which employs the signal measurement data recorded by the embedded sensors in the structure. The inverse analysis requires to solve the forward simulation of the underlying system several thousand times. These simulations are often exorbitantly expensive and triggered the need for improving their computational efficiency. A PMOR approach hinged on the proper orthogonal decomposition method is presented in this paper. An adaptive parameter sampling technique is established with the aid of a surrogate model to efficiently update the reduced-order basis in a greedy fashion. A numerical experiment is conducted to illustrate the parametric training of the reduced-order model. The results show that the reduced-order solution based on the PMOR approach is accurately complying with that of the high fidelity solution.

Rail transit tunnels span long distances, are large-scale structures and pass through complicated geological conditions; thus, the risk of uneven settlement cannot be ignored. To address this issue, a method for diagnosing the uneven settlement of regional railway tunnels based on the spatial correlation of high-density strain measurement points is proposed in this study. First, distributed optical fiber sensing technology is implemented to obtain a massive amount of strain data from densely distributed measurement points along regional railway tunnels, and a method for determining the intervals of strain measurement points with strong spatial correlations is proposed based on a support vector machine. Second, combined with the statistical analysis of the influence range of the uneven settlement of a tunnel, an algorithm for diagnosing the uneven settlement of regional railway tunnels based on the spatial correlation of high-density strain measurement points is proposed; this approach realizes the accurate identification of the uneven settlement area of long-distance urban railway tunnels. Finally, the effectiveness of the proposed method is verified by numerical simulation and actual tunnel data.

A new optical steganography scheme is proposed that transmits a stealth optical code-division multiple-access (OCDMA) signal through a public binary phase-shift keying (BPSK) channel. Polarization beam splitters and arrayed waveguide gratings are used to implement a spectral-polarization coding (SPC) system with an incoherent optical source. We employ a Walsh–Hadamard code as the signature code of the user who wants to transmit stealth information using the system. A free space optical link applied to this system maintains the polarization states of light during propagation. The secret data is extracted using correlation detection and balanced subtraction in the OCDMA decoder of the intended receiver, and the other signal from the public channel is reduced by the OCDMA decoder. At the demodulator of the public channel, BPSK demodulation eliminates the stealth signal so that the public channel is not affected by the stealth signal. The two signals cannot interfere with each other. The results of this study show that our proposed optical steganography system is highly secure. The stealth signal can be favorably hidden in the public channel when the average source power of the stealth signal, public noise, and public signal are −5, −3, and 0 dBm, respectively.

A multiscale (micro-macro) approach is proposed for the establishment of the full thermal and induced stress fields in cracked composites that are subjected to heat flow. Both the temperature and stresses distributions are determined by the solution of a boundary value problem with one-way coupling. In the micro level and for combined thermomechanical loading, a micromechanical analysis is employed to determine the effective moduli, coefficients of thermal expansion and thermal conductivities of the undamaged composite. In the macro level, the representative cell method is employed according to which the periodic damaged composite region is reduced, in conjunction with the discrete Fourier transform, to a finite domain problem. As a result, a boundary value problem is obtained in the Fourier transform domain which is appropriately discretized and solved. The inverse transform and an iterative procedure provide the full thermal and stress fields. The proposed method is verified by comparisons with exact solutions. Applications are given for the determination of the thermal and stress fields in cracked fiber-reinforced polymeric composite, cracked porous ceramic material and cracked periodically layered ceramic composite caused by the application of heat flow. The presented formulation admits however the application of a combined mechanical and heat flux on cracked composites.

Structural deformations are one of the most significant factor that affects machine tool (MT) positioning accuracy. These induced errors are complex to be represented by a model, nevertheless they need to be evaluated and predicted in order to increase the machining performance. This paper presents a novel approach to calibrate a machine tool in real-time, analyzing the thermo-mechanical errors through Fibre Bragg Grating (FBG) sensors embedded in the MT frame. The proposed configuration consists of an adaptronic structure of passive materials, Carbon Fibre Reinforced Polymers (CFRP), equipped by FBG sensors that are able to measure in real-time the deformed conditions of the frame. By using a proper thermo-mechanical kinematic model, the displacement of the end effector may be predicted and corrected when it is subjected to external undesired factors. By starting from a set of FE simulations to develop a model able to describe the MT structure stresses, a prototype has been fabricated and tested. The scope was to compare the numerical model with the experimental tests using FBG sensors. The experimental campaign has been performed varying the structure temperature over time and measuring the tool tip point (TTP) positions. The obtained results showed a substantial matching between the real and the predicted position of TTP confirming the effectiveness of the proposed calibration system.

Throughout this paper the impact of anxiety on adolescent athlete’s is highlighted through analyzing neurological and psychological aspects involved in sports performance. The neuroanatomy and neuropsychology of the human brain plays a major role in developing athlete’s that has only begun to be analyzed within recent years. Especially in young athletes, there are numerous factors that affect performance on the field that originate from the environment and training the adolescent athlete is involved in. Sports performance is viewed as a major physical factor such as training and lifting weights, however the psychological aspect of sports performance often goes unnoticed. Athletes can begin to develop mental fatigue and anxiety which inevitably can decrease their ability to perform. The athlete’s internal suffering begins to go unnoticed, as the only tangible factor is watching their performance decrease. This causes the athlete to push themselves further in training resulting in greater mental fatigue. This paper emphasizes the numerous factors neurologically that play a role in athletic performance which should be focused on in adolescent athletes as they navigate the challenges and competition that are apparent within athletics. It is critical to understand the processes and hormonal changes the body undergoes with training and playing a sport, this information can change the way adolescent sports are approached and advanced.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by memory loss and progressive deterioration of cognitive functions. Being able to identify reliable biomarkers in easily available body fluids such as blood plasma is vital for the disease. To achieve this, we used a technique that applied human plasma to organotypic brain slice culture via microcontact print-ing. After a 2-week culture period, we performed immunolabeling for neurofilament and myelin oligodendrocyte glycoprotein (MOG) to visualize newly formed nerve fibers and oligodendro-cytes. There was no significant change in the number of new nerve fibers in the AD plasma group compared to the healthy control group, while the length of the produced fibers significantly de-creased. A significant increase in the number of MOG+ dots around these new fibers was detected in the patient group. According to our hypothesis, there are factors in the plasma of AD patients that affect the growth of new nerve fibers, which also affect the oligodendrocytes. Based on these findings, we selected the most promising plasma samples and conducted mass spectrometry us-ing a differential approach and we identified 3 putative biomarkers: aldehyde-dehydrogenase 1A1, alpha-synuclein and protein S100-A4. Our method represents a novel and innovative ap-proach to translate research findings from mouse models to human applications.

Quantum cryptography revolutionizes secure information transfer, providing defense against both quantum and classical computational attacks. The primary challenge in extending the reach of quantum communication comes from the exponential decay of signals over long distances. Addressing this challenge, we have developed Quantum-protected Control-based Key Distribution (QCKD), overcoming transmission range limitations by monitoring signal leakages and rendering leaked quantum states significantly non-orthogonal. This paper reports on the experiments with the QCKD, conducted over a 1,707 km fiber line. We demonstrate advancements in critical components of the protocol, showing its remarkable scalability and adaptability for extended distances and multi-user configurations.

The main objective of this this cross-sectional study was to analyze the influence of lifestyle fac-tors (diet, physical activity, sleep), which can affect the concentrations of fecal short-chain fatty acids (SCFAs) and SCFAs potential role in modulating cardiometabolic disease risk by interact-ing with biochemical and body composition parameters. The study comprised 77 healthy, non-obese individuals, aged 30-45 years who were assessed in the light of SCFAs concentration in stool, diet, physical activity level and sleep duration. Moreover, body composition measurement and patients’ biochemical parameters were included in the analysis. We have indicated a signifi-cant negative correlation between several SCFAs [especially acetic acid (AA), isobutyric acid (IBA), butyric acid (BA), isovaleric acid (IVA) and valeric acid (VA)] with BMI, VAT/SAT ratio (visceral to subcutaneous fat ratio) and percentage of fat mass in a group of females enrolled in the study as well as with waist circumference (WC) in case of both sexes included in the study. Moreover, the results of our study acknowledged the importance of a diet in shaping SCFAs pro-file - we noticed the significant negative associations between energy and fat intake and some SCFAs in males [IBA, IVA, VA, isocaproic acid (ICA)]. In terms of fiber intake, we noticed elevat-ed concentrations of vast majority of SCFAs and amount of SCFAs in total in case of both sexes included in the study. These strong correlations reflect the fact that diet shapes the composition of the gut microbiota and SCFAs (main microbial metabolites) are synthesized from dietary fiber. Furthermore, we noticed that in a group of women, the concentration of AA, propionic acid (PA) and ICA as well as the total concentration of SCFAs showed a significant positive association with their sleep duration. We concluded that SCFAs can have a potential role in modulating car-diometabolic disease risk by interacting with adiposity parameters and diet. In addition, this potential direct link between diet and SCFAs may at least partly contribute to sleep improvement.

Muscarinic acetylcholine receptors are well-known for their crucial involvement in hippocampus-dependent learning and memory, but the exact roles of the various receptor subtypes (M1-M5) are still not fully understood. Here, we studied how M1 and M3 receptors affect plasticity at the mossy fiber (MF)-CA3 pyramidal cell synapse. In hippocampal slices from M1/M3 receptor double knockout (M1/M3-dKO) mice, the signature short-term plasticity of the MF-CA3 synapse was not significantly affected. However, the rather unique, NMDA receptor-independent and presynaptic form of long-term potentiation (LTP) of this synapse was much larger in M1/M3-deficient slices compared to wild type slices, in both field potential and whole-cell recordings. Consistent with its presynaptic origin, induction of MF-LTP strongly enhanced the excitatory drive onto single CA3 pyramidal cells, with the effect being more pronounced in M1/M3-dKO cells. In an earlier study [1], we found that deletion of M2 receptors in mice disinhibits MF-LTP in a similar fashion, suggesting that endogenous acetylcholine employs both M1/M3 and M2 receptors to constrain MF-LTP. Importantly, such synergism was not observed for MF long-term depression (LTD). Low-frequency stimulation, which reliably induced LTD of MF synapses in control slices, failed to do so in M1/M3-dKO slices and gave rise to LTP instead. In striking contrast, loss of M2 augmented LTD when compared to control slices. Taken together, our data demonstrate convergence of M1/M3 and M2 receptors on MF-LTP, but functional divergence on MF-LTD, the net effect being well-balanced bidirectional plasticity of the MF-CA3 pyramidal cell synapse.

Hemoconcentration membranes used in cardiopulmonary bypass require a pore structure design with high pure water permeability, and which does not allow protein adsorption and useful protein loss. However, studies on hemoconcentration membranes have not been conducted yet. The purpose of this study was to analyze three-dimensional pore structures and protein fouling before and after blood contact with capillary membranes using the tortuous pore diffusion model and a scanning probe microscope system. We examined two commercially available capillary membranes of similar polymer composition that are successfully used in hemoconcentration clinically. Assuming the conditions of actual use in cardiopulmonary bypass, we perfused these membranes with bovine blood. Pure water permeability before and after bovine blood perfusion was measured using the dead-end filtration. The scanning probe microscopy system was used for analysis. High-resolution three-dimensional pore structures on the inner surface of the membranes were observed before blood contact. On the other hand, pore structures after blood contact could not be observed due to protein fouling. The pore diameters calculated by the tortuous pore diffusion model and scanning probe microscopy were mostly similar and could be validated reciprocally. Achievable pure water permeabilities showed no difference despite protein fouling, leading to low values of albumin SC. This is due to the mechanism that protein fouling occurs on the membrane surface, while there is little internal pore blocking. Therefore, controlling the fouling is essential for membranes in medical use. These characteristics of the hemoconcentration membranes examined in this study are suitable for clinical use.

This work describes a new transducer prototype for continuous monitoring both in the structural and geotechnical fields. The transducer is synthetically constituted by a wire of optical fiber embedded between two fiber tapes (fiberglass or carbon fiber) and glued by a matrix of polyester resin. The fiber optical wire ends have been connected to a control unit whose detection system is based on Brillouin optical time-domain frequency analysis. Three laboratory tests were carried out to evaluate the sensor's reliability and accuracy. In each experiment, the transducer was applied to a sample of inclinometer casing sets in different configurations and with different constraint conditions. The experimental data collected were compared with theoretical models and with data obtained from the use of different measuring instruments to perform validation and calibration of the transducer at the same time. Several diagrams allow comparing the transducer and highlighting its suitability for monitoring and maintenance of structures. The characteristic of the transducer suggests its use as a mixed system for reinforcing and monitoring, especially in lifetime maintenance of critical infrastructures such as transportation and service networks, and historical heritage.

Corn fiber is a co-product of commercial ethanol dry-grind plants, which is processed into distillers dried grains with solubles (DDGS) and used as animal feed, yet it holds high potential to be used as feedstock for additional ethanol production. Due to the tight structural make-up of corn fiber, a pretreatment step is necessary to make the cellulose and hemicellulose polymers in the solid fibrous matrix more accessible to the hydrolytic enzymes. A pretreatment process was developed in which whole corn kernels were soaked in aqueous solutions of 2.5, 5.0, 7.5 and 10.0 wt% ammonia at 105oC for 24 h. The pretreated corn then was subjected to a conventional mashing procedure and subsequently ethanol fermentation using a commercial strain of natural Saccharomyces cerevisiae with addition of a commercial cellulase. Pretreatment of the corn with 7.5 wt% ammonia solution plus cellulase addition gave highest ethanol production, which improved the yield in fermentation using 25 wt% solid from 334 g ethanol/kg corn obtained in the control (no pretreatment and no cellulase addition) to 379 g ethanol/kg corn (a 14% increase). The process developed can potentially be implemented in existing dry-grind ethanol facilities as a “bolt-on” process for additional ethanol production from corn fiber, and this additional ethanol can then qualify as “cellulosic ethanol” by the EPA’s Renewable Fuels Standard and thereby receive RINS (Renewable Identification Numbers).

In our recent publications, based on strong and electroweak interactions, we have developed a completely new formula for estimating nuclear binding energy. With reference to currently believed Semi Empirical Mass Formula (SEMF), we call our formula as ‘Strong and Electroweak Mass Formula’ (SEWMF). Our formula constitutes 4 simple terms and only one energy coefficient of magnitude 10.1 MeV. First term is a volume term, second term seems to be a representation of free nucleons associated with electroweak interaction, third term is a radial term and fourth one is an asymmetry term about the mean stable mass number. In this paper, we make an attempt to understand and estimate the maximum binding energy associated with any mass number. It can be expressed as, for A > 4, $\left(BE\right)_A\cong \left[A-0.000935A^2-A^{1/3}-A^{-1/2}\right]$ MeV. We are working on refining the 4^th term with even-odd corrections, shell corrections and other microscopic corrections. Proceeding further, stable mass numbers and super heavy mass numbers can be understood with a relation of the form, $\left[\textrm{RoundOff}\left(\left(Z+2.9464\right)^{1.2}-1.7165\right)\right]\pm\left[0,1\right]\pm\left(2n\right)$ where $n \cong 0,1,2$. It needs a review with respect to even-odd proton numbers and other microscopic corrections.Very interesting point to be noted is that based on the concept of “binding energy per nucleon”, the most complicated Avogadro number and Unified atomic mass unit can be estimated in a unified approach.

This literature review investigates the morphological and behavioral significance of the horns of Carnotaurus sastrei, a theropod dinosaur from the Late Cretaceous period. Through a comprehensive analysis of fossil specimens, comparative anatomy, and biomechanical modeling, this review explores the evolutionary adaptations and potential functions of these distinctive cranial structures. The horns of Carnotaurus are hypothesized to serve multiple roles, including species recognition, thermoregulation, and intraspecific combat. Our findings suggest that its cranial horns likely served a primary role in species recognition, intimidating rivals and signaling mating readiness. It also could have been used occasionally in head-butting contests, potentially as a display of dominance, but likely did not play a role in thermoregulation. Additionally, we examine the ecological context in which Carnotaurus lived, assessing how environmental factors could have influenced the development of such features. The implications of this study extend to broader discussions on the functional morphology and adaptive strategies of theropod dinosaurs, highlighting the complex relationship between form and function in the evolutionary history of predatory dinosaurs like Carnotaurus sastrei.

This paper examines the quantitative and qualitative situation of the current fixed and mobile Internet and its expected future. First, the number of users and penetration rate of the Internet, various types of services in different countries, the ranking of countries in terms of the mean and median download and upload Internet data speeds, Internet data volume, and number and location of data centers in the world are presented. The second task introduces and details twelve performance evaluation metrics for broadband Internet access. Third, different wired and wireless Internet technologies are introduced and compared based on data rate, coverage, type of infrastructure, and their advantages and disadvantages. Based on the technical and functional criteria, in the fourth work, two popular wired and wireless Internet platforms, one based on optical fiber and the other based on the 5G cellular network, are compared in the world in general and Australia in particular. Moreover, this paper has a look at Starlink as the latest satellite Internet candidate, especially for rural and remote areas. The fifth task outlines the latest technologies and emerging broadband Internet-based services and applications in the spotlight. Sixthly, it focuses on three problems in the future Internet in the world, namely the digital divide due to the different quality of the Internet and new Internet-based services and applications of emerging technologies, the impact of the Internet on social interactions, and hacking and insecurity on the Internet. Finally, some solutions to these problems are proposed.

Erosion caused by the repeated impact of particles on a substance surface is a usual wear method resulting in gradual and continual loss of objects. It is a crucial problem in several modern industries because their surfaces are frequently subjected to destructive erosive situations. Polymers and their hybrid materials include several applications to be used as a coating in the form of powder for different applications. This review paper aims to provide extensive information on the erosion behavior of thermoset and thermoplastic neat resin and their hybrid materials composites. Focus is specifically paid to highlight the influence of properties of selected materials, impingnation parameters such as incident Angle of erodent, impact velocity of erodent, erodent nature, and the erosion mechanism. The review further extends the information about the erosion techniques and numerical simulation methods used for wear studies of surfaces. An investigation has been carried out for researchers to explore the selection of materials and methods in terms of conditions and parameters to meet the current and future needs and challenges for the protection of surfaces of the advanced industries. During review according to the findings achieved from the literature of the past fifty years, it has been noted that the thermoplastic nature of the composite is a key component to determine the anti-wear properties, the composites with lower glass transition, higher ductility, and greater crystallinity can provide better protection to erosion in advance surface applications.

The preservation of the authenticity of a building artefact is a responsible practice. On the other side, the need to save the building artefact from the natural and anthropic degradation, to ensure the structural reliability to the different actions, to define an efficient maintenance program are big challenges, that involves the cooperation of several professionals, responsible use of innovative techniques and materials that are nowadays available. This paper focuses on a specific design approach for the rehabilitation works of ancient constructions in archaeological sites. The proposed conceptual design approach implies different steps that allow the optimization of the design at an increasing level of knowledge on the existing structures and their materials. The design procedure on historical constructions generally includes the following steps: the collection of data, the structural identification, hazard, and vulnerability analysis, damage and risk analysis, a cost-benefit analysis, so only at the end of the process, the final design is achieved. In the archaeological area, some important design aspects cannot be defined before the execution work phase, since some elements could be revealed and identified during work execution, as a consequence, the final design has been often optimized after all this information has been acquired. A studied case in the archaeological site of Pompeii is herein presented to prove the efficiency of the proposed approach.

Pasmo is one of the most widespread diseases threatening flax production. To identify genetic regions associated with pasmo resistance (PR), a genome-wide association study was performed on 370 accessions from the flax core collection. Evaluation of pasmo severity was performed in the field from 2012 to 2016 in Morden, MB, Canada. Genotyping-by-sequencing has identified 258,873 single nucleotide polymorphisms (SNPs) distributed on all 15 flax chromosomes. Marker-trait associations were identified using ten different statistical models. A total of 692 unique quantitative trait nucleotides (QTNs) associated with 500 putative quantitative trait loci (QTL) were detected from six phenotypic PR datasets (five individual years and average across years). Different QTNs were identified with various statistical models and from individual PR datasets, indicative of the complementation between analytical methods and/or genotype × environment interactions of the QTL effects. The single-locus models tended to identify large-effect QTNs while the multi-loci models were able to detect QTNs with smaller effects. Among the putative QTL, 67 had large effects (3-23%), were stable across all datasets and explained 32-64% of the total variation for PR in the various datasets. Forty-five of these QTL spanned 85 resistance gene analogs including a large toll interleukin receptor, nucleotide-binding site, leucine-rich repeat (TNL) type gene cluster on chromosome 8. The number of positive effect QTL (NPQTL) in accessions was significantly correlated with PR (R²=0.55), suggesting additive effects. NPQTL was also significantly associated with morphotype (R²=0.52) and major positive effect QTL were present in the fiber type accessions. The 67 large effect QTL are suited for marker-assisted selection and the 500 QTL for effective genomic prediction in PR molecular breeding.

Event detection provides a crucial foundation for intelligent text analysis and supports numerous downstream applications. However, existing detection models often fail to meet the high accuracy requirements and typically require a human–machine collaborative detection mode involving “machine detection followed by manual audit and correction.” Analysis reveals that the recall rate of machine detection is a major factor limiting the efficiency of human–machine collaboration. To address this at its root and ensure high recall, an event trigger recommendation task is introduced, and a span-based recommendation model for Chinese, SpETR (Span-based Event Trigger Recommender), is developed. This model integrates confidence information from both trigger identification and event classification stages to recommend candidate triggers and their event types for each event. To enhance recall, a semantic boundary smoothing method is proposed, which assigns soft labels to spans around gold triggers based on semantic completeness and part-of-speech, combined with a modified focal loss function to make the model predictions smoother. Experiments on DuEE and a self-built dataset show that SpETR is most effective when the number of recommendations is set to 3, achieving recall rates of 97.76% and 98.70%, respectively, comprising improvements of 4.30% and 5.22% over the optimal baseline models. In terms of human–machine collaborative detection, SpETR saved 30.6% and 25.8% of time compared to traditional detection models on two datasets, and the average F1 score of the annotation results was also improved by 5.35% and 3.48%, respectively.

As fatigue properties of as-built components of additively manufactured (AM) metals are considerably weaker than those of wrought metals because of rougher surface, post-processing is necessary to improve fatigue properties. To demonstrate improvement of fatigue properties of AM metals by post-processing, powder bed fusion (PBF) using laser sintering (LS) AlSi10Mg, i.e., PBF-LS/AlSi10Mg was treated by “submerged laser peening (SLP)” using a fiber laser and/or a Nd:YAG laser, then evaluated by plane bending fatigue tests. At SLP, “laser ablation (LA)” is generated by a pulsed laser, and a bubble is generated after LA, which behaves like a cavitation bubble that is named as “laser cavitation (LC)”. In the present paper, LA-dominated SLP is called as “laser treatment (LT)”, while LC-collapse-dominated SLP is called as “laser cavitation peening (LCP)”, as impact at LC collapse is used for peening. It was revealed that SLP using the fiber laser was LT rather than LCP. It was demonstrated that the fatigue strength at N = 10^7 was 85 MPa for LCP, and 103 MPa for combined process of blasting (B) + LT + LCP, whereas the fatigue strength of as-built specimen was 54 MPa.

This research is completed in development of researches devoted to relations between elastic modulus (MoE) and thermal expansivity (CTe) of different materials. This study experimentally confirmed the relation of MoE and CTe for thermosetting polymers and FRPs both under normal and heating temperatures. As the thermosetting polymers, the epoxy compositions were used and glass fiber and mineral additives for FRP. The experiment was based on dilatometric and elastic deformations’ testing. Also, the relaxation model of MoE/CTe was proposed, that is based on physical properties of polymers’ supramolecular structures. The comparative analyzing of MoE/CTes’ different models is done. The most accurate models are determined, and the relaxation model has demonstrated the high accuracy.

(1) Background: Sensing of critical events or flow signatures in nature often presents itself as a coupled interaction between a fluid and arrays of slender flexible beams, such a wind-hairs or whiskers. It is hypothesized that important information is gained in highly noisy environments by the inter-correlation within the array. (2) Methods: The present study uses a model sea lion head with artificial whiskers in the form of slender beams (optical fibres), which are subjected to a mean flow with overlaid turbulent structures generated in the wake of a cylinder. Motion tracking of the array of fibres is used to analyse the correlation of the bending deformations of pairs of fibres. (3) Results: Cross-correlation of the bending signal from tandem pairs of whiskers proves that the detection of vortices and their passage along the animals head is possible even in noisy environments. The underlying pattern, during passage of a vortex core, is a jerk-like response of the whiskers, which can be found at later arrival-times in similar form in the downstream whisker's response. (4) Conclusion: Coherent vortical structures can be detected from cross-correlation of pairs of cantilever-beam like sensors even in highly turbulent flows. Such vortices carry important information within the environment, e.g. the underlying convection velocity. More importantly in nature, these vortices are characteristic elementary signals left by prey and predators. The present work can help to further develop flow, or critical event, sensory systems which can overcome high noise levels due to the proposed correlation principle.

We dive into the axion-dilaton model within the supergravity framework, with a specific focus on the intricacies of domain wall construction and stability. Employing holographic vitrification, we unravel the dynamics of domain wall formation in gauge theories featur- ing periodic vacuum structures. Our model, incorporating a QCD-like axion term and a stabilizing dilaton, undergoes scrutiny for conductivity variations under weak disorder. The investigation reveals the model’s resilience, manifesting near-perfect conductivity under mild disorder conditions. However, the rigorous mathematical motivation for the holographic setup demands further elucidation. The scattered nature of our results prompts the neces- sity for a more systematic interpretation of QCD phenomena and conductivity transitions. This study contributes to the mathematical understanding of the axion-dilaton model’s be- havior, highlighting the imperative for a refined holographic framework and a more coherent interpretation of observed phenomena.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

Spin-orbit coupling and nonparaxiality effects during propagation of vortex vector light beams in a cylindrical graded-index waveguide are investigated by solving the full three-component field Maxwell’s equations. Symmetry breaking effects for left- and right-handed circularly polarized vortex light beams propagating in a rotationally symmetric graded-index optical fiber are considered. The mode-group delay in a graded-index fiber due to spin-orbit interaction is demonstrated. It is shown that the relative delay times between vortex pulses of opposite circular polarizations of the order of 10 ps/km can be observed in graded-index fibers for high-order topological charges.

How do sensor research and technologies grow over time? This paper applies the network analysis with a new computational approach to map the structure and evolution of sensor research and technologies over a 30-year time frame (1990-2020).The goal of this study is to analyze the evolution of sensor research for forecasting emerging scientific and technological trajectories. Results show that the scientific interaction within ecosystem (represented with networks) of sensor generates a co-evolution of scientific fields supporting the accelerated growth of different technological tra-jectories, such as: wireless sensors, fiber optic and optical sensors, gas sensors and biosensors. These results suggest main theoretical implications that explain the evolution of sensor research with critical aspects of innovation management to support R&D investments towards new technological trajectories having a high potential of growth.

This article introduces a new way of using a Fibre Bragg Grating (FBG) sensor for detecting the presence and number of occupants in the monitored space in a Smart Home (SH). CO₂ sensors are used to determine the CO₂ concentration of the monitored rooms in an SH. CO₂ sensors can also be used for occupancy recognition of the monitored spaces in SH. To determine the presence of occupants in the monitored rooms of the SH, the newly devised method of CO₂ prediction, by means of an Artificial Neural Network (ANN) with a Scaled Conjugate Gradient (SCG) algorithm using measurements of typical operational technical quantities (indoor temperature, relative humidity indoor and CO₂ concentration in the SH) is used. The goal of the experiments is to verify the possibility of using the FBG sensor in order to unambiguously detect the number of occupants in the selected room (R104) and, at the same time, to harness the newly proposed method of CO₂ prediction with ANN SCG for recognition of the SH occupancy status and the SH spatial location (rooms R104, R203, and R204) of an occupant. The designed experiments will verify the possibility of using a minimum number of sensors for measuring the non-electric quantities of indoor temperature and indoor relative humidity and the possibility of monitoring the presence of occupants in the SH using CO₂ prediction by means of the ANN SCG method with ANN learning for the data obtained from only one room (R203). The prediction accuracy exceeded 90% in certain experiments. The uniqueness and innovativeness of the described solution lie in the integrated multidisciplinary application of technological procedures (the BACnet technology control SH, FBG sensors) and mathematical methods (ANN prediction with SCG algorithm, the Adaptive Filtration with of LMS algorithm) employed for the recognition of number persons and occupancy recognition of selected monitored rooms of SH.

Gilbert's syndrome (GS) is a common hereditary condition characterized by mild increases in serum bilirubin levels due to inherited defects in bilirubin metabolism. This review, based on data from peer-reviewed articles and journals spanning from 1977 to January 2024, provides a comprehensive overview of over four decades of research on GS. Early studies primarily focused on defining the clinical and genetic characteristics of the syndrome, laying the foundation for subsequent investigations. More recent research has delved into the genetic mechanisms underlying the reduced expression of bilirubin UDP-glucuronosyltransferase, which has significantly enhanced our understanding of the pathogenesis of GS. Furthermore, recent studies have shed light on the clinical implications of GS, including its association with non-alcoholic fatty liver disease and mortality risk, highlighting the complex interplay between genetic factors, bilirubin metabolism, and clinical outcomes. Despite its generally benign nature, thorough research is essential to fully understand the impact of GS on patients' lives. This review emphasizes the importance of ongoing research to deepen our understanding of GS and its broader implications.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

A large body of evidence reports about the positive effects of physical activity in pathophysiological conditions associated with aging. Physical exercise, alone or in combination with other medical therapies, unquestionably causes reduction of symptoms in chronic non-transmissible diseases often leading to significant amelioration or complete healing. The molecular basis of this exciting outcome, however, remain largely obscure. Epigenetics, exploring at the interface between environmental signals and the remodelling of chromatin structure, promises to shed light on this intriguing matter possibly contributing to the identification of novel therapeutic targets. In this review, we shall focalize on the role of sirtuins (Sirts) a class III histone deacetylases (HDACs) which function has been frequently associated, often with a controversial role, to the pathogenesis of aging-associated pathophysiological conditions including cancer, cardiovascular, muscular, neurodegenerative, bones and respiratory diseases. Numerous studies, in fact, demonstrate that Sirt-dependent pathways are activated upon physical and cognitive exercises linking mitochondrial function, DNA structure remodelling and gene expression regulation to designed medical therapies leading to tangible beneficial outcomes. However, in similar conditions, other studies assign to sirtuins a negative pathophysiological role. In spite of this controversial effect, it is doubtless that studying sirtuins in chronic diseases might lead to an unprecedented improvement of life quality in the elderly.

This case report demonstrates the rare but potentially serious complication of pulmonary vein stenosis (PVS) diagnosed several years after radiofrequency ablation for atrial fibrillation. Pulmonary vein stenosis can remain asymptomatic until significant occlusion occurs, after which it can present with a variety of symptoms, mimicking numerous cardiovascular and pulmonary pathologies. Early diagnosis and treatment rely on consistent follow-up using appropriate diagnostic imaging modalities, which are paramount in preventing severe complications.

Peripheral and autonomic neuropathy are common disease manifestations in systemic amyloidosis. Neurofilament light chain (NfL), a neuron-specific biomarker, is released into the blood and cerebrospinal fluid after neuronal damage. This systematic review provides an overview on the value of NfL in early detection of neuropathy, central nervous system involvement, monitoring of neuropathy progression, and treatment effect in systemic amyloidosis. A literature search in PubMed, Embase and Web of Science was performed on 14-02-2024 for studies investigating NfL levels in patients with systemic amyloidosis and transthyretin gene variant (TTRv) carriers. Only studies containing original data were included. Included were twelve full-text articles and six abstracts describing 1604 participants: 298 controls and 1306 TTRv carriers or patients with or without polyneuropathy. Patients with polyneuropathy demonstrated higher NfL levels compared to healthy controls and asymptomatic carriers. Disease onset was marked by rising NfL levels. Following initiation of transthyretin gene-silencer treatment, NfL levels decreased and remained stable over an extended period. NfL is not an outcome biomarker, but an early and sensitive disease process biomarker for neuropathy in systemic amyloidosis. Therefore, NfL has potential to be used for early detection of neuropathy, monitoring treatment effect, and monitoring disease progression in patients with systemic amyloidosis.

A paper impregnated with silver nanoparticles (AgNPs) has been prepared. For the preparation of the substrates, aqueous suspensions of pulp fines, a side product from the paper production, have been mixed with Ag nanoparticles (AgNP) suspensions. The nanoparticle synthesis thereof was carried out via laser ablation of pure Ag in water. After the sheet formation process, the leaching of the AgNPs was determined to be low while the sheets exhibited antimicrobial activity towards E. Coli.

Distributed deformation based on Fiber Bragg Grating sensors or other kinds of strain sensors can be used to evaluate safety in operating periods of bridges. However, most of the published researches about distributed deformation monitoring are focused on solid rectangular beam rather than box girder—a kind of typical hollow beam widely employed in actual bridges. Considering that the entire deformation of a single-cell box girder contains not only bending deflection but also two additional deformations respectively caused by shear lag and shearing action, this paper again revises the improved conjugated beam method (ICBM) based on the LFBG sensors to satisfy the requirements for monitoring two mentioned additional deformations. The best choice for the LFBG sensor placement in box gilder is also proposed in this paper due to strain fluctuation on flange caused by shear lag effect. Results from numerical simulations show that most of the theoretical monitoring errors of the revised ICBM are 0.3%~1.5%, and the maximum error is 2.4%. A loading experiment for a single-cell box gilder monitored by LFBG sensors show that most of the practical monitoring errors are 6%~8%, and the maximum error is 11%.

The document sets out three differentiated proposals for the transport of medicines through RPAS with their respective regulations, adapted to different operational categories: open category, special category and military scope. In the open category, an economical and efficient solution is prioritized for urban and rural areas, complying with weight and height regulations, in addition to guaranteeing the stability and quality of medications during transportation. The special category allows more complex operations and in more adverse conditions, such as densely populated areas and long routes, incorporating advanced security measures and training for personnel. In the military field, RPAS are used in conflict zones and hard-to-reach areas, ensuring the safe and rapid delivery of medical supplies under extreme conditions. Success stories in different countries are highlighted, demonstrating significant improvements in delivery times and risk reduction for health personnel.

We delve into the axion-dilaton model within the supergravity framework, with a specific focus on the intricacies of domain wall construction and stability. Employing holographic vitrification, we unravel the dynamics of domain wall formation in gauge theories featuring periodic vacuum structures. Our model, incorporating a QCD-like axion term and a stabilizing dilaton, undergoes scrutiny for conductivity variations under weak disorder. The investigation reveals the model's resilience, manifesting near-perfect conductivity under mild disorder conditions. However, the rigorous mathematical motivation for the holographic setup demands further elucidation. The scattered nature of our results prompts the necessity for a more systematic interpretation of QCD phenomena and conductivity transitions. This study contributes to the mathematical understanding of the axion-dilaton model's behavior, highlighting the imperative for a refined holographic framework and a more coherent interpretation of observed phenomena.

Spinal Cord (SC) Anatomy is often assimilated to a morphologically encapsulated neural entity, but its functional anatomy remains only partially understood. We hypothesized that it could be possible to reexplore SC neural networks by performing live electrostimulation mapping, based on “super-selective” Spinal Cord Stimulation (SCS), originally designed as a therapeutical tool to address chronic refractory pain. As a starting point, we initiated a systematic SCS lead programming approach using live electrostimulation mapping on a chronic refractory perineal pain patient, previously implanted with multicolumn SCS at the level of the conus medullaris (T12-L1). It appeared possible to (re)explore the classical anatomy of the conus medullaris using statistical correlations of paresthesia coverage mappings, resulting from 165 different electrical configurations tested. We highlighted that sacral dermatomes were not only located more medially but also deeper than lumbar dermatomes at the level of the conus medullaris, in contrast with classical anatomical descriptions of SC somatotopical organization. As we were finally able to find a morpho-functional description of ‘Philippe-Gombault’s triangle’, in 19th century historical textbooks of neuroanatomy, matching remarkably with these conclusions, the concept of “Neuro-Fiber-Mapping” was introduced.

This paper introduces an innovative theoretical framework for quantum-inspired data embeddings, grounded in foundational concepts of quantum mechanics such as superposition and entanglement. This approach aims to advance semi-supervised learning in contexts characterized by limited labeled data by enabling more intricate and expressive embeddings that capture the underlying structure of the data effectively. Grounded in foundational quantum mechanics concepts such as superposition and entanglement, this approach redefines data representation by enabling more intricate and expressive embeddings. Emulating quantum superposition encodes each data point as a probabilistic amalgamation of multiple feature states, facilitating a richer, multidimensional representation of underlying structures and patterns. Additionally, quantum-inspired entanglement mechanisms are harnessed to model intricate dependencies between labeled and unlabeled data, promoting enhanced knowledge transfer and structural inference within the learning paradigm. In contrast to conventional quantum machine learning methodologies that often rely on quantum hardware, this framework is fully realizable within classical computational architectures, thus bypassing the practical limitations of quantum hardware. The versatility of this model is illustrated through its application to critical domains such as medical diagnosis, resource-constrained natural language processing, and financial forecasting—areas where data scarcity impedes the efficacy of traditional models. Experimental evaluations reveal that quantum-inspired embeddings substantially outperform standard approaches, enhancing model resilience and generalization in high-dimensional, low-sample scenarios. This research marks a significant stride in integrating quantum theoretical principles with classical machine learning, broadening the scope of data representation and semi-supervised learning while circumventing the technological barriers of quantum computing infrastructure.

Synthetic fiber ropes are frequently used as mooring lines in floaters supporting Floating Offshore Wind Turbines (FOWTs) due to their various advantages. Damages in these lines can lead to the disruption of the FOWTs normal operation and thus their early detection is crucial. Currently, this damage detection problem has been investigated exclusively for FOWT chain mooring lines. This study focuses on the damage detection in FOWT synthetic mooring lines under varying environmental-operational conditions (EOCs) via two types of vibration-based Structural Health Monitoring methods: those based on Multiple Models and those based on a single Functional Model. The methods are based on multivariate AutoRegressive or on scalar Transmittance Function (TF) AutoRegressive with eXogenous input models. All methods are evaluated through a Monte Carlo study involving 390 simulations with a 10MW wind turbine mounted on the semi-submersible OO-Star wind floater and two damage scenarios (10%, 14% stiffness reduction) to a single mooring line. The results using acceleration signals from only two measuring positions on the mooring line, indicate the great potential for robust SHM in FOWTs synthetic mooring lines with the TF model-based methods successfully detecting the considered early stage damage scenarios, even for EOCs not encountered in the methods training.

The durability of bridge decks is a critical factor in ensuring the safety and longevity of transportation infrastructure. This article explores advanced materials and innovative techniques designed to mitigate cracking in bridge decks, a common issue that can compromise structural integrity and increase maintenance costs. It provides a comprehensive review of cutting-edge solutions such as Fiber-Reinforced Polymers (FRP), High-Performance Concrete (HPC), Ultra-High Performance Concrete (UHPC), and self-healing concrete technologies. Each material is analyzed for its ability to enhance strength, reduce permeability, and improve resistance to environmental stressors. Additionally, the article examines the role of surface treatments, sealants, and routine maintenance practices in prolonging the life of bridge decks. By synthesizing current research and practical applications, this article offers valuable insights and recommendations for engineers, contractors, and policymakers seeking to advance bridge deck durability through innovative materials and methodologies.

In this paper, based on the symmetrical reliability theory, a research method for the safety factor of overall overturning stability of continuous beam bridge under carbon fiber reinforced polymers (CFRP) during cantilever and horizontal rotation construction is proposed. Under the premise that the given target reliability index is known, the method solves the overall overturning stability safety factor of continuous beam bridge under carbon fiber reinforced polymers during cantilever and horizontal rotation construction by using the symmetrical reliability analysis theory and considering the randomness of structural parameters. This method is used to calculate the safety factor and the design reinforcement aera of CRFP of overturning stability and the design reinforcement aera of CRFP of a continuous beam bridge, and the parameters are analyzed. The calculation results show that the randomness of parameters will have a great impact on the overall safety factor and the CRFP aera of overturning stability of cantilever and horizontal rotation construction of continuous beam bridge, and ignoring the influence of randomness of parameters will lead to overestimation of the overall safety factor and underestimation of the CRFP aera of overturning stability of cantilever and horizontal rotation construction of continuous beam bridge.

Throughout the world, salinity is a major environmental issue that limits agricultural productivity, particularly in arid and semi-arid regions. In addition, climate change is the most important reason for the salinization of agricultural soils in the world, so it is now essential to find solutions to increase salinity tolerance in plants. This study investigated the potential of arbuscular mycorrhizal fungi (AMF) inoculation to enhance the growth and yield performances of flax under different salinity levels by conducting a pot experiment. The experiment was laid out in a two-factor completely randomized design including AMF inoculation (AMF+: with and AMF-: without inoculation) and irrigation water salinity (0, 50, 100, and 150 mM NaCl). According to the results, it is evident that salt stress caused negative physiological effects, including limited growth, reduced photosynthesis, and decreased nitrogen (N) and phosphorus (P) content in shoots and roots of flax plants. Moreover, mycorrhizal association improved the salt tolerance of the plants by increasing chlorophyll content, enhancing N and P shoot and root contents, and consequently yield parameters, such as seed, and stem fiber yield, particularly at moderate salt concentrations (50 and 100 mM NaCl). As a result of using AMF, flax plants grown under salt stress exhibited tolerance, suggesting that AMF could be applied in saline environments to maintain ecological stability.

Using coherent optical detection and digital signal processing, laser phase noise and equalization enhanced phase noise can be effectively mitigated using the feed-forward and feed-back carrier phase recovery approaches. In this paper, theoretical analyses of feed-back and feed-forward carrier phase recovery methods have been carried out in the long-haul high-speed n-level phase shift keying (n-PSK) optical fiber communication systems, involving a one-tap normalized least-mean-square (LMS) algorithm, a block-wise average algorithm, and a Viterbi-Viterbi algorithm. The analytical expressions for evaluating the estimated carrier phase and for predicting the bit-error-rate (BER) performance (such as the BER floors) have been presented and discussed in the n-PSK coherent optical transmission systems by considering both the laser phase noise and the equalization enhanced phase noise. The results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). In addition, the one-tap normalized LMS algorithm is more sensitive to the level of modulation formats.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

Research question/problem: This comprehensive review and comparative analysis aims to investigate the significance of enhancing oxygen provision in the context of COVID-19, focusing on the implications for healthcare policies and services.Background/context: The study addresses the shift in the oxygen dissociation curve of blood in COVID-19 patients, emphasizing the impact on oxygen delivery to tissues and the challenges it poses for clinical management. It also explores the disruption of healthcare systems due to the pandemic and the integration of social determinants of health in clinical environments.Methodology: The research incorporates a thorough literature review, comparative analysis of diverse approaches to oxygen delivery, and examination of successful interventions through case studies and best practices. Data collection techniques include the review of scholarly articles, case studies, and policy documents.Results/Key findings: The study highlights the imperative for augmented oxygen supply and the significance of maintaining appropriate oxygen saturation levels, especially in the context of respiratory illnesses like COVID-19. It also emphasizes the positive correlation between increased oxygen saturation levels and life expectancy, indicating potential health benefits of enhanced oxygen availability.Conclusions/Implications: The findings underscore the need for a structured approach to oxygen therapy and the importance of equitable distribution of oxygen to underserved regions. The implications of the research extend to enhancing healthcare policies and services regarding oxygen provision during the COVID-19 pandemic, especially in rural and remote areas.

Long-span steel structure trusses are widely used in factory buildings, but with the growth of service time and the increase of dynamic load fatigue, a considerable part of the long-span truss with dynamic load appears serious transverse cracks at the bottom of the middle span and oblique deformation of the abdomen in the operation process. The U-shaped cracks at the bottom and belly, as well as the mid-span down deflection of the main truss, reduced the functional function of the factory building truss structure, and had to limit the original crane load, which affected the normal safety and durability of the structure. Therefore, the application principle of the variable axial force cable system in the long-span factory building truss structure and 3D3S software modeling [1] were used. Analyzing and studying the reinforcement method of large-span powerhouse truss can provide practical experience for subsequent similar projects. In view of the above phenomenon, the large-span powerhouse trusses of Hongcheng Powerhouse 1 and No.2 located in Tonglu, Zhejiang Province are used as the research object, and the variable axial force cable method is proposed to strengthen and lift the load. Considering the span of large-span powerhouse truss, the cable system with 22m controlling force of 400kN is proposed to be selected for powerhouse 1, and the cable system with variable axial force of 24m is proposed to be selected for Powerhouse 2. The force model of large-span truss is established by using the finite element method commonly used to analyze the force of truss. Under two working conditions, The influence of reinforcement effect is analyzed and compared from three aspects: stiffness, bearing capacity and stability. And the phenomenon of uneven stress distribution is analyzed. The stress distribution characteristics of each node are understood by simulating the most disadvantageous node plates with the greatest internal force before and after reinforcement.

This study delves into the intricate interplay between cosmology and gravity in dilaton-based models, enhancing our understanding. Exploring boundary theories coupled to gravity, we derive a four-dimensional effective theory from the cosmological constant. Dilaton gravity is then scrutinized, revealing elegant solutions and insights into brane embedding. The analysis extends to probe scalar fields, employing the WKB approximation in both conformal and non-conformal cases. In summary, this work contributes to a nuanced understanding of the complex relationship between cosmology and gravity in dilaton-based frameworks.

This paper proposes a paradigm shift in AI governance by integrating Indigenous knowledge systems to foster inclusivity and cultural sensitivity. Traditional AI governance frameworks are primarily Western-centric, often overlooking the community-oriented values and ethical considerations essential to Indigenous cultures. This study highlights principles such as Kaitiakitanga from Māori culture, which emphasizes guardianship and environmental stewardship, and Hózhó from Navajo philosophy, which stresses harmony and balance. By engaging Indigenous leaders and knowledge holders throughout the AI lifecycle, this approach ensures technology aligns with community values, addressing critical issues like data sovereignty, ethical technology use, and cultural sensitivity. This paper underscores the necessity of relational accountability in AI governance, which includes prioritizing the health of ecosystems alongside community welfare. This model advocates for an AI framework that not only rectifies historical marginalization but also empowers Indigenous communities to shape the technologies affecting their lives. Furthermore, integrating Indigenous perspectives strengthens the ethical foundation of AI systems, advancing sustainability, social justice, and cultural responsiveness in technology applications. The proposed framework illustrates how Indigenous ethical concepts can transform AI governance by aligning technological progress with values of ecological stewardship and community welfare, creating an AI landscape that respects and reflects diverse cultural contexts. Ultimately, this research demonstrates that Indigenous knowledge systems can significantly enhance AI’s effectiveness and equity, paving the way for more sustainable and culturally attuned technological solutions.

Abstract: Although the pathophysiology of fibromyalgia syndrome has been better understood in recent decades, a unified model of its pathogenesis and an effective therapeutic approach are still far from being realized. The main aim of this article will be to delve into the fundamental mechanisms of the pathophysiology of fibromyalgia conceptualized as stress intolerance syndrome. Using the biopsychosocial model of chronic pain syndromes, we will describe the potential role of the attachment system, C tactile fibers, and oxytocinergic system dysfunction in the pathophysiology of fibromyalgia syndrome and other central sensitivity syndromes. At the end of the article, the therapeutic implications of this new global and translational pathophysiological model will be briefly discussed.

We introduce the linear subgroup of volume-preserving diffeomorphism as the underlying symmetry to construct an action within the effective field theory framework and the Schwinger-Keldish formalism. The formulated action is posited to effectively incorporate dissipative effects into the Navier-Stokes equations.