The key links of face recognition are digital image preprocessing, facial feature extraction and pattern recognition, this article aimed at the current problem of slow speed and low recognition accuracy of face recognition , from the above three key links, on the basic of analyzing the therories of Fractional Differential Masks Operator (FDMO), Principal Component Analysis (PCA) and Support Vector Machine (SVM), design a kind of FDMO+PVA+SVM coupling algorithm that applies to face recognition to improve the speed and accuracy of it. To realize FDMO+PCA+SVM coupling algorithm, first, we should apply FDMO to face image processing binary marginalization, the purpose is getting face contour; Then, we apply PCA to get the feature of face image which is disposed by binary marainalization. At last, we can apply One-Against All of the SVM classifier and LibSVM software package to realize face recognition. Beside, the article with nine different coupling algorithm design four groups of experimental reaults on the ORL face database verified by comparative analysic FDMO+PCA+SVM coupling algorithm in the superiority of face recognition accuracy and speed.

The influence of growth temperature on the crystalline quality and optical properties of AlGaN at 325 nm, grown using plasma-assisted molecular beam epitaxy (MBE), was investigated. The growth temperature exhibited a significant impact on the growth mode and surface morphology. Specifically, at a growth temperature of 750 degrees Celsius, when appropriate Al and Ga flow rates were employed, the AlGaN layer exhibited exceptional surface morphology and favorable optical properties. The optical properties of the AlGaN material were explored, revealing the presence of two distinct non-radiative recombination centers characterized by different activation energies. The minority carrier lifetimes were measured as 560 ps at 10 K and 64 ps at room temperature. The underlying mechanism was analyzed from the perspective of carrier dynamics, shedding light on the observed phenomena.

The pharmacological effects of the fruiting body of Ophiocordyceps sinensis (Os) exerted antioxidant, anti-virus, and immunomodulatory, whereas the anti-inflammatory effects and active components of Os mycelial submerged culture (OMSC) are not known. This study aimed to investigate the active compounds in the fermented liquid (FLOS), hot water (WEOS), and 50-95% (EEOS-50, EEOS-95) ethanol extracts of OMSC and their anti-inflammatory effects and potential mechanisms in LPS-stimulated microglial BV2 cells. The results demonstrated that all of the OMSC extracts could inhibit NO production in BV2 cells. EEOS-95 exhibited the strongest inhibitory effects (41 % inhibitory ability at 500 µg/mL), and its ergosterol, GABA, total phenolic, and total flavonoid contents were significantly higher than those of the other extracts (18.60, 18.60, 2.28, and 2.14 mg/g, p < 0.05, respectively). EEOS-95 also has a strong inhibitory ability against IL-6, IL-1β and TNF-α with IC50 of 617, 277 and 507 µg/mL, respectively, which is higher than that of 1 mM melatonin. The anti-inflammatory mechanism of EEOS-95 seems to be associated with up-regulation of PPAR-γ/Nrf-2/HO-1 antioxidant-related expression and down-regulation of NF-κB/COX-2/iNOS pro-inflammatory expression signaling. Therefore, we hypothesized that EEOS-95 can prevent neurodegenerative diseases, but the effect on the application in vivo should be further investigated.

Hox gene clusters are crucial in Embryogenesis. It was observed that some Hox genes are located in order along the telomeric to centromeric direction of the DNA sequence: Hox1, Hox2, Hox3…. These genes are expressed in the same order in the ontogenetic units of the Drosophila embryo along the Anterior-Posterior axis. The two entities (genome and embryo) differ significantly in linear size and in-between distance. This strange phenomenon was named Spatial Collinearity (SP). Later, it was observed that, particularly in the Vertebrates, a Temporal Collinearity (TC) coexists: first is Hox1 expressed, later Hox2 and even later Hox3,…,. According to a Biophysical Model (BM), pulling forces act at the anterior end of the cluster while a cluster fastening applies at the posterior end. Hox clusters are irreversibly elongated along the force direction. During Evolution, the elongated Hox clusters are broken at variable lengths thus split clusters may be created. An Empirical Rule was formulated distinguishing development due to a complete Hox cluster from development due to split Hox clusters. BM can ‘explain’ this Empirical Rule. In a spontaneous mutation where the cluster fastening is dismantled, a weak pulling force automatically shifts the cluster inside the Hox activation domain. This cluster translocation can probably explain the absence of Temporal Collinearity in Drosophila.

In this paper, we first discuss the research status and application progress of the finite element method and the smoothed particle method. By analyzing the advantages of the smoothed particle method and the finite element method, a new coupling algorithm, namely FEM-SPH algorithm, is proposed. By the method of comparison, it shows that finite element method and SPH method in the simulation of large deformation problems each have advantages and disadvantages, the finite element method smoothed particle coupling algorithm is effective to achieve the performance of high computational efficiency and can naturally simulate large deformation problems across. In the process of calculation, the large deformation unit can be freely into an algorithm to facilitate the calculation accuracy and efficiency of three methods of numerical simulation. Through the study found, FEM-SPH algorithm not only overcome the defect of smooth particle tensile instability, but also overcomes the problem of low efficiency of finite element computation. To further test the FEM-SPH algorithm has advantages in the practical engineering, we have carried out the actual test to the example of the super high speed collision, concluded that, since the target of most of the computational domain is always finite element, smoothed particle focused only in contact with the projectile and target of local area, particle number is not much, the whole calculation process just ten minutes, computational efficiency has been greatly improved, at the same time in the simulation of large deformation, the advantage is very obvious .This provides a criterion for the actual project, depending on the specific material deformation mode and choose a more appropriate conversion algorithm.

The aim of this research work is to study the influence of temperature, solar irradiation and wind dust on the production of solar energy. In addition, it aims to study the assessment of water quality, in particular groundwater used for cooling and cleaning photovoltaic panels (quality analysis). it's an important source, stable and sustainable can be used entirely for cooling and cleaning PV modules from the sales dust, in order to improve their performance. To date, all research studies carried out in this context of cooling and cleaning using water have not taken account of the nature of this water. We have taken a sample of water from a well in a rural area in the Darra Tafilalet region of Morocco. This region has an arid and semi-arid climate, with very high temperatures and dust-laden winds, particularly in summer. These meteorological characteristics influence the efficiency of cells, particularly photovoltaic (PV) panels, reducing their performance. Next, the water sample was analysed in the laboratory. The results obtained show that the groundwater in this area is very sensitive to cooling and cleaning photovoltaic panels. Moreover, these results indicate that the temperature, solar irradiation and wind-blown dust have a significant influence on energy production.

Tellurium exhibits exceptional intrinsic electronic properties. However, investigations into the modulation of tellurium's electronic properties through physical modification are notably scarce. Here, we present a comprehensive study focused on the evolution of the electronic properties of tellurium crystal flakes under plasma irradiation treatment by employing conductive atomic force microscopy and Raman spectroscopy. The plasma-treated tellurium experienced a process of defect generation through lattice broken. Prior to the degradation of electronic transport performance due to plasma irradiation treatment, a remarkable observation emerged: in the low-energy region of hydrogen plasma-treated tellurium, a notable enhancement in conductivity was unexpectedly detected. The mechanism underlying this enhancement in electronic transport performance was thoroughly elucidated by comparing it with the electronic structure induced by argon plasma irradiation. This study not only fundamentally uncovers the effects of plasma irradiation on tellurium crystal flakes, but also unearths an unprecedented trend of enhanced electronic transport performance at low irradiation energies when utilizing hydrogen plasma. This abnormal trend bears significant implications for guiding the prospective application of tellurium-based 2D materials in the realm of electronic devices.

Brain is the most complex organ in the human body and it is divided into two hemispheres - left and right hemispheres. Left hemisphere is responsible for control of right side of our body whereas right hemisphere is responsible for control of left side of our body. Brain image segmentation from different neuroimaging modalities is one of the important parts in clinical diagnostic tools. Neuroimaging based digital imagery generally contain noise, inhomogeneity, aliasing artifacts, and orientational deviations. Therefore, accurate segmentation of brain images is a very difficult task. However, the development of accurate segmentation of brain images is very important and crucial for a correct diagnosis of any brain related diseases. One of the fundamental segmentation tasks is to identify and segment inter-hemispheric fissure/mid-sagittal plane, which separate the two hemispheres of the brain. Moreover, the symmetric/asymmetric analyses of left and right hemispheres of brain structures are important for radiologists to analyze diseases such as Alzheimer's, Autism, Schizophrenia, Lesions and Epilepsy. Therefore, in this paper we have analyzed the existing computational techniques used to find brain symmetric/asymmetric analysis in various neuroimaging techniques (MRI/CT/PET/SPECT), which are utilized for detecting various brain related disorders.

The Atmospheric Dynamics Mission ADM-Aeolus was successfully launched in August 2018 by the European Space Agency (ESA). The Aeolus mission carried a single instrument, the first-ever Doppler Wind Lidar (DWL) in space, called Atmospheric LAser Doppler INstrument (ALADIN). Aeolus circled the Earth in a polar sun-synchronous orbit at about 320 km altitude with a repeat cycle of 7 days, providing vertical profiles of horizontal line-of-sight (HLOS) winds on a global scale. Exceeding scientific expectations, Aeolus, initially designed for a 3-year lifetime, provided global coverage of wind profiles for almost five years. In this long-term validation study, we assessed the accuracy of the Level 2B (L2B) Rayleigh-clear and Mie-cloudy wind products by collecting radiosonde data from three stations in the Brazilian Amazon: Cruzeiro do Sul (7.62° S, 72.67° W), Porto Velho (8.76° S, 63.91° W), and Rio Branco (10.00° S, 67.80° W). Statistical validation was conducted by comparing Aeolus L2B wind products and radiosonde data, launched daily at 12:00 UTC from October 2018 to March 2023. Considering all data collected during the mission period, Pearson’s coefficient (R) of 0.73 was observed in Rayleigh-clear and 0.85 in Mie-cloudy, revealing a strong correlation between Aeolus and radiosonde winds. No significant biases were detected, with values of -0.14 m/s for Rayleigh-clear and -0.40 m/s for Mie-cloud, fulfilling the mission requirement of having absolute biases below 0.7 m/s. However, when analyzed annually, in 2022, the bias for Rayleigh-clear was -0.95 m/s, exceeding the mission requirements.

In order to explore the yield-increasing mechanism of mechanized potato planting with corn straw mulching, a two-year ( 2021 and 2022 ) field experiment was conducted to study the effects of mechanized no-tillage with straw mulching on potato yield and water use efficiency. This experiment included corn straw mulching potato mechanized no-tillage planting ( JG ), plastic film mulching ( HM ) and open flat planting ( CK ). The results showed that mechanical no-tillage with straw mulching had significant effects on soil water content, yield and water use efficiency in 0-100 cm soil layer (p< 0.05). There was no significant difference in yield between JG and HM, but it was significantly higher than that of CK. The yield of JG was 3.09 %~12.27 % higher than that of CK. The yield increase was mainly achieved by increasing the potato weight per plant ( 0.697 ~ 0.862** ) and the average single potato weight ( 0.048 ~ 0.631 ). The tuber weight per plant was positively correlated with the plant height at seedling stage ( 0.03 ~ 0.92** ), and positively correlated with the dry weight of stems and leaves at tuber expansion stage and starch accumulation stage ( 0.74** ~ 0.95**). It was negatively correlated with the number of branches at tuber formation stage ( -0.33 ~ -0.88** ). Compared with CK, JG could significantly improve the water use efficiency of potato and reduce the water consumption during the whole growth period of crops. In 2021, JG was 6.5 % higher than CK, and HM was 6.88 % lower than CK. In 2022, JG and HM increased water use efficiency by 26.17 % and 14.50 % compared with CK. It can be seen that JG is a green and efficient mechanized potato cultivation technology suitable for dry farming areas.

In this work we looked for a stable and accurate procedure to perform feature selection in datasets with a much higher number of predictors than individuals, as in Genome-Wide Association Studies. Due to the instability in feature selection when many potential predictors are measured, a variable selection procedure is proposed that combines several replications of shrinkage regression models. A weighted formulation is used to define the final predictors. The procedure is applied to investigate Single Nucleotide Polymorphisms (SNPs) predictors associated to Alzheimer’s disease in the Alzheimer’s disease Neuroimaging Initiative (ADNI) dataset. Two data scenarios are investigated: one considering only the set of SNPs and another with the covariates age, sex, educational level and APOE4 genotype. The SNP rs2075650 and the APOE4 genotype are given as risk factors for AD, which is in line with the literature, and other four new SNPs are pointed, opening new hypotheses for in vivo analyses. These experiments demonstrate the potential of the new method for stable feature selection.

This paper constituted an extension of two previous studies concerning the mathematical development of the grain boundary grooving in polycrystalline thins films in the cases of the evaporation/condensation and diffusion taken separately. The thermal grooving processes are deeply controlled by the various mass transfer mechanisms of evaporation–condensation, surface diffusion, lattice diffusion, and grain boundary diffusion. This study proposed a new original analytical solution to the mathematical problem governing the grain groove profile in the case of simultaneous effects of evaporation-condensation and diffusion in polycrystalline thin films submitted to thermal and mechanical stress, and fatigue effects; by resolving the corresponding fourth-order partial differential equation ∂y∂t=C∂2y∂x2-B∂4y∂x4 obtained from the approximation y'2≪1. The comparison of the new solution to that of diffusion alone proved an important effect of the coupling of evaporation and diffusion on the geometric characteristics of the groove profile. A second analytical solution based on the series development was also proposed. It was proved that change of the boundary conditions of the grain grooving profile largely affected the different geometric characteristics of the groove profile.

Arthropods, the most abundant group in ecosystems, play crucial roles in human production. Soil physicochemical properties reflect soil health and are linked to arthropods through cascading effects. Gravel-sand mulching, commonly practiced in dry farming regions, initially aids in water retention and temperature regulation. However, long-term cultivation can lead to land degradation and habitat fragmentation. This study aimed to investigate field systems using multiple comparison, linear, and nonlinear correlation analyses to explore the effects of different tillage durations on soil properties and arthropod diversity under gravel-sand mulching. Results indicate that arthro-pod diversity was lower while the fields maintained better soil fertility than the desert steppe. Both soil fertility and arthropod diversity declined significantly with increased years of cultivation. Mantel tests revealed no significant response of desert steppe arthropods to the altered soil properties of gravel-sand mulched fields. However, the Generalized Additive Model analysis indicated significant linear correlations between arthropod occurrence and total nitrogen (positive), available phosphorus, and water content (negative). Arthropod abundance showed significant nonlinear correlations with total potassium, alkali hydrolyzable nitrogen, and organic matter (OM), with OM changes having the most pronounced impact. Thus, gravel-sand mulching can maintain soil fertility over time but at the expense of local arthropod diversity.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

Boeing and Airbus developed a special testing procedure to investigate the compressive response of laminates that have been impacted (following standards ASTM D 7137 and DIN 65561). This study focuses on both experimental and numerical analysis of Kevlar plates subjected to compression after impact. To ensure high quality and appropriate mechanical properties, the composite plates were manufactured using autoclaving. The DIN 65561 protocol was followed for all three test systems. Initially, ultrasonic C-scanning was performed on all plates before testing to confirm they were free of any significant defects arising from the manufacturing process. Subsequently, low-energy impact testing was conducted at levels ranging from 0 to 8 Joules. Three specimens were tested at each energy level. After the impact, all specimens underwent ultrasonic C-scanning again to assess the internal delamination damage caused by the impactor. Finally, both pristine and impacted specimens were subjected to compressive testing using the special jig specified in DIN 65561. The compressive impact strength results obtained from these tests were plotted against the delamination area measured by C-scanning. This data was then compared to results obtained from specimens with artificial damage. Semi-empirical equations were used to fit both sets of curves. The same procedure (impact testing, C-scanning, and data analysis) was repeated to investigate the relationship between impact energy and total delamination area. Lastly, finite element modeling was employed to predict the buckling stresses that develop under compression in the impacted systems studied. These modelling approaches have demonstrated good accuracy in reproducing experimental results for CAI tests.

The development of accurate dynamic battery pack models for electric vehicles (EVs) is critical for the ongoing electrification of the global automotive vehicle fleet, since these serve as a key element in the energy performance of an EV powertrain system. The Equivalent Circuit Model (ECM) technique at the cell level is commonly employed for this purpose, combining accuracy and efficiency in the representation of battery operation within the broader powertrain system. In this study, a second-order ECM model of a battery cell is being developed using Modelica, an equation-based modeling language. Parameter lookup tables at multiple levels of state of charge (SoC), extracted from Li-ion battery cells with 4 different commonly used cathode materials, have been utilized. This approach allows for a representation of the battery systems that are used in a wide range of commercial EV applications. To verify the model, an integrated EV model is developed and simulation results of the FTP75 driving cycle have been compared against an equivalent application in MATLAB Simulink. The findings demonstrate a close match between the results obtained from both software across different system points. Specifically, the maximum deviation of SoC is limited to 0.08% and the maximum value of relative voltage deviation is 1.4%. The verified model enables the exploration of multiple possible architecture configurations of EV powertrains with Modelica.

This study chose the indoor soil column test as the main method and the field test as the validation test to investigate the effects of various straw mulching techniques (surface, deep and straw mulching + deep burial) on evaporation and salt dynamics in saline soils. The results showed that straw mulching treatment could effectively reduce soil water evaporation, promote desalination in the stage of leaching infiltration and alleviate salt return in the stage of water evaporation, and the effect of straw mulching + deep burial treatment was better than that of single-layer straw mulching treatment. The indoor soil column test showed that S2D1 treatment (a 2:1 ratio of soil surface cover to the amount of straw buried 40cm below the soil surface) had the best effect on the suppression of soil moisture evaporation, and the cumulative evaporation of soil moisture was reduced by 65.85% compared with that of the CK, and the rate of salinity return in the evaporation stage was effectively reduced by 92.04% compared with that of the CK. In addition, there is a significant positive correlation between cumulative evaporation of soil moisture and cumulative soil salinity, which implies that cumulative soil salinity increases with cu-mulative evaporation of soil moisture. The results of the field experiment were consistent with the soil column test, and the S2D1 treatment was able to maintain high soil moisture content in all soil layers in all periods of the experiment and kept soil salinity in the 0-40 cm soil layer at a low level. However, in the 40-80 cm soil layer, the soil salinity suppression effect of DB treatment (straw buried at 40 cm below soil surface) was the best. So in summary, the S2D1 treatment had the best salinity and evapo-transpiration suppression effect in saline soils. This study is of great significance for the resource uti-lization of straw waste, improvement of water utilization and efficiency, and soil salinization manage-ment.

This study was to determine the effects of different irrigation, fertigation and mulching applications on the yield and quality parameters of strawberries. The study was conducted at the Bursa Uludağ University Yenişehir Ibrahim Orhan Vocational School Agricultural Research Field in 2019-2020. In the research, four different irrigation topics, three different fertigation and three different mulching topics were selected The maximum and minimum yield values of the study years were calculated as 5.05-18.70 t ha-1 and 1.20-8.7 t ha-1, respectively, from I100F100M1 and I25F50M0 treatments. As a result, a three-factor study determined that irrigation, fertigation, and mulching had a significant effect on the yield and quality characteristics of strawberries. However, when the reductions in yield and quality losses are evaluated together, despite the reductions in irrigation water and fertigation levels, I75 and F75 topics can be recommended. Also, in mulching treatments, black mulch material (M1) should be chosen over clear mulch material (M1) and no mulch (M0).

Soil salinity is seen as a major restriction for crop production, and with water scarcity this problem becomes more complicated. Mulching is crucial to salinity dynamics management by decreasing evaporation with improving the soil’s characteristics. Using chitosan as an eco-friendly biostimulant can enhance plant defense genes during different abiotic stresses. Recently, agricultural research has recognized nanoparticles as a pioneer material due to their distinctive physicochemical features. Therefore, a lysimeter experiment was conducted to investigate the interactive effects of mulching (UNM: un-mulched, WPM: white plastic, RSM: rice straw and SDM: sawdust) and chitosan foliar application (Ch0: control, Ch1: 250 mg chitosan L-1, Ch2: 125 mg nano chitosan L-1, and Ch3: 62.5 mg nano chitosan L-1) on the biochemical soil characteristics and common beans productivity under salt affected soil conditions. Organic mulching (RSM and SDM) treatments significantly improved the soil's organic carbon, available nutrient content, and total count of bacteria. WPM treatment lowered soil EC to 6.63 dS m-1 and increased soil water content to 34.13%. The application of Ch3 caused considerable increases in the plant height, shoot dry weight, root dry weight, grain yield, and nutrient content in the seed. The total fungi count in the soil and Na% in the seed was significantly decreased due to chitosan foliar applications. Moreover, the interactive effect of different mulch materials plus foliar by chitosan applications gave a statistically similar seed yield in both seasons. Overall, this study revealed the potential of the mulching treatments and foliar application of nano chitosan in improved biochemical soil characteristics and common bean productivity under saline soil conditions.

This narrative review synthesizes recent basic and clinical research on visual disturbances in low-light environments, highlighting evaluation techniques for these conditions. It focuses on the degradation of visual acuity under dim lighting, exacerbated by pupil dilation, known as night vision disturbances (NVD). Key contributors to NVD include optical scattering, intraocular diffraction, ocular aberrations, and uncorrected refractive errors, all significantly impacting quality of life and functional abilities. The review also examines the effects of aging, eye disorders, surgical interventions, and corneal irregularities on NVD. It details the definitions, distinctions, and measurement methodologies for various optical phenomena, using both objective and subjective approaches, such as visual function questionnaires, simulators, and the Light Distortion Analyzer (LDA). The LDA is validated for clinical characterization and quantification of light distortion, proving useful in both clinical and research settings. The review advocates for continued innovation in therapeutic interventions to improve patient outcomes and alleviate the impact of visual disturbances.

Quite a number of cottonseed varieties are existed. The seeds of each variety produce a different amount of gossypol as a natural toxic compound. The increased interest in this natural product and its toxic effects were enhanced the demand for establishing simple silica-gel-based methods for its isolation, purification, and characterization. Historically, silica gel plays a significant role in isolation and purification of many different natural products. Silica gel is variants and can intro-duce a lab, simple tool for tracking a compound in certain plants during its purification process. In this study, gossypol was isolated and purified in the form of yellow crystals as gossypol acetic ac-id. Several methods and tools were used for its characterization including TLC, preparative TLC, silica gel column, UV/IR spectrophotometer and HPLC (Robust spherical silica gel). A compara-tive study between its amounts in both Egyptian and Chinese varieties were performed. Under the experimental condition, the Egyptian cottonseeds contain 8.705 gm/kg, while the Chinese contains 5.395 gm/kg. Thin Layer Chromatography (TLC) had been flourished the science of the phytochemistry and still popular till nowadays and is recommended for fast, accurate, and inex-pensive evaluation and quantification of gossypol. It is recommended to isolate and purify gossy-pol as gossypol acetic acid using optimized combined methods used in this study. Using Silica gel different protocols will assist and facilitate the parallel comparison and save the compact column from any unexpected contaminants during the purification steps. During each step the silica gel itself could be simply removed by paper filtration.

Reducing fertilizer-N rate, applying nitrification inhibitor (NI), and incorporating straw are widely recommended to improve N use efficiency of crops and decrease N losses. However, how these practices affect crop N uptake by regulating the fertilizer-N fate during the growing season is not well understood. We conducted a field 15N tracer study to explore the effectiveness of reduced N application, NI, and straw incorporation on fertilizer-N fates for maize cultivation in Northeast China. The following six treatments were used: 1) no N fertilization (control); 2) 200 kg urea-N ha−1 (100%N); 3) 200 kg urea-N ha−1 and 2400 kg dry-straw ha−1 (100%N+S); 4) 160 kg urea-N ha−1 (80%N, i.e., 20% reduction of N fertilization); 5) 160 kg urea-N ha−1 and nitrification inhibitor (Nitrapyrin) (80%N+NI); 6) 160 kg urea-N ha−1, nitrification inhibitor and 2400 kg dry-straw ha−1 (80%N+NI+S). Our results showed that the five N fertilization treatments yielded 16%–25% more grain and 39%–60% more crop N uptake than the control receiving no N fertilizer, but the differences among the five treatments were not statistically significant. In contrast to plant growth, changes in fertilizer-N fates in soil and plant pools were more pronounced. Compared with the 100%N treatment, 20% fertilizer-N reduction (80%N) decreased 15N concentration in topsoil and plant pools but increased the proportion of plant 15N recovery at harvesting (N use efficiency, NUE15N, 60% vs. 50%) (P < 0.05). Nitrapyrin co-application (80%N+NI) delayed soil nitrification and increased soil 15N retention at harvesting (52% vs. 36%), thereby decreasing NUE15N significantly (P < 0.05). Straw incorporation (100%N+S) decreased fertilizer-N retention compared with NI co-application because it promoted NUE15N significantly (P < 0.05). The combined application of NI and straw (80%N+NI+S) was more conducive to fertilizer-N retention in soil. Our findings demonstrate that NI and straw additions are efficient strategies for stabilizing fertilizer-N in soils and potentially minimizing N loss; however, their effects on NUE15N vary and the related mechanism must be further clarified in long-term trials.

Mannosylerythritol lipids (MELs), one of the most promising biosurfactants (BS), are glycolipids produced by yeasts or fungi, with great environmental performance and a high compatibility with the human body. MELs besides working as typical surfactants, can form diverse structures when in the critical aggregation concentration (CAC), reducing the surface tension of water and other solutions, and being stable over a wide range of conditions. Among others, MELs present anti-microbial, antitumor, antioxidant and anti-inflammatory activity, skin and hair repair capacity, which opens possibilities for their use in applications from cosmetics and pharmaceutics to bio-remediation and agriculture. However, their market share is still low when compared to other glycolipids, due to their less developed production process and higher production cost. This re-view gathers information on the potential applications of MELs mentioned on the literature since 1993. Furthermore, it is also explored the current strategies being developed to enhance the market presence of MELs, in parallel with the ones developed for rhamnolipids and sophorolipids.

Based on DFT (density functional theory) using B3LYP/6-31G method, theoretical investigations applied to demonstrate the structural, electronic properties and stability of (N,Nˊ-(1,4-phenylene)bis(1,8-naphthalimide)) is more stable than the compound (N-(4-amino phenyl)1,8-naphthalimide) by (-1.2762 eV or -29.4299 Kcal.mol-1) depending on the values of HOMO, synthesis reaction of imide is spontaneous and endothermic at temperature 275˚C according to the values of ∆rS, ∆rG and ∆rH.

Three-dimensional (3D) printing technology, also known as additive manufacturing (AM), has emerged as an attractive state-of-the-art tool for precisely fabricating functional materials with complex geometries, championing several advancements in tissue engineering, regenerative medicine, and therapeutics. However, this technology has an untapped potential for biotechnological applications, such as sensor and biosensor development. By exploring these avenues, the scope of 3D printing technology can be expanded and pave the way for groundbreaking innovations in the biotechnology field. Indeed, new printing materials and printers would offer new possibilities for seamlessly incorporating biological functionalities within the growing 3D scaffolds. Herein, we review the extrusion-based 3D printing modalities emphasizing biosensor applications. We highlighted the application of natural, synthetic, and composite biomaterials as 3D-printed soft hydrogels. Emphasis was placed on the approach by which the sensing molecules were introduced during the fabrication process. Finally, the future perspective was provided.

There are several well-described molecular mechanisms that influence cell growth and are relat-ed to the development of cancer. Chemokines constitute a fundamental element which are not only involved in local growth but also affect angiogenesis, tumor spread and metastatic disease. Among them, the C-X-C motif chemokine ligand 12 (CXCL12) and its specific receptor the chemo-kine C-X-C motif receptor 4 (CXCR4) have been widely studied. The overexpression in cell mem-branes of CXCR4 has been shown to be associated with the development of different kinds of his-tological malignancies, such as adenocarcinomas, epidermoid carcinomas, mesenchymal tumors or neuroendocrine neoplasms (NENs). The molecular synapsis between CXCL12 and CXCR4 leads to the interaction of G proteins and activation of different intracellular signaling pathways in both gastroenteropancreatic (GEP) and bronchopulmonary (BP) NENs conferring greater ca-pacity for locoregional aggressiveness, epithelial-mesenchymal transition (EMT) and the ap-pearance of metastases. Therefore, it has been hypothesized how to design tools that target this receptor. The aim of this review is to focus on current knowledge of the relationship between CXCR4 and NENs, with a special emphasis on diagnostic and therapeutic molecular targets.

Dipole antennas, fundamental components in wireless communication systems, have garnered significant attention due to their versatility and efficiency across various applications. This literature review explores the performance analysis of dipole antennas, focusing on recent advancements and methodologies from 2019 to 2024. Employing a systematic approach, the review synthesizes findings from multiple databases, emphasizing peer-reviewed studies that delve into dipole antenna designs and applications. Through meticulous data extraction, key parameters influencing dipole antenna performance, such as material properties and operating frequency, are identified and analyzed. Results highlight the widespread utilization of dipole antennas in wireless communication systems, including indoor positioning, mobile communication, and antenna calibration, among others. Discussions underscore the evolution of dipole antennas in base station environments and their role in filtering applications. The review concludes by emphasizing the continued relevance and evolution of dipole antennas, showcasing their adaptability and potential across diverse wireless communication contexts.

Fires constitute a significant threat due to the pollutants emitted and the destruction they cause. People who take part in fire-fighting operations must be equipped with appropriate tools, including special clothing that will allow them to work and guarantee safety. One of the threats are compounds from the PAH group, which are characterized by high toxicity and carcinogenicity. Therefore, it is important that the materials used constitute a barrier to contamination. Various materials from which individual elements of special firefighter's clothing are made were tested. Additionally, the importance of height on the possibility of sorption of PAH compounds on a given type of material was analyzed. Based on the results obtained, it was found that the type of material and the zone in which the clothing items are used are important in the sorption processes of pollutants. Data in this area may be important for taking further actions regarding the modification of materials used in special fire brigade clothing and in their cleaning processes.

Materials engineering based on metal oxides for manipulating the solar spectrum and producing solar energy have been under intense investigation over the last years. In this work, we present NiO thin films double-doped with niobium (Nb) and nitrogen (N) as cation and anion dopants (NiO:(Nb,N)) to be used as p-type layers in all oxide transparent solar cells. The films were grown by sputtering a composite Ni-Nb target on room-temperature substrates in plasma containing 50% Ar, 25% O2 and 25% N2 gases. The existence of Nb and N dopants in the NiO structure was confirmed by the Energy Dispersive X-Ray and X-Ray Photoelectron Spectroscopy techniques. The nominally undoped NiO film, which was deposited by sputtering a Ni target and used as the reference film, was oxygen-rich, single-phase cubic NiO, having a visible transmittance of less than 20%. Upon double doping with Nb and N the visible transmittance of NiO:(Nb,N) film increased to 60%, which was further improved after thermal treatment to around 85%. The respective values of the direct band gap in the undoped and double-doped films were 3.28 eV and 3.73 eV just after deposition and 3.67 eV and 3.76 eV after thermal treatment. The changes in the properties of the films such as structural disorder, direct and indirect energy band gaps, Urbach tail states and resistivity were correlated with the incorporation of Nb and N in their structure. The thermally treated NiO:(Nb,N) film was used to form a diode with a spin-coated two-layer, mesoporous on top of a compact, TiO2 film. The NiO:(Nb,N)/TiO2 heterojunction exhibited visible transparency of around 80%, showed rectifying characteristics and the diode’s parameters were deduced using the I-V method. The diode revealed photovoltaic behavior upon illumination with UV light exhibiting a short circuit current density of 0.2 mA/cm2 and open-circuit voltage of 500 mV. Improvements of the output characteristics of the NiO:(Nb,N)/TiO2 UV-photovoltaic by proper engineering of the individual layers and device processing procedures are addressed. Transparent NiO:(Nb,N) films can be potential candidates in all-oxide ultraviolet photovoltaics for tandem solar cells, smart windows and other optoelectronic devices.

Many protein expression systems are primary utilised to produce a single, specific recombinant protein. In contrast, most biological processes such as virus assembly rely upon a complex of several interacting proteins rather than the activity of a sole protein. The high complexity of the baculovirus genome, coupled with a multiphase replication cycle incorporating distinct transcriptional steps, made it the ideal system to manipulate for high-level expression of a single or co-expression of multiple foreign proteins within a single cell. We have developed and utilised a series of recombinant baculovirus systems to unravel the sequential assembly process of a complex non-enveloped model virus, Bluetongue virus (BTV). The high protein yields expressed by the baculovirus system not only facilitated structure-function analysis of each viral proteins but were also advantageous to crystallography studies and supported the first atomic level resolution of a recombinant viral protein, the major BTV capsid protein. Further, the formation of recombinant double-shelled virus-like particles (VLPs) provided insights into the structure-function relationships among the four major structural proteins of the BTV whilst also representing a potential candidate for a viral vaccine. The baculovirus multi-gene expression system facilitated the study of structurally complex viruses (both non-enveloped and enveloped viruses) and heralded in a new generation of viral vaccines.

Heat pumps are increasingly becoming a key solution in the quest for decarbonization, offering a significant advantage over traditional boilers due to their superior energy efficiency. Not only can heat pumps provide both heating and cooling, but they also achieve thermal efficiencies exceeding 500%, which can seem to defy conventional expectations. The outdoor unit of a heat pump consists of about twenty main components, one of which is a complex network of copper pipes and sheets welded to valves, connectors, and other fittings. This set involves over thirty welded joints, highlighting a significant opportunity for reducing manufacturing time through process optimization. Copper is a critical material extensively used in various applications due to its excellent thermal and electrical conductivity. However, these very properties make welding copper particularly challenging, especially when aiming to automate and streamline industrial processes. Traditionally, connecting copper pipes and fittings is done through brazing, yet, alternative methods such as LASER welding, electron beam welding, resistance welding, friction welding, and ultrasonic welding also exist. This study focuses on the ultrasonic welding of copper, aiming to identify the optimal parameters that maximize the mechanical strength of overlapping joints and ensure effective tube sealing. Experimental results showed that for copper sheets, the best outcomes were achieved with a welding time of 3 s and a pressure of 6 bar. For tube sealing, the optimal conditions were a welding time of 3 s and a pressure of 4 bar. For both scenarios, the same variables were used, retention time of 0.62 s, initial pressure of 2 bar, retention pressure of 2 bar and sonotrode rising pressure of 3 bar. The analysis reveals that ultrasonic welding of copper can achieve both robust mechanical strength and reliable sealing, making it a promising technique for industrial applications.

Graphene was synthesized through a two-step pyrolysis method using waste candlenut (Aleurites moluccanus) shells as the precursor. Cerium (Ce)/graphene composites were prepared via an impregnation technique. The resulting graphene and Ce/graphene were characterized using various analytical methods, including Scanning Electron Microscopy with Energy-Dispersive Spectroscopy (SEM-EDS), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), Thermo Gravimetric Analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, Cyclic Voltammetry (CV), and Linear Sweep Voltammetry (LSV). The bio-carbon produced predominantly exhibited a graphene structure with flat carbon morphology and an interlayer distance of 0.33 nm. This structural information is supported by XRD data, which shows a broad and weak peak at 2θ = 26° corresponding to the C (002) plane, indicative of graphene presence. FTIR, XPS, and Raman spectroscopy further confirmed the presence of graphene through the detection of Csp2 aromatic bonds and the characteristic D, G, and 2D peaks. Notably, the performance of cerium can be enhanced by the incorporation of graphene, attributed to the large surface area and chemical interactions between Ce and graphene. Consequently, candlenut-derived graphene shows potential as a supportive material for modifying the properties of cerium, thereby opening avenues for various advanced applications, such as sustainable and high-performance energy storage systems.

Resveratrol (RSV), a naturally occurring phytoalexin, is the most important stilbenoid synthesized by plants, as a defense mechanism, in response to microbial aggression, toxins or ultraviolet radiation. RSV came to the attention of researchers both as a potential chemopreventive agent and a possible explanation for the low incidence of cardiovascular disease (CVD) in French people with a high-fat diet. RSV is mainly administered as a food supplement, its properties being evaluated in vitro or in vivo, on various experimental models. RSV modulates signaling pathways that limit the spread of tumor cells, protects nerve cells from damage, is useful in the prevention of diabetes, and generally acts as an anti-aging natural compound. It was highlighted that RSV could ameliorate the consequences of an unhealthy lifestyle caused by an exaggerated caloric intake. This paper reviews the evidence supporting the beneficial effect of RSV for various pathological conditions, e.g., neoplastic diseases, neurodegeneration, metabolic syndrome, diabetes, obesity, CVDs, immune diseases, bacterial, viral, and fungal infections. The study also focused on the chromatographic analysis of trans-RSV (tRSV) in Romanian wine samples, providing a comprehensive overview of tRSV content across different types of wine.

A field experiment to assess the effect of mulch on growth (days to maturity, plant height, leaf length and leaf number) of Garlic (Allium Sativum L.) was conducted in 2015 - 2016 at Addis Ababa University Selale campus, on demonstration field to identify optimum plant growth using different mulches for Garlic tested independently. The experiment was designed using randomized complete block. The analyzed result using ANOVA shows significance difference among the treatments. Plots treated with black polyethylene mulch and grass mulch enhanced maturity by about 114 and 116 days, respectively, while garlic in control showed slightly delayed maturity of 125 days. Maximum plant height (66.5 cm) was recorded in the plants mulched by black polyethylene mulch followed by grass mulch which records 62.3 cm and 52.3 cm, respectively. A highly significant variation (p<0.05) in the leaf length was observed at the different mulch treatments. Significantly maximum leaf number (15.3) was recorded in plants mulched with black polyethylene followed by grass mulch with 14.0 leaf number. Thus, black polyethylene and grass mulch performs better than control treatment in growth parameter evaluation of garlic plants under fiche condition.

The pervasive presence of atmospheric pollution, particularly polycyclic aromatic hydrocarbons such as 7,12-dimethylbenz(a)anthracene, instigates aberrant cellular and tissue conditions, precipitating oxidative damage and inflammatory cascades conducive to the onset of cancer, notably mammary cancer. Given the hepatic metabolism of 7,12-dimethylbenz(a)anthracene, the imperative of employing natural antioxidants becomes apparent. In this study, we delve into the antioxidant and hepato-protective properties of Pistacia lentiscus against 7,12-dimethylbenz(a)anthracene-induced toxicity, alongside exploring its potential anticancer attributes. Our investigations unveil Pistacia lentiscus's anti-proliferative efficacy against human breast cancer cell lines. Notably, 7,12-dimethylbenz(a)anthracene-intoxication escalates body weight, disrupts lipid profiles, and incites serum oxidative damage. Concurrently, hepatic and renal oxidative stress ensue, accompanied by heightened antioxidant enzyme activity in the 7,12-dimethylbenz(a)anthracene-exposed-group compared to controls (p&lt;0.05). Nonetheless, Pistacia lentiscus co-administration rectifies biochemical imbalances, significantly attenuates oxidative stress aberrations, and augments antioxidant enzyme responses (p&lt;0.05). Importantly, histological analysis evinces Pistacia lentiscus's shielding effect against 7,12-dimethylbenz(a)anthracene induced hepatocyte injury and steatosis. Our findings underscore Pistacia lentiscus's robust anti-proliferative, antioxidant, and hepato-protective capacities, mitigating metabolic disturbances, oxidative stress propagation in liver and kidney functions, and potential histological alterations, thereby impeding 7,12-dimethylbenz(a)anthracene-induced mammary cancer initiation. We posit that Pistacia lentiscus may serve as a prophylactic agent against breast cancer instigated by this carcinogen.

Circulating tumor cells (CTCs) are cells released from the primary tumor and intravasate into the blood or lymphatic vessels, where they are transported to distant sites and act as seeds that initiate cancer metastases. Recent advances in CTC research have shown their relevance as prognostic markers for early and metastatic disease detection, predictive biomarkers for relapse, and response to medical intervention or therapy. The rapidly evolving landscape of CTC biology has opened new avenues for understanding cancer progression, metastasis, and treatment response. Additionally, translating these findings into clinical applications holds promise for improving cancer diagnostics, prognosis, and personalized therapeutic strategies. This review discusses the significance of CTCs in cancer research and their associated challenges. We explore recent developments in the detection and characterization of CTCs and their implications in cancer research and clinical practice.

Performing optimisation and scale-up studies of crystallisation systems requires accurate and computationally efficient mathematical models. The assumption of the ideal mixing conditions in batch reactors typically produce inaccurate results while the computational expense of CFD models is still prohibitively high. Therefore, in this work, a new intermediary approach is proposed that takes into account the non-ideal mixing conditions in the reactor and requires less computational resources than full CFD simulations. Starting with the Danckwerts concept of the intensity of segregation, an analogy between its application to chemical reactions and the kinetics of the crystallisation phenomena (such as nucleation and growth) has been made. As a result, the modified kinetics expressions have been derived which incorporate the effect of non-idealities present in stirred reactors. This way, based on the experimental measurements of the mixing time using the Laser Induced Fluorescence (LIF) technique, computationally more efficient mathematical models can be developed in two ways: (1) the accurate semi-empirical correlations are available for standard mixing configurations with the most often used types of impellers, (2) CFD simulations can be utilised for estimation of the mixing time; in this case it is necessary to simulate only the mixing process. The benefits offered by the LIF experimental technique have been demonstrated and some frequent problems in its application analysed. The mixing time results for configurations with and without baffles for three types of impellers and four different rotational speeds have been presented. The false shorter mixing times in the non-baffled configurations have been observed and this phenomena explained by the existence of two segregated zones in the reactor and confirmed by additional experiments. The precise measurements in these cases have been shown as difficult using the LIF technique, particularly for higher rpms. The experimental data has been compared to the preliminary simulation results obtained from the Smoothed Particle Hydrodynamics method and the standard k-ε turbulence model with the modest success. The shortcomings of the SPH model have been recognized and the directions for the future work discussed.

Oilseed plants of the Brassicaceae plant family are cultivated for food, feed and industrial purposes on large-scale in Europe. This review gives an overview of current market-oriented applications of new genomic techniques (NGTs) in relevant Brassicaceae oilseed crops based on a literature survey. In this respect, changes in oil quality, yield, growth and resistance to biotic and abiotic stress are goals in oilseed rape (B. napus) and camelina (C. sativa). Environmental risk assessment scenarios are developed for specific NGT applications in Brassicaceae oilseed crops with either a changed oil composition or with fitness related traits. In case of a changed oil composition an increase or decrease of polyunsaturated fatty acids (PUFA) demonstrates risks for health and survival of pollinators. In case of fitness related traits other risks were identified, i. e. an increased risk of spread and persistence of NGT plants. Furthermore, there are indications for potential disturbance of interactions with the environment, involving signalling pathways and reaction to stress conditions. It is shown that for a comprehensive risk assessment the technological potential of NGTs, the plants’ biology and the scale of releases have to be considered in combination. Therefore, the release of NGT plants into the environment for agricultural purposes will require risk assessment and monitoring of single traits as well as of combinatorial and long-term cumulative effects. In addition, risk management should develop concepts and measures to control and potentially restrict the scale of releases. This is especially relevant for NGT Brassicaceae in Europe which is a centre of diversity of this plant family.

A detailed review of the scientific literature was undertaken to examine the most recent developments in plasma processing in the field of medicine. The first part of the review includes a detailed breakdown of the different types of coatings that can be applied onto medical devices using plasma, with a specific focus on antimicrobial surfaces. The developments during 2023 in plasma deposited biocompatible, drug delivery and adhesive coatings are described and specific applications in additive manufacturing are highlighted. The use of plasma and plasma activated liquids as standalone therapeutics continues to evolve and pertinent advances in this field are described. In addition, the combination of plasma medicine with conventional pharmaceutical interventions was reviewed and key emerging trends were highlighted, including the use of plasma to enhance drug delivery directly into tissue. The potential synergies between plasma medicine and chemotherapeutics for oncology and infection treatment is a growing area and recent advancements are noted. Finally, the use of plasma to control excess antibiotics and to intentionally degrade such materials in waste streams is described.

Polyhydroxyalcanoates (PHAs) are biodegradable polymers synthesized in cytoplasmic granules in bacteria, such as Cupriavidus necator (Ralstonia eutropha), Alcaligenes latus, Pseudomonas spp., Comamonas spp. and other species. PHAs accumulation occurs in response to stress conditions, i.e. under high carbon and low nitrogen (24:1 ratio). PHA can be synthesized using recombinant microorganisms (provided with the operon phbA/phbB/phbC), escaping the constrains of nutrient request, except addition of high amount of sugar (glucose, lactose, fructose). In this study; E. coli was genetically modified for PHB production in biofermentors. The production of PHA at industrial scale requires a continuous supplementation of fermentable sugars to support the availability of nutrients and to assess the level of the exponential growth phase; since sugars are required either for bacterial growth either for PHA synthesis and energy storage. The biofermentors need to be run in automated system. Sensors are used at many points in fermentators; in the evaluation of parameters: consumption of sugars; cell density; quantification of PHB synthesis. The need of operational control during the fermentation has prompted us to application of three measurements; one unit linked to a Nanodrop to evaluate OD; one linked to a reaction chamber to measure sugars consumed by enzyme based fluorescence detection; and one for bacteria Nile Blue staining and fluorescence intensity reads. The growth of bacteria on three different plant by-products was monitored and PHB production in four days using a banana by-product feed was optimised. These detectors will make possible to exploit the full potential of bioreactors optimizing the time of use and maximizing the number of bacteria synthesizing PHA.

This study offers an in-depth analysis of the COVID-19 pandemic’s trajectory in several member countries of the European Union (EU) to assess similarities in their crisis experiences. We also examine data from the United States to facilitate a larger comparison across continents. We introduce our new approach, which uses a spatio-temporal algorithm to identify five distinct and recurring phases that each country undergoes at different times during the pandemic. These stages include a Comfort Period characterized by minimal COVID-19 activity and limited impacts. The Preventive Situation demonstrates the implementation of proactive measures, with relatively low numbers of cases, deaths, and Intensive Care Unit (ICU) admissions. The Worrying Situation is defined by high levels of concern and preparation as deaths and cases begin to rise and reach substantial levels. The Panic Situation is marked by a high number of deaths relative to the number of cases and a rise in ICU admissions, denoting a critical and alarming period of the pandemic. Finally, the Epidemic Control Situation distinguishes itself by limiting COVID-19 deaths despite a high number of new cases. By examining these phases, we identify the various waves of the pandemic, indicating periods where the health crisis has a significant impact. This comparative analysis highlights the time lags between countries as they transition through these different critical stages and navigate the waves of COVID-19.

Feature selection is predominantly used in machine learning tasks, such as classification and regression. It selects a subset of features (relevant attributes of data points) from a larger set that contributes as optimally as possible to the informativeness of the model. There are exponentially many subsets of a given set, and thus, the exhaustive search is only practical for problems with at most a few dozen features. In the past, there have been attempts to reduce the search space using dynamic programming. However, models that consider similarity in pairs of features besides the quality of individual features do not provide the required optimal substructure. As a result, algorithms, which we will call suboptimal dynamic programming algorithms, find a solution that may deviate significantly from the optimal one. In this paper, we propose a dynamic programming algorithm with an iterative upgrade where the order of feature processing is inverted in each iteration. Such an alternating approach allows for improving the optimization function by using the score from the previous iteration to estimate the contribution of unprocessed features. The iterative process is proven to converge and terminate when the solution does not change in three successive iterations or when the number of iterations reaches the threshold. Results in more than 90 % of tests align with those of the exhaustive search, being competitive and often superior to the reference greedy approach. The validation was done by comparing the scores of output feature subsets and examining the accuracy of different classifiers learned on these features. In the context of feature selection, the proposed algorithm can be characterized as a filter method. However, we expect that the idea of alternating suboptimal optimization will soon be generalized to tasks beyond feature selection.

The rapid proliferation of Internet of Things (IoT) technology has ushered in a new era of connectivity, allowing billions of devices to produce extensive data. Significant challenges in software engineering need to be addressed for full utilization of Internet of Things (IoT) applications. This article examines the challenges in Internet of Things, software engineering and discusses current developments aimed at addressing these issues and seizing new opportunities. We examine the challenges associated with Internet of Things software development, including resource constraints, device diversity, security vulnerabilities, and data management concerns. New studies have indicated the use of advanced techniques like as containerization, model-driven development, AI and ML integration, and robust security frameworks. Moreover, the significance of system architecture is explained, including the device, network, and cloud layers, with an emphasis on the principles of reusability, scalability, and modularity. Results and conversations explore the complexities of security measures, emerging opportunities, and scaling solutions made possible by simulation tools, penetration testing, and cross-domain development platforms. The study expects IoT system evolution and emphasises the need for continual software and firmware changes, testing, and deployment.

Splines and quasi-interpolation operators are important both in approximation theory and applications. In this paper, we construct a family of quasi-interpolation operators for the bivariate quintic spline spaces S₅³ (∆_mn⁽²⁾). Moreover, the properties of the proposed quasi-interpolation operators are studied, as well as its applications for solving two-dimensional Burgers’ equation and image reconstruction. Some numerical examples show that these methods, which are easy to implement, provide accurate results.

Graphene hybrid-filler polymer composites have emerged as prominent materials that revolutionize heavy industries. This study encapsulates the in-depth analysis of different influential factors such as filler/graphene type, aspect ratios, dispersion methods, filler-matrix compatibility, fiber orientation, synergistic effects, different processing techniques, and post-curing conditions that affect the processing, properties and determine the resultant applications of graphene hybrid polymer composites. Additionally, it discusses the substantial role of graphene collaboration with other fillers such as carbon nanotubes, silica, nano-clays and metal oxides to produce functionalized hybrid polymer composites with synergistically enhanced tailored properties to offer solutions for heavy industries like aerospace, automotive, electronics, and energy harvesting. The review concludes with some suggestions and outlook on the future of these composite materials by emphasizing the need for continued research to fully optimize their potential.

Nowadays, the growing concern about improving thermal comfort in textiles, asphalt pavements and buildings has stimulated research into phase change materials (PCMs). However, the incorporation of PCMs directly causes mechanical impacts. Therefore, this study herein reported focuses on designing coaxial phase change fibres using commercial cellulose acetate (CA) or recycled CA obtained from cotton fabrics (CAt) as a coating and polyethylene glycol (PEG) 2000 as a core. The phase change fibres (PCF) were produced by wet spinning, varying the parameters: (i) CA concentration, molecular weight and source (virgin versus recycled); and (ii) PEG concentration and ejection. For phase change recycled fibres (PCFt), PEG concentration and ejection were varied. The fibres were assessed for their optical, chemical, thermal and mechanical properties. Bright-field microscopy images and Scanning Electron Microscopy (SEM) micrographs proved the coaxial structure. Fourier Transform Infrared spectroscopy (FTIR) confirmed the presence of PEG in the core. Thermogravimetric Analysis (TGA) proved the ability of PCFs to tolerate high temperatures. Differential Scanning Calorimetry (DSC) attested to the presence of PEG2000 peaks, since their melting points were close to those of virgin PEG2000, with a slight change in the PCFs and PCFts caused by the protective sheath of CA and CAt.

This study analyzed the structural changes of semicrystalline polylactide (PLA) in the form of spun-bonded mulching nonwoven, during outdoor composting. The investigation was carried out at the microstructural, supramolecular and molecular levels using scanning electron microscopy (SEM), wide-angle X-ray diffraction (WAXD) and the viscosity method, respectively. The results showed the varying degree of influence of the climatic condition, prepared compost mixtures and time on the molecular, supramolecular and micromorphological structure of PLA spun-bonded mulching nonwoven and its degradation rate. The obtained experimental results revealed how the popular outdoor composting method, realized under two different European climatic conditions (in Poland and in Bulgary), affects the degradation of PLA nonwoven, designed for agriculture use.

Titanium alloys belong to the metal biomaterials that are one of the most widely used in medicine. In recent years, in order to reduce the use of vanadium, Ti6Al4V alloy is increasingly replaced by Ti6Al7Nb alloy. In addition, to ensure the best possible biocompatibility, its surface is subjected to appropriate modifications, for example, anodic oxidation. Despite the extensive use of anodic oxidation of titanium implants in orthopedics, there are few works focused on a detailed analysis of the chemical composition of the surface layers. In addition, the effect of treatments before anodic oxidation on the properties of the produced layer has not been analyzed. Thus, the purpose of this study was to analyze in detail the chemical composition of the passive layer of Ti6Al7Nb alloy obtained by anodic oxidation preceded by sandblasting. Moreover, the physicochemical properties of the analyzed surface affecting biocompatibility were determined. For this purpose, surface observation, wettability and roughness tests, microhardness tests, electrochemical tests and phase composition analysis were carried out. In addition, the preclinical suitability, of the surface modified in this way, was evaluated by cytotoxicity tests.

In polymer-based dental composites, wear is a three-body wear system mainly abrasive, because of the food particles and wear products suspended in the oral cavity, which are transferred to the microcavities of the surface of the replacements. Due to this fact, the incorporation of nanodiamond as reinforcement in these polymer matrix composites, which promotes the creation of a solid lubricant tribofilm surface could be advantageous. When nanodiamond is added in contents of 0.8, 1.6 and 3.2 wt %, an increase in microhardness from 95 up to 420 %, compared to the one of neat BisGMA/TEGDMA, is observed. Additionally, the incorporation of a content of 1.6 wt % is enough to cause a diminution of ~78 % in the friction coefficient and a reduction of the specific wear rate and Archard’s coefficient of ~50 %. Nevertheless, the addition of relatively high contents reduces the effectiveness of photoinitiation and UV-curing, which is related to the scattering and absorption of UV radiation by ND.

This study investigates the long-term stability of the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) moderate-resolution Thermal Emissive Bands (M TEBs; M12 – M16) covering a period from February 2012 to August 2020. It also assesses inter-sensor consistency of the VIIRS M TEBs among three satellites-S-NPP, NOAA-20, and NOAA-21 over eight months spanning from March 18 to November 30, 2023. The field of interesting is limited to the ocean surface between 60°S and 60°N, specifically under clear-sky conditions. Taking radiative transfer modeling (RTM) as the transfer reference, we employed the Community Radiative Transfer Model (CRTM) to simulate VIIRS TEB brightness temperature (BTs), incorporating European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data as inputs. Our results reveal two key findings. Firstly, the reprocessed S-NPP VIIRS TEBs exhibit a robust long-term stability, as demonstrated through analyses of the observation minus background BT differences (O-B ∆BTs) between VIIRS measurements (O) and CRTM simulations (B). The drifts of the O-B BT differences are consistently less than 0.105 K/Decade across all S-NPP VIIRS M TEB bands. Notably, observations from VIIRS M14 and M16 stand out with drifts well within 0.04 K/Decade, reinforcing their exceptional reliability for climate change studies. Secondly, excellent inter-sensor consistency among these three VIIRS instruments is confirmed through the double-difference analysis method (O-O). This method relies on the O-B BT differences obtained from daily data. The mean inter-VIIRS O-O BT differences remain within 0.08 K for all M TEBs, except for M13. Even in the case of M13, the O-O BT differences between NOAA-21 and NOAA-20/S-NPP have values of 0.312 K and 0.234 K, respectively, which are comparable to the 0.2 K difference between some TEBs among VIIRS and MODIS. These disparities are primarily attributed to the significant differences in the Spectral Response Function (SRF) of NOAA-21 compared to NOAA-20 and S-NPP. Our study confirms the RTM-based TEB quality evaluation method’s versatility and effectiveness in assessing long-term sensor stability and inter-sensor consistency. The double-difference approach effectively mitigates uncertainties and biases inherent to CRTM simulations, establishing itself a robust mechanism for assessing inter-sensor consistency. In addition, we’ve observed that, except for M13, M12 always exhibits larger spatial variations of O-O BT differences with greater uncertainties compared to the other M TEBs. The influence of solar contribution through sea surface reflection on the Top of Atmosphere (TOA) radiance measurements during daytime in M12 should not be underestimated.

The review aims to assess fifteen (15) academic literature sources, highlighting the application of machine learning algorithms in the maintenance operations of optical fiber networks. It exhibits the collection of data using PRISMA methodology—Preferred Reporting Item for Systems Review and Meta-Analyses. The application, results, and performance metrics are discussed based on the collected observations, computations, and statistics in the studies, which revealed records of high accuracy degrees ranging from 86% to 98% on average and quality ML models including Neural Networks (NNs), Support Vector Machines (SVMs), and LSTM, as well as deep learning models that disclosed effective results of determining challenges and problems within the optical fiber lines. The review mainly centralized on superior machine learning technologies that surpass traditional techniques in fault detection and localization for improved optical fiber networks’ operations while providing insights into the limitations and challenges encountered in real-world applications of these models, offering a comprehensive perspective on the optical fiber network’s domain.

Cell-culture meat is a novel concept to replace traditional meat produced from animals, and to satisfy rising food demands due to the world population growth. It is still a young field and requires to solve technical issues including cell sources and types, efficient culture for large scale production, taste and texture for customer satisfaction. The current review summarized traditional beef meat production and evaluation methods for customer satisfaction. In particular, serum biomarkers for beef meat evaluation are discussed, which can be applicated for cell-culture meat production.

Halide perovskite materials gain enormous attention for their semiconducting properties, higher power conversion efficiency and potential applications in a wide range field of studies along with their two key limitations: stability and toxicity. In spite of great progress made on the halide perovskites and many promising research developments, overcoming these limitations is not realized yet. Therefore, coordination engineering of new framework for obtaining alternative new halide perovskite materials and fundamental understanding of the coordination chemistry and electronic interactions forming the structure of these newly engineered halide perovskite materials might be one way in order to overcome the issues related to both stability and toxicity. In this review, the current development of halide perovskite families, both lead halide perovskites and lead free halide perovskites followed by coordination engineering of the new frameworks to engineer new halide perovskite materials will be reviewed comprehensively. Moreover, all the concerns of the fundamental ideas of coordination chemistry and electronic interactions that are keys in forming the halide perovskite structures are discussed in detail and form the main aim of this review. Interestingly, we also discuss recent potential energy applications beyond photovoltaic and this review has completed with an essential and open question: ‘what could happen in the future of halide perovskites?’ in order to excite commercial enterprises and research institutions again as well as to get motivating new predictions on the future continuity of this field.

Merkel cell carcinoma (MCC) is a rare, highly aggressive skin cancer characterized by two etiologies: the first one, observed in most cases, is attributed to Merkel cell polyomavirus (MCPyV), a DNA tumor virus, while the second one is due to ultraviolet (UV) radiation exposure. Currently, there are limited diagnostic, prognostic, and therapeutic biomarkers available for MCC. MicroRNAs (miRNAs) are small RNA molecules that do not code for proteins but regulate various cellular processes, including cell cycle progression, proliferation, differentiation, and apoptosis. The dysregulation of miRNAs has been associated with a wide range of cancers since they can act as either tumor suppressors or oncogenes. This paper aims to collect, summarize and re-organize the recent discoveries concerning miRNAs, whose dysregulation in the pathogenesis and progression of MCC is slowly emerging. Furthermore, the potential clinical applications of miRNAs as diagnostic biomarkers, possible differentiation between MCPyV-related and unrelated MCC, predictors of response to therapy and prognostics are also discussed. From this review, it emerges that miRNAs may have, in the near future, the potential to become clinically significant in improving the diagnostic accuracy, prognostic evaluation, and therapeutic options of MCCs. Finally, the new perspectives on the poorly explored field of artificial intelligence in MCC are provided.

The Metaverse of Things (MoT) is an advanced technology that has the potential to revolutionise urban living in the present era. This article explores the advantages, uses, and transformative outcomes of MoT in smart cities. The covered subjects encompass sustainability, urban planning, citizen participation, infrastructure management, and various more. MoT integrates the Internet of Things (IoT) with metaverse technologies. The ultimate objective is to develop virtual environments that are highly interactive, interconnected, and immersive while maintaining a high level of fidelity to reality. The IoT utilises virtual reality (VR), augmented reality (AR), and other digital technologies to gather data, facilitate communication, and automate certain processes, thereby enhancing several elements of urban living. It is all a component of the metaverse. The IoT will bring about a profound transformation in the way cities gather and utilise data to enhance services and optimise efficiency. Cities that can efficiently distribute this data can enhance public safety, optimise energy usage, regulate traffic, and manage waste properly. MoT apps that utilise immersive technologies and the IoT can be used to generate more intelligent and captivating cityscapes. The implementation of MoT can greatly enhance the quality of life for residents of smart cities through improvements in transportation, healthcare, education, and community engagement. The study's author examined how smart cities utilise the IoT to enhance the daily experiences of their inhabitants. This study examines the technical structure, possible advantages, and difficulties of implementing MoT in urban settings, aiming to enhance the resilience, responsiveness, and adaptability of cities. The findings emphasise the importance of robust legislative frameworks, stringent security requirements, and well-developed infrastructure to facilitate the extensive use of MoT technology. These factors are crucial for establishing a highly interconnected and efficient urban environment.

The 20th century, global temperatures underwent significant changes, impacting agricultural climate zones worldwide. Xinjiang, China, a key player in machine-picked cotton production, was influenced by various heat-related indicators(sum of active temperature ≥ 10℃、mean temperature in July、climatological growing season length, April-May sum active temperature、Last spring frost, and Defoliator spray time). Using meteorological data from 58 weather stations in Xinjiang, we examined the spatio-temporal trends of these indicators during the period of 1981-2020. Additionally, we considered the effects of climate warming and plastic mulching on the sowing area and zoning area of machine-picked cotton in different suitable zones. Overall, Xinjiang experienced an trend in heat resources, with a pattern of "more in the southern part than the northern part, and more in plains and basins than in mountainous areas." Under climate warming conditions, the sowing area of the most suitable cotton zone and the suitable cotton zone has increased, while the sowing area of the moderately suitable cotton zone and unsuitable cotton zone has decreased. Under the plastic mulching mechanism, a comparison of the zoning area and sowing area from 1991 to 2020 revealed that there was no difference in the zoning area of the most suitable zone compared to the sowing area, while the zoning area of the suitable zone increased by 15.7% (2.15×103km2) compared to the sowing area. The zoning area of the moderately suitable zone decreased by 14.5% (0.26×103km2), and the unsuitable zone decreased by 7.8% (0.17×103km2) compared to their respective sowing areas. These results indicate that climate warming and plastic mulching have increased the cultivable area of machine-picked cotton in Xinjiang, but there are also instances of unreasonable zoning. It is necessary to allocate land resources reasonably based on climatic conditions to ensure the healthy development of the cotton industry in Xinjiang.

This manuscript offers a concise overview of paper microfluidics, emphasizing its sustainable sensing applications in healthcare, environmental monitoring, and food safety. Researchers have developed innovative sensing platforms for detecting pathogens, pollutants, and contaminants by leveraging the paper’s unique properties, such as biodegradability and affordability. These portable, low-cost sensors facilitate rapid diagnostics and on-site analysis, making them invaluable tools for resource-limited settings. The review discusses fabrication techniques, principles, and applications of paper microfluidics, showcasing its potential to address pressing challenges and enhance human health and environmental sustainability.

Motivated by a common Mathematical Finance topic, this paper surveys several results concerning windings of 2-dimensional processes, including planar Brownian motion, complex-valued Ornstein-Uhlenbeck processes and planar stable processes. In particular, we present Spitzer's asymptotic Theorem for each case. We also relate this study to the pricing of Asian options.

Transportation plays an important role in urban development. Population growth and environmental burden have turned the efforts of cities globally towards smarter and greener mobility. Cooperative and Connected Automated Mobility (CCAM) serves as a concept with the power and potential to help achieve these goals building upon technological fields like Internet of Things, computer vision and distributed computing. However, its implementation is hindered by various challenges covering technical parameters such as performance and reliability in tandem with other issues, such as safety, accountability and trust. To overcome these issues, new distributed and decentralized approaches like blockchain and smart contracts are needed. This paper aims at identifying a comprehensive inventory of CCAM challenges and use it as a framework to describe methodologies using blockchain and smart contracts to address them. It provides a comparative analysis of the findings to draw useful conclusions and discuss future directions in CCAM and relevant blockchain applications. The paper contributes to intelligent transportation systems’ research by offering an integrated view of the difficulties in substantiating CCAM and providing insights on the most prominent blockchain and smart contract technologies that tackle them.

The cooling of server components has been continuously developed over the past few years in order to meet the increasing cooling requirements of server component manufacturers such as for the processor chips. The growth in performance and power density increases the cooling demand. These requirements directly influence the energy consumption and performance of the hardware. To gain a better understanding of the historical evolution and possible future technology development paths in the field of data center cooling, a patent analysis method was used. The focus is on previous and current development priorities and possible research gaps within the server and computer room levels. The European patent database was selected as data source. To determine relevant patents, the search terms for various cooling technologies were developed iteratively. After the patent extraction for the period 2000 - 2023 (earliest priority year), the search results were classified and analysed. Most of the patents deal with air or liquid cooling. In the area of liquid cooling, the focus was on direct liquid cooling, followed by total liquid cooling. Since 2015 a technological shift from air to liquid cooling can be identified on the level of patent activities. In this context, the patent groups with focus on “constructional details for different types of electric apparatus” and “electrical digital data processing” have the largest share of patents. In addition, the technology focus of the TOP 10 patent applicants was in the field of liquid cooling. In conclusion from the patent analysis, it can be derived that liquid cooling will continue to gain in importance in the future and could also be combined with other approaches in the form of hybrid cooling. However air cooling may still be relevant, even if the main cooling load is handled by liquid-based approaches. At the same time, the optimisation potential for air cooling seems to have been largely exploited in comparison to liquid cooling, as can be seen from the falling number of the patent applications.

Digital Twin (DT) technology is a pivotal innovation within the built environment industry, facilitating digital transformation through advanced data integration and analytics. DTs have demonstrated significant benefits in building design, construction, and asset management, including optimizing lifecycle energy use, enhancing operational efficiency, enabling predictive maintenance, and improving user adaptability. By integrating real-time data from IoT sensors with advanced analytics, DTs provide dynamic and actionable insights for better decision-making and resource management. Despite these promising benefits, several challenges impede the widespread adoption of DT technology, such as technological integration, data consistency, organisational adaptation, and cybersecurity concerns. Addressing these challenges requires inter-disciplinary collaboration, standardization of data formats, and the development of universal design and development platforms for DTs. This paper provides a comprehensive review of DT definitions, applications, capabilities, and challenges within the Architecture, Engineering, and Construction (AEC) industries. This paper provides important insights for researchers and professionals, helping them gain a more comprehensive and detailed view of DT. The findings also demonstrate the significant impact that DTs can have on this sector, contributing to advancing DT implementations and promoting sustainable and efficient building management practices. Ultimately, DT technology is set to revolutionize the AEC industries by enabling autonomous, data-driven decision-making and optimizing building operations for enhanced productivity and performance.

In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and re-analysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, to capture the nuanced dynamics of Cyprus's atmospheric conditions. With a temporal resolution of 15 minutes and a spatial of 0.05°x0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models' accuracy but also highlights their proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), of -2 to -4% per decade have been found in Autumn, especially marked on the island’s Northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of -2 to -3% per decade that were found in Spring do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the Daylight Integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data.

The terpolymers of N-vinylpyrrolidone (VP) with acrylic acid and triethylene glycol methacrylate were synthesized with more than 90% yield by radical copolymerization in ethanol from monomeric mixtures of different composition (98 : 2 : 2, 95 : 5: 2 and 98 : 2: 5). Their physical and chemical characteristics such as monomer composition, absolute molecular masses and hy-drodynamic radii in aqueous media at different temperature were determined. The temperature effect on the behavior of terpolymers in water and aqueous saline buffer solution with pH 7.4 has been studied and the ability of a copolymer enriched with dimethacrylates units was discovered to respond to a temperature change in these media. On the basis of terpolymers and linear polyvi-nylpyrrolidone (PVP), polymer compositions of hydrophobic dye methyl pheophorbide a, MPP, that is fluorescent in the red region of the spectrum, were obtained; the sizes of the polymer nanostructures of MPP in water were determined. The structures based on terpolymers were demonstrated to be more stable than MPP-PVP ones. It was carried out the quantum-chemical modelling of the possible structures of MPP-copolymer that formed as a result of intermolecular interaction between MPP and terpolymer’s chains; the possibility of the formation of hydrogen bonds between the donors of the electrons of terpolymer units and the proton donors of the MPP molecule was shown. Using the MTT test, it was established that copolymers of various compositions are low toxic for non-tumor Vero cells and HeLa tumor cells. It was shown that the cytotoxicity of polymer particles loaded with MPP for FetMSC and HeLa cells increased. Using fluorescence microscopy, the accumulation and distribution of polymer particles in non-tumor (FetMSC) and tumor (HeLa) cells was studied and an increase in the accumulation of MPP with both types of particles was shown.

Biomaterials are the basis for the development of medicine because they allow safe contact with a living organism. The aim of this work was to produce innovative oxide layers with a porous microstructure on the surface of commercially pure titanium Grade 4 (CpTi G4), and to characterize their properties as drug carriers. Anodization of the CpTi G4 subjected to mechanical grinding and electrochemical polishing was carried out in a solution of 1M ethylene glycol with the addition of 40 g of ammonium fluoride at a voltage of 20 V for 2, 18, 24 and 48 hours at room temperature. It was found that the longer anodization time, the greater the number of pores formed on the CpTi G4 surface as revealed by FE-SEM method, and the greater the surface roughness determined in profilometric tests. As the anodizing time increases, the amount of the drug in the form of gentamicin sulfate incorporated into the resulting pores decreases. The most favorable drug release kinetics profile determined by UV-VIS absorption spectroscopy was found for the CpTi G4 anodized for 2 h making them the best choice when it comes to the drug carrier allowing full use of the therapeutic dose of the drug.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz need to provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT) and fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

To address the requirements of sonar imaging, such as high receiving sensitivity, wide bandwidth, wide receiving angle, an AlN PMUT with an optimized ratio of 0.6 for the piezoelectric layer diameter to backside cavity diameter is proposed in this paper. A sample AlN PMUT is designed and fabricated with SOI substrate-based bulk MEMS process. The characterization test result of the sample demonstrates a -6 dB bandwidth of approximately 500 kHz and a measured receiving sensitivity per unit area of at 1.37 V/μPa/mm2, which significantly surpasses the performance of previously reported PMUTs. The -6 dB horizontal angles of the AlN PMUT at 300 kHz and 500 kHz are measured 68.30° and 54.24°, respectively. To achieve an accurate prediction of its characteristics when being packaged and assembled in a receive array, numerical simulations with the consideration of film stress are conducted. The numerical result shows a maximum deviation of ±7% in the underwater receiving sensitivity across the frequency range of 200 kHz to 1000 kHz and a deviation of about 0.33% in the peak of underwater receiving sensitivity comparing to the experimental data. By such good agreement, the simulation method reveals its capability of providing theoretical foundation for enhancing the uniformity of the AlN PMUTs in future studies.

The analysis of chemical warfare agents and their degradation products has become increasingly important for public and military safety in recent years. In the article, we drew attention to the possibilities of the HPLC-ICP-MS analytical technique, which has been relatively rarely used for identifying and quantitatively analyzing highly toxic and hazardous substances in environmental samples. This technique enables the identification and determination of minimal amounts (ppt range) of chemicals in various matrices. This fact is important for the analysis of chemical warfare agents and other highly harmful compounds, even small amounts of which can have serious consequences for living organisms. The article critically analyzes the results of scientific research on the identification and quantitative analysis of extremely toxic organophosphorus, organosulfur and organoarsenic substances, their derivatives and degradation products using high-performance liquid chromatography (HPLC) coupled with inductively coupled plasma mass spectrometry (ICP-MS).

Recent research emphasises the importance of Artificial Intelligence applications as supporting tools for students in higher education. Simultaneously, an intensive exchange of views has started in the public debate in the international educational community. However, for a more proper use of these applications, it is necessary to investigate the factors that explain their intention and actual use in the future. With the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, this work analyses the factors influencing students' use and intention to use artificial intelligence technology. For this purpose, a sample of 199 Greek students at the School of Humanities and Social Sciences from the University of Patras participated in a survey. The findings highlight that expected performance, habit, and enjoyment of these Artificial Intelligence applications are key determinants influencing teachers' intentions to use them. Moreover, behavioural intention, habit, and facilitating conditions explain the usage of these Artificial Intelligence applications. The study did not reveal any moderating effects. The limitations, practical implications, and proposed directions for future research based on these results are discussed.

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data–driven grey–box identification approach provided the physically meaningful nonlinear continuous–time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte–Carlo analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model–based and data–driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.

The integration of Wireless Power Transfer (WPT) technologies with Artificial Intelligence (AI) is poised to revolutionize multiple industries, including consumer electronics and industrial applications. This study delves into the latest advancements in WPT, with a focus on AI-enhanced efficiency, range, and reliability. AI-driven algorithms optimize power transfer, improve device alignment, and predict maintenance needs, leading to smarter and more sustainable power solutions. Machine learning and computer vision are employed to achieve precise alignment, while predictive maintenance minimizes downtime and costs. Additionally, AI-powered power management systems adapt to varying demands, optimizing energy usage. This research highlights the transformative potential of AI in enhancing WPT technologies, with significant implications for next-generation applications. The findings emphasize the importance of ongoing research in this interdisciplinary field to address existing challenges and unlock new opportunities for innovation.

The objective of this research was to explore the impact of a gradual replacement of Ca2+ with Mn1+ on the crystal structure of CaHPO4·2H2O, which could be beneficial for producing Ca1−xMnxHPO4·nH2O compounds. In order to prepare the starting solutions required for this study, Ca(NO3) 2·4H2O, (NH4)·2HPO4, and MnNO3·4H2O were used at various molar concentrations. The findings reveal that Mn substitutes Ca partly at low Mn/Ca molar ratios, and Mn doping reduces the unit cell of CaHPO4·2H2O. The produced biphasic compound was composed of monoclinic CaHPO4·2H2O and triclinic/monoclinic nanostructured Mn3PO4O11 after a continuous increase in the Mn/Ca molar ratio to 1. When the Ca/Mn molar ratio is 1.5, a triphasic compound of monoclinic CaHPO4·2H2O, triclinic Mn3P4O11, and Orthorhombic MnHPO4·(H2O)3 phases is formed. The formation of the monophasic MnHPO4·(H2O)3 compound was achieved by increasing the Mn/Ca molar ratio above 4. By adjusting the Mn/Ca molar ratio in the initial solutions, it is possible to produce biomaterials with specific and bespoke characteristics in the future. The Mn/Ca ratio of the starting solution can be modified to produce Ca1-xMnxHPO4-nH2O phases with weight percent compositions, as established. For the first time, Ca1−xMnxHPO4·nH2O compounds were synthesized using novel methods in this manuscript.

Biochar is a carbonaceous material derived from the thermochemical conversion of biomass under oxygen-lean conditions. Its properties render it many applications in agriculture, environmental remediation, and catalysis. Commonly produced by pyrolysis under a nitrogen atmosphere, the biochar composition is influenced mainly by residence time, heating rate, and process temperature. The existing literature primarily assesses biochar properties, such as ultimate, proximate, calorific, porosity, and combustibility, generated under various thermo-conversion conditions. However, there is a notable lack of sufficient investigation and attention given to the practical application of biochar. This article seeks to bridge that gap by enhancing the comprehension of the necessary experimental assessment for specific biochar applications and proposing process optimization methods using Multi-Criteria Decision Analysis (MCDA). By delving into these aspects, the study offers a concise overview of biochar production and presents a comprehensive panorama based on articles and patents. Additionally, the research explores the physicochemical characterization techniques associated with biochar and its various applications in conjunction with MCDA. This comprehensive approach aims to uncover valuable insights that could further advance the practical and sustainable utilization of biochar in a wide range of fields.

Hyperspectral imaging data holds great potential for various stages of the mining life cycle in active and abandoned mines. The technology, however, has yet to achieve large-scale industrial implementation and acceptance. While hyperspectral satellite im-agery yields high spectral resolution, high signal-to-noise ratio (SNR), and global availability with breakthrough satellite sys-tems like EnMAP, EMIT, and PRISMA, limited spatial resolution poses challenges for mining sectors, which require decimeter- to centimeter-scale spatial resolution for applications such as reconciliation, ore/waste estimates, geotechnical assessments, and en-vironmental monitoring. Hyperspectral imaging from drones (Uncrewed Aerial Systems; UASs) offers high spatial resolution data relevant to the pit/ mine scale, with the capability for frequent, user-defined re-visit times. Collecting data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions offers to detect different minerals and surface alteration patterns, potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. In this paper, we review of applicable instrumentation, software components, and relevant studies deploying hyperspectral imaging in or appropriate to the mining sector, especially for hyperspectral VNIR-SWIR UASs. If directly applicable, draw on previous insights derived from airborne, satellite, and ground-based imaging systems. We also discuss common practices for UAS survey planning and sampling considerations for interpretation.

The fitting and modeling of skewed, complex, symmetric, and asymmetric datasets is an exciting research topic in many fields of applied sciences, notably lifetime, medical, and financial sciences. The Heavy tailed Nadarajah Haghighi model is introduced by compounding the heavy tailed family and Nadarajah Haghighi distribution in this paper. The so obtained model has three parameters accounting for the scale and shape of the distribution. The proposed distribution's fundamental characteristics such as probability density, cumulative distribution, hazard rate, and survival functions are provided, and several key statistical properties are established, and several entropy information measures are proposed. The estimation of model parameter is performed via the ML procedure. Further, different simulation experiments are conducted to demonstrate the performance of proposed estimator’s using some measure, like the average estimate, the average bias, and associated mean square error. Finally, we are applied our proposed model to analyze three different real datasets. In our illustration, we are compared the practicality of the recommended model with several well-known competing models.

The surface characterization of indium tin oxide (ITO) films was processed by oxygen (O2) plasma gas using a magnetron sputtering method of varying O2-plasma gas from 20 sccm to 100 sccm for potentially fostering in electronic devices applications on dye-sensitize solar cells (DSSC) in this work. In order to gain an outstanding performance rate with high-quality thin films, the affect of correlation between the electrical, optical, and morphology properties was significantly investigated. Clearly, the content of investigation exhibited that the films properties was changed by variation of the gas composition. These changes have contemporary relevance to the sputtering gas during the deposition process. To conclude, the greatest electrical properties was displayed by O2 -plasma gas flow rate of 20 sccm, which showed the lowest resistivity. In addition to this, the final products were practically fabricated to active layers for dye-sensitize solar cells (DSSC) applications. The highest efficiency of DSSC device was indicated of approximately 0.35% which was located by 40 sccm of the O2-plasma gas. Consequently, the study could be a possibility way of preparing ITO thin films with improved special properties of substantial applications for solar cells devices in the near future.

The objective of this study was to detail the monomer composition of resin-based dental materials sold in the market in 2023 and to evaluate the proportion of BPA derivatives in relation with their applications. A search on manufacturers’ websites was performed to reference resin-based dental materials currently on the market. Their monomer composition was determined from material safety data sheets and completed with a search on PubMed database. Among the 543 material compositions exploitable, 382 (70.3%) contained BPA derivatives. Among them, 56.2% contained BisGMA, 28% BisEMA, the most frequently reported. A total of 59 monomers of which 6 BPA-derivatives were found. 309 materials (56.9%) contained UDMA and 292 (53.8%) TEGDMA. Less than one third of materials identified contained no BPA derivatives. These proportions vary a lot depending on their applications with materials dedicated to dental care of young populations containing the highest proportions of BPA-derivatives monomers. The long-term effects on human health of the different monomers identified including BPA-derivatives monomers is a source of concern. For children and pregnant or lactating women arises the question to take a precautionary principle and avoid the use of resin-based dental materials likely to release BPA by opting for alternative materials.

Semenov-Tian-Shansky has introduced the modified classical Yang-Baxter equation, which is called the modified $r$-matrix. Relevant studies have been extensive in recent times. This paper is devoted to study cohomology theory of modified Rota-Baxter pre-Lie algebras and its applications. First we introduce the concept and representations of modified Rota-Baxter pre-Lie algebras. We then develop the cohomology of modified Rota-Baxter pre-Lie algebras with coefficients in a suitable representation. As applications, we consider the infinitesimal deformations, abelian extensions and skeletal modified Rota-Baxter pre-Lie 2-algebra in terms of lower degree cohomology groups.

We investigate and discuss in detail the structure of the restricted singular value decomposition for a tensor triplet under t-product (T-RSVD). The algorithm is provided with a numerical example illustrating the main result. For applications, we consider color image watermarking processing with T-RSVD.

Enhancing soil fertility and maize productivity is crucial for sustainable agriculture. This study aimed to evaluate the effects of tillage practices, nitrogen management strategies, and acidified hydrochar on soil fertility and maize productivity. The experiment used a randomized complete block design with split-split plot arrangement and four replications. Main plots received shallow tillage and deep tillage. Sub-plots were treated with nitrogen (120 kg ha⁻¹) from farmyard manure and urea, including control, 33% FYM + 67% urea (MU), and 80% FYM + 20% urea (MF). Acidified hydrochar treatments H0 (no hydrochar) and H1 (with hydrochar, 2 t ha⁻¹) were applied to sub-sub plots. Deep tillage significantly increased plant height, biological yield, grain yield, ear length, grains ear-1, thousand grain weight, and nitrogen content compared to shallow tillage. MU and MF improved growth parameters and yield over the control. Hydrochar effects varied; H1 enhanced certain yield components but reduced plant height and soil properties compared to H0. Canonical discriminant analysis linked deep tillage and MU/MF nitrogen management with improved yield and soil characteristics. In conclusion, deep tillage combined with integrated nitrogen manage-ment enhances maize productivity and soil health. However, hydrochar application requires op-timization. These findings highlight the importance of selecting appropriate tillage and nitrogen strategies for sustainable maize production. These insights guide policymakers, agronomists, and agricultural extension services in adopting evidence-based strategies for sustainable agriculture, enhancing food production, and mitigating environmental impacts. Future research should in-vestigate long-term impacts across diverse environments to validate these results.

One of the main constraints of agriculture in sub-Saharan Africa is the steady decline in the level of soil fertility resulting in a continuous decline in crop yields. This study assessed the impact of grass mulch on: the productivity, the income, the soil carbon, and the phytodiversity within three pineapple-based systems of the ecovillage of Donomade in Togo. They are: a model farm with mulch, adopters’ farms, and non-adopters. Production-related data (e.g., number of plants, the number of productive individuals, the mass of products harvested) was obtained by a sampling an area of 100 m². These measurements were coupled with a semi-structured individual’s interviews of producers on the history of the plots and production costs in order to assess their profitability. The fruit production was three times higher within the adopters’ plots (21240 ± 11890 kg/ha) than the non-adopters (7840 ± 7890 kg/ha) and the two thirds of the model farm (33838 ± 9460 kg/ha). Consequently, the net income was 8 to 11 times higher than the conventional pineapple cropping system. According to the cropping systems, the total soil carbon was higher within mulching plots including the model farm and the adopters’ plots and lower within the non-adopters’ plots.

Biopolymer gels have gained tremendous potential for therapeutic applications due to their biocompatibility, biodegradability, and ability to adsorb and bind biological fluids, making them attractive for drug delivery and therapy. The versatility of biopolymer gels in theranostic backgrounds, with a focus on integrating imaging features and facilitating real-time monitoring of drug delivery. Different methods of delivery are explored imaging agents into biopolymer gels, including encapsulation, surface functionalization, nanoparticle encapsulation and layer-by-layer assembly techniques. Integration of Agents and Real-Time Monitoring Drug Delivery We summarize the synthesis methods, general properties, and mechanisms of biopolymer gels functionality, demonstrating their broad applications as multimodal systems for imaging-based therapeutics. These techniques not only enable multiple imaging but also provide signal enhancement and imaging a targeted facilitates, increasing the diagnostic accuracy and therapeutic efficacy. In addition, current techniques for incorporating imaging agents into biopolymer gels are discussed, and their role in precise drug delivery and monitoring.

The objective of this study was to carry out the extraction and characterization of chitin and chitosan from the exoskeletons of the Farfantepenaeus californiensis species of shrimp, as well as its application in the formulation of polymeric films plasticized with glycerol used in the process of food packaging. The characterization of the extracted polymer was made by Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and physicochemical analysis of chitin and chitosan, resulting in a theoretical performance of 29.33% and 16.46%, respectively. In terms of quality, it was determined that the extracted chitosan had a molecular weight of 1.10 x105 g/mol and a deacetylation degree of 80.23%, which classifies it as a low-molecular weight chitosan, suitable for food packaging. It was shown that the extracted chitosan is fit for the production of the films by using the casting method, presenting a tension resistance of 1 MPa. The Antibacterial analysis was carried out using Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli), bacterial models commonly found in food. The results showed an effective inhibition capability of the polymeric materials. Overall, the results for both chitosan and the films indicate a high potential for application in the food packaging sector.

Long COVID, a name often given to the persistent symptoms following acute SARS-CoV-2 infection, poses a multifaceted challenge for health. This review explores the intrinsic relationship between comorbidities and autoimmune responses in shaping the trajectory of long COVID. Autoantibodies have emerged as significant players in COVID-19 pathophysiology, with implications for disease severity and progression. Studies show immune dysregulation persisting months after infection, marked by activated innate immune cells and high cytokine levels. The presence of autoantibodies against various autoantigens suggests their potential as comorbid factors in long COVID. Additionally, the formation of immune complexes may lead to severe disease progression, highlighting the urgency for early detection and intervention. Furthermore, long COVID is highly linked to cardiovascular complications and neurological symptoms, posing challenges in diagnosis and management. Multidisciplinary approaches, including vaccination, tailored rehabilitation, and pharmacological interventions, are used for mitigating long COVID's burden. However, numerous challenges persist, from evolving diagnostic criteria to addressing the psychosocial impact and predicting disease outcomes. Leveraging AI-based applications holds promise in enhancing patient management and improving our understanding of long COVID. As research continues to unfold, unravelling the complexities of long COVID remains paramount for effective intervention and patient care.

Our study essentially concerns the dynamic behavior of an SIRS epidemic model in discrete time. Two equilibrium points are obtained; one is disease-free while the other is endemic. We are interested in the endemic fixed point as well as its asymptotic stability. Depending on the parameters which are estimated using the data from US Department of health and SIRS modelling with optimization, two Flip and Transcritical bifurcations appear. We illustrate their diagrams, as well as their bifurcation curves using the method of Carcasses \cite{carcasses1993determination,carcasses1995singularities} for the Flip bifurcation and by an implicit function deduced from such an equation for the Transcritical bifurcation. We use the scanning of the parametric plane to have a global view of the behavior of the model and to highlight the zones of stability of the existing singularities. A superposition of the bifurcation curves with the parametric plane can show the overlap of the curves with the boundaries of the stability domains, which confirms the smooth running of the simulation and its correspondence with the theory, we finish this article with constrained optimal control applied to infection rate and recruitment rate for an SIRS discrete epidemic model. Pontryagin's maximum principle is used to determine these optimal controls. Finally using COVID-19 data in the USA, we obtain results that demonstrate the effectiveness of the proposed control strategy to mitigate the spread of the pandemic.

Input reconstruction problem is usually encountered in the areas such as virtual sensing, image restoration, sensor linearization, and communications. The input reconstruction problem can be seen as an inverse problem. Given a nominal system, two types of approaches are commonly used for solving the inverse problem. The first one is to directly invert the nominal system, and the second one is to derive an inversion of the nominal system in an indirect way. However, for the first type of approaches, system inversion cannot be directly conducted under some conditions such as there exist nonminimum-phase zeros in the nominal system, while for the second type of approaches, simultaneously guaranteeing stability and causality of the obtained inversion is still not solved well. In order to avoid the drawbacks existing in the two types of approaches, an alternative approach is proposed for input reconstruction. In this approach, the input signal is first modeled as the output of a state-space model, afterwards two Kalman filters for the model resulted by combining the input signal model and the nominal system model are implemented alternatively such that the input signal can be sequentially reconstructed in an infinite horizon. The proposed input reconstruction approach is applied in two examples, and simulation results can illustrate the effectiveness of the proposed approach.

Background: Though ancient Greece preserves many pictures of combat sports, there is research in terms of biomechanics on the principles of human motion. This research aimed to investigate Pankration postures of ancient Greek athletics, expecting to bridge the gap between historical sports practices and contemporary biomechanical applications. Methods: This study employed computational tools to analyze two images from ancient Greek Pankration, constructing a static multi-segmental model. Anthropometric models simulated postures analogous to those in historical depictions. Analysis estimated joint forces and moments, along with weight distribution and ground reaction forces for these postures. Implications for training and strength development were deduced through integration with modern scientific insights. Moreover, strategic elements of these postures were assessed using game theory to explore their correspondence with contemporary theoretical constructs. Results: The findings indicated that static postures facilitate the development of tendon stiffness, joint stability, and neuromuscular control. In the "readiness" posture, 68% of the athlete's centre of gravity (CoG) was distributed to the hind leg, enhancing stability and power generation, while the front leg promoted agility. Analysis of the kick posture revealed delivery with a dorsiflexed ankle and pronounced heel protrusion.Conclusion: The application of the proposed model suggests that ancient athletes optimized their performance using biomechanical principles, thereby gaining a competitive advantage. This study highlights the value of integrating ancient biomechanical strategies with contemporary athletic training and injury prevention, advocating for a synthesis of historical practices and modern biomechanical analysis in combat sports.

Hyperspectral imaging data holds great potential for the different stages of the mining life cycle in active and post-mining environments. However, the technology has yet to reach the stage of large-scale industrial implementation and acceptance. While hyperspectral satellite imagery can achieve high spectral resolution, signal-to-noise ratio (SNR) and global availability with break-through satellite systems like EnMAP, EMIT and PRISMA, limited spatial resolution poses chal-lenges for sectors like mining, which require decimetre to centimetre scale resolution for applica-tions such as reconciliation, ore/waste estimates, geotechnical assessments and environmental monitoring. Hyperspectral imaging from drones (referred to herein as Uncrewed Aerial Systems; UASs) offers high spatial resolution data relevant to the camp/ mine scale, with the capability for frequent, user-defined re-visit times. This has been made possible by the miniaturization of hy-perspectral imaging systems. Collection of data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions enables the detection of different minerals and surface altera-tion patterns potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. In this paper, we provide a review of relevant studies de-ploying hyperspectral imaging in or applicable to the mining sector, especially for the use of hy-perspectral VNIR-SWIR Uncrewed Aerial Systems. Where required, we draw on previous in-sights derived from satellite or ground-based systems. We also discuss UAS survey planning, and sampling considerations for validation and interpretation.

Uterine tube extracellular matrix is a key component that regulates tubal tissue physiology, and it has a region-specific structural distribution, which are directly associated to their functions. Considering this, application of biological matrices in culture systems is an interesting strategy to develop biomimetic tubal microenvironments and enhance their complexity. However, there are no established protocols to produce tubal biological matrices that consider the organ morphophysiology for such applications. Therefore, this study aimed to establish region-specific protocols to obtain decellularized scaffolds derived from porcine infundibulum, ampulla, and isthmus to provide suitable sources of biomaterials for tissue-engineering approaches. Porcine uterine tubes were decellularized in solutions of 0.1% SDS and 0.5% Triton X-100. Decellularization efficiency was evaluated by DAPI staining and DNA quantification. We analyzed ECM composition and structure by optical and scanning electronic microscopy, FTIR and Raman spectroscopy. DNA and DAPI assays validated the decellularization, presenting significative reduction of cellular content. Structural and spectroscopy analyses revealed that produced scaffolds remained well structured and with ECM composition preserved. YS and HEK293 cells were used to attest cytocompatibility, allowing cell survival and successful interaction with the scaffolds. These results suggest that such matrices are applicable for future biotechnological approaches in the reproductive field.

In Functional Analysis as well as Topology, we frequently encounter sets, say $X$, that contain elements close to each other. These sets display a defining "finite-ness" property: for all open cover $\mathcal{O}$ of $X$, there exists a finite subcollection $\mathcal{U}\subseteq\mathcal{O}$ such that $\mathcal{U}$ covers $X$. Such spaces $X$ are called $\textbf{compact}$, and the above "finite-ness" property afford us great convenience, because we can always investigate $X$ by investigating its finite open cover $\mathcal{U}$Arzela-

We consider several unification problems in mathematics. We refer to transcendental numbers. Also, we present some ways to unify the main non-associative algebras (Lie algebras and Jordan algebras) and associative algebras.

Cobalt oxide nanoparticles are promising candidates for various kinds of practical application. The interest of researchers and scientists in these nanoparticles is due to their unique physical and chemical properties such as density, melting point, magnetic characteristics and band gap. The need to develop high performance and low-cost technologies for obtaining Co3O4 nanoparticles is a major reason in research in this area. The widespread commercial use of Co3O4 nanoparticles will open doors for numerous novel cost effective technologies, which are mostly dependent on the type of synthesis method and raw materials. A possible solution to this problem is to use Cobalt nitrates as a cost-effective precursor using the solution combustion method. Solution combustion synthesis method is one of the best candidate methods that have the potential for high performance and is also cost-effective. This review examines recent progress in the synthesis of Co3O4 nanoparticles by solution combustion method and underscores their significance across various fields, highlighting the need for further research and exploration of their multifaceted applications. In addition, the most recent advancements in the applications of Co3O4 nanoparticles in sensitive sensing, catalysis, supercapacitors/batteries and water treatment/pollutants removal are reviewed and described, focusing on current trends, challenges, and future outlooks.

Wide bandgap semiconductors-based photocatalysts are usually limited by their low solar energy conversion efficiency due to their limited absorption solar wavelength, surface’s fast recombination of photoelectron–hole pairs and low charge-carrier mobility. Here we report a new stepwise solution synthesis for making a new photocatalytic core/shell of titanate nanowire/reduced graphene oxide shell (or titanate/rGO) 1D-nanocomposite. The new core/shell nanocomposite maximized the specific surface area, largely reduced the charge transfer resistance and reaction energy barrier, and significantly improved the absorption of the visible light. The core/shell nanocomposites’ large on/off current ratio and rapid photo-responses boosted the photocurrent by 30.0%, the photocatalysis rate by 50.0%, and the specific surface area by 16.4%, when comparing with the pure titanate nanowire core. Our numerical simulations support the effective charge separation on the new core-shell nanostructure, which can help further advance the new photocatalysis.

Clustered regularly interspaced short palindromic repeats (CRISPR) based gene-editing has begun to transform the treatment landscape of genetic diseases. The history of the discovery of CRISPR/CRISPR-associated (Cas) proteins/single guide RNA (sgRNA)-based gene-editing since the first report of repetitive sequences of unknown significance in 1987 is fascinating, instructive, and inspiring for future advances. The recent approval of CRISPR-Cas9-based gene therapy to treat patients with severe sickle cell anemia and transfusion-dependent beta thalassemia has renewed hope for treating other hematologic diseases, including patients with germline predisposition to hematologic malignancies, who would benefit greatly from the development of CRISPR-based gene therapies. The purpose of this manuscript is three-fold: first, a chronological description of the history of CRISPR-Cas9-sgRNA-based gene editing; second, a brief description of the current state of clinical research in hematologic diseases, including selected applications in treating hematologic diseases with CRISPR-based gene therapy; and third, the current progress in gene therapies in inherited hematologic diseases and bone marrow failure syndromes, to hopefully stimulate efforts towards developing these therapies for patients with inherited bone marrow failure syndromes and other inherited conditions with germline predisposition to hematologic malignancies.

Solid polymer electrolytes and composite polymer electrolytes serve as crucial components in all-solid-state energy storage devices. Structural batteries and supercapacitors present a promising alternative for electric vehicles, integrating structural functionality with energy storage capability. However, despite their potential, these applications are hampered by various challenges, particularly in the realm of developing new solid polymer electrolytes that require more investigations. In this study, novel solid polymer electrolytes and composite polymer electrolytes were synthesized using epoxy resin blends, ionic liquid, lithium salt, and alumina nanoparticles, and subsequently characterized. Among the formulations tested, the optimal system, designated as L70P30ILE40Li1MAl2 and containing 40 wt.% of ionic liquid and 5.7 wt.% of lithium salt, exhibited exceptional mechanical properties. It displayed a remarkable storage modulus of 1.2 GPa and reached ionic conductivities of 0.085 mS/cm at 60°C. Furthermore, a proof-of-concept supercapacitor was fabricated, demonstrating the practical application of the developed electrolyte system.

This study introduces a novel nanocomposite coating composed of PANI/CeO2 nanocomposite films, aimed at addressing corrosion protection needs. Analysis through FTIR spectra and XRD patterns confirms the successful formation of the nanocomposite films. Notably, the PANI/CeO2 nanocomposite films exhibit a hydrophilic nature. The bandgap energy of the PANI composite film measures at 3.74 eV, while the introduction of CeO2 NPs into the PANI matrix reduces the bandgap energy to 3.67 eV. Furthermore, the electrical conductivity of the PANI composite film is observed to be 0.40 S.cm-1, with the incorporation of CeO2 NPs leading to an increase in electrical conductivity to 1.07 S.cm-1. To evaluate its efficacy, electrochemical measurements were conducted to assess the corrosion protection performance. Results indicate a high protection efficiency of 92.25% for the PANI/CeO2 nanocomposite film.

Transportation systems through the ages have seen drastic evolutions in terms of transportation methods, speed of transport, infrastructure, technology, connectivity, influence on the environment, and accessibility. The massive transformation seen in the transportation sector has been fueled by the industrial revolutions which have continued expansion and progress into the fourth industrial revolution. However, the methodologies of data collection and processing used by the many drivers of this progress differ. The significance of standardized data and its mode of collection cannot be overstated as it has a major impact on the process outcomes. In order to achieve a better understanding of the impact of this, this study methodically reviewed the literature on the subject of the data collection and processing mechanism of 4IR technologies in the context of the transport industry with an emphasis on the areas of accomplishment of several studies and drawing attention to their limitations. Although the industry has advanced significantly as a result of the adoption and application of various research studies in this field, considerable focus needs to be placed in the areas of standardized data collection and computational approaches, which will ultimately assist in achieving various benefits in the transportation industry.

Background: The transversus abdominis plane (TAP) block has gained increasing importance as a very effective pain relief in for caesarean section. This study aimed to compare bupivacaine (Group B), bupivacaine with dexmedetomidine (Group BD) and bupivacaine with dexamethasone (Group BDx) applied in ultrasound-guided TAP block in the treatment of CS postoperative pain. Material and Method: American Society of Anesthesiologists I and II pregnant women who underwent cesarean section were included in the study. Forty patients were admitted in each group. All patients were applied TAP block with ultrasound guidance by administering the medications of the group in which they were included. Results: Body mass index (BMI) and operation duration were higher in Group B (p*=0.01 and 0.004, respectively). Instant tramadol requirement and amount were higher in Group B at some of follow up times. Patient satisfaction scale were better in Group BD and Group BDx. Conclusion: TAP block significantly reduces pain after cesarean section, prolongs the time to first analgesic request, and reduces the need for additional opioid analgesics. The addition of adjuvant to the TAP block usually improves the postoperative clinical condition. However, some special conditions such as body mass index (BMI) may negatively affect the clinical situation. Comprehensive, standardized, randomized controlled studies are needed to compare results under different conditions.

The delivery of therapeutical molecules through the skin, particularly to its deeper layers is impaired due to the stratum corneum layer, which acts as barrier to foreign substances. Thus, for the past years, scientists have focused on the development of more efficient methods to deliver molecules to skin distinct layers. Microneedles, as a new class of biomedical devices, consists on an array of microscale needles. This particular biomedical device had been drawing attention due to their ability to breach the stratum corneum, forming micro-conduits to facilitate the passage of therapeutical molecules. The microneedle device has several advantages over conventional methods, such as better medication adherence, easiness and painless self-administration. Moreover, it is possible to deliver the molecules swiftly or over time. Microneedles can vary in shape, size and composition. The design process of a microneedle device must take in account several factors, like the location delivery, the material and manufacturing process. Microneedles have been used in a large number of fields from drug and vaccine application, cosmetics, therapy, diagnosis, tissue engineering, sample extraction, cancer research, wound healing, among others.

this paper we present approaches for generating random numbers along with potential applications. Rather than trying to provide extensive coverage of several techniques or algorithms that have appeared in the scientific literature, we focus on some representative approaches presenting their workings and properties in detail. Our goal is to delineate their strengths and weaknesses as well as their potential application domains so as the reader can judge what would be the best approach for the application in hand, possibly a combination of the available approaches. For instance, a physical source of randomness can be used for the initial seed, then suitable preprocessing can enhance its randomness and then the output of the preprocessing can feed different types of generators, e.g. a linear congruential generator, a cryptographically secure one and one based on the combination of one way hash functions and shared key cryptoalgorithms in various modes of operation. Then, if desired, the outputs of the different generators can be combined giving the final random sequence. Moreover, we present a set of practical randomness tests which can be applied on the outputs of random number generators in order to assess their randomness characteristics. In order to demonstrate the importance of unpredictable random sequences, we present an application of cryptographically secure generators in domains where unpredictability is one of the major requirements, i.e. eLotteries and cryptographic key generation.

In this note we study the computation of the minimum polynomial of a matrix $A$ and how we can use it for the computation of the matrix $A^n$. We also describe the form of the elements of the matrix $A^{-n}$ and we will see that it is closely related with the computation of the Drazin generalized inverse of $A$. Next we study the computation of the exponential matrix and finally we give a simple proof of the Leverrier - Faddeev algorithm for the computation of the characteristic polynomial.