Degradation is an inevitable companion in the operation of solid oxide fuel cell (SOFC) systems since it directly deteriorates the reliability of the system’s operation and the system’s durability. Both are seen as barriers that limit the extensive commercial use of SOFC systems. Therefore diagnosis and prognosis are valuable tools that can contribute to raising the reliability of the system operation, efficient health management, increased durability and implementation of predictive maintenance techniques. Remaining useful life (RUL) prediction has been extensively studied in many areas like batteries and proton-exchange membrane fuel cell (PEM) systems, and a range of different approaches has been proposed. On the other hand, results available in the domain of SOFC systems are still relatively limited. Moreover, methods relying on detailed process models and models of degradation turned out to have limited applicability for in-field applications. Therefore, in this paper, we propose an effective, data-driven approach to predicting RUL where the trend of the health index is modelled by an adaptive linear model, which is updated at all times during the system operation. This allows for a closed-form solution of the probability distribution of the RUL, which is the main novelty of this paper. Such a solution requires no computational load and is as such very convenient for the application in ordinary low-cost control systems. The performance of the approach is demonstrated first on the simulated case studies and then on the data obtained from a long-term experiment on a laboratory SOFC system. From the tests conducted so far it turns out that, the quality of the RUL prediction is usually rather low at the beginning of the system operation, but then gradually improves while the system is approaching the end-of-life (EOL), making it a viable tool for prognosis.

When a grid-forming (GFM) inverter is connected to a low or medium voltage weak power grid, the line impedance with resistive-inductive characteristics will cause power coupling. Typical GFM decoupling control strategies are designed under nominal line impedance parameters. However, there are deviations between the nominal line impedance and actual parameters, resulting in poor decoupling effects. Aiming at this problem, this paper proposes a power decoupling strategy based on a reduced-order extended state observer (ESO). Firstly, the power dynamic model of GFM is established based on the dynamic phasor method. Then, the model deviation and power coupling due to line impedance parameter perturbation are estimated as internal disturbances of the system, and the disturbances are compensated on the basis of typical power control strategy and virtual impedance decoupling. Good decoupling performance is obtained under different impedance parameters, improving the control strategy's robustness. Finally, the effectiveness of the proposed method is verified by the results of RT Box hardware-in-the-loop experiments.

A hypothesis that the generally accepted value of the LiPON conductivity should be attributed to the absorption and displacement currents is substantiated. The reason is a small contribution of the drift current due to field screening by the electric double layer. The basis for this assumption is the measurement of the LiPON absorption capacitance, according to which its dielectric constant is about 106. An alternative equivalent circuit containing a non-ideal absorption element is proposed and its impedance is calculated. It is shown that the Bode diagrams of the alternative circuit well approximate the experimental curves. Parameters and the magnitude of electric field screening are calculated basing on proposed model of a double electric layer. Considering the screening effect, the drift conductivity of LiPON is obtained, which value is in good agreement with the data on lithium concentration and mobility.

The many limitations of implementing anticancer strategies under the term “precision oncology” have been extensively discussed. While some authors propose promising future directions, others are less optimistic and use phrases such as illusion, hype and false hypotheses. The reality is revealed by practicing clinicians and cancer patients in various online publications, one of which has stated that “in the quest for the next cancer cure, few researchers bother to look back at the graveyard of failed medicines to figure out what went wrong.” The message is clear: novel therapeutic strategies with catchy names (e.g., synthetic “lethality”) have not fulfilled their promises despite decades of extensive research and clinical trials. The main purpose of this review is to discuss key challenges in solid tumor therapy that surprisingly continue to be overlooked by the nomenclature committee on cell death and numerous other authors. These challenges include: the impact of chemotherapy-induced genome chaos (e.g., multinucleation) on resistance and relapse, oncogenic function of caspase 3, cancer cell anastasis (recovery from late stages of apoptosis), and pitfalls of ubiquitously used preclinical chemosensitivity assays (e.g., cell “viability” and tumor growth delay studies in live animals) that score such pro-survival responses as “lethal” events. Studies outline herein underscore the need for new direction in the management of solid tumors.

In the context of the minimally extended varying speed of light (meVSL) model, both the absolute magnitude and the luminosity distance of type Ia supernovae (SNe Ia) differ from those predicted by general relativity (GR). Utilizing the Pantheon+ data, we examine the plausibility of various dark energy models under meVSL. Both ωCDM and CPL parameterization dark energy (DE) models exhibit indications of cosmic variations in the speed of light at the 1-σ level. For Ωm0=0.30,0.31, and 0.32 with (ω0,ωa)=(−1,0), the 1-σ range of c˜˙0/c˜0(10−13yr−1) is (-8.76 , -0.89), (-11.8 , 3.93), and (-14.8 , -6.98), respectively. Meanwhile, the 1-σ range of c˜˙0/c˜0(10−12yr−1) for CPL dark energy models with −1.05≤ω0≤−0.95 and 0.28≤Ωm0≤0.32, is (-6.31 , -2.98). The value of c˜ at z=3 can exceed that of the present by 0.2∼3 % for ωCDM models and 5∼13 % for CPL models. Additionally, for viable models except for the CPL model with Ωm0=0.28, we find −25.6≤G˜˙0/G˜0(10−12yr−1)≤−0.36. For this particular model, we obtain an increasing rate of the gravitational constant within the range 1.65≤G˜˙0/G˜0(10−12yr−1)≤3.79.

The triplet excited state reactivity towards phenolic hydrogen of the -diketones benzil and 2,2´-furil in the ionic liquid 1-n-butyl-3-methyl imidazolium hexafluorophosphate [bmim.PF6] was investigated employing the nanosecond laser flash photolysis technique. Irradiation (lmax=355 nm) of benzil yields its triplet excited state with lmax at 480 nm and tT=9.6 μs. Under the same conditions, 2,2’-furil shows a triplet-triplet absorption spectrum with bands at 380, 410, 450, and 650 nm and tT=1.4 μs. Quenching rate constants (kq) of the reaction between benzil triplet and substituted phenols ranged from 1.4x107 L mol-1 s-1 (para-chlorophenol) to 1.8x108 L mol-1 s-1 (para-methoxyphenol). A new transient was formed in all cases, assigned to the benzil ketyl. Similar results were obtained for the quenching of 2,2’-furil triplet by phenols, for which kq ranged from 1.9x108 L mol-1 s-1 (para-chlorophenol) to 2.2x108 L mol-1 s-1 (para-methoxyphenol). The 2,2’-furil ketyl radical was also observed in all cases (lmax=380 nm). The quenching rate constants are almost independent of the substituent and diffusion-controlled (kq ~ 108 L mol-1 s-1). The proposed mechanism for the phenolic hydrogen abstraction by benzil and 2,2´-furil triplet may involve a proton-coupled electron transfer reaction, ultimately leading to the radical pair ketyl/aryloxyl.

The problem of normal impact of a rigid sphere onto a Maxwell viscoelastic solid half-space is considered. The first-order asymptotic solution is constructed in the framework of Hunter’s model of viscoelastic impact [Hunter, S. C., 1957. Energy absorbed by elastic waves during impact. Journal of the Mechanics and Physics of Solids, 5(3), 162–171.]. In particular, simple analytical approximations have been derived for the maximum contact force and the time to achieve it. A linear regression method is suggested for evaluating the instantaneous elastic modulus and the mean relaxation time from a set of experimental data collected for different impactors and impact velocities.

This paper describes an entropy equation that can be used for measuring energy. It originated from measuring economy in AI models, where the assumption would be that any organic system makes use of energy efficiency to form its structures. Looking at clustering and cohesion resulted in the equation E = (mean * variance). It was apparent however, that it was a very generic type of equation and it could be adjusted so that distance represents mean. This new version was applied to the domain of physics and the universe, when the equation can support the idea that work is done through the energy released by the 'change' in entropy. A comparison with Einstein's relativity equation is made and also the audacious suggestion that a black hole has only potential energy inside, which converts to kinetic energy after a Big Bang, for example. From that suggestion, a universal theory about state change can be made.

The current state-of-the-art does not provide a universal and rapid method of determining the state of health (SOH) of a battery or a supercapacitor without carefully examining the degradation of hundreds of full charge/discharge cycles. Lithium-ion batteries, sodium-ion batteries and supercapacitors of different cell chemistries were studied by impedance spectroscopy during lifetime tests. Faradaic and capacitive charge storage are distinguished by the relationships between stored electric charge and capacitance. For batteries, impedance spectroscopy is best applicable in the flat region of the voltage-charge curve. An approximately linear correlation between pseudocapacitance and Ah capacity is observed as long as overcharge and deep discharge are avoided. The correct calculation of quantities related to complex impedance and differential capacitance is outlined – which may also be useful as an introductory text and tutorial for newcomers to the field. Novel diagram types are proposed for the purpose of instant performance and failure diagnosis of batteries and supercapacitors.

Epithelial–mesenchymal transition (EMT) is defined as a cellular process during which epithelial cells acquire mesenchymal phenotypes and behavior following the downregulation of epithelial features. EMT and its reversed process, the mesenchymal-epithelial transition (MET), and the special form of EMT, the endothelial-mesenchymal transition (EndMT), have been thought as a universal dogma controlling developmental and pathological processes. More than half a century of EMT study has made it a large research field and a mainstream concept. However, discrepancies and disputes over EMT and EMT research have also grown over time. Particularly, neither the epithelial and mesenchymal states/properties nor their regulatory networks nor specific markers have been defined, rendering the EMT, MET and EndMT concepts groundless. Moreover, EMT and MET effects should not be a cause, but rather a consequence of or an accompanying effect during developmental and pathological processes. EMT and MET represented by the change in cell shapes or adhesiveness or symbolized by EMT factors are biased interpretation of the overall change in cellular property and regulatory networks during development and cancer progression. The true meaning of EMT effects in some developmental and pathological processes, such as fibrosis, needs re-evaluation. But the core EMT factors are actually a few components of the regulatory networks of neural stemness, which determines tumorigenicity and pluripotency. The EMT effects in cancer progression and neural crest formation are wrong attribution of the role of neural stemness during cancer progression and the cell-intrinsic property of neural crest cells to the unknown mesenchymal state. It is time to reassess the significance of EMT and its related concepts in scientific research.

Time series forecasting has been a challenging area in the field of Artificial Intel-ligence. Various approaches such as linear Neural Networks, Recurrent Linear Neural Networks, Convolutional Neural Networks and recently Transformers have been attempted for the time series forecasting domain. Although, Trans-former-based architectures have been outstanding in the Natural Language Pro-cessing domain, especially in autoregressive language modeling, the initial at-tempts to use transformers in the time series arena have met with mixed success. One of the recent papers demonstrated that modeling the multi-variate time se-ries problem as independent channels on a transformer architecture produced lower mean square and mean absolute errors on benchmarks, however, another recent paper claimed that a simple linear neural network out-performs previous approaches including transformer-based designs. We investigate this paradox in detail comparing the linear Neural Network and Transformer based designs, provide insights to why a certain approach may be better for a particular type of problem. We also improve upon the recently proposed simple linear Neural Network based architecture by using dual pipelines with batch normalization and reversible instance normalization. Our enhanced architecture outperforms all existing architectures for time series forecasting on majority of the popular benchmarks.

The crust region is a tiny fraction of neutron stars, but it has a variety of physical properties and plays an important role in astronomical observations. One of the properties characterizing the crust is the elasticity. In this review, with the approach of asteroseismology, we systematically examine neutron star oscillations excited by crust elasticity, adopting the Cowling approximation. In particular, by identifying the quasi-periodic oscillations observed in magnetar flares with the torsional oscillations, we make a constraint on the nuclear saturation parameters. In addition, we also discuss how the shear and interface modes depend on the neutron star properties. Once one detects an additional signal associated with neutron star oscillations, one can get a more severe constraint on the saturation parameters and/or neutron star properties, which must be a qualitatively different constraint obtained from terrestrial experiments, and help us to complementarily understand astrophysics and nuclear physics.

The emphasis in the automotive industry towards sustainable mobility has led to a significant interest in hybrid-electric propulsion systems with high energy density batteries. Addressing the needs of this strategy, the battery market is exploring new technologies to improve the safety and lifespan of electric vehicles. To this end, there is a focus on the all-solid-state battery (ASSB) technology for its cycle capabilities. Filling the current void in the literature pertaining to accurate ageing models for ASSBs, in this work, we present an enhanced version of the numerical ageing model, originally developed for liquid electrolyte based batteries, to forecast the development of the solid electrolyte interface layer that is the major cause of battery capacity fading. The model has been tested on prototype batteries and reveals an accuracy of 99%. The capacity fade in ASSBs has been investigated under different conditions, and the enhanced ageing model has been validated using experimental data from these batteries. The findings suggest that there is potential for solid-state batteries to be commercialized, although significant work is needed to match the manufacturing level of lithium-ion batteries with liquid electrolytes.

The present exploratory study tested the hypothesis that computerized cognitive training (CCT) in home telemonitoring may beneficially affect eyes-closed resting-state electroencephalographic (rsEEG) rhythms in Parkinson's disease patients with cognitive deficits (PDCD). A Eurasian database provided clinical-demographic-rsEEG datasets in 40 PDCD patients, 29 PD patients without cognitive deficits (PDNCD), 40 Alzheimer’s disease patients with cognitive deficits (ADCD), and 40 cognitively normal older adults (Healthy). Sixteen of the 40 PDCD patients completed a cross-over unsupervised CCT program of simple, serious video games (versus a sham program) consisting of 14 daily sessions of approximately 20 minutes each in the patients' homes. Compared to the Healthy, PDNCD, and ADCD groups, the PDCD group was characterized by greater diffuse rsEEG delta (about 2-4 Hz) and theta (about 4-7 Hz) source activity. The PDCD patients who underwent the CCT program showed an improvement in video game performance and a reduction in these delta-theta source activities after this program compared to the control condition. In conclusion, these results suggest that the 2-week CCT program in home telemonitoring may mitigate the abnormal “slowing” of rsEEG rhythms in PDCD patients, possibly enhancing the regulation of brain arousal and quiet vigilance.

This article aimed to evaluate, using statistical tools, the generation and composition of urban solid waste (MSW) in the city of Belém, Pará, from nine urban collection sectors in the municipality, and the average nominal income of the population. Approximately 900kg of urban solid waste were col-lected from the municipality in the period from 2021 to 2022. Statistical tests were carried out on hypotheses with 5% significance in comparative evaluations, and their respective average nominal incomes. The results indicated that the organic fraction corresponds to 55.57% of the waste generated in the municipality, 14.26% is inert waste (potentially contaminating) and 0.67% is miscellaneous waste. It was observed that the waste generated by families with high purchasing power tends to contain higher percentages of recyclables, while in families with lower purchasing power the highest percentages tend to be organic. Knowledge of the generation of MSW is fundamental for the choice and dimensioning of operations and processes involved in the management chain at the municipal level. The decentralization of services offered based on solid waste management would enable greater success in serving the population.

Based on the dynamic strength variation mechanism of concrete under complex loading conditions, two approaches were devised: numerical testing and CT scanning, guided by the principle of minimizing energy dissipation. A methodology for calculating concrete's failure area and measuring its strength was developed. The analysis delves into the mechanisms behind failure patterns and variations in concrete specimen strength, focusing on crack initiation, development, and the resultant failure surface formed by crack propagation, along with the stress distribution in concrete specimens subjected to diverse loading conditions. Through evaluating the strength and computed failure area of concrete specimens, it is evident that the loading method influences both the strength and failure area of concrete specimens. In general, a larger failure area correlates with a higher measured strength.

Pulverized coal pyrolysis based on solid heat carrier has a huge advantage in high tar yield. In this study, pyrolysis experiments of pulverized coal were conducted in a lab-scale fluidized bed reactor at 650 ℃, utilizing char as the solid heat carrier. The influence of mass ratio of char to coal (RATIO) was investigated. Results show that the incorporation of solid heat carrier of char significantly enhanced the initial reaction in coal pyrolysis, resulting in increasing yields of tar and gas but reducing one of char. The yield of tar maximally reached 148.80-262.22% of the Gray-King analysis value at the RATIO of 14.52 g/g. As the RATIO increased, the tar contained more light component content, indicating that incorporating solid heat carriers improved the tar quality. These findings offer significant insights for the design of fluidized bed pyrolysis unit utilizing char as solid heat carrier.

Brain imaging studies have recently provided some evidence in favour of covert cognitive processes ongoing in patients with disorders of consciousness (DoC) (e.g., minimally consciousness states, vegetative state/unresponsive wakefulness syndrome) engaged in passive sensory stimulation or active tasks such as motor imagery. In this exploratory study, we used transcranial magnetic stimulation (TMS) of the motor cortex to assess modulations of corticospinal excitability induced by action observation in eleven patients with DoC. Action observation is known to facilitate corticospinal excitability in healthy subjects, unveiling how the observer’s motor system maps others’ actions onto her/his motor repertoire. Additional stimuli were non-biological motion and acoustic startle stimuli, provided that sudden and loud acoustic stimulation is known to lower corticospinal excitability in healthy subjects. Results indicate that some form of motor resonance is spared in a subset of patients with DoC with some significant difference between biological and non-biological motion stimuli. However, there was no covariation between corticospinal excitability and the type of DoC diagnosis (i.e., whether VS/UWS or MCS). Similarly, no covariation was detected with clinical changes between admission and discharge in clinical outcome measures. Both motor resonance and biological/non-biological motion discrimination correlated with the amplitude of the N20 somatosensory evoked potentials following the stimulation of the median nerve at the wrist (i.e., the temporal marker signalling the activation of the contralateral primary somatosensory cortex). Moreover, the startle-evoking stimulus produced an anomalous increase in corticospinal excitability, suggesting a functional dissociation between cortical and subcortical circuits in patients with DoC. Further work is needed to better comprehend the conditions in which corticospinal facilitation occurs and whether and how they may relate to individual clinical parameters.

Body-centered cubic bismuth (Bi) is considered an enticing pressure marker, and therefore it is highly desirable to command its accurate equation of state (EOS). However, significant discrepancies are noted among the previous experimental EOSs. In the present work, the EOS up to 300 GPa is theoretically obtained by direct solving the partition function via a direct integral approach (DIA). The calculated results nearly reproduce the hydrostatic experimental measurements below 75 GPa, and the deviations from the measurements gradually get larger with increasing pressure. Based on the ensemble theory of equilibrium state, DIA works with high precision particularly in high-pressure conditions, so the hydrostatic EOS presented in this work is expected to be a reliable pressure standard.

The medium-voltage DC (MVDC) technology has gained increasing interests in recent years. Power electronics devices dominate those grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system level control model of such a modern MVDC distribution grid. Aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/- 10 kV MVDC grid case study, including Solid State Transformer (SST) and Modular Multilevel Converter (MMC) based Active Front End (AFE). Additional aim of this paper is to supply an educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented.

Abstract: Thermostability of vaccines, particularly enveloped viral vectored vaccines, remains a challenge for their delivery wherever needed. Freeze-drying of viral vectored vaccines is a prom-ising approach but remains challenging due to the water removal process from the outer and in-ner parts of the virus. In the case of enveloped viruses, freeze-drying induces increased stresses on the envelope, which often leads to inactivation of the virus. In this study, we design a method to freeze-dry a recombinant Vesicular Stomatitis Virus (VSV) expressing the SARS-CoV-2 spike glycoprotein. Since the envelope of VSV is composed of 50% lipid and 50% protein, the formula-tion study focused on both the protein and lipid portions of the vector. Formulations were pre-pared primarily using sucrose, trehalose, and sorbitol as cryoprotectants; mannitol as a lyopro-tectant; and histidine as a buffer. Initially, the infectivity of rVSV-SARS-CoV-2 and cake stability were investigated at different final moisture contents. High recovery of the infectious viral titer ( 0.5 to 1 log loss) was found at 3-6% moisture content with no deterioration of the freeze-dried cakes. To further minimize infectious viral titer loss, the composition and concentration of the ex-cipients were studied. An increase from 5 to 10% of both cryoprotectants and lyoprotectant, to-gether with the addition of 0.5% gelatin, resulted in the improved recovery of infectious virus titer and stable cake formation. Moreover, the secondary drying temperature of the freeze-drying pro-cess showed a significant impact on the infectivity of rVSV-SARS-CoV-2. The infectivity of the vector declined drastically when the temperature was raised above 20°C. Throughout a long-term stability study, formulations containing 10% sugar (sucrose/trehalose), 10% mannitol, 0.5% gelatin, and 10 mM of histidine showed satisfactory stability for six months at 2-8°C. The development of this freeze-drying process and the optimized formulation minimizes the need for a costly cold chain distribution system.

The aim of the work is to study the effect of the 3D printing process on the microstructural and hydrophilic properties of polylactic acid (PLA) samples with various model printing patterns obtained from the black Filament PLA by sequentially applying polymer layers using the FDM (Fused Deposition Modeling) method. X-ray phase analysis revealed partial crystallization of PLA polymer chains in printed samples, which occurs under thermal and mechanical action on the original amorphous PLA filament during 3D printing to varying degrees, depending on the geometry of the pattern and the morphology of its surface. At the same time, IR spectroscopy data indicate the preservation of all intrastructural chemical bonds of polylactide. Measured at the original installation, the values of the wetting edge angles on the surface of the printed samples are in the range φ = 50-60°, which is significantly less than the right angle. This indicates the hydrophilic properties of all samples’ surface. At the same time, the influence of different geometries of model drawings in printed samples was found not only on the morphology of the samples’ surface according to SEM data, but also on its wettability.

The equation of state of asymmetric nuclear matter as well as the neutron and proton effective masses and their partial-wave and spin-isospin decomposition are analyzed within the Brueckner–Hartree–Fock approach. Theoretical uncertainties for all these quantities are estimated by using several phase-shift-equivalent nucleon-nucleon forces together with two types of three-nucleon forces, phenomenological and microscopic. It is shown that the choice of the three-nucleon force plays an important role above saturation density, leading to different density dependencies of the energy per particle. These results are compared to the standard form of the Skyrme energy-density functional and we find that it is not possible to reproduce the BHF predictions in the (S,T) channels in symmetric and neutron matter above saturation density, already at the level of the two-body interaction, and even more including the three-body interaction.

African scientific research faces formidable challenges, particularly with limited access to state-of-the-art measurement instruments. The high cost associated with these devices presents a significant barrier for regional research laboratories, impeding their ability to conduct sophisticated experiments and gather precise data. This predicament not only hampers the individual laboratories but also has broader implications for the African scientific community and the advancement of knowledge in developing nations—the financial cost barrier considerably impacts the research quality of these laboratories. Reflection on technical and economical solutions needs to be quickly found to help these countries advance their research. In civil Engineering, the thermal conductivity property is the most important measurement for characterising heat transfer in construction materials. Existing devices (i.e., conductometers) in a laboratory are expensive (approximately 30,000 euros) and unavailable for some African laboratories. The study proposes a new and affordable device to evaluate thermal conductivity in construction materials. The method involves establishing a thermal flux between a heat source ( from the Joule effect provided by steel wool where a current is circulating) and a cold source (generated by ice cube) under steady-state conditions. The development of the cylindrical prototype is based on the comparative flux-meter method outlined in the measuring protocol of the ASTM E1225 standard document. Experiments were conducted on four distinct materials (polystyrene, wood, agglomerated wood, and rigid foam). The results indicate a correct correlation between the experimental values obtained from the newly developed prototype and the reference values found in the literature. For example, concerning the experimental polystyrene study, the detailed case analysis reveals a good correlation, with a deviation of only 4%. The percent error found falls within the acceptable range indicated by the standards recommendations of the ASTM E1225 standard, i.e., within 5% acceptable error.

Partially state-owned firms are common in both developed and developing countries and contribute around 10% of the world's GDP. This has led to a rich literature exploring various aspects of competition between such “mixed”-ownership firms. This paper contributes to the existing literature by studying the effects of mixed ownership on the intensity of competition in oligopoly markets. Our findings indicate that state ownership exerts an anti-competitive influence, with a higher state ownership share resulting in less aggressive behavior by firms in the product market. This result implies that industries with a higher proportion of state ownership yield lower total surplus. Further, when considering factors such as taxes, soft budget constraints, and weak property rights, the anti-competitive effects of state ownership are accentuated.

The accurate state of health (SOH) estimation of lithium-ion batteries (LIBs) during operation is crucial to ensure optimal performance, prolonging battery life and preventing unexpected failure or safety hazards. This work presents a storage and performance optimised deep learning approach to predict the capacity based SOH of LIBs using raw sensor data from partial charging curves under constant current condition. The proposed model is based on a combination of a 1-dimensional convolutional and long-short term memory neural network and processes time, voltage and incremental capacity of partial charging curves as time series. The model is cross-validated on different aging scenarios reaching an overall MAE = 0.418% and RMSE = 0.531%, promising an accurate SOH estimation of LIBs under varying usage and environmental conditions in a real world application.

This research paper focuses on the synthesis and characterization of Cu-doped Mg-Co ferrites with varying compositions (Mg_0.6-xCo_0.4Cu_xFe₂O₄, where x = 0.0, 0.1, 0.2, and 0.3) using a solid-state reaction method. This paper also investigates the structural, morphological, magnetic, and electrical characteristics of synthesized Mg_0.6-xCo_0.4Cu_xFe₂O₄, where x = 0.0, 0.1, 0.2, and 0.3. The X-ray diffraction (XRD) technique confirms the ferrites spinel structure in the Fd-3m space group, with average crystallite sizes ranging from 57.29 to 48.57 nm. Fourier Transform Infrared (FTIR) spectroscopy verifies chemical and structural changes, while scanning electron microscopy (SEM) reveals cubic crystal growth with an average grain size of 1 to 1.5 μm. DC electrical resistivity decreases with increasing temperature and Cu²⁺ substitution, ranging from 1.4 x 10⁶ Ω-cm to 6.7 x 10⁵ Ω-cm. The study suggests a correlation between resistivity and Cu²⁺ concentration. Magnetic behaviour, studied using a Vibrating Sample Magnetometer (VSM), shows dependence on dopant concentration, with coercivity ranging from 157 Oe to 256 Oe. The results indicate potential applications in magnetic storage devices, antennas, transformers, and high-frequency electronics.

In this paper, a proof similar to the Pusey-Barrett-Rudolph (PBR) theorem is given to prove that time in quantum theory is not epistemic but has ontological reality. For this, we first discuss how time can be encoded as an intrinsic property of a quantum system. We prepare a quantum state containing time as an intrinsic property and show by a PBR-type proof that time cannot be an epistemic notion. In fact, the PBR theorem implies an ontic notion of time. Indeed, if the quantum state is a physical property, then quantum state reduction is a physical process involving information destruction. In this case, quantum probabilities are intrinsic probabilities without epistemic origin, and they generate a genuinely new sequence of events. This novelty introduced by quantum probabilities can be interpreted as time.

Understanding clinical significance of variants of unknown significance (VUS) reported in next-generation sequencing (NGS) has become essential in cancer treatment. Our study examined six widely used in silico tools: PolyPhen-2, Align-GVGD, MutationTaster2, CADD, REVEL, and Chat-GPT. We utilized a dataset of gene variants known to potentially affect immune therapy. No single tool could comprehensively determine mutation variant pathogenicity. MutationTaster2021 showed the highest overall accuracy and MCC among the tools. Notably, REVEL and Chat-GPT exhibited 100% specificity, suggesting their proficiency in accurately identifying pathogenic variants and minimizing false positives. In contrast, CADD displayed optimal sensitivity, making it suitable for effectively ruling out benign variants.

Owing to the growing concerns due to dwindling fossil fuel reserves, increasing energy demand and climate emergency, it is imperative to develop and deploy sustainable energy technologies to ensure future energy supply as well as transition to the net zero world. In this context, there is great potential in the biorefinery concept for supplying drop in biofuels in the form of biodiesel. Biodiesel as a fuel can certainly bridge the gap where electrification or the use of hydrogen is not feasible, for instance heavy vehicles, farm and marine transportation sector. However, biodiesel industry also leads to formation of large amount of crude glycerol as the byproduct. Crude glycerol due to presence of several impurities may not be a suitable feedstock for all high value products derived from glycerol but fits well with glycerol esterification for producing glycerol acetins, which have numerous applications. This review critically looks at the processes using nanostructured solid/liquid acid catalysts for glycerol esterification including the economic viability of the scale up.

Recurrent neural networks (RNNs) transmit information over time through recurrent connections. In contrast, biological neural networks use many other temporal processing mechanisms. One of these mechanisms is the inter-neuron delays caused by varying axon properties. Recently, this feature was implemented in echo state networks (ESNs), a type of RNN, by assigning spatial locations to neurons and introducing distance-dependent inter-neuron delays. These delays were shown to significantly improve ESN task performance. However, thus far it is still unclear why distance-based delay networks (DDNs) perform bettern than ESNs. In this paper, we show that by optimizing inter-node delays, the memory capacity of the network matches the memory requirements of the task. As such, networks concentrate their memory capabilities to the points in the past which contain the most information for the task at hand. Moreover, we show that DDNs have more total linear memory capacity, with the same amount of non-linear processing power.

Solid-state fermentation (SSF) is the bioprocess where microorganisms are cultivated in the absence of free water under control conditions. Lactic acid can be produced by fermenting grape stalks with Rhizopus oryzae in SSF. During the microorganism growth, the temperature and water content of the solid bed fluctuate, leading to areas of either dry or excessive moisture in the solid substrate. Therefore, it's crucial to control the supply of water to the matrix. In this work, we obtain lactic acid through SSF of grape stalks using Rhizopus oryzae NCIM 1299. The SSF was conducted at a fixed temperature of 35 °C, with three constant relative humidity levels: 50, 65, and 80 %RH. Mathematical models, including the Logistic and First Order Plus Dead Time models for fungal biomass growth and the Luedeking and Piret with Delay Time model for lactic acid production, were adjusted to kinetic curves. Growth kinetic parameters (Xmax, μmax, Tp, T0, Yp/x and td) were determined for all conditions. These kinetic parameters were then correlated with relative humidity using a second-degree polynomial relationship. We observed a decrease in Xmax with increasing %RH, while the value of Yp/x increased at higher %RH. Finally, the optimal variable relative humidity profile was obtained by applying the Dynamic Optimization Technique, resulting in a 15.30% increase in lactic acid production.

Background: Previous neuroimaging studies have identified brain regions related to respiratory motor control and perception. However, little is known about the resting-state functional connectivity (FC) associated with respiratory impairment. We aimed to determine the FC involved in mild respiratory impairment without changing the saturation of percutaneous oxygen. Methods: We obtained resting-state functional magnetic resonance imaging data from 36 healthy volunteers during normal respiration and mild respiratory impairment induced by resistive load (effort breathing). ROI-to-ROI and seed-to-voxel analyses were performed using Statistical Parametric Mapping 12 and the CONN toolbox. Results: Compared to normal respiration, effort breathing activated FCs within and between the sensory perceptive area of respiration (the postcentral gyrus, anterior insular cortex (AInsula), and anterior cingulate cortex) and visual cortex (the visual occipital, occipital pole (OP), and occipital fusiform gyrus). Graph theoretical analysis showed strong centrality in the visual cortex. A significant positive correlation was observed between the dyspnoea score (modified Borg scale) and FC between the left AInsula and right OP. Conclusions: These results suggested that the FCs within the respiratory sensory area via the network hub may be neural mechanisms underlying effort breathing and modified Borg scale scores.

In recent times, there has been significant enthusiasm for the development of all solid state batteries. This interest stems from a dual focus on safety—addressing concerns related to toxic and flammable organic liquid electrolytes—and the pursuit of high energy density. \cite{SCHNELL2018160,Zheng2018}. While liquid electrolyte batteries constitute for now the vast majority of commercial cells, solid electrolyte batteries show great promise. In parallel with experimental research, computational models \cite{GrazioliEtAlCM2016} clarify the several fundamental physics \cite{LiMonroeARCBM2020} that take place throughout battery operations. We review some classical models, emphasizing the conceptual advancements documented in the most recent works.

: Sputtering of silicon in a Helium magnetron discharge (MS) has been reported as a bottom-up procedure to obtain He-charged silicon films (i.e. He nanobubbles encapsulated in a silicon matrix). The incorporation of heavier noble gases is demonstrated in this work with a synergistic effect producing increased Ne and Ar incorporations when using He-Ne and He-Ar gas mixtures in the MS process. Microstructural and chemical characterizations are reported by ion beam analysis (IBA) and scanning and transmission electron microscopies (SEM and TEM). In addition to gas incorporation, helium promotes the formation of larger nanobubbles. For the case of Ne high resolution X-ray photoelectron and absorption spectroscopies (XPS and XAS) are reported with remarkable dependence of the Ne 1s photoemission and the Ne K-edge absorption on the nanobubbles size and composition. The gas (He, Ne, Ar) charged thin films are proposed as “solid” targets for the characterization of spectroscopic properties of noble gases in a confined state without the need for cryogenics or high-pressure anvils devices. Also their use as targets for nuclear reaction studies is foreseen.

Motivated by the PEACOC project on metal recovery from solid wastes, an innovative magnetic density separation (MDS) process has been developed for granular material sorting. It has intrinsic advantages over the existing industrialized MDS by eliminating fluid turbulence and particle jamming problems. The new MDS applies an inclined planar magnet and a horizontal basin containing a static magnetic fluid as the separation medium. A particle sliding phenomenon is identified as a feature of the process which could help the separation. The MDS successfully sorted shredded PCBAs to concentrate valuable metals and sorted shredded wires to reduce metallic contaminants in the plastic fractions. A pilot scale facility is introduced to show the design to achieve continuous production and to reduce the consumption of ferrofluid.

This study demonstrates the efficacy of structured pruning and architectural fine-tuning on the YOLOv7-tiny model for eye state detection, emphasizing optimization for real-time applications. Structured pruning significantly reduced the model's complexity and storage size while maintaining high detection accuracy, as evidenced by stable precision, recall, and mAP@.5 metrics across iterations. Further fine-tuning adjusted the model's width and depth, optimizing efficiency and processing speed without compromising performance. These optimizations yielded YOLOv7-tiny variants that are both computationally efficient and accurate, suitable for resource-constrained environments. The findings highlight the critical role of model optimization in deploying effective neural networks for specific detection tasks in real-time scenarios.

In recent years, the economics of emotions (EoE) field, which aims to create models of the human mind, has grown quickly. EoE models work well with simulation theory (ST), which is one of the main theories of mind. EoE models show how people's behavior and emotions change based on their knowledge and perception of others. It is hoped that by developing this model, it will be possible to quantitatively analyze not only the mental states of real others, but also the subtleties of the minds of characters in novels in the future. Until now, the decision-making or the factual-reasoning mechanisms have been a black box in ST. This study analyzes how EoE models add to the understanding of ST.

Alternative fertilizations are essential to minimize the deteriorating effects of chemical fertilizers on soil and water quality/health. Accordingly, the present work investigated the effects of combined organic-inorganic fertilization (COIF) on wheat and rice yields, soil nutrients, and soil Cd accumulation. Hence, seven different treatments were set up: control (CK); conventional fertilization (CF); optimized fertilization (OF); organic fertilizer replacing 25% (T1) and 50% (T2) of OF; and organic nitrogen (N) replacing 25% (M1) and 50% (M2) of OF-N. Overall, significant increases occurred in the yields of COIF crops. Compared with the CF, the highest wheat and rice yields happened in M1 treatment (approximately by18.5%) (P < 0.05). COIF slightly alleviated soil acidification, and improved the cation exchange capacity (CEC) of the study soils. Besides, COIF treatments significantly increased the contents of total phosphorus, total potassium, available phosphorus, and available potassium by 6.35 to 16.9 %, 3.17 to 10.9 %, 5.53 to 28.7 %, and 2.6 to 12 %, respectively (P <0.05). Nevertheless, negligible increases took place in Cd content of COIF soils compared with the CK. Altogether, our results concluded on 25% replacement of OF-N by organic N (M1) to effectively improve the fertility/ecological sustainability of the study soils.

The aim of this study is to solve the problems of complicated pretreatment and high analytical cost in the detection technology of trace drug toxicants in municipal wastewater. A high-performance magnetic sorbent was synthesized for enrichment of trace drug substances in wastewater to develop magnetic solid-phase extraction pretreatment combined with the acoustic ejection mass spectrometry (AEMS) analytical methods for the molecules in wastewater drug toxicants. The magnetic nanospheres was successfully prepared by magnetic nanoparticles modified with divinylbenzene and vinyl pyrrolidone.The results showed that the linear dynamic range of 17 drugs was 1-500 ng/L, the recovery was 43%-105%, the matrix effect was more than 67%, the limit of quantitative detection was 1-2 ng/L, and the detection time of each sample was 2.98s. It can be seen that the developed magnetic solid-phase extraction (MSPE) method is a good solution to the problem of complicated pre-treatment and analytical cost in the detection of drugs in wastewater. The developed magnetic material and acoustic excitation coupled mass spectrometry analysis method can realize the low-cost, efficient enrichment and fast analysis of different kinds of drug molecules in urban sewage.

In the modern power grid, characterized by the increased penetration of power electronics and extensive utilization of renewable energy, inverters-based power plants play a pivotal role as the principal interface of renewable energy sources (RESs) and the grid. Considering the stability characteristics of grid-following (GFL) inverters when the grid is relatively weak, the application of grid-forming (GFM) controls becomes imperative to enhance the stability of the entire power plant. Thus, there is an urgent need for suitable and effective models to study the interaction and stability of the paralleled inverters employing GFL and GFM controls. Thus, the small-signal modeling with full-order state space model and eigenvalues analysis is presented in this paper. First, the small-signal state-space model of the individual GFL and GFM inverters is obtained considering the control loop, interaction, reference frame, transmissions, and time delays. Then, the models of the individual inverter are extended to the hybrid inverters to study the effects of the GFM inverters on the small- signal stability of the entire system. And, the impacts of the inertia and damping are analyzed by the eigenvalues of the state-transition matrix. Case comprising three parallel GFL inverters and two GFL inverters with one GFM inverter, respectively, are studied to examine the effectiveness and accuracy of the model. Finally, the stability margin obtained from the eigenvalue analysis of the entire system is verified by time-domain simulations.

Background: Healthcare workers are exposed to several hazardous chemicals in the workplace that can result in numerous adverse health effects. Several published studies from many different countries have documented the presence of metabolites from antineoplastic drugs in the urine of healthcare workers and demonstrated contaminated working surfaces with these agents. This study is a literature review that aims to compare the prevalence and degree of exposure to cyclophosphamide (CP), ifosfamide (IFO), and methotrexate (MTX) in physicians, nurses, and pharmacists in the hospital setting. Methods: An extensive search was conducted on PubMed, Google Scholar, HINARI, OARE, and Science Direct where applicable research about healthcare workers and antineoplastic drugs exposure were identified. Medical Subject Headings (MeSH) keywords: occupational exposure, antineoplastic drugs (cytotoxic drugs, cyclophosphamide, ifosfamide, methotrexate), hazardous chemicals, healthcare workers (healthcare professionals, nurses, pharmacists, physicians), hospital setting, and adverse health outcomes were used. Thereafter, relevant articles from 2000 to 2020 were selected to perform this literature review. Results: Review of literature demonstrated that cyclophosphamide was the most prevalent contaminant in the hospital setting. Additionally, pharmacists are among the group of healthcare workers with the highest prevalence of antineoplastic agents in urine samples while nursing stations had the highest rate of surface contamination. Conclusion: There is an urgent need to develop a system to monitor and detect the pathway of environmental exposure to antineoplastic drugs in the healthcare setting, and to evaluate the effectiveness of the existing protective measures. Well designed studies focusing on improving the standard safety precautions is a priority to protect healthcare workers.

Due to the difficult metallurgical conditions during production, advanced processing techniques are required to produce functionally graded metal matrix composites. In this study, we explored a novel approach by using a combination of two different methods to produce Functionally Graded 7075 Al / SiCp composites. First process was direct semi-solid stirring that was used to prevent particle agglomeration, brittle reaction products, floating or settling of the reinforcements and poor wettability for the production of SiCp (wt. 5-20%) reinforced aluminum matrix composites. In the direct semi-solid mixing process, the matrix material remains in a semi-solid state until the reinforcement addition process is completed. The second novel process was sequential squeeze casting to provide liquid diffusion between two composite layers that were used to produce functionally graded aluminum matrix composite. The microstructure and interlayer zones were characterized by using optical microscopy and scanning electron microscopy. The resulting functionally graded material was subjected to spectrometer analyses, density measurements, and metallographic examinations in order to determine the characteristics of its layers and interfacial zones, as well as to assess the formation of the graded structure. The results obtained from this research provide the potential to use this new combined manufacturing method, which is relatively inexpensive, efficient and easily applicable, in order to produce functionally graded SiCp reinforced aluminum composites.

The belief in online news has become a hot topic. Previous studies have shown the role of emotion in susceptibility to believing fake news. However, Few studies have explored the effect of empathy on belief in online news. This study investigated the relationships between trait empathy, state empathy, the belief in online news, and the potential moderating effect of the news type. One hundred and forty undergraduates evaluated 50 online news pieces (25 real, 25 fake) regarding their believability, state empathy, valence, arousal, and familiarity. Trait empathy data were collected using the Chinese version of the Interpersonal Reactivity Index. State empathy was positively correlated with affective empathy in trait empathy and believability, and affective empathy was positively correlated with believability. The influence of affective empathy on news belief was partially mediated by state empathy, regulated by the news type (fake, real). We discussed the influence of empathy on the belief in online news and its internal processes. This study explains some unique insights for researchers, practitioners, social media users, and social media platform providers.

Bridges enable communications and transportation of goods nationally and internationally, underpinning economic and social activities, thus they are pylons of our prosperity and mobility. Bridges worldwide are constantly subjected to physical wear, ageing, deterioration, hazards, environmental influences, and increased loading. Loss of performance and functionality of bridge structures would have a crucial impact on overall infrastructural resilience and would cause significant negative economic and social consequences. Monitoring their behaviour for different loading conditions relies on accurate estimations of the stress-strain state of various critical components and remaining capacities. These activities are of high importance for better planning lifespan prolongation, that is the extension of their service life and prevention of unforeseen collapses, in line with sustainability principles of well-informed maintenance. In many cases, access to the structure is limited or even impossible, which causes the need for the deployment of remote and contactless methods. One such innovative technique, which has recently attracted attention in scientific and practical applications is the digital image correlation (DIC). DIC is a contactless approach applicable for long-term measurements, which enables obtaining the full field of strains and deformations. Although the DIC approach has been widely used in world engineering practice for monitoring bridges and has proved to be a reliable and accurate method, there is a lack of systematic integral review on previous practical applications, revealing limitations and perspectives. This is the main motivation and novelty of this study, which will describe selected case studies, in which DIC was used on real full-scale bridge structures and propose improvements for the method.

A model of a single-server queuing-inventory system (QIS) with catastrophes and a finite waiting room for consumer customers (c-customers) has been developed. When a catastrophe occurs, all inventory in the system's warehouse is destroyed, but c-customers in the system are still waiting for restocking. In addition to c-customers, negative customers (n-customers) are also taken into account, which displaces one c-customers (if any). The policy (?, ?) is used to replenish stocks. If upon arrival of the c-customer the inventory level is zero, then according to Bernoulli’s scheme this c-customer is either lost or joining the queue. The mathematical model of the studied QIS is constructed in the form of a two-dimensional continuous-time Markov chain (2D CTMC). Exact and approximate methods for calculating the steady-state probabilities of constructed 2D CTMCs are developed and closed-form expressions are derived for calculating the performance measures. The results of numerical experiments are presented, demonstrating the high accuracy of the developed approximate formulas, as well as the behavior of performance indicators depending on the reorder point. In addition, an optimization problem is solved to obtain the optimal reorder point to minimize the expected total cost.

Abstract: Field studies with large-stemmed plants Artemisia dubia (wormwood) have been carried out at Vėžaičiai Branch LAMMC since 2018. According to three years of experimental results, annual dry matter (DM) yield varied from 7.94 to 10.14 t ha-1. Growing conditions, nitrogen ap-plication level and harvesting time had significant impacts on Artemisia dubia productivity. This article presents the results of research on preparation and use of Artemisia dubia biomass for en-ergy conversion and evaluation of technological-technical and environmental parameters of these plants utilization for solid biofuel. For experiments were used 6 variants of Artemisia dubia samples, which were grown in 2021: plants were cut three times and two fertilization options were used: (1) no fertilization and (2) fertilization with 180 kg ha-1 of nitrogen fertilizer. These harvested plants were chopped, milled and were pressed into the pellets. The physi-cal-mechanical characteristics (mоisture content, density and strength) of Artemisia dubia pellets were investigated. During this study, it was found that the density in dry mass (DM) of pellets ranged from 1119.86 to 1192.44 kg m-3. The pellet moisture content ranged from 8.80 to 10.49%. After testing of pellet strength, it was found that the pellets which were made from plant bio-mass PK-1-1, were the most resistant to compression, they withstood 560.36 N of pressure. Dry fuel lower heating value (LHV) of pellets was sufficiently high and was very close to pine saw-dust pellets, it varied from 17.46±0.25 MJ kg-1 to 18.14±0.28 MJ kg-1. The ash content of burned pellets ranged from 3.62±0.02% to 6.47±0.09%. Emissions of harmful pollutants – CO2, CO, NOx and unburnt hydrocarbons (CxHy) did not exceed the maximum permissible levels. Summariz-ing the results of investigated properties, cоmbustion and emissiоns of Artemisia dubia pellets, it can be concluded that this biofuel can be used for production of pressed biofuel and it is charac-terized by sufficient high quality, efficient combustion and permissible emissions to the envi-ronment.

We consider a constrained optimal control problem and an extension of it, in which the set of strict-sense trajectories is enlarged. Extension is a common procedure in optimal control, used to derive necessary and sufficient optimality conditions for the original problem from the extended one, which usually admits a minimizer and has a more regular structure. However, this procedure fails if the two problems have different infima. It is therefore relevant to identify such situations. Following on from earlier work by Warga but adopting perturbation techniques developed in non-smooth analysis, we investigate the relation between the occurrence of an infimum gap and abnormality of necessary conditions. For a notion of local minimizer based on control distance and an extension including the impulsive one, we prove that (i) a local extended minimizer which is not a local minimizer of the original problem and (ii) a local strict-sense minimizer which is not a local minimizer of the extended problem, both satisfy the extended maximum principle in abnormal form. The main novelty is result (ii), as until now it had only been shown that a strict-sense minimizer which is not an extended minimizer is abnormal for an `averaged version’ of the maximum principle.

We propose a theoretical method for the deterministic shaping of quantum light via photon number state selective interactions. Nonclassical states of light are an essential resource for high precision optical techniques that rely on photon correlations and noise reshaping. Notable techniques include quantum enhanced interferometry, ghost imaging, and generating fault tolerant codes for continuous variable optical quantum computing. We show that a class of nonlinear-optical resonators can transform many-photon wavefunctions to produce structured states of light with nonclassical noise statistics. The devices, based on parametric down conversion, utilize the Kerr effect to tune photon number dependent frequency matching, inducing photon number selective interactions. With a high amplitude coherent pump, the number selective interaction shapes the noise of a two-mode squeezed cavity state with minimal dephasing, illustrated with simulations. We specify the requisite material properties to build the device and highlight the remaining material degrees of freedom which offer flexible material design.

The purpose of the study is to establish compliance of the design of the modernized car with the requirements for safe operation. An option has been proposed for upgrading a passenger wagon to a Mobile Diagnostic Complex for transporting a combined vehicle equipped with appropriate flaw detection equipment intended for rail diagnostics. The authors have established the most optimal option for locating the diagnostic vehicle on board the Mobile Diagnostic Complex (MDC) wagon, taking into account the additional load from the vehicle. To achieve this goal, the article developed a three-dimensional model of the supporting structure of the wagon body, proposed a methodology and presented the results of a study of the stress-strain state of the wagon body, taking into account the additional weight of the wagon. The article develops a methodology for studying the natural frequencies of vibrations of the wagon body and develops a three-dimensional model of the wagon for calculating dynamic indicators in the Universal Mechanism software package. Taking into account the previously carried out strength calculations, as well as in order to maintain the factory life cycle indicators of the supporting structure of the wagon body, it is recommended to use the model in the first version.

Solid-liquid interfacial phenomena play an essential role in our everyday lives and are often regarded as the outcome of interactions at the solid-liquid interface. However, the intricately intrinsic mechanism underlying interfacial interactions renders in-situ simulations and direct measurements challenging. As an effective analytic method for studying solid-liquid interfacial interactions, Microcalorimetry can provide the most basic thermodynamic information (including changes in enthalpy, entropy, and Gibbs free energy during solid-liquid binding/separation processes), which is extremely crucial for understanding interaction directionality and limitation. This review is dedicated to highlighting the pivotal role of microcalorimetry in studying solid-liquid immersion and adsorption processes. Specifically, we provide an overview of the commonly employed microcalorimetric methods, delve into the influence factors of enthalpy change, and finally discuss the specific applications of microcalorimetry in studying various solid-liquid binding processes. There remains a vast expanse of thermodynamic information regarding solid-liquid interactions that await exploration via calorimetry.

Pyrethroid pesticides (PYRs) as the third most widely used pesticides, following organophosphorus and carbamate pesticides, which are of significant importance in the analysis and detection of vegetables. However, the current pretreatment technology for PYRs confronts challenges of difficult separation and low enrichment efficiency, resulting in a cumbersome and time-consuming pretreatment process with poor selectivity. Here, a simple and efficient magnetic solid-phase extraction (MSPE) strategy was developed to simultaneously purify and enrich five PYRs in vegetables, with the magnetic covalent organic framework nanomaterial COF-SiO2@Fe3O4 as an adsorbent. The COF-SiO2@Fe3O4 was prepared by a simple solvothermal conditions method, using Fe3O4 as magnetic core, benzidine and 3,3,5,5-tetraaldehyde biphenyl as two building units. COF-SiO2@Fe3O4 could effectively capture the targeted PYRs by virtue of its abundant π-electron system and hydroxyl groups. The impact of various experimental parameters on extraction efficiency was investigated to optimize the MSPE conditions, including adsorbent amount, extraction time, elution solvent type and elution time. Subsequently, method validation was conducted under the optimal conditions in conjunction with gas chromatography-mass spectrometry (GC-MS). Within the range of 5.00–100 μg·kg-1 (1.00–100 μg·kg-1 for bifenthrin and 2.5–100 μg·kg-1 for fenpropathrin), the five PYRs exhibited a strong linear relationship, with determination coefficients ranging from 0.9990 to 0.9997. The limits of detection (LODs) were 0.3–1.5 μg·kg-1, and the limits of quantification (LOQs) were 0.9–4.5 μg·kg-1. The recoveries were 80.2–116.7% with relative standard deviations (RSDs) below 7.0%. Finally, COF-SiO2@Fe3O4, NH2-SiO2@Fe3O4 and Fe3O4 were compared as MSPE adsorbents for PYRs. The results indicated that COF-SiO2@Fe3O4 was an efficient and rapid selective adsorbent for PYRs. This method holds promising prospects for the determination of PYRs in real samples.

The pharmaceutical industry usually utilizes either hydrophobic or hydrophilic substances extracted from raw plant materials for preparing a final product, However, the plant material waste still contain substances with an opposite solubility. The aim of this study was to enhance the comprehensive usability of plant materials by developing a new non-wasting extraction method for eucalypt leaves and by investigating the phytochemical and pharmacological properties of eucalypt extracts and their 3D-printed dosage forms. The present extraction method enabled to prepare both hydrophobic soft extracts and hydrophilic (aqueous) dry extracts. We identified total 28 terpenes in the hydrophobic soft extract. In the hydrophilic dry extract, total 57 substances were identified, and 26 of them were successfully isolated. The eucalypt extracts studied showed a significant antimicrobial activity against Staphylococcus aureus, Pseudomonas aeruginosa, Bacillus subtilis, Candida albicans, Corynebacterium diphtheriae gravis, and Corynebacterium diphtheriae mitis. The anti-inflammatory activity of the dry extract was studied with a formalin oedema model in mice. The maximum anti-exudative effect of the dry extract was 61.5% at a dose of 20 mg/kg. The composite gels of polyethylene oxide and eucalypt extract were developed, and the key process parameters for semi-solid extrusion (SSE) 3D printing of such gels were verified. The SSE 3D-printed preparations of novel synergistically acting eucalypt extracts could have uses in antimicrobial and anti-inflammatory medicinal applications.

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

This paper provides a new discovery that adds to the contemporary theory of modelling of non-stationary queues, by capturing analytically the behavior of the root parameter, for the G1/M/1 PSFFA model of non-stationary Ek/M/1 queue. Additionally, it has been also revealed that the resulting root parameter reduces to the PSFFA model of non-stationary queue. Potential applications of PSFFA to Computer engineering are provided. Some challenging open problems are addressed combined with closing remarks and future research directions.

An eight-sided prism sample, obtained from a hot-rolled AZ31 magnesium alloy sheet, was compressed at room temperature along the transverse direction to investigate the influence of local strain on twinning behavior using electron backscatter diffraction (EBSD) measurements. The octagonal surface of the sample was divided into distinct regions based on hardness distribution and metallographic observations. The EBSD maps of different areas show significant variations, suggesting that these areas experienced different local strain conditions. The EBSD measurements provided detailed data from three distinct regions, with the strain state known in two regions and uncertain in the third. The combined analysis of the Schmid factor (SF) and the strain compatibility factor (m') was employed to study twin variant selection. The comparison of twinning behavior in different regions showed that the strain compatibility factor offered a more comprehensive explanation for the observed twinning pattern in the region with local shear strain.

The organic fraction of municipal solid waste (OFMSW) is a significant environmental threat, and an economic and social challenge to manage. As such, the efficient treatment of OFMSW is a significant key factor in achieving sustainable waste management. Decentralized Composting (DC) develops a new framework of waste management. The DC Analysis Model (DCAM), proposed in our previous study, provides a powerful tool for decision makers, based on the quantification of the DC project characteristics. In this paper, we focus on the qualitative analysis as a complementary tool to support decision making, in cases where quantitative analysis is unequivocal. The qualitative analysis identifies the main players in the field, the critical stakeholders and the potential conflicts between them. It also reveals the root problems and the core competencies for the project's implementation. DCAM qualitative analysis in Shefa-Amr (case study) indicates that unresolved root problems, such as the “lack of national regulation”, “clear ownership of the project” and “lack of ongoing budget” can result in an unsustainable composting system. Countering that, “the commitment of the municipality”, together with “economic viability” and securing “suitable areas for placing composters” are among the most important core competencies for the effective implementation of DC projects.

From their discovery in 2002, BRAF mutations have been identified as clear drivers of oncogenesis in several cancer types. Currently, their incidence rate is nearly 7% of all solid tumors with BRAF V600E constituting approximately 90% of these diagnoses [1]. In melanoma, thyroid cancer, and histiocytic neoplasms, BRAF hotspot mutations are found at a rate of about 50%, while in lung and colorectal cancers they range from 3 to 10% of reported cases [2-5]. Though present in other malignancies such as breast and ovarian cancers, they constitute a small portion of diagnoses (<1%). Given their frequency along with advancements in screening technologies, various methods are used for the detection of BRAF-mutant cancers. Among these are targeted next-generation sequencing (NGS) on tumor tissue or circulating tumor DNA (ctDNA) and immunohistochemistry (IHC)-based assays. With advancements in detection technologies, several approaches have been taken for the treatment of BRAF mutant cancers. In this review we retrace the milestones that led to the clinical development of targeted therapies currently available for these tumors.

The binary metal oxide mesoporous interfacial layers (bi-MO meso IF layer) templated by a graft copolymer is synthesized between a fluorine-doped tin oxide (FTO) substrate and nanocrystalline TiO2 (nc-TiO2). Amphiphilic graft copolymers, Poly(epichlorohydrin)-graft-poly(styrene), PECH-g-PS, was used as a structure-directing agent, and the fabricated bi-MO meso IF layer exhibits good interconnectivity and high porosity. Even if the amount of ZnO in bi-MO meso IF layer increased, it was confirmed that the morphology and porosity of bi-MO meso IF layer was well maintained. In addtion, bi-MO meso IF layer coated onto FTO substrates show higher transmittance compared with a pristine FTO substrate and dense-TiO2/FTO, due to the reduced surface roughness of FTO. The overall conversion efficiency (η) of a solid state photovoltaic cells, dye-sensitized solar cell (DSSC) fabricated with nc-TiO2 layer/bi-MO meso IF layer TZ1 used as a photoanode reaches 5.0% at 100 mW cm-2, which is higher than that of DSSC with a nc-TiO2 layer/dense-TiO2 layer (4.2%), resulting from enhanced light harvesting, good interconnectivity, and reduced interfacial resistance. The cell efficiency of the device did not change after 15 days, indicating that the bi-MO meso IF layer with solid-state electrolyte has improved electrode/electrolyte interface and electrochemical stability. Additionally, commercial scattering layer/nc-TiO2 layer/bi-MO meso IF layer TZ1 photoanode fabricated solid state photovoltaic cells (DSSC) achieved an overall conversion efficiency (η) of 6.4% at 100 mW cm-2.

The purpose of this study is to assess the solid waste management status and practice in Sendafa town, Oromia regional state residents. In order to achieve this goal, the researcher intends to employ both primary and secondary data from the Sendafa town municipality. With the aid of multi-cluster sampling and a purposive sampling method, the researchers chose a sample size of 398 people and 10 interview responders. To utilize a systematic sampling technique at intervals of residences, individual samples were chosen. Quantitative data was cleaned and analysed using STATA software. A multiple linear regression model and logistic regression other descriptive statistics methods were then used to change the results. The qualitative data were imported, coded, and thematised using ATLAS.ti.9 in order to prepare respondents' interviews for analysis. The findings indicate that residents' poor solid waste management practices are a result of a lack of awareness, low family income transportation issues, issues with waste collectors, a lack of a sense of responsibility and belonging, and a failure to enforce current solid waste management laws. Solid waste accumulates near roads, bridges, and residential areas that are close to landfills, contaminating the area and leading to diseases like TB and Asthma (and other related health issues in children and adults who live there). Thus, researcher recommends that to have sustainable solid waste management the town administrators should have plan to develop awareness creation symposium or panel of discussion, resolve transportation issues, monitor and guide the routine activities of waste collectors, develop sense of belongingness for themselves and for the community, develop integrated solid waste land fill projects and working with all stakeholders like NGO and health institution will minimize the adverse effect of improper solid waste management. Keywords: Solid Waste, Status of Solid Waste Management, Land fill site suitability

2023 was the hottest year ever recorded, global warming accelerates its rising, we witness a series of extreme weather events, more frequent and more intense, climate refugees, infrastructure harmed, forests burning, “meteorological tsunamis”. We failed to meet the main goals of the Kyoto protocol; we are very close to fail in meeting the Paris agreement’s slowing global warming goal. Greenhouse gases emissions are at rise and, even if completely halt, temperatures would keep rising, enhancing the global average. Carbon capture and storage technologies are being developed to counterbalance these emissions by removing such gases from the atmosphere and physically storing or transforming them into useful molecules for the society. In this work we prospect microorganisms that can serve as a platform for developing carbon capture technologies. We process samples from the seabed of Brainsfield Strait region, Antarctica, prospecting for an organism capable of fixing carbon dioxide without light (chemoautotrophic bacterias) and capable of enduring extreme conditions of pressure (100 bar) under 100% supercritical state carbon dioxide atmosphere (scCO2), conditions like those found in oil deposits, where the technology can be of particular use.

End-of-life electric vehicle (EV) batteries can be reused to reduce their environmental impact and economic costs. However, the growth of a second-life market is limited by the lack of information on the characteristics and performance of these batteries. As the volume of end-of-life EVs may exceed the amount of batteries needed for stationary applications, investigating the possibility of repurposing them in mobile applications is also necessary. This article presents an experimental test that can be used to collect the data necessary to fill a battery passport. The proposed procedure can facilitate the decision making process regarding the suitability of a battery for reuse at the end of its first life. Once the battery passport has been completed, the performance and characteristics of the battery are compared with the requirements of several mobile applications. Mobile charging stations and forklift trucks were identified as relevant applications for the reuse of high capacity prismatic cells. Finally, a definition of a state of health (SoH) is proposed to track the suitability of the battery during use in the second life application considering not only energy but also power and efficiency of the battery. This SoH shows that even taking into account accelerated ageing data, a repurposed battery can have an extended life of 11 years at 25~°C. It has also been shown that energy fade is the most limiting performance for lifetime and that cell-to-cell variation should be tracked as it has been shown to have a significant impact on battery life.

The proliferation of deep learning in natural language processing (NLP) has led to the development and release of innovative technologies capable of understanding and generating human language with remarkable proficiency. Atinuke, a Transformer-based neural network, optimises performance across various language tasks by utilising a unique configuration. The architecture interweaves layers for processing sequential data with attention mechanisms to draw meaningful affinities between inputs and outputs. Due to the configuration of its topology and hyperparameter tuning, it can emulate human-like language by extracting features and learning complex mappings. Atinuke is modular, extensible, and integrates seamlessly with existing machine learning pipelines. Advanced matrix operations like softmax, embeddings, and multi-head attention enable nuanced handling of textual, acoustic, and visual signals. By unifying modern deep learning techniques with software design principles and mathematical theory, the system achieves state-of-the-art results on natural language tasks whilst remaining interpretable and robust.

Hong Kong is the biggest consumer of eggs in the world and ranks on the top with an average consumption of 24.52kg/capita/year. The egg consumption trend in Hong Kong has been increasing specifically; a drastic increase of about 100% has been observed from 2008 to 2020. One of the reasons behind this significant increase is the increase in the gross national income of Hong Kong in addition to the population growth rate. However, there was a slight decline in egg consumption trend in the year 2020 amid the COVID-19 pandemic. It has been estimated that there was a bulk of 17,100 tons of recoverable waste eggshells in 2019 (pre-COVID-19 situation), having a daily yield of 47 tons per day. Based on the linear regression, it may be expected that if the pre-COVID-19 trend of egg consumption remains sustained, there will be a big bulk of more than 45,000 tons per year and up to 125 tons per day of waste eggshells till 2050. In addition, a public survey was conducted across the city targeting individuals, families, and restaurants majorly on egg consumption and reuse. The survey outcomes revealed that Chinese eggs have an extensive market in Hong Kong, and people have a positive attitude towards eggshell recycling. Also, a massive population disposes of the waste eggshells while only a trace population reuses them. Therefore, Hong Kong has a very high potential to improve the circular economy by reusing waste eggshells on a commercial level in cementitious products.

This study describes the seasonal course of denitrifying and nitrate reducing bacteria in a dimictic mesotrophic lake (Lake Scharmützelsee, Brandenburg, Germany) within a three-year period from 2011 to 2013. The bacterial cell numbers were quantified by fluorescence microscopy, most probable number (MPN) and PCR dependent quantification of the chromosomal 16S rDNA and of the nirS and nirK gene copy number. The highest seasonal differences (up to three orders of magnitudes) has been measured by MPN in the epilimnion. This variation was not reflected by PCR dependent approaches or direct microscopical enumeration. At adverse conditions (low temperature and/or low nitrate concentrations), the differences between MPN and gene copy numbers increased up to five orders of magnitudes and decreased to one magnitude at favorable environmental conditions. These results can be explained best by an increasing ratio of viable but not cultivable (VBNC) cells or dead cells at impairing conditions. In the hypolimnion, the courses of MPN and nir gene copy numbers were similar. This can be explained by higher feeding pressure and therefore smaller amounts of dormant cells. In the pelagial in general, the total cell numbers enumerated by either microscopical or molecular approaches were similar. In the sediment, more than 99 % of the DNA was obviously not related to viable bacteria but was rather “dead DNA” in dead cells or adsorbed to particle surfaces.

A facile and environmentally benign method for a single-phase barium titanate synthesis in water vapor medium was studied to reveal the mechanism of phase transformation of the initial simple oxides mixture and estimate the capability of the product to be used as a raw material for low-frequency dielectric ceramics. The composition and structure of the reaction mixture treated in vapor at 130…150 °C as well as 230 °C for various time were investigated by means of XRD, SEM, HRTEM, EDX, and FTIR methods. The kinetics of the occurring phase transformation was described by Johnson-Mehl-Avrami-Erofeev equation. The reaction between the initial oxides was considered as a topochemical process with an apparent activation energy of 74…80 kJ mol^-1. A crucial role in this process belonged to the water vapor medium, which facilitated the generation of the reaction zone and its spreading inward the solid particles. The synthesized tetragonal barium titanate powder (mean particle size of 135 ± 24 nm) was sintered by a conventional technique at 1250 °C to obtain ceramics with grains of about 2 μm. Capacitance measurements performed a dielectric constant and loss tangent of ceramics, which reached 3879 and 6.7 10^-3, respectively, at 1 kHz and room temperature.

An exposition is undertaken to reveal the significant impact of the time-dependent root parameter, on the stability of Pointwise Stationary Fluid Flow Approximation (PSFFA) model of the non-stationary queueing system. This opens new grounds to stability analysis of non-stationary queueing systems. Potential PSFFA applications of IoT are highlighted.

With continued scaling of semiconductor devices , the value of predictive analysis through 1 accurate quantum transport modeling is exponentially increasing. Quantum transmitting Boundary 2 method (QTBM) has been a well-known method of choice to model quantum transport in simple 1-D 3 devices. Here, we present an extension of the QTBM to the 2-D domain and apply it for more realistic 4 devices for accurate performance analysis.

The lactic acid bacteria Streptococcus thermophilus and Lactobacillus helveticus are commonly used as starter cultures in dairy product production. This study aimed to investigate the characteristics of fermented milk using different ratios of these strains and analyze the changes in volatile compounds during fermentation and storage. The 10:1 ratio of Streptococcus thermophilus CICC 6063 to Lactobacillus helveticus CICC 6064 showed optimal fermentation time (4.2 h), viable cell count (9.64 log10 colony-forming units/mL), and sensory evaluation score (79.1 points). In total, 56 volatile compounds were identified and quantified by solid-phase microextraction and gas chromatography–mass spectrometry (SPME-GC-MS), including aldehydes, ketones, acids, alcohols, esters, and others. Among these, acetaldehyde, 2,3-butanedione, 2,3-pentanedione, 2-heptanone, acetoin, and 1-heptanol had the highest odor activity values and contributed to the characteristic flavor of fermented milk. The concentrations and types of key flavor compounds reached their peak at the end of fermentation. Throughout the fermentation and storage process, the levels of 2,3-pentanedione and acetoin exhibited synergistic dynamics. These findings enhance our understanding of the chemical and molecular characteristics of milk fermented with Streptococcus thermophilus and Lactobacillus helveticus, providing a basis for improving the flavor and odor of dairy products during fermentation and storage.

Artificial intelligence (AI) has found extensive applications in the sustainability domain. The municipal solid waste incineration (MSWI) process can achieve waste-to-energy (WTE) goals through the assistance of automation and information technologies. In theory, AI can facilitate the intelligent operation of the MSWI process, simultaneously achieving low pollution emissions and high production efficiency. This study provides an overview of AI applications in the MSWI process. Addressing fundamental challenges, the optimal control of the MSWI process is categorized into four aspects: modeling, control, optimization, and maintenance. Subsequently, this study conducts a detailed analysis and discussion of AI applications in each of these technological domains. In conclusion, this paper outlines the future research directions and provides an outlook on the fundamental issues pertaining to AI applications in the optimal control of the MSWI process.

The solutions of the radial Schrödinger equation for a pseudoharmonic potential and Kratzer potentials has been studied separately in the past. The Kratzer potential despite different reports, the basic theoretic quantity such as Fisher information has not been reported. In this study, the solution of the radial Schrödinger equation for the combination of the pseudoharmonic and Kratzer potentials in the presence of a constant-dependent potential is obtained using the concepts and formalism of the supersymmetric and shape invariance approach. The position expectation value and momentum expectation value are calculated employing the Hellmann-Feynman Theory. The expectation values are used to calculate the Fisher information for both the position and momentum spaces in both the absence and presence of the constant-dependent potential. The obtained results revealed that the presence of the constant-dependent potential leads to an increase in the energy eigenvalue, as well as in the position and momentum expectation values. The presence of the constant-dependent potential also increases the Fisher information for both position and momentum spaces. Furthermore, the product of the position expectation value and the momentum expectation value along with the product of the Fisher information, satisfies both the Fisher’s inequality and the Cramer-Rao’s inequality.

This paper offers a novel geometric and visual approach to the renowned Four Color Map Theorem and K5 non-planarity problem while unveiling their profound connection to the "kissing number" problem in 2D. We represent planar graphs through circles and tangents, simplifying complex structures and shedding light on these classic problems. Our proofs by contradiction, rooted in the kissing number concept, reveal that both the Four Color Map Theorem and K5 non-planarity are fundamentally linked, as they pivot around the concept of coloring. This study bridges the realms of geometry and graph theory, providing fresh insights and emphasizing the significance of the kissing number problem in various fields.

Rising demand and urbanization have led to the global increase and intensification of livestock production. Intensive production has harmful effects on the environment, public health (due to the emergence of zoonotic diseases), and animal welfare. In order to better understand how livestock production intensifies as countries develop and incomes rise, we examine the relationship between income per capita and intensification of poultry and cattle, using the states of India as a study region. We also replicate this analysis at the district level to test whether the relationship holds at different spatial scales. We identify outlying states and districts to see if there are policies that can keep agriculture production largely extensive, even as economic growth occurs. The results support the relationship of income being positively correlated with the proportion of livestock in intensive conditions. However, there are notable outlier states which have grown wealthy while still maintaining largely extensive production, indicating that there may be some cases where economic growth can occur without intensification.

The swelling behavior of titanium-modified austenitic stainless steel 15-15Ti was investigated by pre-implantation of He at room temperature followed by Ni irradiation at 580 °C to peak doses of 120, 240 and 400 dpa. Relatively smaller cavities were observed in the zone of helium implantation while large cavities appeared in the region near the damage peak. A correction formula of the dpa curve was proposed and applied for samples with large swelling. It is found that the steady-state swelling rate of 15-15Ti keeps at ~1% /dpa even to high doses. By comparing the swelling data of the helium-implanted and helium-free regions at same doses, 70 dpa and 122 dpa, the suppression of excessive helium on swelling can be deduced at such doses.

This scientific paper presents a comprehensive investigation into transient Fourier analysis in some electrical engineering applications. The article deals with two effective approaches for solving transient analysis whose application is rather novel. The first contribution uses combined the Fourier series analytic Laplace-Carson (L­C) transform methods in the complex domain using complex time vectors, thereby significantly simplifying the calculation of the original function. As the inverse transform goes back into the time domain, it employs the Cauchy-Heaviside (C­H) method. The second contribution uses the Fourier transform (F­Τ)for transient analysis of a power converter electrical circuit with the passive and the active load. The method of complex conjugated amplitudes is used for steady-state analysis. Both contributions represent a new approach to this paper. The starting point is the Fourier series/expansions, computation of the Fourier coefficients, then continuing by solving the steady and transient states of the system and confirming the transient states using the Fourier transform. To validate our findings, the worked-out analytical results are verified by modelling in Matlab/Simulink environment.

This research explores the transformation of learning methodologies from traditional to modern approaches, focusing on the development of a gamified educational application with an Artificial Intelligence (AI) mentor for secondary school graduates preparing for Croatian state graduation exams. Traditionally, education has been marked by a passive student role and teacher-centric transmission of knowledge. In contrast, modern learning tools, such as gamified applications, introduce interactive and engaging elements. The purpose of this study is to identify user-centric learning approaches through a comprehensive survey of graduating students, assessing their readiness for exams, learning styles, and preferences. The research explores issues such as financial burdens on parents for preparatory courses and copyright concerns with external educational materials. In summary, the learning application should prioritise sustained knowledge retention, motivation, and stress reduction, offering an alternative to external preparatory courses. Conclusions underscore the importance of fostering an engaging learning environment, incorporating teacher-like elements, and aligning with user expectations. As digital technology positively impacts the learning experience, understanding user preferences is crucial in designing educational apps that cater to learners' needs. The study provides insights for developing a gamified learning application that not only prepares students for exams but also enhances long-term knowledge acquisition and engagement.

: Protease-producing yeasts were isolated from potato wastes and screened for protease production on skim milk agar plates The best producer of protease isolate was identified as Clavispora lusitaniae. The strain showed better enzyme production using tomato pomace and bread waste mix as a solid fermentation substrate. The optimized conditions improved enzyme activity and showed a maximal production of 33450±503 IU/g compared with the initial activity of 11205,78 ±360 without medium optimization. A threefold increase in protease activity after medium optimization proved the reliability of using the PBD and CCD design. A 19.76-fold purified enzyme and a yield of 32.94% were obtained after purification. The protease showed maximum activity at pH 4 and 60 °C and was resistant to Tween 20, Tween 40, SDS, and β-mercaptoethanol, Ca2+, and Mg2+ stimulated it. The protease activity was strongly inhibited in the presence of urea, and EDTA. The results revealed Clavispora lusitaniae protease's ability to degrade wheat seeds and flour gluten by 98.7% and 97% respectively under pH 4 for 24 hours at 40 °C. According to this study, this enzyme could be a potential candidate for the food industry, particularly for treating wheat seed and flour to reduce the immunogenicity of gluten.

We extend Ziv and Lempel's model of finite-state encoders to the realm of lossy compression of individual sequences. In particular, the model of the encoder includes a finite-state reconstruction codebook followed by an information lossless finite-state encoder that compresses the reconstruction codeword with no additional distortion. We first derive two different lower bounds to the compression ratio that depend on the number of states of the lossless encoder. Both bounds are asymptotically achievable by conceptually simple coding schemes. We then show that when the number of states of the lossless encoder is large enough in terms of the reconstruction block-length, the performance can be improved, sometimes significantly so. In particular, the improved performance is achievable using a random-coding ensemble that is universal, not only in terms of the source sequence, but also in terms of the distortion measure.

The primary goal of this review is to provide a comprehensive overview of the state-of-the-art in solid-state batteries (SSBs), with a focus on recent advancements in solid electrolytes and anodes. The paper begins with a background on the evolution from liquid electrolyte lithium-ion batteries to advanced SSBs, highlighting their enhanced safety and energy density. It addresses the increasing demand for efficient, safe energy storage in applications like electric vehicles and portable electronics. A major part of the paper analyzes solid electrolytes, key to SSB technology. It classifies solid electrolytes as polymer-based, oxide-based, and sulfide-based, discussing their distinct properties and application suitability. The review also covers advancements in anode materials for SSBs, exploring materials like lithium metal, silicon, and intermetallic compounds, focusing on their capacity, durability, and compatibility with solid electrolytes. It addresses challenges in integrating these anode materials, like interface stability and lithium dendrite growth. This review includes a discussion on the latest analytical techniques, experimental studies, and computational models to understand and improve the anode-solid electrolyte interface. These are crucial for tackling interfacial resistance and ensuring SSBs' long-term stability and efficiency. Concluding, the paper suggests future research and development directions, highlighting SSBs' potential in revolutionizing energy storage technologies. This review serves as a vital resource for academics, researchers, and industry professionals in advanced battery technology development. It offers a detailed overview of materials and technologies shaping SSBs' future, providing insights into current challenges and potential solutions in this rapidly evolving field.

This review provides an extensive overview of the developments in the field of polymer science, focusing on the solid-state modification (SSM) of thermoplastic materials. The background of the study places thermoplastics within the context of their increased use over the past century, highlighting their versatility in various applications and the associated environmental and health concerns due to certain additives. The methods section delves into the specifics of SSM, a technique that involves the incorporation of monomers or oligomers into the amorphous phase of polymers through multiple exchange reactions, distinguishing it from traditional melt polymer modification methods. The results section outlines the unique aspects of SSM and its increasing recognition for its potential to enhance material performance in areas such as catalysts and composites. It also discusses the application of SSM in modifying different thermoplastic polymers, highlighting various studies demonstrating the method's effectiveness in altering polymer properties. Finally, this work emphasizes SSM's importance in environmental sustainability and its potential in the recycling and upcycling of plastic materials. It acknowledges the challenges and future perspectives in the field, particularly regarding the scalability of SSM techniques for industrial applications and their role in advancing a circular economy in the polymer industry.

There is a continuous interest in cannabinoids like Δ9-tetrahydro cannabinol (Δ9-THC) and cannabidiol (CBD). A patent of Webster et al., described the conversion of CBD to either D8-THC or D9-THC, depending on the acid catalyst applied. The use of para-toluene sulfonic acid (pTSA) led to the formation of D8-THC, while boron trifluoride etherate (BF3·Et2O) yielded mainly D9-THC. The enormous difference in product selectivity between these two catalysts was investigated with Molecular Modeling. It was found that pTSA leads to fast isomerization of Δ9-CBD to Δ8-CBD and subsequent ring closure to Δ8-THC. BF3·Et2O catalysis leads to the formation of tertiary carbenium ions in the Transition States which yield D9-THC and some iso D8-THC. Under dry conditions in refluxing toluene, it was found that pTSA is predominantly present as a dimer, and only a small fraction is available as monomeric catalyst. Applying the computationally derived activation barriers in Transition State theory yielded reaction rates predicting amounts of cannabinoids that are in close agreement with the experimental findings.

Exploring effective oxygen reduction reaction (ORR) electrocatalysts is crucial for progress in solid-state alkaline zinc-air batteries (ZAB). In this paper, silver-manganese dioxide-carbon nanotubes (SMC) ternary composites, which function as Electrocatalyst for air Electrodes, was produced via the pyrolysis of silver permanganate under microwave irradiation in one step. A scanning electron microscope (SEM), X-ray diffraction (XRD), and an energy dispersion spectrometer (EDS) have consistently determined that SMC consists of silver and alpha-manganese dioxide, which anchored on the surface of CNTs. Through polarization and chronoamperometery curves, the electrocatalytic activity of SMC for ORR was examined. The results reveal that SMC has higher catalytic activity than the chemically produced electrocatalyst for ORR in alkaline condition. Finally, a solid-state zinc-air cell with an electrocatalyst was constructed and tested. Constant current discharge curve of the zinc-air cell with SMC has a long discharge voltage plateau and a 60.03 mAh capacity at 30 mA · cm−2 . The mechanism of improvement in electrocatalytic activity was also discussed. In a summary, the strategy described in this study and the electrocatalyst produced can be regarded as an effective method for making a robust oxygen reduction catalyst toward solid-state zinc-air batteries.

The earth pressure acting on soilbag reinforced retaining structures subjected to surcharge loads under non-limited states, is crucial for designing these structures. In this study, the earth pressures are investigated through model tests of the soilbag reinforced retaining wall. Findings from these tests reveal a non-linear distribution of lateral earth pressure on the wall when subjected to surcharge loads in non-limited states, with an observed escalation in pressure corresponding to increased surcharge loads. Compression tests on soilbags were conducted to analyze their lateral stress-strain behavior. Insights from these tests facilitated the development of a predictive method for estimating lateral pressure on soilbag reinforced retaining walls under similar conditions. This method, rooted in the principle of force equilibrium in differential elements, has its accuracy and reliability substantiated by the alignment of its predictions with the model test outcomes.

Contacting bodies in extreme environments are prone to severe wear and failure due to friction and seizure, which are associated with significant thermal and mechanical loads. This phenomenon greatly impacts the economy since most essential components encounter these challenges during machining, an unavoidable step in most manufacturing processes. In machining, stress can reach 4 GPa, and temperatures can exceed 1000 °C at the cutting zone. Severe seizure and friction are the primary causes of tool and workpiece failures. Liquid lubricants are popular in machining for combatting heat and friction; however, concerns about their environmental impact are growing, as two-thirds of the 40 million tons used annually are discarded and they produce other environmental and safety issues. Despite their overall efficacy, these lubricants also have limitations, including ineffectiveness in reducing seizure at the tool/chip interface and susceptibility to degradation at high temperatures. There is therefore a push towards solid lubricants, which promise a reduced environmental footprint, better friction management, and improved machining outcomes but also face challenges under extreme machining conditions. This research aims to provide a thorough insight into solid lubricant use in machining, discussing their mechanisms, effectiveness, constraints, and potential to boost productivity and environmental sustainability.

Solid-state transformer (SST) is a promising technology for smart grids due to its flexible power control (better reliability) and high efficacy (by decreasing losses) compared with traditional transformers. The SST is designed in tandem with three stages, i.e., the input, isolation, and output stages. As three converter stages are used to design the SST to make a more reliable device in practice, it is highly prone to instabilities. Moreover, the key objective of SST design is to implement a modern power distribution system to make it more intelligent and reliable. The stability issue can be even more complicated by the presence of distributed energy resources in the distribution system. Thus, the stability of SST must be measured prior to /during the design, and to determine, a state-space model is used, which is developed in this paper. Each stage of SST is modeled with its controller, and the system's stability is measured through the controllability and observability test. Further, the conversion from state-space to transfer function model is done, and the stability of SST is shown using frequency and time-domain diagrams. With these, the different plots, namely, the Bode plot, Nyquist plot, Nichols chart, Root locus, pole-zero plot, and Eigen plot, are used to ascertain the relative and absolute stability. Finally, the SST Simulink model is tested and validated through hardwate-in-the-loop simulation, i.e., OPALRT, to show its effectiveness and applicability.

In this work, Density Functional Theory (DFT) calculations were employed to study the photocatalytic CO2 to CO reduction by a series of Pt(II) square planar complexes with general formula [Pt(5-R-dpb)Cl] (dpb = 1,3-di(2-pyridyl)benzene anion, R = H, N,N-dimethylaniline,T thiophene, diazaborinine). The CO2 to CO conversion process is thought to proceed via two main steps, namely the photocatalytic/reduction step and the main catalytic step. The simulated absorption spectra exhibit strong bands in the 200 – 400 nm UV-Vis region. The calculated excited state reduction potentials are in the range 0.32 — -0.36 V revealing that the reductive quenching of the T1 state of the complexes could be modulated with suitable changes of the N^C^N pincer ligands. The CO2 fixation and activation by the ‘real’ three coordinated Pt(II) catalyst/intermediate is predicted to be favorable with Pt-CO2 bond dissociation energies, D0 in the range -36.9—-10.3 kcal/mol. The nature of the Pt-CO2 bond is complex with covalent, hyperconjugative and H-bonding interactions prevailing the repulsive electrostatic interactions. The main catalytic cycle is estimated to be a favorable exergonic process.

Control over the composition of III-V ternary nanowires grown by the vapor-liquid-solid (VLS) method is essential for bandgap engineering in such nanomaterials and fabrication of functional nanowire heterostructures for a variety of applications. From the fundamental viewpoint, III-V ternary nanowires based on group V intermix (InSbxAs1-x, InPxAs1-x, GaPxAs1-x and many others) present the most difficult case, because the concentrations of highly volatile group V atoms in a catalyst droplet are beyond the detection limit of any characterization technique and therefore principally unknown. Here, we present a model for the vapor-solid distribution of such nanowires, which fully circumvents the uncertainties that remained in the theory so far, and link the nanowire composition to the well-controlled parameters of vapor. The unknown concentrations of group V atoms in the droplet do not enter the distribution, despite of the fact that a growing solid is surrounded by the liquid phase. The model fits quite well the available data on the vapor-solid distributions of VLS InSbxAs1-x, InPxAs1-x and GaPxAs1-x nanowires grown with different catalyst. Even more importantly, it provides a basis for the compositional control of III-V ternary nanowires based on group V intermix, and can be extended over other material systems where two highly volatile elements enter a ternary solid alloy through a liquid phase.

This article explores the crucial task of estimating State of Charge (SOC) in Hybrid Electric Vehicles (HEVs) and examines the applicability of various regression models for this purpose. We delve into the strengths and limitations of Linear Regression, Support Vector Regression (SVR), and Neural Network Regression (NNR) in the context of SOC estimation. Linear regression provides a simple and interpretable baseline, SVR extends this to nonlinear relationships, while NNR emerges as a powerful tool with adaptive capabilities. The choice of model depends on factors such as data characteristics, interpretability, and computational resources. As the field evolves, the article advocates for a nuanced approach, possibly incorporating hybrid models, to achieve robust and accurate SOC estimation, contributing to the ongoing enhancement of HEV efficiency and sustainability.

(3+1)D quantum mechanics is a four-dimensional quantum formalism, which is developed neither in a Minkowski spacetime, nor in a purely Hilbert space and not its metric is Lorentzian. This quantum mechanics also yields the quantum Einstein field equation in (3+1)D quantum spacetime. Every observable (3+1)D quantum spacetime can be found to contain internally hidden opposite spin quantum state, that results Supersymmetry. Closed continuous mappings of this hidden quantum state immediately yield more extra hidden dimensions including string. This string is found to be fundamentally eleven-dimensional (rather than lower dimensional) by nature within this quantum spacetime, which is necessarily a natural phenomenon of (3+1)D Quantum Mechanics.

The poor solvent crystallization of carbapenem CS-023 has been performed at 25 °C. The following results have been obtained: 1) A solvate crystal Form A (5/2 Ethanol·1/2 H2O) is recovered from 80 v/v% ethanol solution, 2) Form A transforms to Form H (4H2O) by the solid-phase transition through the solvate-free polymorph, Form A-2, and Form A also transformed to Form C (1Ethanol·3H2O) by the solvent-mediated transformation. In the present study, we found that Form C also transforms to Form H by the solid-phase transition through the solvate-free polymorph, Form C-2. The three polymorphs, Form A, H, and C, were composed of the helical-chain structures, respectively. However, there was an incomprehensible affair in the solid phase transition among the three polymorphs. Namely, Form A comprised a left-handed helix.On the other hand, Form C and Form H’s helix chains were in a left- and right-handed helix complex. The solid-phase transition of Form A into Form H suggested the switch of helicity in the solid. We attempted to explain the helicity change in the solid phase transition. As a result, it was suggested that the over-absorption of water of Form A-2 at high humidity plays a vital role in the helicity change.

Zidovudine (AZT) has significantly reduced the mortality and morbidity rates among AIDS patients, but it has been associated with hepatotoxicity. AZT treatment has been linked to disrupted lipid and glucose metabolism, and the enhancement of pro-inflammatory chemokines and other mediators, which can lead to liver steatosis. In contrast, the administration of adenosine (ADO) has proven to be an effective hepatoprotector against both acute and chronic liver damage. Therefore, present study was aimed to investigate the harmful effects of chronic AZT administration and the beneficial effects of the co-administered ADO. Chronic oral AZT administration did not induce hyperglycemia or dyslipidemia, but serum liver marker enzyme activities were increased, as well as evidence of liver steatosis and inflammation. These findings were associated with low insulin and glucagon levels, elevated serum levels of pro-inflammatory cytokines and disruptions in cell redox states in these animals. ADO co-administration attenuated the deleterious effects induced by AZT: blocking the production of inflammatory molecules, increasing serum insulin and glucagon levels, and restoring liver cellular redox state. Then, blood insulin levels seemed to be greatly influenced by the cellular redox state, which was altered by AZT administration. This alteration is likely to be connected to mitochondrial integrity and metabolism.

Stroke is a major leading cause of chronic disability, often affecting patients’ motor and sensory functions. Functional magnetic resonance imaging (fMRI) is the most commonly used method of functional neuroimaging and allows the non-invasive study of brain activity. The time-dependent coactivation of different brain regions at rest is described as resting-state activation. As a non-invasive task-independent functional neuroimaging approach, resting-state fMRI (rs-fMRI) may provide therapeutically useful information on both the focal vascular lesion and the connectivity-based reorganization and subsequent functional recovery in stroke patients. Considering the role of prompt and accurate prognosis in stroke survivors along with the potential of rs-fMRI in identifying patterns of neuroplasticity in different post-stroke phases, this review provides a comprehensive overview of the latest literature regarding the role of rs-fMRI in stroke prognosis in terms of motor and sensory outcome. Our comprehensive review suggests that with the advancement of MRI acquisition and data analysis methods, rs-fMRI emerges as a promising tool to study the motor and sensory outcome in stroke patients and evaluate the effect of different interventions.

This paper focuses on leveraging a cutting-edge 3D state-space model for a holistic eco-friendly assessment in petrochemical operations. - By applying the ecological carrying capacity theory and the three-dimensional state-space model, this research aims to unleash the next frontier of sustainability in the petrochemical industry. - The proposed methodology will enable advanced and comprehensive eco efficiency evaluation in petrochemical operations. - Through the integration of the ecological carrying capacity theory and advanced modeling techniques, this research seeks to revolutionize sustainability assessments in the petrochemical sector. - The utilization of the cutting-edge 3D state-space model will provide a more advanced and accurate understanding of eco-friendly practices in petrochemical operations. This research presents a unique approach distinct from existing literature, which primarily examines business eco efficiency from behavioral motivation and strategic perspectives. In contrast, this paper introduces a novel three-dimensional state-space model to evaluate the ecological efficiency of petrochemical operations. By combining the ecological carrying index and state space, this model represents the ecological impact of petrochemical operations in a three-dimensional geometric space. It considers petrochemical operations as a significant factor exerting pressure on natural resources and the natural environment. In this three-dimensional state-space model, the three axes represent different dimensions of petrochemical operations. The first axis represents the economic status, which quantitatively describes the financial aspects of the operation. The second axis represents the utilization of resources, capturing the extent to which resources are consumed in the operation. The third axis focuses on the impact of the operation on the environment, allowing for a quantitative assessment of its ecological footprint. By incorporating these dimensions, the model aims to provide a comprehensive and quantitative description of the economic activities of petrochemical operations and their interactions with resources and the environment.The primary focus of this research is to apply the three-dimensional state-space model to calculate the ecological carrying capacity of petrochemical operations. By doing so, it aims to verify the feasibility and applicability of the model in determining the ecological efficiency of these operations. The research also aims to provide theoretical tools that can assist operations in making more informed ecological efficiency judgments. By utilizing this model, petrochemical operations will have a quantitative framework to assess and improve their environmental impact, thus fostering more sustainable practices. The findings of this research demonstrate that the implementation of this method can effectively identify issues related to resources, economy, and environment throughout the development of petrochemical operations. By identifying these problems, it provides managers with a solid foundation for making strategic decisions that promote sustainable development. With this valuable information at their disposal, managers can proactively address challenges, optimize resource utilization, and minimize environmental impacts, thus steering the petrochemical operations towards a more sustainable and responsible path.

Nano-drugs and nano-delivery systems are rapidly evolving, with new strategies emerging in the current practices. The evolution of these technologies began with modifying the chemical structure, progressing to supramolecular ionic complexes, and culminating in elegant ad hoc delivery systems. Nanoparticles have numerous benefits as a carrier system for delivering therapeutic agents to intra-arterial sites. These benefits include their subcellular size, targeted surfaces, good suspensibility, and uniform dispersity, making them an ideal choice for catheter-based delivery. Despite the advancements made in the field of nano-drugs and nano-delivery systems, there are still some hurdles to overcome in terms of their commercial availability.The current review presents an updated summary of recent advancements in nano-drugs and nano-delivery systems, including their commercial availability. We aim to discuss the present challenges and prospects of commercially available nano-drugs and nano-delivery systems. Here, we provide a precise and informative overview of the current state of these technologies and underscore the potential they hold for future developments. Further, we have categorized commercially available modifications, name, parent company and their main applications in nano-drugs.

The phytoplankton community in 66 reservoirs ubicated at the hydrographic basin of the Ebro River (Spain) was analyzed. Samples were collected in the summer season during the period 2010-2015, with the main purpose of evaluate the Trophic State and Ecological Potential according to the Water Framework Directive of the European Union. In this work we presented a representative overview of several consecutive years of the state of the reservoirs and their associated trophic status; methodology was to obtain statistically significant relationships between the phytoplankton community and main physicochemical water quality variables (water transparency, pH, chlorophyll a, total and soluble phosphorus, anoxic zone depth, nitrite, nitrate and ammonium concentrations). We provide data for retrospective comparative of the state of the reservoirs with previous and current studies in order to improve the management of these reservoirs, and to serve as data reference for future works in a context of global change (climate and pollution).

Peptide/Histidine Transporter PHT1 (SLC15A4) is expressed in lysosomal membranes of immune cells where it plays an important role in metabolic and inflammatory signaling. PHT1 is an H+-coupled/histidine symporter that can transport a broad range of oligopeptides, including a variety of bacterial-derived peptides. Moreover, it enables the scaffolding of various metabolic signaling molecules and interacts with key regulatory elements of the immune response. Therefore, it is not surprising that PHT1 is associated with the development of autoimmune diseases, such as systemic lupus erythematosus (SLE). Unfortunately, the pharmacological development of PHT1 has been hampered by the lack of appropriate transport assays. With the aim to address this shortcoming, a novel transport assay based on solid supported membrane-based electrophysiology (SSME) is presented. Key findings of the present SSME studies include the first recordings of electrophysiological properties, a pH dependence analysis, an assessment of PHT1 substrate selectivity, as well as the transport kinetics of the identified substrates. In contrast to previous works, PHT1 is studied its native lysosomal environment. Moreover, observed substrate selectivity is validated by molecular docking. Overall, this new SSME-based assay is expected to contribute to unlock the pharmacological potential of PHT1 and to deepen the understanding of its functional properties.

Changing the symmetry of spin from SU(2) to the quaternion group, $Q_8$, has many ramifications. In this paper we first summarize the properties of Q-spin and then discuss some of those resulting changes.

In a Water-Cooled Lithium-Lead (WCLL) Breeding Blanket (BB), the heat generated by the plasma thermal radiation and nuclear reactions is removed mainly by two components; namely, the First Wall (FW) and the Breeding Zone (BZ). The FW faces the neutrons and charged particles fluxes generated by the fusion reactions and the thermal radiation coming from the plasma. The present work takes into account the FW cooling system inspired by the WCLL BB 2018 design of DEMO 2017 baseline. Unlike the baseline where a Pressurized-Water Reactor (PWR) setup is used for the coolant, various setup between the Boiling Water Reactor (BWR) and the High-Pressure (HP) BWR are studied in the present work operating in the Two-Phase Flow (TPF) regime. The 3D model of the FW in the WCLL BB 2018 design is simplified into a 1D model and a steady state analysis is carried out to optimize the mass flow rate of the water and the number of parallel channels at the BB cells at different poloidal locations of the reactor, which helps not only in reducing the used coolant but also in improving the Tritium Breeding Ratio (TBR). The present work takes into account forced convection in the liquid only region, the subcooled boiling region, and the saturated boiling region using suitable empirical or semi-empirical models from the literature. The results are validated against the existing results in the literature. In the end, related conclusions are made regarding the pros and cons of the studied operating conditions.

Karate is a martial art that originated in Japan It is characterized by its diverse techniques, including punches, kicks, strikes, and open hand techniques. Generally, karate practitioners shall execute techniques fast, with an impactful finishing towards the target. The present study aims to examine the effectiveness of customized gym sessions in enhancing the athletes’ general performance with a duration of 3-months’time. A total of 7 tests were monitored, i.e., anthropometric measurement, sit and reach test, stork balance stand test, T-test, counter movement jump, 20m sprint, and Yo-Yo endurance test. 4 male amateur athletes (state representative) that has practiced karate for at least 6 years, with at least 5 days training per week, were selected. The age ranges from 15 to 20 years old. The athletes were requested to have a proper rest (at least 7 hours sleeping time) five days before the actual test day. The results show that all athletes have at least maintained or improved stork balance for both legs. The balance improvement ranges from 0% up to 134.69%. However, both the T-test and 20m sprint test demonstrated a negative outcome. The time consumed to complete 20m is increased, which deteriorated the linear speed capability by 1.89% up to 8.93%. Also, 3 out of 4 athletes show that the T-test performance does not provide a satisfactory achievement. The agility of athletes was found to drop by 3.58% up to 10.60%. Interestingly, the athletes’ stamina was found to improve based on the VO2 max prediction and Yo-Yo test. The enhancement of VO2 max prediction and Yo-Yo test recorded as 0% - 7.53% and 9.09% - 20%, respectively. So far, there is no clear indicator on the flexibility of the athletes’ spine and length of the hamstring muscles, based on the sit and reach test. Short-term gym sessions with a duration of 3 months might improve the strength and body balance of athletes. However, the impact on the responsiveness and agility of athletes did not show any significant breakthrough. In future study, it is recommended that a large sample of participants should be included in the analysis.

The rate constants of elementary processes in the atom-diatom system O(³P)+H₂(v), including the processes of vibrational relaxation and dissociation, were studied using the quasi-classical trajectory method. All calculations were carried out along the ground potential energy surface (PES) ³A′′ that was approximated by a neural network. Approximation data were obtained using ab initio quantum chemistry methods at the extended multi-configuration quasi-degenerate second-order perturbation theory XMCQDPT2 in a basis set limit. The calculated cross sections of the reaction channels are in good agreement with the literature data. A complete set of state-to-state rate constants was obtained for the metathesis reaction, the dissociation and VT relaxation of the H₂ molecule upon collision with an O atom. According to this data Arrhenius approximations over a wide temperature range were obtained for the thermal rate constants of considered processes. Data obtained on the dissociation constants and VT relaxation of vibrationally excited H₂ molecules can be used in constructing kinetic models describing the oxidation of hydrogen at high temperatures or highly nonequilibrium conditions.