A new three-dimensional numerical model of a polymer electrolyte fuel cell (PEFC) with a single straight channel has been developed to primarily investigate the important impact of the double-sided microporous layer (MPL) coating on the overall performance of the fuel cell and the distribution of the current and the oxygen concentration within the cathode gas diffusion layers (GDLs). Realistic experimentally estimated interfacial contact resistance values between the gas diffusion layer and each of the bipolar plates and the catalyst layer values were incorporated into the model, and parametric studies were performed. The results showed that the double-sided MPL coating could significantly improve the fuel cell performance by up to 30%. Also, it was shown that the neglect of the contact resistance between the MPL and the catalyst layer could overestimate the fuel cell performance by up to 6%. In addition, the results showed that the fuel cell performance and the distribution of the current and oxygen are more sensitive to the porosity of the MPL facing the bipolar plate than the porosity of the MPL facing the catalyst layer. All the above results are presented and critically discussed in detail.

Increased proliferation of IT services in all sectors has reinforced the adoption and diffusion across all levels of education and training institutions. However, lack of awareness of and knowledge about the key challenges and opportunities of elearning, seem to allude policymakers, resulting in low adoption or increased failure rate of many e-learning projects. Our study tries to address this problem through a review of relevant literature in e-learning. Our goal was to draw from the existing literature, insights into the opportunities and challenges of e-learning diffusion, and the current state-of-research in the field. To do this, we employed a systematic review of literature on some of the salient opportunities and challenges of e-learning innovation for educational institutions. These results aimed to inform policymakers and suggest some interesting issues to advance the research and adoption and diffusion of e-learning. Moreover, the bibliometric analysis shows that the field is experiencing high research attraction among scholars. However, several research areas in the field witnessed relatively low research paucity. Based on these findings, we discussed topics for possible future research.

In the present study, a mathematical model of non-steady partial differential equation from the process of oxygen mass transport in the human pulmonary circulation is proposed. Mathematical modelling of this kind of problems lead to a non-steady partial differential equation and for its numerical simulation, we have used finite differences. The aim of the process is the exact numerical analysis of the study, wherein consistency, stability and convergence is proposed. The necessity of doing the process is that, we would like to increase the order of numerical solution to a higher order scheme. An increment in the order of numerical solution makes the numerical simulation more accurate, also makes the numerical simulation being more complicated. In addition, the process of numerical analysis of the study in this order of solution needs more research work.

A new model for risk assessment of urban rainstorm disasters, based on information diffusion method and variable fuzzy sets (IDM-VFS) was proposed. In addition, an integrated index system of urban rainstorm risk was established. In the proposed model, IDM was employed to calculate the classification standards of urban rainstorm risk levels, then the VFS was adopted to assess the dangerousness, sensitivity, vulnerability and comprehensive risk of urban rainstorm disasters. In the present study, the urban rainstorm risk of Jiangsu province was evaluated with the proposed model. The results show that Wuxi, Changzhou, Nanjing and Suzhou have higher dangerousness, due to sustained rainfall and strong rainfall intensity in short duration; Wuxi, Changzhou and Nanjing have higher sensitivity because of lower disaster resistance ability; and Wuxi and Suzhou have higher vulnerability because these cities have higher potential losses in face of urban rainstorm disasters. The comprehensive risk zoning map of urban rainstorm shows apparent regional characteristics: the northwestern cities have lower risk than the southern cities. Moreover, most cities of the Jiangsu province are of the moderate urban rainstorm risk level. The results are consistent with the actual situation of Jiangsu province, and the study can provide some decision-making references for the urban rainstorm management.

In this paper, we work with a diffusion-perturbed risk model comprising a surplus generating process and an investment return process. The investment return process is of standard Black-Scholes type, that is, it comprises a single risk-free asset that earns interest at a constant rate and a single risky asset whose price process is modelled by a geometric Brownian motion. Additionally, the company is allowed to purchase noncheap proportional reinsurance priced via the expected value principle. Using the Hamilton-Jacobi-Bellman approach, we derive a second-order Volterra integrodifferential equation which we transform into a linear Volterra integral equation of the second kind. We proceed to solve this integral equation numerically using the block-by-block method for the optimal reinsurance retention level that minimizes the ultimate ruin probability. The numerical results based on light- and heavy-tailed distributions show that proportional reinsurance and investments play a vital role in enhancing the survival of insurance companies. But the ruin probability exhibits sensitivity to the volatility of the stock price.

Many empirical and theoretical studies indicate that Brownian motion and diffusion models as its mean field counterpart provide appropriate modelling techniques for individual insect movement. However, this traditional approach has been challenged and conflicting evidence suggests that an alternative movement pattern such as Lévy walks can provide a better description. Lévy walks differ from Brownian motion since they allow for a higher frequency of large steps, resulting in a faster movement. Identification of the ‘correct’ movement model that would consistently provide the best fit for movement data is challenging and has become a highly controversial issue. In this paper, we show that this controversy may be superficial rather than real if the issue is considered in the context of trapping or, more generally, survival probabilities. In particular, we show that almost identical trap counts are reproduced for inherently different movement models (such as the Brownian motion and the Lévy walk) under certain conditions of equivalence. This apparently suggests that the whole ‘Levy or diffusion’ debate is rather senseless unless it is placed into a specific ecological context, e.g. pest monitoring programmes.

We propose a wave-like design on the surface of cathode channels (wave form cathode channels) to improve oxidant delivery to gas diffusion layers (GDLs) [1-2]. We performed experiments using PEMFCs combined with wave form surface design on cathodes. We varied the factors of the distance between wave-bumps (the Adhesive distance, AD), and the size of the wave-bumps (the Expansion ratio, ER). The ADs are 3, 4, and 5 times the size of the half-circle bump’s radius, and the ERs are 1/1.5, 1/2, and 1/3 times the channel’s height. We evaluated the performances of the fuel cells, and compared the current-voltage (I-V) relations. For comparison, we prepared PEMFCs with conventional flat-surfaced oxygen channels. Our aim in this work is to identify fuel cell operation by modifying the surface design of channels, and ultimately to find the optimal design of cathode channels that will maximize fuel cell performance.

To date, radiation adaptation response has been reported as a low-dose related phenomenon and has been associated with radiation hormesis. Well-known cancers are caused by non-radiation active reactants, in addition to radiation. A model of suppression for radiation-specific cancers was previously reported, but the model did not target radiation-nonspecific cancers. In this paper, we describe kinetic models of radiation-induced suppressors for general radiation non-specific cancers, estimating the dose that induces the maximum hormesis effect while satisfying the condition that the risk is approximately proportional to dose above 100 mSv. It was found that the radiation hormesis effect is maximal at about 20 mSv when the rate constant for generation is the same as the rate constant for decomposition. When the two rate constants are different, the dose at which the radiation hormesis effect is maximized depends on both rate constants, but the dose increases as the two rate constants approach each other, reaching a maximum of about 20 mSv. This conclusion may lead to the discovery of unknown cancer suppressors at low doses and the development of cancer suppression methods in the future.

A single type I RC (Fe-S type, ferredoxin reducing) is found in several of the phyla of anoxygenic phototrophic bacteria. They include the heliobacteria (HB), the green sulfur bacteria (GSB) and the chloroacidobacteria (CAB), for which high-resolution homodimeric RC-PS structures have recently appeared [1-4]. The 2.2-Å Xray structure of the RC-PS of Heliomicrobium modesticaldum [1] revealed that the core PshA apoprotein (PshA1 and PshA2 homodimeric pair) exhibits a structurally conserved PSI arrangement comprised of five C-terminal transmembrane helices (TMHs) forming the RC domain and six N-terminal TMHs coordinating the light-harvesting (LH) pigments. The Hm. modesticaldum structure lacked quinones, indicating that electrons were transferred directly from the A0 (81-OH-chlorophyl (Chl) a) primary acceptor to the FX [4Fe4S] component, serving as the terminal RC acceptor. A pair of additional TMHs designated as Psh X were found, that function as a low-energy antennae. The 2.5Å resolution cryo-electron microscopy (cryo-EM) structure for the RC-PS of the GSB Chlorobaculum tepidum [2] included two Fenna-Matthews-Olson protein (FMO) antennae, which transfer excitations from the chlorosomes to the RC-PS (PscA1 and PscA2) core. Two cytochromes c (PscC) molecules were revealed, which act in series as electron donors to the photooxidized RC BChl a’ special pair, as well as PscB, housing the [4Fe-4S] cluster FA and FB, and the associated PscD protein [3]. Although their FMO components were missing from the 2.6-Å cyro-EM structure of the Zn-BChl a’ special pair containing RC-PS of Chloroacidobacterium thermophilum [4], a unique architecture was revealed that consisted of seven additional subunits including PscZ in place of PscD, the PscX and PscY cytochrome c serial electron donors and four low mol. wt. subunits of unknown function. Overall, these diverse structures have revealed that: (i) the HB RC-PS is the simplest light-energy transducing complex yet isolated, and represents the closest known homolog to a common homodimeric RC-PS ancestor; (ii) the symmetrically localized Ca2+binding sites found in each of the Type I homodimeric RC-PSs likely gave rise to the analogously positioned Mn4CaO5 cluster of the PSII RC and the TyrZ RC donor site; (iii) a close relationship between the GSB RC-PS and Chl protein (CP)43 and CP47 of PSII was demonstrated by the strongly conserved locations of their LH-(B)Chls; (iv) LH-BChls of the GSB-RC-PS are also localized in the conserved RC-associated positions of the PSII ChlZ-D1 and ChlZ-D2 sites; (v) glycosylated carotenoids of the GSB RC-PS are located in the homologous carotenoid-containing positions of PSII, reflecting an O2-tolerance mechanism capable of sustaining early stages in the evolution of oxygenic photosynthesis. In addition to the close relationships found between the homodimeric RC-PS and PSII, duplication of the gene encoding the ancestral Type I RC apoprotein, followed by genetic divergence my well account for the appearance of the heterodimeric Type I and Type II RC found in extant oxygenic phototrophs. Accordingly, the long-held view that PSII arose from the anoxygenic Type II RC is now supplanted by the new evidence provided by Type I RC-PS homodimer structures, indicating that the evolutionary origins of anoxygenic Type II RCs along with their distinct antenna rings are likely to have occured later than the events which gave rise to their oxygenic counterparts.

Malaria is rare in Europe, but it is a medical emergency and programs for its control should ensure access to early diagnosis and prompt treatment within 24-48 h of the symptom’s onset. The consistent number of imported malaria cases and the risk of reappearance of autochthonous cases stimulated laboratories in non-endemic countries to evaluate diagnostic methods/algorithms: microscopy remains the gold standard, but with limitations. RDTs have greatly expanded the ability to diagnose malaria for rapid results due to simplicity and low cost, but they lack sensitivity and specificity. PCR-based assays provide more relevant information but need well-trained technicians. According to WHO global Technical Strategy for Malaria 2016-2030, the future direction for a rapid diagnosis is the development of Point-Of-Care Testing, which would be helpful for prompt/accurate treatment and for preventing the diseases spread. Despite the limitations of current diagnostic methods, they play important roles in dealing with the global malaria situation, including decreasing its incidence. Recently evidence suggested that Artificial Intelligence could be utilized for assisting pathologists in malaria diagnosis. Future studies need to be conducted to see whether this system can be used for routine malaria diagnostic procedures.

Oxygen evolution reaction (OER) is a key half-reaction in electrocatalytic water splitting. Large-scale water electrolysis is hampered by the commercial precious metal-based OER electrocatalysts owing to their high cost and slow kinetics. To address these issues, we present a facile one-pot room-temperature coprecipitation method to quickly synthesize carbon nanotubes-interconnected amorphous NiFe-layered double hydroxides (NiFe-LDH@CNT) as low-cost, efficient and stable OER electrocatalyst. NiFe-LDH@CNT hybrid catalyst delivers outstanding OER performance with a low onset overpotential of 255 mV and a small Tafel slope of 51.2 mV dec-1, as well as outstanding long-term stability. The terrific catalytic capability of NiFe-LDH@CNT can be associated with the synergistic effects of its room-temperature synthesized amorphous structure, bi-metallic modulation, and conductive CNT skeleton. The room-temperature synthesis can not only offer economic feasibility, but also obtain amorphous NiFe-LDH without crystalline boundaries, facilitating long-term stability during OER process. The bi-metallic nature of NiFe-LDH guarantees a modified electronic structure, providing additional catalytic sites. Simultaneously, the highly conductive CNT network fosters a nanoporous structure, facilitating electron transfer, O2 release and enriching catalytic sites. This study presents a strategy to purposefully design nanoarchitecture and facilely synthesize amorphous transition metal-based OER catalysts, ensuring the cost effectiveness, production efficiency, and long-term stability.

Large volume bone defect regeneration is complex and demands time to complete. Several regeneration phases with unique characteristics including immune responses follow, overlap, and interdepend on each other and, if successful, lead to the regeneration of the organ bone's form and function. However, during traumatic, infectious, or neoplastic clinical cases, the intrinsic bone regeneration capacity may exceed, and surgical intervention is indicated. Scaffold-guided bone regeneration (SGBR) has recently shown efficacy in preclinical and clinical studies. To investigate different SGBR strategies over periods of up to 3 years we have established a well characterized large segmental tibial bone defect ovine model, for which we have developed and optimized immunohistochemistry (IHC) protocols. We present an overview of the immunohistochemical characterization of different experimental groups in which all ovine segmental defects were treated with a bone grafting technique combined with a three-dimensionally printed medical-grade polycaprolactone-tricalcium phosphate (mPCL-TCP) scaffold. The qualitative data set is based on osteoimmunological findings gained from IHC analyses of over >350 sheep surgeries over the past two decades. Our systematic and standardized IHC protocols enabled us to gain further insight into the complex and long-drawn-out bone regeneration processes, which ultimately proved to be a critical element for successful translational research.

Two reversible furan-maleimide resins, in which there are rigid -Ph-CH2-Ph- structure and flexible -(CH2)6- structures in bismaleimides, were synthesized from furfuryl glycidyl ethers (FGE), 4,4′-diaminodiphenyl ether (ODA), N,N'-4,4'-diphenylmethane-bismaleimide (DBMI) and N,N'-hexamethylene-bismaleimide (HBMI). The structures of the resins were confirmed by Fourier transform infrared analysis, and the thermoreversibility was evidenced by differential scanning calorimetry (DSC) analysis as well as sol-gel transformation process. Mechanical properties and recyclability of the resins were preliminarily evaluated by the flexural test. The results show the Diels-Alder (DA) reaction occurs at about 90°C and reversible DA reaction does at 130-140°C for the furan-maleimide resin. Thermally reversible furan-maleimide resins have high mechanical properties. The flexural strength of cured FGE-ODA-HBMI resin arrives at 141 MPa. The resins have a repair efficiency of over 75%. After being hot-pressed for three times, two resins display higher flexural strength than 80 MPa.

Iron-containing nickel sulfides, selenides, and sulfoselenides were synthesized via a simple two-step hydrothermal reaction (temperature 160 °C) for their application as electrocatalysts in the oxygen evolution reaction (OER) in an alkaline solution (1 mol L–1 KOH). The study demonstrated that iron-containing nickel cobalt sulfides and selenides exhibit superior OER performance with lower overpotentials compared to iron-free nickel cobalt sulfide and selenide, which highlights the significant role of iron in enhancing OER nickel cobalt electrocatalysts: Fe0.1Ni1.4Co2.9(S0.87O0.13)4, η50 = 318 mV; Fe0.2Ni1.5Co2.8(S0.9O0.1)4, η50 = 310 mV; Fe0.3Ni1.2Co2.5(S0.9O0.1)4, η50 = 294 mV; Fe0.6Ni1.2Co2.5(S0.83O0.17)4, η50 = 294 mV, Fe0.4Ni0.7Co1.6(Se0.81O0.19)4, η50 = 306 mV compared to Ni1.0Co2.1(S0.9O0.1)4, η50 = 346 mV and Ni0.7Co1.4(Se0.85O0.15)4, η50 = 355 mV (all values at current densities η50 of 50 mA cm–2). Furthermore, the iron-containing nickel cobalt sulfoselenide Fe0.5Ni1.0Co2.0(S0.57Se0.25O0.18)4 displayed exceptional OER performance with η50 = 277 mV, surpassing the benchmark RuO2 electrode with η50 = 299 mV. The superior performance of the sulfoselenide was attributed to its low charge transfer resistance (Rct) of 0.8 Ω at 1.5 V vs. the reversible hydrogen electrode (RHE). Moreover, the sulfoselenide demonstrated remarkable stability, with only a minimal increase in overpotential (η50) from 277 mV to 279 mV after a 20 h chronopotentiometry test. These findings suggest that trimetallic iron, nickel and cobalt sulfide, selenide and especially sulfoselenide materials hold promise as high-performance, cost-effective, and durable electrocatalysts for sustainable OER reactions. This study provides a valuable approach for the development of efficient electrocatalytic materials, contributing to the advancement of renewable energy technologies.

The present work is a numerical simulation of velocity and mixture fraction fields in a turbulent non-reaction Propane jet flow issuing into parallel co-flowing air, in isothermal condition which has been experimentally described here: http://www.sandia.gov/TNF/DataArch/ProJet.html. The objective is a better understanding of the flow structure and mixing process, a situation in which there is no chemical interaction and heat-transfer. The two-equation Realizable k-ε eddy viscosity turbulence model has been used to simulate the turbulent flow field on a 2D plane (i.e., on a 5-degree sector of the experimental domain), because Realizable k-ε more accurately predicts the spreading rate of both planar and round jets and presents the best proficiency in comparison with all versions of the k-ε models. Afterward, axial and radial profiles of mean velocities, turbulence energy, mean mixture fraction, the mixture fraction half radius (Lf), and the mass flux diagram have been numerically elicited for grid independent mesh (mesh B) and compared with corresponding experimental data to assess the numerical model. To obtain turbulence kinetic energy, k, due to lack of w' in the experimental data, the assumption of w'=v' seems to be valid. Simulations have demonstrated that mean mixture fraction (at radial profiles at locations x/D=0, 4, 15, 30 and 50) and its half radius, Lf, which characterizes jet width expanse, are prominently well-captured; Moreover, mean vertical velocity fields (in X-direction: Umean) have revealed less accuracy but still conspicuously well-captured. However, mean vertical velocity fields (in Y-direction: Vmean) have disclosed less resolution; Likewise, turbulence kinetic energy, k, have manifested moderate accuracy (between Umean and Vmean). It should be noticed that although numerical results for absolute pressure, p, have been obtained on aforementioned sections, there were no experimental data to compare with them. Thus, the corresponding numerical data has not been demonstrated in this study.

This work presents a nonlinear model predictive control scheme that challenges overcoming the obstacles holding back over decades to develop affordable autonomous control and monitoring systems applied in the large-scale industry. Among the numerous proposals in the literature, most do not consider the significant fluctuation of kinetic parameters in the reduced mathematical model ADM2, widely used for control and monitoring purposes. The prevalent cause, on a basis, is the lack of information caused by some dynamics and parameters that cannot be measured in real-time by reliable sensors. In addition, to make matters worse, those systems inherently act with nonlinear nature and have a high sensitiveness to uncontrollable inputs and perturbations. Therefore, to prevent these drawbacks, this work proposes a new methodology that reconstructs the lack of information from the non-measurable dynamics, concentration of bacterias, and the kinetic parameters related to reaction rates. Simulations results demonstrate the effectiveness of the methodology compared with traditional industrial control schemes.

A right frontoparietal neoplastic lesion was found in a young-aged patient with analgesic refractory headache. Surgical resection was performed, and the pathologist analysis turned out a cellular ependymoma with signs of anaplasia. In the follow-up, a MRI showed a suspicious lesion, so a [18F]Fluorocholine PET/CT was performed. An increased uptake was described in the right parietal region on the margin of residual cystic lesion. The patient got a complete resection which was confirmed later by MR. In the pathology analysis, a focally congestive cerebral parenchyma with a central histiocytic reaction to foreign body area was described. Foreign body reaction in brain tissue is a very rare immune response that has not been well studied. Haemostatic material has been reported as a possible trigger of this response in other organs and could be detected by [18F]FDG PET/CT. Following the experience of the current case report, [18F]Fluorocholine PET/CT could also show a false positive related to foreign body reaction.

This study investigated the reduction of organic loads from mixed agro-food industrial wastewaters (dairy and slaughterhouse) of Nablus city using advanced oxidation process (AOP), a high- rate chemical oxidation reaction. Bench-scale Jar tests using an advanced oxidation process (AOP) were performed as a pretreatment stage. Direct applications of classical Fenton’s process on mixed raw agro-food wastewater samples (COD: 15400-18200 mg/l) revealed unsatisfactory results. The performance of the Fenton process was evaluated using three mixed samples with different pre-treatment trials: (A) coagulant (FeCl3.6H2O) addition, (B) settling (2h) allowed, and use of flocculent (lime Ca(OH)2) in sample (C). Compared with other partial treatments, sample (C), Fenton`s process lime preceded, was the most effective in the removal of organic (89% COD; 80% TKN) and inorganic loads (91% TSS; 62% TS) under H2O2/COD (w/w ratio 2:1), H2O2/Fe+2 (w/w ratio 10:1) and acidic conditions (pH =3). Obtained results comply with Nablus municipal by-law (COD below 2000 mg/l), which help decision-makers within the agro-food industries install pollution reduction systems. Investment in the Fenton-based peroxidation process, allow agro-food industries to obtain connection permits to sewage networks.

The influence of the type and amount of oxygen (O), nitrogen (N), and/or phosphorus (P) heteroatoms on the surface of carbon nanotube (CNT) on stability and catalytic activity in the oxygen reduction reaction (ORR) was investigated in alkaline media. It is shown that the functionalization of CNT leads to the growth of the electrochemically active surface and to an increase in the activity in ORR. At the same time, a decrease in stability is observed after the functionalization of CNT under accelerated corrosion testing in an alkaline media. These results are most significant on CNT after functionalization in HNO3 due to the formation of a large number of structural defects. However, the subsequent doping by N and / or P atoms provides a further activity increase and enhances the corrosion stability of CNT. Thus, as shown by the studies of characteristic parameters (SEAS, E1/2, corrosion stability), CNT doped with N and NP are a promising catalytic system that can be recommended for use as fuel cell cathodes. An important condition for effective doping is the synthesis of carboxyl and carbonyl oxygen containing group on the surface of CNT.

A 47-year-old physician suddenly noticed a persistent difficulty maintaining attention. He was awake, alert, and oriented. After two hours he developed fever, ageusia, and anosmia. He denied any previous history of psychiatric illness and was hydrated at the time of the subjective attention impairment. On admission, the patient remained oriented. He reported the persistence of attention problems, anosmia, and mild fatigue. The oxygen saturation 99% while he was breathing ambient air. Laboratory tests were unremarkable. A high-resolution computed tomography of the chest was normal. Nasopharyngeal and throat swabs specimens on reverse transcription-polymerase chain reaction analysis tested positive for SARS-CoV2. On illness day 3, the examination was unchanged, but he continued to complain of difficulties to stay focused. Then, he performed an objective attention test. The test demonstrated a moderate attentional impairment. On day 6, the patient reported a subjective worse in his concentration and performed a second test. Although his physical examination remained normal, the attention performance was worse as compared to day 3. Eight hours after worsening of attention impairment, the patient’s oxygen saturation dropped to 94%. From illness days 9 to 14, the patient evolved with clinical improvement. On day 10, a third objective attention test indicated a mild deficit. On day 16, he did not report any other symptom and the attention test was completely normal. Then, the patient returned to work. Neurological symptoms had been previously described in COVID- 19 patients. However, no previous research had investigated early cognitive deficits preceding the traditional symptoms.

This study is focused on the experimental investigation of compressive strength and durability properties of lightweight concrete mixtures with fine expanded glass and expanded clay aggregates using different microfillers. The paper proposes the relationships between the compressive strength and density of concrete mixtures with different proportions of lightweight aggregates mentioned above. The performed experimental studies have revealed the tendencies of possible usage of different amount of fine lightweight aggregates and their combinations in the production of concrete mixtures depending on the demands of practical application. Following the requirements for structural concrete subjected to environmental effects, durability properties (alkaline corrosion and freeze–thaw resistance) of the selected concrete mixtures with expanded glass aggregate were studied. The results of the experimental investigations have shown that durability of tested concrete specimens was sufficient. The study has concluded that the mixtures under consideration can be applied for the production of structural elements to which durability requirements are significant.

Inherent in every Active Magnetic Bearing (AMB) are differences between the expected geometric axes and the actual magnetic axes due to a combination of discrepancies, including physical variation from manufacturing tolerances and misalignment from mechanical assembly, fringing and leakage effects, as well as variations in magnetic material properties within a single AMB. A method is presented here for locating the magnetic axes of an AMB that will facilitate the accurate characterization of the bearing air gaps for potential improvement in field tuning, performance analyses and certain shaft force measurement techniques. This paper presents an extension of the application of the bias current perturbation method for the determination of the magnetic center [4] to the determination of magnetic axes for the further development of accurate current-based force measurement techniques [1].

Lithium-metal batteries offer high energy density, but are challenged by dendrite growth, which can lead to short circuits and battery failure. Various models with varying degrees of accuracy and computational cost have been developed to understand and predict dendrite growth. In this study, a simple simulation model to predict macroscale dendrite growth on lithium metal electrodes is presented. The model uses a 3D single-particle diffusion-limited aggregation (DLA) algorithm, biased by the electric field, to simulate dendrite growth. The model was validated using 3D MRI of dendrite growth in a lithium symmetric cell. It was used to simulate deposition between consecutive measured dendrite structures. The model also introduces an important parameter, namely the biasing factor c, which determines the balance between diffusion and electric field effects. This parameter was calibrated using the overlap and displacement of deposition sites metrics, achieving optimal results at c = 0.7. The model predictions were in good agreement with experimental data confirmed by fractal dimension analysis. This model provides a useful tool for predicting and studying dendrite formation in lithium and other metal batteries.

A two-layer Fe-Cr-Al-Zr surface alloy was synthesized on a zirconium substrate by magnetron sputtering and subsequent low-energy high-current electron-beam (LEHCEB) processing. Thicknesses of the top Fe69Cr20Al11 (at.%) relatively large-grained (~1 µm) and transition Fe-Zr Cr-Al amorphous layers were about 0.7 and 0.6 µm, respectively. In turn, the amorphous layer consisted of two Fe64–54Zr8–22Cr21–17Al8–7 and Fe40–16Zr42–78Cr12–4Al6–2 (at.%) sublayers, differing in both zirconium and iron concentrations in wide ranges, which were separated by another nanocrystalline interlayer. The Fe-Cr-Al-Zr surface alloy serve as a diffusion barrier, preventing interaction of the zirconium substrate with oxygen from an environment. It was thermally stable up to ≈1173 K.

The main objective of this work was to evaluate the application of individual and ensemble machine learning models to classify malignant and benign breast masses using features from two-dimensional (2D) correlated spectroscopy spectra extracted from five-dimensional Echo Planar-Correlated Spectroscopic Imaging (5D EP-COSI) and Diffusion-weighted imaging (DWI). Twenty-four different metabolite and lipid ratios with respect to 2D diagonal peaks at 1.4ppm and 5.4ppm, and water from one-dimensional non-water-suppressed (NWS) spectra were used as the features. Additionally, water fraction, fat fraction and water-to-fat ratios from NWS spectra and apparent diffusion coefficients (ADC) from DWI were included. Nine most important features were identified using recursive feature elimination. XGBoost (AUC:93.0%, Accuracy:85.7%, F1-score:87.6%), GradientBoost (AUC:94.4%, Accuracy:87.0%, F1-score:89.4%), CatBoost (AUC:95.2%, Accuracy:86.9%, F1-score:88.4%) and RandomForest (AUC:92.2%, Accuracy:85.3%, F1-score:87.6%) were the best performing models. While the conventional biomarkers like choline, myo-Inositol, and glycine were statistically significant predictors, the key features contributing to the classification were ADC, 2D diagonal peaks at 0.9ppm, 2.1ppm and 2.3ppm, cross peaks between 1.4 and 0.9ppm, 4.3 and 4.1ppm, 2.1 and 1.4ppm and the triglyceryl-fat cross peak. The results highlight the contribution of the 2D spectral peaks to the model, and they demonstrate the potential of 5D EP-COSI for early breast cancer detection.

Abstract: Coal bed methane (CBM) reservoirs are complex systems whose properties differ from those of conventional reservoirs. Coal seams are dual-porosity systems that comprise the porosities of the matrix and cleat system. Gas in the coal seams can be stored as free gas in the cleat system and as adsorbed gas in the porous medium. The flow mechanisms of the natural gas through the formation include desorption, diffusion, and Darcy’s flow regimes. The permeability of CBM reservoirs is more sensitive to pressure variations than conventional gas reservoirs. To study the flow behavior of CBM reservoirs it is mandatory to use a model that considers their unique characteristics. The objective of this study was to propose a physical and mathematical model of production performance for horizontal wells in CBM reservoirs whose permeability is dependent on pressure. A solution for the model was obtained by applying Pedrosa´s transformation, perturbation theory, Laplace transformation, the point source method, and Sthefest´s algorithm. The solution to this problem was validated with previous work thoroughly. The type curves of the model were built and the pressure transient behavior of the model was analyzed and discussed. The effects of several parameters on pressure behavior were also discussed.

Single-molecule fluorescence detection (SMFD) experiments are useful in distinguishing sub-populations of molecular species when measuring heterogeneous samples. One experimental platform for SMFD is based on a confocal microscope, where molecules randomly traverse an effective detection volume. The non-uniformity of the excitation profile and the random nature of Brownian motion, produce fluctuating fluorescence signals. For these signals to be distinguished from the background, burst analysis is frequently used. Yet, the relation between the results of burst analyses and the underlying information of the diffusing molecules is still obscure and requires systematic assessment. In this work we performed three-dimensional Brownian motion simulations of SMFD, and tested the positions at which molecules emitted photons that passed the burst analysis criteria for different values of burst analysis parameters. The results of this work verify which of the burst analysis parameters and experimental conditions influence both the position of molecules in space when fluorescence is detected and taken into account, and whether these bursts of photons arise purely from single molecules, or not entirely. Finally, we show, as an example, the effect of bursts that are not purely from a single molecule on the accuracy in single-molecule Förster resonance energy transfer measurements.

Immersion in salt-lake solution was adopted to periodically test the concrete chloride-ion diffusion coefficient. The regression analysis was also completed. Also investigated was the time-dependent law of concrete chloride-ion diffusion coefficient with time. The influence of chloride-ion concentration in solution, water-to-cement ratio, and corrosion time on the largeness and accumulation rate of the concrete chloride-ion diffusion coefficient was also analyzed. Test results show that the concrete chloride-ion diffusion coefficient gradually decreased with increasing time and increased with increasing chloride-ion concentration in a salt lake . Taking into account the influence of factors such as water–binder ratio, chloride-ion concentration, and time-varying characteristics, a multi-factor calculation model for the concrete chloride-ion diffusion coefficient was established. Combining the prediction results and the measured data reported in this paper, the effectiveness and applicability of the established concrete chloride-ion diffusion coefficient calculation model were compared and verified, and the durability design and service life of a concrete structure under cool chlorine were compared. The results of analysis provide important boundary conditions.

The separation of sister chromatids during anaphase is the culmination of mitosis and one of the most strikingly beautiful examples of cellular movement. It consists of two distinct processes: Anaphase A, the movement of chromosomes toward spindle poles via shortening of the connecting fibers, and anaphase B, separation of the two poles from one another via spindle elongation. I focus here on anaphase A chromosome-to-pole movement. The chapter begins by summarizing classical observations of chromosome movements, which support the current understanding of anaphase mechanisms. Live cell fluorescence microscopy studies showed that poleward chromosome movement is associated with disassembly, or ‘melting’ of the kinetochore-attached microtubule fibers that link chromosomes to poles. Microtubule-marking techniques established that kinetochore-fiber disassembly often occurs through a ‘pac-man’ mechanism, where tubulin subunits are lost from kinetochore-attached plus ends and the kinetochore appears to consume its microtubule track as it moves poleward. In addition, kinetochore-fiber disassembly in many cells occurs partly through ‘flux’, where the microtubules flow continuously toward the poles and tubulin subunits are lost from minus ends. Molecular mechanistic models for how load-bearing attachments are maintained to disassembling microtubule ends, and how the forces are generated to drive pac-man and flux-based movements, are discussed.

Papillomaviruses (PVs) are oncogenic and infect the skin and mucosa of various host species. Considering the recent advances in research on PVs using rolling circle amplification (RCA) followed by high-throughput sequencing (HTS), in this study, we aimed to investigate the bovine papillomavirus (BPV) types associated with proliferative lesions in the upper alimentary tract of an affected bull and characterize the viral strains through complete genome sequencing using this strategy. We analyzed the PV strains associated with two hyperplastic esophageal lesions through PCR using degenerate primer pairs and RCA, followed by HTS. HTS of the libraries generated using RCA products provided the whole genome sequence of BPV4 present in squamous papilloma, whereas, the complete genome sequence of BPV2 and subgenomic fragments of BPV4 were identified in carcinoma in situ (CIS). We, for the first time, have sequenced BPV2 identified from the CIS of the bovine upper alimentary canal. Additionally, RCA followed by HTS allowed characterization of the mixed infection by BPV2 and BPV4 in this lesion. These data reveal that BPV4 is not the only BPV type present in CIS of the esophageal mucous membrane; moreover, a mixed infection caused by BPV2 and BPV4 at the tested anatomical site was demonstrated.

Semi-autonomous vehicles (AVs) enable drivers to engage in non-driving tasks but require them to be ready to take control during critical situations. This "out-of-the-loop" problem demands a quick transition to active information processing, raising safety concerns and anxiety. Multimodal signals in AVs aim to deliver take-over requests and facilitate driver-vehicle cooperation. However, the effectiveness of auditory, visual, or combined signals in improving situational awareness and reaction time for safe maneuvering remains unclear. This study investigates how signal modalities affect driver’s behavior using virtual reality (VR). We measured drivers’ reaction times from signal onset to take-over response and gaze dwell time for situational awareness across twelve critical events. Furthermore, we assessed self-reported anxiety and trust levels using the Autonomous Vehicle Acceptance Model questionnaire. Results showed visual signals significantly reduced reaction times, whereas auditory signals did not. Additionally, any warning signal, together with seeing driving hazards, increased successful maneuvering. Analysis of gaze dwell time on driving hazards revealed that audio and visual signals improved situational awareness. Lastly, warning signals reduced anxiety and increased trust. These results highlight the distinct effectiveness of signal modalities in improving driver reaction times, situational awareness, and perceived safety, mitigating the “out-of-the-loop” problem and fostering human-vehicle cooperation.

This study investigates the potential of a hybrid nanofluid composed of MoS2 and ZnO nanoparticles dispersed in engine oil, aiming to enhance the properties of lubricant's chemical reaction with the Soret effect on stretching sheet under the influence of applied magnetic field. With the growing demand for efficient lubrication systems in various industrial applications, including automotive engines, the development of novel nanofluid-based lubricants presents a promising avenue for improving engine performance and longevity. However, the synergistic effects of hybrid nanoparticles in engine oil remain relatively unexplored. This research addresses this gap by examining the thermal conductivity, viscosity, and wear resistance of the hybrid nanofluid, shedding light on its potential as an advanced lubrication solution. By analyzing the dispersion stability and interaction mechanisms between nanoparticles and base oil, valuable insights are gained into the fundamental aspects governing the entertainment of hybrid nano lubricants. Overall, the objectives of studying hybrid nano lubricant MoS2+ZnO with engine oil aim to advance the development of more efficient and durable lubrication solutions for automotive engines, contributing to improved reliability, fuel efficiency, and environmental sustainability. Governing non-linear partial differential equations are simplified as ordinary differential equations by utilizing similarity variables. MATLAB Bvp4c technique is used to solve the obtained linear ODE equations. The outputs are presented through graphs and tables for various state variables. The comparative survey in all the graphs is presented for the nanofluid (MoS2/Engine oil) with the hybrid nanofluid (MoS2+ZnO/Engine oil). These graphs show the effect of various parameters M, Q, β, Pr, Ec, Sc, Sr, Kp, Kr and (hybrid nano lubricant parameter). The velocity profile diminished against the values of M, Kp, and β. Temperature profile rising with Ec and Q. reciprocally goes down to Pr. The concentration profile incremented with the value of Sr and decremented with the value of Sc, and Kr. With the increasing value of both f′ (η) and θ(η) increases. But in θ(η) hybrid nanofluid slows down with the higher value of .

Sphingosine 1-phosphate (S1P) is a signaling lipid molecule involved in various cellular processes. It is important to develop a quantitative method for S1P to determine endogenous levels and to investigate its functions. Especially since S1P is a tiny lipid component of most biological samples, highly sensitive analysis by LC-MS/MS is required. The main challenge in S1P analysis by chromatography is peak broadening due to the presence of a polar phosphate and zwitterion formation in S1P. In this study, we used hydrogen fluoride (HF) to efficiently remove a phosphate and then analyzed the surrogate, sphingosine, as a sharp peak by LC-ESI-MS/MS. We optimized the dephosphorylation reaction in terms of reaction time, temperature, and HF concentration. Multiple reaction monitoring (MRM) for dephosphorylated form of S1P and C17-S1P as internal standard at m/z transition 300.4>282.4 (quantification ion), 300.4>262.4 (qualification ion), 286.3>268.2 (internal standard). This method was validated by essential parameters such as specificity, linearity, range, LOQ, LOD, accuracy, precision, and repeatability. To confirm this new method, we quantified S1P levels in various serum products (100.02 ~ 284.38 nM). To apply the method in vivo, we analyzed S1P in plasma and kidney tissues obtained from a chronic kidney disease (CKD) mouse model. S1P levels were increased only in CKD kidney tissue but not in plasma. In conclusion, by applying the dephosphorylation step with HF, we established a new sensitive LC-MS/MS quantitative method for S1P that can be applied to biological samples.

A unique method for synthesizing a surface modifier for metallic hydrogen permeable mem-branes based on non-classic bimetallic pentagonally structured Pd-Pt nanoparticles has been de-veloped. It was found that nanoparticles had unique hollow structure. This significantly reduces the cost of their production due to economical use of metal. According to the results of electro-chemical studies, synthesized bimetallic Pd-Pt/Pd-Ag modifier showed excellent catalytic activi-ty (up to 60.72 mA cm–2), long-term stability and resistance to COads poisoning in alkaline oxida-tion reaction of methanol. The membrane with pentagonally structured Pd-Pt/Pd-Ag modifier showed the highest hydrogen permeation flux density up to 27.3 mmol s–1 m–2. Obtained hy-drogen flux density were 2 times higher than that for membranes with classic Pdblack/Pd-Ag modifier and an order of magnitude higher than that for unmodified membrane. Since the rate of transcrystalline hydrogen transfer through a membrane increased, while the speed of transfer through defects remained unchanged, a one and a half times rise in selectivity of the developed Pd-Pt/Pd-Ag membranes was recorded and it amounted to 3514. Achieved results are due to both the synergistic effect of the combination of Pd and Pt metals in the modifier composition and the large number of available catalytically active centers, which are present as a result of non-classic morphology with high-index facets. The specific faceting, defect structure and unusual properties provide great opportunities for the application of nanoparticles in the areas of membrane reac-tors, electrocatalysis, petrochemical and hydrogen industries.

Na⁺/H⁺ exchangers (NHEs) are known to be important regulators of pH in multiple intracellular compartments of eukaryotic cells. Sperm function is especially dependent on changes in pH and thus it has been postulated that NHEs play important roles in regulating the intracellular pH of these cells. For example, in order to achieve fertilization, mature sperm must maintain a basal pH in the male reproductive tract and then alkalize in response to specific signals in the female reproductive tract during the capacitation process. Eight NHE isoforms are expressed in mammalian testis/sperm: NHE1, NHE3, NHE5, NHE8, NHA1, NHA2, NHE10, and NHE11. These NHE isoforms are expressed at varying times during spermatogenesis and localize to different subcellular structures in developing and mature sperm where they contribute to multiple aspects of sperm physiology and male fertility including proper sperm development/morphogenesis, motility, capacitation, and the acrosome reaction. Previous work has provided evidence for NHE3, NHE8, NHA1, NHA2, and NHE10 being critical for male fertility in mice and NHE10 has recently been shown to be essential for male fertility in humans. In this article we review what is known about each NHE isoform expressed in mammalian sperm and discuss the physiological significance of each NHE isoform with respect to male fertility.

Transition metal alloys have emerged as promising electrocatalysts due to their ability to modulate key parameters such as d-band electron filling, Fermi level energy, and interatomic spacing, thereby influencing their affinity towards reaction intermediates. However, the structural stability of alloy electrocatalysts during alkaline hydrogen evolution reaction (HER) remains a subject of debate. In this study, we systematically investigate the structural evolution and catalytic activity of the c-Co/Co3Mo electrocatalyst under alkaline HER conditions. We reveal that the instability of the Co3Mo alloy and H0.9MoO3 during alkaline HER leads to the destruction of the crystal structure, resulting in the formation of hexagonal cobalt (h-Co) from hexagonal Co(OH)2 as an intermediate species. Furthermore, we explore the re-adsorption and surface coordination of the Mo element, which enhances the catalytic activity for alkaline HER. This work provides valuable insights into the dynamic behavior of alloy-based electrocatalysts, shedding light on their structural stability and catalytic activity during electrochemical reduction processes

Proteins in biological systems function at the interface of single molecule and bulk chemistry and thus provide novel insights into the basic physical chemistry of scaling and emergent phenomena. For example, a binary mechanical model based on the chemistry of muscle contraction unifies molecular mechanics and thermodynamics and provides an explicit solution to the Gibbs paradox. Using the same model system, here I show that chemical activities of molecular states have no effect on chemical kinetics or energetics. Specifically, while the concentration or number of molecules in a molecular state is widely thought to contribute to reaction free energies, here I show that it is not the physical presence of molecules that pushes a reaction forward but the number of microstates, , accessible in a chemical state that pulls a reaction toward equilibrium with an entropic force down an entropic funnel. With the derivation of an entropic contribution to chemical kinetics, I develop a novel chemical kinetic formulation that fully describes the chemical thermodynamics of both equilibrium and non-equilibrium reactions in terms of an a priori system reaction energy landscape.

In this work, the influence of catalyst reuse and reaction time on the yield and quality of organic liquid products (OLP) obtained in a cracking pilot plant at 450 °C and 1.0 atm has been systematically investigated. The distillation of OLP produced 04 (four) distilled fractions. The quality of the biofuels was certified by physical-chemical analysis, as well as FT-IR and GC-MS analysis. The experimental results showed the feasibility of applying the spent sodium carbonate twice in catalytic cracking of vegetable oils. The physical-chemical properties (density, viscosity, acid value, saponification value, and flash point) of OLP decrease as the reaction time increases. The distillation of OLP yields 62.35% (wt.), producing green-like gasoline, kerosene, and diesel fractions rich in hydrocarbons. Therefore, biofuels-like fractions produced by distillation of OLP have a great potential for replacing partially petroleum derived fuels.

Leaf mechanical wounding triggers a rapid, within minutes, release of a blend of volatile organic compounds (VOCs). Wounding-induced VOC blend is mainly composed of oxygenated ubiquitous stress volatiles such as methanol and volatile products of lipoxygenase (LOX) pathway (mainly C5 and C6 alcohols and aldehydes and their derivatives), but also includes multiple minor VOCs that collectively act as infochemicals inducing defences in non-damaged plant leaves, neighbouring plants and attracting herbivore enemies. Till present, interspecific variability of the rate of induction and magnitude of wounding-induced emissions, and the extent to which plant structural traits and physiological activity alter these emissions are poorly known. Particularly scarce is the information of the induced emissions in tropical agricultural plant species despite their economic importance and large area of cultivation at regional to global scales. We chose five tropical crops with varying photosynthetic activity and leaf structural characteristics: Abelmoschus esculentus, Amaranthus cruentus, Amaranthus hybridus, Solanum aethiopicum and Telfairia occidentalis to characterize the kinetics and magnitude of wounding-induced emissions, hypothesizing that the induced emission response is greater and faster in physiologically more active species with greater photosynthetic activity than in less active species. Rapid highly repeatable leaf wounds (12-mm cuts) were generated by a within-leaf-chamber cutting knife. Wounding-induced VOC emissions were measured continuously with a proton-transfer reaction time-of-flight mass spectrometer and gas-chromatography mass spectrometry was used to separate isomers. Twenty-three ion VOCs and twelve terpenoid molecule structures were identified, whereas ubiquitous stress volatiles methanol (on average 40% of total emissions), hexenal (24%), and acetaldehyde (11%) were the main compounds across the species. Emissions of low-weight oxygenated compounds (LOC, 70% of total), and LOX products (29%) were positively correlated across species, but minor VOC components, monoterpenoids and benzenoids were negatively correlated with LOC and LOX, indicating a reverse relationship between signal specificity and strength. There was a large interspecific variability in the rate of induction and emission magnitude, but the hypothesis of a stronger emission response in physiologically more active species was only partly supported. In addition, the overall emission levels were somewhat lower with different emission blend compared to the data reported for wild species, as well as different shares for the VOCs in the blend. The study demonstrates that wounding-dependent emissions from tropical agricultural crops can significantly contribute to atmospheric volatiles, and these emissions cannot be predicted based on current evidence of wild plant model systems.

Biphasic bone substitutes (BBS) are nowadays established biomaterials. Through their constant development even natural components like hyaluronic acid (HY) are added to improve both their handling and also their regenerative properties. However, low knowledge exists regarding the consequences of the HY addition for their biocompatibility and the inflammatory tissue reactions. Thus, the present study was conducted aiming to analyze the influence of two different amounts of high molecular weight HY (HMWHY) combined with a BBS on the in vitro biocompatibility and the in vivo tissue reaction. Established in vitro procedures using L929 cells were used for cytocompatibility analyses under the test conditions of DIN EN:ISO 10993-5. For the in vivo study part, calvarial defects were created in 20 Wistar rats and subsequently filled with the BBS and the BBS combined with two different HMWHY amounts, i.e., BBS+HY(L) and BBS+HY(H). As controls empty defects were used. Established histological, immunohistochemical and histomorphometrical methods were applied to analyze the tissue reactions to the three different materials, including the induction of pro- and anti-inflammatory macrophages and multinucleated giant cells (BMGCs). The in vitro results showed that none of the materials or compositions caused biological damages to the L929 cells and can considered to be non-toxic. The in vivo results showed that only the addition of high doses of HY to a biphasic bone substitute significantly decreases the occurrence of proinflammatory macrophages (* p < 0.05) comparable to the numbers found in the control group, while no significant differences within the three study groups for M2-macrophages nor BMGCs were detected. In conclusion, the addition of different amounts of HMWHY does not seem to affect the inflammation response to the BBS while improving the material handling properties.

Mixing is considered as a critical process parameter (CPP) during process development due to its significant influence on reaction selectivity and process safety. Nevertheless, mixing issues are difficult to identify and solve owing to their complexity and dependence on knowledge of kinetics and hydrodynamics. In this paper, we proposed an optimization methodology using Computational Fluid Dynamics (CFD) based compartmental modelling to improve mixing and reaction selectivity. More importantly, we have demonstrated that through the implementation of surrogate-based optimization, the proposed methodology can be used as a computationally non-intensive way for rapid process development of reaction unit operations. For illustration purpose, reaction selectivity of a process with Bourne competitive reaction network is discussed. Results demonstrate that we can improve reaction selectivity by dynamically controlling rates and locations of feeding in the reactor. The proposed methodology incorporates mechanistic understanding of the reaction kinetics together with an efficient optimization algorithm to determine the optimal process operation and thus can serve as a tool for quality-by-design (QbD) during product development stage.

The mobile payment has been emerging as an alternative to cash and credit cards and is rapidly evolving around the world. This study integrated the general model of innovation diffusion theory (IDT) with the technology acceptance model (TAM) to examine the impact of near-field-communication (NFC) mobile payment environment on the restaurant operating performance (ROP). This paper used convenience sampling to distribute questionnaires to restaurant owners and managers in order to investigate the impact of NFC mobile payment environment on ROP. A total of 279 valid questionnaires were collected. The empirical results show that sales growth, cost saving, flexibility, accessibility and trust &amp; safety had significantly positive impacts on ROP. After considering the restaurant size as a moderator for analysis, there are only two constructs- accessibility and trust &amp; safety had significant impacts on ROP. This empirical finding could provide restaurateurs with a reference to improve ROP by increasing the mobile payment environment.

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

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

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

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

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

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

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

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

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

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

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

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

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

Degenerative spinal cord (SC) compression is a frequent pathological condition with increasing prevalence throughout aging. Initial non-myelopathic cervical SC compression (NMDC) might progress over time into potentially irreversible degenerative cervical myelopathy (DCM). While quantitative MRI (qMRI) techniques demonstrated the ability to depict intrinsic tissue properties, longitudinal in-vivo biomarkers to identify NMDC patients who will eventually develop DCM are still missing. Thus, we aim to review the ability of qMRI techniques (such as diffusion MRI, diffusion tensor imaging (DTI), magnetization transfer (MT) imaging, magnetic resonance spec-troscopy (1H-MRS)) to serve as prognostic markers in NMDC. While DTI in NMDC patients con-sistently detected lower fractional anisotropy and higher mean diffusivity at compressed levels caused by demyelination and axonal injury, MT and 1H-MRS along with advanced and tract-specific diffusion MRI recently revealed microstructural alterations also rostrally pointing to Wallerian degeneration. Recent studies also disclosed significant relationship between micro-structural damage and functional deficits, assessed by qMRI and electrophysiology, respectively. Thus, tract-specific qMRI in combination with electrophysiology critically extend our under-standing of the underlying pathophysiology of degenerative SC compression and may provide predictive markers of DCM development for accurate patient management. However, the prog-nostic value must be validated in longitudinal studies.

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

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

To mitigate the spread of the COVID-19 coronavirus, some countries have enforced more stringent non-pharmaceutical interventions in contrast to those widely adopted (for e.g. the state of Kuwait). In addition to standard practices such as enforcing curfews, social distancing, and closure of non-essential service industries, other non-conventional policies such as the total confinement of highly populated areas has also been implemented. In this paper, we model the movement of a host population using a mechanistic approach based on random walks, which are either diffusive or super-diffusive. Infections are realised through a contact process, whereby a susceptible host may be infected if in close spatial proximity of the infectious host. Our focus is only on the short-time scale prior to the infectious period, so that no further transmission is assumed. We find that the level of infection depends heavily on the population dynamics, and increases in the case of slow population diffusion, but remains stable for a high or super-diffusive population. Also, we find that the confinement of homogeneous or overcrowded sub-populations has minimal impact in the short term. Finally, we discuss the possible implications of our findings for total confinement in the context of the current situation in Kuwait.

The COVID-19 infections in Pakistan are spreading at an exponential rate and a point may soon be reached where rigorous prevention measures would need to be adopted. Mathematical models can help define the scale of an epidemic and the rate at which an infection can spread in a community. I used ARIMA Model, Diffusion Model, SIRD Model and Prophet Model to forecast the magnitude of the COVID-19 pandemic in Pakistan and compared the numbers with the reported cases on the national database. Results depicts that Pakistan could hit peak number of infectious cases between June 2020 and July, 2020.

Master equations define the dynamics that govern the time evolution of various physical processes on lattices. In the continuum limit, master equations lead to Fokker-Planck partial differential equations that represent the dynamics of physical systems in continuous spaces. Over the last few decades, nonlinear Fokker-Planck equations have become very popular in condensed matter physics and in statistical physics. Numerical solutions of these equations require the use of discretization schemes. However, the discrete evolution equation obtained by the discretization of a Fokker-Planck partial differential equation depends on the specific discretization scheme. In general, the discretized form is different from the master equation that has generated the respective Fokker-Planck equation in the continuum limit. Therefore, the knowledge of the master equation associated with a given Fokker-Planck equation is extremely important for the correct numerical integration of the latter, since it provides a unique, physically motivated discretization scheme. This paper shows that the Kinetic Interaction Principle (KIP) that governs the particle kinetics of many body systems, introduced in [G. Kaniadakis, Physica A 296, 405 (2001)], univocally defines a very simple master equation that in the continuum limit yields the nonlinear Fokker-Planck equation in its most general form.

Aiming at the industrial scale development of a Scandium (Sc)-selective leaching process of Bauxite Residue (BR), a sufficiently numerous set of process design aspects has been investigated, by appropriate exploitation of available experimental data. The interpretation of experimental data for Sc leaching yield, with sulfuric acid as the leaching solvent, has shown significant impact from acid feed concentration, mixing residence time, liquid to solids ratio, and times of leachate re-usage onto fresh BR. The thin film diffusion model, as the fundamental theory for leaching, either with constant particle size for selective leaching, or with shrinking particle size for less-, or non-, selective leaching, interprets sufficiently well the relevant experimental data. In both cases, a concept for an unyielding core supplements the basic model. Especially for the selective leaching mild conditions, the simplest model version keeps step with the experiments, since both prove 1^st order kinetics, while especially for the extreme conditions including very low solvent excess, it is proposed a combined conversion rate model with diffusion and chemical reaction inside particles. The maximization of Sc recovery per unit of consumed solvent (i.e., specific recovery) emerged as highly critical for the process economics.

In this paper we present the measurement of charged pion two-particle femtoscopic correlation functions in $\sqrt{S_{NN}}$= 200 GeV Au+Au collisions, in 31 average transverse mass bins, separately for positive and negative pion pairs. Lévy-shaped source distributions yield a statistically acceptable description of the measured correlation functions, with three physical parameters: correlation strength parameter λ , Lévy index α and Lévy scale parameter R. The transverse mass dependence of these Lévy parameters is then investigated. Their physical interpretation is also discussed, and the appearance of a new scaling variable is observed.

There are many features of homeostasis worth investigating such as how it works (information pathways, set point processing), where its command and control processors are located in the cell, the language used and how homeostasis interacts with all aspects of an organism's functional maintenance and development. All are necessary and valid inquiries, but this paper examines the implications of ignoring it as a factor of disease causation. Alternatively when properly understood the homeostasis profile becomes a rational explanation for any individual’s range of health; where some areas are very resistant to disease (resilient) and other areas of homeostasis are dysfunctional leading to minor, moderate or very susceptible tendencies to disease (lack of resilience in homeostasis). An understanding of this phenomenon, its interactions with gene expression (epigenetics) is necessary in order to evaluate the solutions for acute and chronic diseases. By this method diseases can be defined more precisely as specific susceptibilities in homeostasis, leading to a method to restore specific homeostasis functions.

A 70-year-old female with a significant medical history of hypertension, hypothyroidism, chronic back pain, and a left hip prosthetic joint infection experienced complications following a total hip replacement. After multiple revisions and eventual discharge to a rehabilitation facility, she developed surgical site bleeding and a femoral head dislocation extending into the pelvis. At our hospital, imaging revealed a failed hip arthroplasty with extensive damage and infection, necessitating complex revision surgery and an antibiotic regimen. During her treatment, she developed a diffuse rash diagnosed as vancomycin-induced hypersensitivity reaction (DRESS), prompting a switch to oral linezolid and systemic corticosteroids. Despite transient eosinophilia and elevated inflammatory markers, her condition stabilized, and she was discharged with instructions for follow-up. This case underscores the importance of vigilant monitoring and timely intervention in managing complex postoperative infections and drug reactions.

In this research work the study of Buongiorno Model Darcy Forchheimer flow of Hybrid nanofluid flow on isothermal permeable stretch/shrink sheet with homogeneous and heterogeneous reaction is investigated. The effects of MHD, thermal radiation, viscous dissipation, Joule heating, and heat generation/absorption are taken into account. Hybrid nanofluids can act as a medium for heterogeneous-homogeneous reactions. The nanoparticles dispersed in the fluid can influence reaction kinetics and species transport, potentially, altering reaction rates and pathways. The applications of HNF in reactions, both homogeneous and heterogeneous, lie in leveraging their enhanced thermal properties, catalytic potential, and improved mixing capabilities to optimize reaction efficiency and control reaction conditions. Similarity transformation is used to convert a set of PDEs into a set of ODEs. HAM is used for the solution of the obtained ODEs system. In a heterogeneous reaction, the concentration gradient is amplified; in a homogeneous reaction, the impact is opposite. Moreover, at higher compositions of HNPs, the concentration and velocity rise while the temperature falls. Furthermore, as the values of homogeneous and heterogeneous reactions increase, the concentration falls. It is reliable with the idea that a greater reaction rate lowers the diffusion rate. Nevertheless, these parameters do not affect temperature or velocity.

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), one of the components constituting jumps, through a biomechanical model-based approach enables analysis even in environments where force plates or machine learning training data cannot be utilized. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs) and estimated GRFs and body loads using a 3D forward dynamics model. Our estimation method, based on forward dynamics and optimization calculations, generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of the dynamic acceleration in the optimization calculation, the 3D orientation using sensor fusion composed of acceleration and angular velocity data obtained from IMUs and an extended Kalman filter was estimated. As a result, by generating movements based on the cost function, it was possible to calculate biomechanically valid GRFs while following the measured movements even if not all joints are covered by IMUs. This estimation method allows for 3D motion analysis independent of measurement conditions or training data.

The resistance of Candida spp to fluconazole is a serious problem; Therefore, it must be investigated to expand the understanding of the phenomenon with a view to its clinical applicability. The aim was to evaluate the expression of ERG3, ERG11, CDR1, and SNQ2 genes involving computational analysis. Relative expression was quantified by RT-qPCR. Metrics were obtained by molecular docking and through Fisher's discriminant functions, a predictive classification against susceptibility to fluconazole was performed. The expression of ERG3, CDR1, and SNQ2 genes was higher in resistant strains than in dose-dependent sensitive strains. The gene with the highest expression in strains exposed to fluconazole was CDR1 and, in both resistant and dose-dependent sensitive strains exposed to fluconazole, the ERG11 gene had lower expression. The molecular docking model generated lower median fluconazole-ERG11 contacts than the median fluconazole-ERG3, -CDR1, and -SNQ2 contacts. The predicted classification through the multivariate model for fluconazole sensitivity obtained an accuracy of 73.5%. Resistant strains had a significant expression of CDR1, SNQ2 and ERG3 genes, compared to a comparatively low expression of ERG11. Molecular analysis identified a low affinity between fluconazole and its drug target, which may explain a lower intrinsic susceptibility of the fungus.

The genetic diversity of coronavirus (CoV) is high, and its infection in animals has not yet been fully revealed. By RT-PCR detection of partial RNA dependent RNA polymerase (RdRp) gene of CoV, we screened a total of 502 small mammals belonging to 18 species in 12 genera and 4 orders collected in Dali and Nujiang Prefecture of Western Yunnan Province, China. The prevalence of β-CoV in Chevrieri's field mouse (Apodemus chevrieri) and Lancangjiang field mouse (A. ilex) were 3.54% (4/113) and 6.67% (6/90), respectively; the prevalence of α-CoV in White-footed Indochinese rat (Rattus nitidus) and long-tailed red-toothed shrew (Episoriculus leucops) was 75% (3/4) and 5.88% (1/17), respectively. The co-infection rates of β-CoV and α-CoV in Kachin red-backed vole (Eothenomys cachinus), Norway rat (R. norvegicus) were 2.22% (2/90), 3.85% (1/26) respectively. The identity of the partial RdRp genes obtained of 13 strains of β-CoV was 83.42%-99.23% at nucleotide level, and it is worth noting that the two strains from Kachin red-backed vole showed highly homology to BOV-36/IND/2015 from Indian bovine and DcCoV-HKU23 from one-humped camel (Camelus dromedarius) in Morocco, the nucleotide similarity between 97.86%-98.33%. Similarly, the identity of the 7 strains of α-CoV among the partial RdRp sequences was 94.00%-99.18% at nucleotide levels. The viral load in different tissues was measured by quantitative RT-PCR (qRT-PCR). The average CoV viral load in small mammalian intestinal tissue was 1.25×106copies/g, differently, the mean CoV viral load in liver, heart, lung, spleen and kidney tissue was from 1.29×103 to 4.02×103copies/g, which revealed that CoV has extensive tropism of intestinal tissue in small mammals (P &lt; 0.0001). This result revealed the genetic diversity, epidemiology, and infective tropism of α-CoV and β-CoV in small mammals from Dali and Nujiang, which deepens the comprehending of the retention and infection of coronavirus in natural hosts.

Personal Mobility Vehicle (PMV) which has an inward tilting angle turns with the lateral force due to large camber angle, so it is necessary to consider the lateral movement of the tire vertical load axis during turning. Although the steering torque mechanism are very different from those of automobiles, there are not many examples which studied the steering torque mechanism of PMV. In this paper, based on the effects of six components force acting on the tires, a method for setting the steering axis specifications is derived, including the geometrical minimization of steering moment disturbance due to the vertical load reaction force during turning. Although, automobile tires have a significant ground camber angle when traveling on rutted roads, they do not have it on slant roads because the vehicle body tilts along the road surface. On the other hand, in PMV, the vehicle body always keeps upright when traveling both on slanted roads and on rutted roads. Therefore, the tires have ground camber angles on both types of road surface. We study the straight running ability under such road surface disturbances based on the geometrical minimization of steering moment disturbance due to the vertical load reaction force during turning. This straight running ability can be a remarkable strong point of PMV with an inward tilt mechanism.

Li₂TiO₃ nanopowders were synthesized by hydrothermal process using anatase TiO₂ and LiOH H₂O as raw materials. Li₂TiO₃ crystallizes in the layered monoclinic structure (space group C2/c) with average crystallite size of 34 nm. Morphology, elemental composition and local structure of products were carried out using HRTEM, FESEM, EDS, Raman and FTIR spectroscopy. Transport properties investigated by d.c. (4-probe measurements) and a.c. (complex impedance spectroscopy) show the activation energy of 0.71 and 0.65 eV, respectively. The ionic transport properties of Li⁺ ions in nanocrystalline Li₂TiO₃ characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) validate the good electrochemical properties of this anode material for lithium-ion batteries.

The authors determined mass concentrations of 12 elements (As, Cd, Cr, Cu, Mn, Ni, Pb, Se, Sr, Tl, V, Zn) in blood and urine taken from 100 rural children living in unremarkable condition in the West Ural region of the Russian Federation. We applied inductively coupled plasma mass spectrometry in conformity with Methodical Guidelines 4.1. 3230-14 (FR.1.31.2014.17064) designed by us and detailed in the paper. The article contains setting parameters for Agilent 7500cx quadrupole inductively coupled plasma mass spectrometer . The authors present grounds for an optimal scheme of samples preparation which helps to eliminate "matrix" effect and explain why it is advisable to use reaction/collision functioning mode as it enables interference overlaps suppression.To prepare whole blood samples for analysis, we used acid dissolution in concentrated nitric acid followed by centrifugation. The arithmetic mean (AM) of element content in blood amounted to 0.34 µg/l (As); 0.39 µg/l (Cd); 6.41 µg/l (Cr); 866.11 µg/l (Сu); 13.73 µg/l (Mn); 5.86 µg/l (Ni); 23.65 µg/l (Pb); 87.43 µg/l (Se); 33.54 µg/l (Sr); 0.04 µg/l (Tl); 0.16 µg/l (V); 4713.48 µg/l (Zn). The validity of the results was confirmed by means of SERONORM ^TM Whole Blood L2 standard samples (Norway). Urine samples were directly analyzed after 1/10 (V/V) dilution with 1% nitric acid solution. The arithmetic mean of element content of urine corresponded to 18.99 µg/l (As); 0.12 µg/l (Cd); 1.91 µg/l (Cr); 13.28 µg/l (Сu); 0.96 µg/l (Mn); 1.84 µg/l (Ni); 0.83 µg/l (Pb); 22.55 µg/l (Se); 239.09 µg/l (Sr); 0.16 µg/l (Tl); 0.68 µg/l (V); 270.56 µg/l (Zn). The validity of the results was confirmed by analyzing the SERONORM ^TM standard urine samples (Norway). Regional differences from levels found in other countries included higher concentrations of Cr, Mn and Ni in blood and lower levels of Se and Zn levels in West Ural children. Urine concentrations of West Ural children showed higher levels of As and Sr.

Sputtered reactive multilayers applied as a heat source in electronic joining processes are an emerging technology. Their use promises low-stress assembly of components while improving the thermal contact and reducing the thermal resistance. Nanostructured surface modifications can significantly enhance adhesion and reliability of joints between different materials. This work examines reactive multilayer of nickel and aluminum, directly sputtered on nanostructured black silicon surfaces and compares their phase transformation with reference samples deposited on pristine silicon surface. The investigation of the quenched self-propagating reaction reveals a clear influence of the nanostructured surface on the prolongation of the phase transition. Rapid thermal annealing tests result in the formation of Al_1.1Ni_0.9 phase. The nanostructured interface seems to hinder the full transformation of the parent material. The surface modification improves the adhesion of the formed alloy on silicon surfaces and can possibly increase the reliability of joints based on reactive aluminum/nickel multilayer. The use of black silicon, a nanostructured surface modification, is thus a promising approach to realize reliable multi-material joints in complex systems.

The purpose of this study was to evaluate the bioactivity and cell response of a well-characterized Nurse´s A-phase (7CaO•P2O5•2SiO2) ceramic and his effect compared to a control (tissue culture polystyrene-TCPS) on the adhesion, viability, proliferation and osteogenic differentiation of ahMSCs in vitro. Cell proliferation (Alamar Blue Assay), Alizarin Red-S (AR-s) staining, alkaline phosphatase (ALP) activity, osteocalcin (OCN) and collagen I (Col I) were evaluated. Also, field emission scanning electron microscopy (FESEM) images were acquired in order to visualise the cells and the topography of the material. The proliferation of cells growing in a direct contact with the material was slower at early stages of the study because of the new environmental conditions. However, the entire surface was colonized after 28 days of culture in growth medium (GM). Osteoblastic differentiation markers were significantly enhanced in cells growing on Nurse´s A phase ceramic and cultured with osteogenic medium (OM), probably due to the role of silica to stimulate the differentiation of ahMSCs. Moreover, calcium nodules were formed under the influence of ceramic material. Therefore, it is predicted that Nurse´s A-phase ceramic would present high biocompatibility and osteoinductive properties being a good candidate to be used as a biomaterial for bone tissue engineering.

The radiation-induced optical absorption at 1.5-5.5 eV (up to the beginning of fundamental absorption) has been analyzed in CVD diamond disks exposed to 231-MeV 132Xe ions with four fluences from 1012 to 3.81013 cm-2. The 5-mm diameter samples (thickness 0.4 mm) were prepared by Diamond Materials, Freiburg (Germany), average grain size at growth site was around 80 m, the range of xenon ions was R= 11.5 m. The intensity of several bands grows with ion fluence thus confirming radiation-induced origin of the defects responsible for these bands. The recovery of radiation damage has been investigated via isochronal (stepwise) thermal annealing procedure up to 650°C, while all spectra were measured at room temperature. Based on these spectra, the annealing kinetics of several defects, in particular carbon vacancies (GR1 centers with a broad band 2 eV) and complementary C-interstitial-related defects ( 4 eV), as well as vacancies located nearby nitrogen substitutional atoms (narrow bands around 2.5 eV) have been constructed. The experimental kinetics have also been analyzed in terms of the diffusion-controlled bimolecular reactions. The migration energies of tentatively interstitial atoms (mobile components in recombination process) are obtained, their dependence on the irradiation fluences is discussed.

Globalized in 1995 through the TRIPs Agreement, humanity’s dominant mechanism for encouraging innovations involves 20-year product patents, whose monopoly features enable innovators to reap large markups or licensing fees from early users. Exclusive reliance on this reward mechanism in the pharmaceutical sector is morally problematic for two main reasons. First, it imposes a great burden on poor people who cannot afford to buy patented treatments at monopoly prices and whose specific health problems are therefore neglected by pharmacological research. Second, it discourages pharmaceutical firms from fighting diseases at the population level with the aim of slashing their incidence. These problems can be much alleviated by establishing a supplementary alternative reward mechanism that would enable pharmaceutical innovators to exchange their monopoly privileges on a patented product for impact rewards based on the actual health gains achieved with this product. Such an international Health Impact Fund (HIF) would create powerful new incentives to develop remedies against diseases concentrated among the poor, rapidly to provide such remedies with ample care at very low prices, and to deploy them strategically to contain, suppress, and ideally to eradicate the target disease. By promoting innovations and their diffusion together, the HIF would greatly enlarge the benefits, and thereby also the cost-effectiveness, of the pharmaceutical sector, in favor of the world’s poor especially.

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

The theory of heavy ion double charge exchange (DCE) reactions proceeding by effective rank–2 isotensor interactions is presented. Virtual pion–nucleon charge exchange interactions are investigated as the source for induced isotensor interactions, giving rise to the Majorana DCE (MDCE) reaction mechanism. MDCE is of a generic character, proceeding through pairs of complementary (π±,π∓) reactions in the projectile and target nucleus. The dynamics of the elementary processes is discussed where the excitation of pion–nucleon resonances are of central importance. Investigations of initial and final state ion–ion interactions show that these effects are acting as vertex renormalizations. In closure approximation, well justified by the finite pion mass, the second order transition matrix elements reduce to pion potentials and effective two–body isotensor DCE interactions, giving rise also to two–body correlations in either of the participating nuclei. Connections to neutrinoless Majorana double beta decay (MDBD) are elucidated at various levels of dynamics, from the underlying fundamental electro–weak and QCD scales to the physical scales of nuclear MDBD and MDCE physics. It is pointed out that heavy ion MDCE reactions may also proceed by competing electro–weak charge exchange processes, leading to lepton MDCE by electrons, positrons, and neutrinos.

This study aimed to evaluate the impact of Candida albicans on subgingival biofilm formation on dental implant surfaces. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) were used to compare biofilm structure and microbial biomass in the presence and absence of the fungus after periods of 24, 48, and 72 h. Quantitative polymerase chain reaction (qPCR) was used to quantify the number of viable and total micro-organisms for each of the biofilm-forming strains. A general linear model was applied to compare CLSM and qPCR results between control and test conditions. The biofilm developed with C. albicans at 72 h had a higher bacterial biomass, with a significantly higher cell viability (p &lt; 0.05). After both 48 and 72 h of incubation, in the presence of C. albicans, there was a significant increase in counts of Fusobacterium nucleatum and Porphyromonas gingivalis and in the cell viability of Streptococcus oralis, Aggregatibacter actinomycetemcomitans, F. nucleatum, and P. gingivalis. Using a dynamic in vitro multispecies biofilm model, C. albicans exacerbated the development of the biofilm grown on dental implant surfaces, significantly increasing the number and cell viability of periodontal bacteria.

This study aimed to compare procedural learning skills between Spanish-speaking preschool children (ages 4 years to 4 years, 11 months) with Developmental Language Disorder (DLD) and their typically developing (TD) peers. Using the Serial Reaction Time task, participants (30 DLD and 30 TD children) respond to visual stimuli in a sequenced manner over four blocks, followed by a random order block. The task assessed reaction time (RT) and accuracy. Results showed a significant interaction between group and block for reaction time (RT) and accuracy, with children with DLD exhibiting longer RTs and accuracy deficits across blocks. In contrast, the TD group showed higher RT efficiency and accuracy in the sequential blocks and as expected, decreased performance in the random block according to the experimental manipulation. Overall, the results of this investigation suggest that there was no implicit learning in the DLD group, as indicated by the SRT task paradigms of procedural memory. These findings align with the Procedural Deficit Hypothesis (PDH), suggesting that linguistic deficits in the TD population may derive from a general dysfunction of the procedural memory system domain in the Spanish context.

Powder mixture with given molar ratio Ca/P = 1.67 consisting of brushite (calcium hydrophosphate dihydrate) CaHPO4·2H2O, calcium oxalate monohydrate CaC2O4·H2O in form of whewellite and weddellite and some quantity of quasi-amorphous phase was obtained as a result of the interaction of hydroxyapatite powder Ca10(PO4)6(OH)2 with an aqueous solution of oxalic acid H2C2O4 at a molar ratio of Ca10(PO4)6(OH)2/H2C2O4 = 1:4 under mechanical activation conditions. This powder mixture was used to produce microporous monophase ceramics based on hydroxyapatite Ca10(PO4)6(OH)2 with aperient density of 1.25 g/cm3 after firing at 1200 oC. Microporosity of sintered ceramics was formed due to presence of particles with plate-like morphology, restraining shrinkage during sintering. Microporous ceramics based on hydroxyapatite Ca10(PO4)6(OH)2 with roughness of the surface as a consequence of the created microporosity can be recommended as a biocompatible material for the bone defects treatment and as a substrate for bone cell cultivation.

The construction of carbon-carbon bonds by direct involvement of two unactivated carbon-hydrogen bonds, without any directing group, ensures an high atom economy of the entire process. Here it is described a simple protocol for the Pd(II)/Cu(II)-promoted intermolecular cross-dehydrogenative coupling (CDC) of 5-arylimidazoles, benzimidazoles, benzoxazole and 4,5-diphenylimidazole at their C-2 position with functionalized styrenes. This specific CDC, known as Fujiwara-Moritani reaction or oxidative Heck coupling, allowed also the C-4 alkenylation of the imidazole nucleus when both 2 and 5 positions are occupied.

The activity and cyclability of Cu-MOF-74 as catalyst was studied for the ligand-free C-O cross-coupling reaction of 4-nitrobenzaldehyde (NB) with phenol (Ph) to form 4-formyldiphenyl ether (FDE). Cu-MOF-74 is characterized by unsaturated copper sites in a highly porous metal-organic framework. The influence of solvent, reaction temperature, NB/Ph ratio, catalyst concentration and basic agent (type and concentration) were evaluated. High conversions were achieved at 120°C, 5 mol% of catalyst, NB/Ph ratio of 1:2, DMF as solvent and 1 equivalent of K2CO3 base. The activity of Cu-MOF-74 material was higher than other ligand-free copper catalytic systems tested in this study. This catalyst was easily separated and reused in five successive runs, achieving a remarkable performance without significant porous framework degradation. The leaching of copper species in the reaction medium was negligible. The O-arylation between NB and Ph took place only in the presence of Cu-MOF-74 material, being negligible without the solid catalyst.

Electrolysis stands as a pivotal method for environmentally sustainable hydrogen production. However, the formation of gas bubbles during the electrolysis process poses significant challenges by impeding the electrochemical reactions, diminishing cell efficiency, and dramatically increasing energy consumption. Furthermore, the inherent difficulty in detecting these bubbles arises from the non-transparency of the wall of electrolysis cells. Additionally, these gas bubbles induce alterations in the conductivity of the electrolyte, leading to corresponding fluctuations in the magnetic flux density outside of the electrolysis cell, which can be measured by externally placed magnetic sensors. By solving the inverse problem of the Biot-Savart Law, we can estimate the conductivity distribution as well as the void fraction within the cell. In this work, we study different approaches to solve the inverse problem including Invertible Neural Networks (INNs) and Tikhonov regularization. Our experiments demonstrate that INNs are much more robust to solving the inverse problem than Tikhonov regularization when the level of noise in the magnetic flux density measurements is not known or changes over space and time.

Acute encephalopathy with biphasic seizures and reduced diffusion (AESD) is characterized by biphasic seizures following febrile viral infections and delayed reduced diffusion of the cerebral white matter on magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) (bright tree appearance, BTA). However, hypoxic encephalopathy with biphasic seizures and AESD-mimicking imaging findings has not been reported. Herein, we report an case of hypoxic encephalopathy due to suffocation with concomitant biphasic seizures and BTA, mimicking AESD. On day 1, a 5-month-old female was found face down with breathing cessation and deteriorating consciousness level. The electroencephalography (EEG) revealed periodic epileptic discharges, suggesting possible nonconvulsive status epilepticus. Despite the improvements in consciousness level and EEG abnormalities on day 2, her consciousness level deteriorated again with generalized tonic-clonic seizures on day 3, and head MRI-DWI revealed restricted diffusion predominantly in the subcortical areas, suggesting BTA. Treatment for acute encephalopathy resolved clinical sei-zures and EEG abnormalities. The persistence of abnormal EEG, reflecting abnormal excitation and accumulation of neurotoxic substances caused by hypoxia, may have contributed to the devel-opment of AESD-like findings. As hypoxic encephalopathy causes AESD-like biphasic seizures, monitoring the consciousness level, seizure occurrence, and EEG abnormalities even after acute symptoms have temporarily improved following hypoxia is essential.

Urination on carpet and subflooring can develop into persistent and challenging to mitigate odor. Very little or no information is published on how these VOCs change over time when urine is deposited on the carpet covering a plywood-type subflooring. This research has investigated the VOCs emitted from carpet+subflooring (control), carpet+subflooring sprayed with water (control with moisture), and cat urine-contaminated carpet+subflooring (treatment) over time (day 0 and 15). In addition, the effect of popular cleaning products on VOCs emitted and evaluated their efficacy in eliminating those indoor odors over time (day 0 and 15). Carpet-subflooring with all treatments were also contaminated with Micrococcus luteus, nonmotile obligate aerobe commonly found in household dust, to observe the impact of the aerobe on carpet-subflooring VOCs emission. VOCs emitted from carpet+subflooring receiving different treatments were collected from headspace using solid-phase microextraction (SPME). The VOCs were analyzed using a multidimensional gas chromatography-mass spectrometer attached to an olfactometry (GC-MS-O). Many common VOCs were released from the carpet on day one and day fifteen, specifically from urine contamination. Cleaning products were effective in masking several potent odors of cat urine contaminated carpet VOCs on day one but unable to remove the odor appeared on day 15 in most cases.

The biophysical consequences of nanoscale curvature have been challenging to resolve due to size-dependent membrane behavior and the experimental resolution limits imposed by optical diffraction. Recent advances in nanoengineering and super-resolution techniques have enabled new capabilities for creating and observing curvature. In particular, draping supported lipid bilayers over lithographically patterned substrates provides a model system for endocytic pits. The experiments and simulations presented below describe the possible detection of membrane curvature through fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS), single particle tracking (SPT), and polarized localization microscopy (PLM). FRAP and FCS depend on diffraction-limited illumination and detection. In particular, a simulation of FRAP shows no effects on lipids diffusion due to a 50 nm diameter membrane bud at any stage in the budding process. Simulated FCS demonstrated small effects due to a 50 nm radius membrane bud that was amplified with curvature-dependent lipid mobility changes. However, PLM and SPT achieve sub-diffraction-limited resolution of membrane budding and lipid mobility through the identification of the single-lipid positions with ≤15 nm spatial and ≤20 ms temporal resolution. By mapping the single-lipid step lengths to locations on the membrane, the effects of curvature on lipid behavior have been resolved.

Severe acute respiratory infection (SARI) is mainly caused by viral pathogens, with a high prevalence in high-risk populations such as infants and older adults. Co-infections by different viruses are frequent and, in some cases, associated with severe disease outcomes. Purpose: The main purpose of this study was to identify respiratory viruses circulating in Barranquilla during the COVID-19 pandemic peaks and estimate the prevalence of viral co-infections in samples from individuals with different degrees of respiratory infection. Methods: Between August and October 2021, 101 samples were collected from individuals with influenza-like illness (ILI) by the District Health Laboratory of Barranquilla and four local health care institutions and analyzed at Universidad Simón Bolívar. Eighteen respiratory viruses, including SARS-CoV-2, were analyzed via qRT-PCR using nasal swabs or nasopharyngeal aspirate samples. Results: Of the 101 study individuals, 56 were male and 45 were female (55.5% and 44.5%, respectively); 25.7% of individuals were infected with at least one of the evaluated viruses. Respiratory syncytial virus (RSV) and human rhinovirus (HRV) were the two most frequently detected viruses (30.7% and 15.4% of total positives, respectively). Co-infections with two or more respiratory viruses accounted for 42% of the total positive cases. Conclusion: Our findings indicate the presence of different respiratory viruses in swab or nasopharyngeal aspirate samples from individuals with ILI, including coinfection. These results reveal the circulation of several respiratory viruses in the city of Barranquilla, confirming their importance as potential causes of SARI in Colombia and the need for their active surveillance.

Introduction Cochlear implants are a modern approach for the treatment of multiple cases of profound sensorineural hearing loss. Factors such as the ethiology of hearing loss and the potential for achieving good postoperative outcomes are considered in cochlear implantation. Additionally, surgical strategies, protocols, the experience of the surgeon and audiologist, and the presence of postoperative issues and risks that may require revision surgery should also be taken into account. The surgeon specialized in cochlear implantation must inform the patient and his relatives not only about the surgical technique but also about possible complications. The literature shows different rates of complications evaluated both in adults and in children. An evaluation of adverse events in order to prevent complications can be made if the definition of medical complications and mistakes is strictly approached based on the CLAVIEN-DINDO classification system. The rate of complications can be compared with existing literature. Studies demonstrate the need for preoperative vaccination for pneumococcus, which can prevent complications, especially in patients with inner ear malformations who present an increased postoperative risk Relevant Sections This review is structured around the collection of specialized literature from PubMed, organized into subchapters related to intraoperative complications such as Gusher syndrome, foreign body reaction, endocochlear inflammation phenomena, issues related to electrode positioning and associated complications, vestibular phenomena related to cochlear implantation, as well as late complications related to the surgical wound and cochlear implant extrusion. The important sections in this review are: Inner Ear Malformations and Gusher Syndrome: Intraoperative Complication Risks, Electrode Insertion and Positioning Issues, Intracochlear Inflammation, Foreign Body Reaction, and Intracochlear Fibrosis: Phenomena That Can Occur with Cochlear Implantation, Vestibular Disorders, Tardive Postoperative Complications: Wound Injuries and Cochlear Implant Extrusion and Otitis Media and Cholesteatoma as Complications of Cochlear Implantation Conclusions: Postoperative complications, although considered quite rare. The surgical limits and long-term evolution of cochlear implants cannot be concretely established, despite the fact that this intervention is considered safe in the medium and long term. Future directions Given that cochlear implants represent the most modern surgical technique for auditory rehabilitation in adults and children, with massive implications for quality of life, there is a tendency to extend surgical indications in the future, and especially to inform doctors in related specialties about the benefits of this medical device. Surgeons must be knowledgeable about cochlear implantation methods, as well as the methods for managing complications that can arise immediately postoperatively, as well as in the medium and long term.

A new mesogenic non-symmetric dimeric monomer with a terminal olefin function, forming a twist bend nematic (Ntb) as well as a nematic (N) phase was synthesized, using an enhanced synthetic methodology, which avoids isomerization of the terminal double bond in the preparation of the dimer. This monomer was attached to a pentamethyldisiloxane group, resulting in SmA LC phase behaviour of the ensuing material. Linking the monomer to a siloxane main chain resulted in nematic phase behaviour. Detailed studies with the Ntb phase forming dimer DTC5C7 show full miscibility of the dimer and the new LC polymer in the LC state, suggesting that the side-chain LC polymer forms a Ntb phase as the low temperature nematic phase. Copolymerizing the monomer with a cyanobiphenyl based monomer allows to tune the glass transition and phase behavior further.

We hereby describe an efficient method for the preparation of a series of new 1-substituted 1,2,3-triazole-based acetaminophen derivatives through a clean, good-yielding, simple, and expeditious procedure based on the O-propargylation reaction of the acetaminophen (APAP) obtained from expired commercial tablets and the CuBr(PPh3)3-catalyzed Huisgen reaction be-tween O-propargylated APAP and diverse organoazides prepared from commercially available anilines as available starting reagents. An interesting nitric oxide-releasing 1,2,3-triazole hybrid of APAP was also obtained easily using the developed method. The structures of the designed hybrid compounds, which are expected to be pharmacologically active, were fully characterized by FT-IR, 1H- and 13C-NMR and are reported for the first time. According to the in-silico studies performed in this work and literature analysis, these hybrids are interesting models in search of new pharmacological nontoxic agents endowed with anti-inflammatory and anticancer properties.

Quantitative polymerase chain reaction (qPCR) has emerged as an important bioanalytical method for assessing the pharmacokinetics of human cell-based medicinal products after xenotransplantation into immunodeficient mice. A particular challenge in bioanalytical qPCR studies is that the different tissues of the host organism can affect amplification efficiency and amplicon detection to varying degrees, and ignoring these matrix effects can easily cause a significant underestimation of the true number of target cells in a sample. Here we describe the development and drug regulatory-compliant validation of a TaqMan® qPCR assay for quantification of mesenchymal stromal cells in the range of 125 to 20,000 cells/200 µl lysate by amplification of a human-specific, highly repetitive αsatellite DNA sequence of the chromosome 17 centromere region HSSATA17. Assessment of matrix effects in 14 different mouse tissues and blood revealed a wide range of spike recovery rates across the different tissue types from 11 to 174%. Based on these observations, we propose to perform systematic spike-and-recovery experiments during assay validation and to correct for the effects of the different tissue matrices on cell quantification in subsequent bioanalytical studies by multiplying the back-calculated cell number by tissue-specific factors derived from the inverse of the validated percent recovery rate.

The simultaneous evaluation of heat/mass transference procures momentous significance in the polymer industry and engineering activities. Extensive utilization of such aspects includes propylene flares, heat exchangers, energy transfiguration in chilling towers, and amputation of post fortuitous heat in nuclear reactors. Owing to such prospective demands, we interpreted the Jeffrey liquid reactive flow under non-linear convection. We scrutinized the transference of heat/mass under generalized Fourier-Fick relations. Thermal conductivity depends on temperature while mass diffusivity is dependent on concentration. Besides, heat source along with first-order chemical reaction aspects are accounted for. Relevant transformations are exerted to achieve non-linear differential systems that are solved through the homotopy scheme. Influences of divers factors are exhibited via graphical benchmark.

Background: Infectious disease is a major challenge in aquaculture and poses a constraint for development of farming of new species. In 2017, Siberian sturgeon (Acipenser baerii) juveniles were imported from Italy to a Swedish farm. Due to stressful conditions, 30% died during transport and in the first days after arrival. Ten days after arrival, mortalities started to occur again. Within two months, only 5% of the juveniles were still alive. Methods: Diseased fish were transported live to the National Veterinary Institute (SVA) for necropsy and further analysis. Pathological and histopathological investigation was conducted. Virology was performed on gills and internal organs by cell culture isolation and specific PCR protocols. Results: The juveniles displayed neurological signs such as lethargy, inability to maintain upright position and erratic swimming. Body condition was low. Gills were pale. One fish had petechial hemorrhage on the abdomen and the snout. The ventricles were air-filled with, but swim bladders were deflated. One specimen had intestinal hemorrhage. Viral cell cultures were negative, but PCR of gills and internal organs detected the presence of Acipenser Iridovirus European (AcIV-E). Conclusions: AcIV-E was associated with disease and high mortality in the sturgeon juveniles. Stress probably aggravated the course of the infection.

Dam breaches have catastrophic consequences, causing severe property damage, life loss, and environmental impact. The Kulekhani reservoir rockfill dam break was studied to evaluate the downstream impact. The appropriate breaching parameter of MacDonald and Langridge (1984) regression equations was selected based on the sixteen observed dam failure cases and cross-sectional geometry of the existing dam of Kulekhani. The 2D Diffusion Wave and Full Dynamic Wave Equation were applied for downstream flood assessment, Full Dynamic Wave was able to capture the physical flow phenomena like river bend effects resulting in higher flow velocity at the outer bend, and formation of eddies considering losses. The application of a Full Dynamic Equation was found to be appropriate for rapidly varying unsteady flow considering steep slopes, and sudden changes in channel geometry. Flood mapping of water depth, flow velocity, flood intensity, and arrival time were carried out for flood hazard assessment classified by the American Society of Civil Engineers (ASCE). Flow depth and extension of the flow area were compared to identify the affected area, higher flow depth and larger extension were observed using a Full Dynamic Wave Equation as a result of less flow velocity considering the losses. Almost 17 minutes of the arrival time of peak difference at the Bagmati River confluence was evaluated between the models which plays an important role in decision-making for selection of the flood model. Flood mitigation with river diversion works through a hydraulic measure of Levee was suggested to protect the highly affected households of Ranche, Nagmar, Khanikhet, and Debaltar towns. Most of the household was found to be safe after the construction of the Levee except for eleven houses that lie along the river below flood elevation of 1269.6 m.a.s.l. This signifies the importance of room for the rivers and the human settlement near the river might be life-threatening.

Our investigations show that electrochemical corrosion of copper is faster than electrochemical corrosion of aluminium at temperatures below 100oC. Literature data analysis shows that the Al atoms diffuse faster than the Cu atoms at temperatures higher than 475oC, Al rich intermetallic compounds (IMCs) are formed faster in the Cu-Al system, and the Kirkendall plane shifts toward Al side. Electrochemical corrosion occurs due to electric current and due to diffusion. An electronic devise working time, for example, depends on initial copper cover thickness on aluminium wire, connected to the electronic devise, temperature, and volume and dislocation pipe diffusion coefficients, so copper, iron, and aluminium electrochemical corrosion rates are investigated experimentally at room temperature and at temperature 100oC. Intrinsic diffusivities ratios of copper and aluminium at different temperatures and diffusion activation energies in the Cu-Al system are calculated by proposed here methods using literature experimental data. Dislocation pipe and volume diffusion activation energies of pure iron are calculated separately by earlier proposed method using literature experimental data. Aluminium dissolved into NaCl solution as the Al3+ ions at room temperature and at temperature 100oC, iron dissolved into NaCl solution as the Fe2+ (not Fe3+) ions at room temperature and at temperature 100oC, copper dissolved into NaCl solution as the Cu+ ions at room temperature and as the Cu+ and the Cu2+ ions at temperature 100oC. It is founded experimentally that copper corrosion is higher than aluminium corrosion, and ratio of electrochemical corrosion rates, kCu/kAl>1, decreases with temperature increasing, although iron electrochemical corrosion rate doesn’t depend on temperature below 100oC. It is obvious, because melting point of iron is more higher then melting point of copper or aluminium. It is calculated that copper electrochemical corrosion rate is approximately equal to aluminium electrochemical corrosion at temperature about 300oC, so copper can dissolve into NaCl solution mostly as the Cu2+ ions at temperature about 300oC. Ratio of intrinsic diffusivities, DCu/DAl <1, increases with temperature increasing, and intrinsic diffusivity of aluminium could be approximately equal to intrinsic diffusivity of copper at temperature about 460oC.

Magnetic nanoparticles are met across many biological species ranging from magnetosensitive bacteria, fishes, bees, bats, rats, birds, to humans. They can be both of biogenetic origin and due to environmental contamination, being either in paramagnetic or ferromagnetic state. The energy of such naturally occurring single-domain magnetic nanoparticles can reach up to 10-20 room k_BT in the magnetic field of the Earth, which naturally led to supposition that they can serve as sensory elements in various animals. This work explores within a stochastic modeling framework a fascinating hypothesis of magnetosensitive ion channels with magnetic nanoparticles serving as sensory elements, especially, how realistic it is given a highly dissipative viscoelastic interior of living cells and typical sizes of nanoparticles possibly involved.

Modern organic synthesis is majorly focused on developing environmentally benign synthetic protocols by employing green chemistry principles. Accordingly, in our recent research work, we herein report the use of modified supramolecular host cyclodextrin as an effective solid based green catalyst for accessing structurally diverse and medicinally relevant pyrimidone architectures. The catalyst and the synthesized compounds 4 (a-r) were characterized using FT-IR, NMR and GC-Mass spectroscopy. Major highlights of the reported work include: atom economical process, extremely milder reaction conditions, operational simplicity, high isolated yields, and excellent catalyst turnover number. The molecular docking studies suggest that the compound 4n has the hydrogen bonding, hydrophobic and π-pair interactions with the active site of active sites of CXT M 15 receptor.

The role of initial state (ISI) and final state (FSI) ion–ion interactions in heavy ion double charge exchange (DCE) reactions A(Z,N)→A(Z±2,N∓2) are studied in the context of double single charge exchange (DSCE) reactions given by sequential actions of the isovector nucleon–nucleon (NN) T–matrix. The second order DSCE reaction amplitude is investigated in momentum representation in a formulation, focused on the extraction of nuclear matrix elements under the conditions of strong initial state (ISI) and final state (FSI) interactions. In closure approximation and using the momentum representation, the reaction amplitude is finally separated into ISI/FSI distortion coefficients and reaction kernels and nuclear matrix elements. The ISI/FSI reaction kernels emerge as the result of the repeated scattering on the avoided volume, introduced by the imaginary parts of the ion–ion optical potential and acting as sinks for the quantal probability current. The closure approximation allows derive a set of induced effective two–body isotensor interactions, given by products of spin–scalar, spin–vector central and rank–2 spin–tensor interactions. The intermediate propagator plays a key role in establishing correlation between the DCE transitions in the projectile and target nucleus. The presented approach emphasizes the special features of DSCE reaction dynamics as proceeding like a system of two coupled isospin dipoles whose strengths are determined by the momentum-space form factors of the NN isovector interaction. The properties of the DSCE interaction form factors are investigated and the approach is applied to data.

New [1,2]dithiolo[3,4-b]pyridine-5-carboxamides were synthesized through the reaction of dithiomalondianilide (N,N'-diphenyldithiomalondiamide) with 3-aryl-2-cyanoacrylamides or by a three-component reaction involving aromatic aldehydes, cyanoacetamide and dithiomalon- dianilide in the presence of morpholine. The structure of 6-amino-4-(2,4-dichlorophenyl)- 7-phenyl-3-(phenylimino)-4,7-dihydro-3H-[1,2]dithiolo[3,4-b]pyridine-5-carboxamide was con-firmed using X-ray crystallography. To understand the reaction mechanism in detail, density functional theory (DFT) calculations were performed with a Grimme B97-3c composite computa-tional scheme. The results revealed that the rate limiting step is a cyclization process leading to the closure of 1,4-dihydropyridine ring with an activation barrier of 28.8 kcal/mol. Some of dithiolo[3,4-b]pyridines exhibited moderate herbicide safening effects against 2,4-D . Additional-ly, ADMET parameters were calculated and molecular docking studies were performed to identify potential protein targets.