Two of the most common activation functions (AF) in deep neural networks (DNN) training are Sigmoid and ReLU. Sigmoid was tend to be more popular the previous decades, but it was suffering with the common vanishing gradient problems. ReLU has resolved these problems by using zero gradient and not tiny values for negative weights and the value “1” for all positives. Although it significant resolves the vanishing of the gradients, it poses new issues with dying neurons of the zero values. Recent approaches for improvements are in a similar direction by just proposing variations of the AF, such as Leaky ReLU (LReLU), while maintaining the solution within the same unresolved gradient problems. In this paper, the combining of the Sigmoid and ReLU in one single function is proposed, as a way to take the advantages of the two. The experimental results demonstrate that by using the ReLU’s gradient solution on positive weights, and Sigmoid’s gradient solution on negatives, has a significant improvement on performance of training Neural Networks on image classification of diseases such as COVID-19, text and tabular data classification tasks on five different datasets.

Infection of hosts by morbilliviruses is facilitated by the interaction between viral hemagglutinin (H-protein) and the signaling lymphocytic activation molecule (SLAM). Recently, the functional importance of the N-terminal region of human SLAM as a measles virus receptor was demonstrated. However, the functional roles of this region in the infection process by other morbilliviruses and host range determination remain unknown partly because this region is highly flexible, which has hampered accurate structure determination of this region by X-ray crystallography. In this study, we analyzed the interaction between the H-protein from canine distemper virus (CDV-H) and SLAMs by a computational chemistry approach. Molecular dynamics simulations and fragment molecular orbital analysis demonstrated that the unique His28 in the N-terminal region of SLAM from Macaca is a key determinant that enables formation of a stable interaction with CDV-H, providing a basis for CDV infection in Macaca. The computational chemistry approach presented should enable determination of molecular interactions involving regions of proteins that are difficult to predict from crystal structures because of their high flexibility.

The small satellite market continues to grow year after year. A compound annual growth rate of 17% is estimated during the period between 2020 and 2025. Low-cost satellites can send a vast amount of images to be post-processed at the ground to improve the quality and extract detailed information. In this domain lies the resolution enhancement task, where a low-resolution image is converted to a higher resolution automatically. Deep learning approaches to Super-Resolution (SR) reached the state-of-the-art in multiple benchmarks; however, most of them were studied in a single-frame fashion. With satellite imagery, multi-frame images can be obtained at different conditions giving the possibility to add more information per image and improve the final analysis. In this context, we developed and applied to the PROBA-V dataset of multi-frame satellite images a model that recently topped the European Space Agency’s Multi-frame Super Resolution (MFSR) competition. The model is based on proven methods that worked on 2D images tweaked to work on 3D: the Wide Activation Super Resolution (WDSR) family. We show that with a simple 3D CNN residual architecture with WDSR blocks and a frame permutation technique as data augmentation better scores can be achieved than with more complex models. Moreover, the model requires few hardware resources, both for training and evaluation, so it can be applied directly from a personal laptop.

Influence of particle size on the mechanical strength of alkali activated material from waste refractory monolithic was investigated in this study. Precursor was chemically and mineralogically analysed, separated on 4 fractions and alkali activated with Na-water glass. Alkali activated materials were thoroughly investigated under SEM and XRD to evaluate the not predicted differences in mechanical strength. Time dependence of curing temperature on mechanical strength was investigated in the sample prepared from a fraction that caused the highest compressive strength.

Normally, the Nernst voltage calculated from the concentration of the reaction gas in the flow channel is considered to be the ideal voltage (reversible voltage) of the oxyhydrogen fuel cell, but actually it will cause a concentration gradient when the reaction gas flows from the flow channel through the gas diffusion layer to the catalyst layer. The Nernst voltage loss in fuel cells in most of the current literature is thought to be due to the difference in concentration of reaction gas in the flow channel and concentration of reaction gas on the catalyst layer at the time when the high net current density is generated. Based on the Butler-Volmer equation in oxyhydrogen fuel cell, this paper demonstrates that the Nernst voltage loss is caused by the concentration difference of reaction gas in flow channel and on the catalytic layer at the time when equilibrium potential (Galvanic potential) of each electrode is generated.

The fixation and activation of the dinitrogen molecule, N2 by hexametallic clusters of the general formula {[(μ2-L)M)]6(μ-η1:η3-Ν2)}0/+6 (L = CH2-, NH2-, PH2-, OH-, SH-, BH2- and NH2-, M = Ru(II) or Os(II)) were scrutinized by means of density functional theory calculations. In these systems, the dinitrogen molecule, acts as a ligand that bridges the two opposite facing triangular metallic rings, cyclo-M3 of the {[(μ2-L)M)]6(μ-η1:η3-Ν2)}0/+6 clusters The hexametallic clusters, that mimick the six Fe cluster of nitrogenase, were found to strongly activate N2, converting it into a hydrazido-like group, N24-. This is substantiated by the calculated N-N bond lengths, Re(N-N) and the stretching frequencies of the N-N bond of dinitrogen, vs(N-N) found in the ranges 1.299 – 1.487 Å and 780 – 1270 cm-1 respectively. Based on the Re(N-N) and vs(N-N) values, the dinitrogen activation depends upon the nature of the hexametallic cluster. Accordingly, the Os(II) clusters were found to activate more strongly the dinitrogen molecule as compared to their Ru(II) counterparts. The nature of the ligand L also affects the extent of the N2 activation by the hexametallic clusters, which follows the order BH2- < NH2- < OH- < CH2- < NH2- < PH2-, SH- for M = Ru(II) and the order BH2- < NH2- < OH- < NH2- < CH2- < PH2- < SH- for M = Os(II). Thus, the strongest N2 activation is observed for the {[(μ2-SH)Os)]6(μ-η1:η3-Ν2)}+6 cluster and the weakest for the {[(μ2-BH)Ru)]6(μ-η1:η3-Ν2)}0 cluster. The calculated Nitrogen-15 NMR isotropic chemical shielding tensors, σiso(15N) exhibit shielding (upfield) upon N2 fixation to the metal centers of the hexametallic clusters, as a results of electron density transfer towards its constituent N nuclei. A multitude of electronic charge distribution partitioning schemes were applied to assist in delineating the bonding properties of the {[(μ2-L)M)]6(μ-η1:η3-Ν2)}0/+6 clusters. Accordingly, it is found that there is a donation/backdonation interaction between the bridging N2 ligand and the two opposing cyclo-M3 rings located on either side. The dinitrogen ligand forms six bonds of mixed covalent/electrostatic nature with the six metal centers of the {[(μ2-L)M)]6)}0/+6 clusters.

Support effect is an important issue in heterogeneous catalysis while the explicit role of a catalytic support is often unclear for catalytic reactions. A systematic density functional theory computational study is reported in this paper to elucidate the effect of a model boron nitride (BN) support on the first N-H bond activation step of NH3 on Run (n =1, 2, 3) metal clusters. Geometry optimizations and energy calculations were carried out using density functional theory (DFT) calculation for intermediates and transition state from the starting materials undergoing the N-H activation process. The primary findings are summarized as follows. The involvement of the model BN support does not significantly alter the equilibrium structure of intermediates and transition state in the most favorable pathway (MFP). Moreover, the involvement of BN support decreases the free energy of activation, ΔG≠, thus improving the reaction rate constant. This improvement is more obvious at high temperatures like 673 K than low temperatures like 298 K. The BN support effect leading to the ΔG≠ decrease is most significant for the single Ru atom case among all three cases studied. Finally, the involvement of model BN may change the spin transition behavior of the reaction system during the N-H bond activation process. All these findings provide a deeper insight into the support effect on the N-H bond activation of NH3 for supported Ru catalyst in particular and for supported transition metal catalysts in general.

Building deep learning models proposed by third parties can become a simple task when specialized libraries are used. However, a great deal of mystery still surrounds the design of new models or the modification of existing ones. These tasks require in-depth knowledge of the different components or building blocks as well as their dimensions. This information is limited and broken up in different literature. In this article, we collect and explain in-depth the building blocks to design deep learning models, starting from the artificial neuron to the concepts involved in building deep neural networks. Furthermore, the implementation of each building block is exemplified using the Keras library.

Introduction: The distribution of typical bacterial redox enzymes such as pyruvate-ferredoxin oxidoreductase (PFOR) in protozoa remains interestingly puzzling. Previous studies have demonstrated diverse cellular localizations of PFOR in amitochondriate anaerobic protozoa such as Trichomonas vaginalis. PFOR is of particular pharmacological importance because it catalyzes the reductive bio-activation of nitro-based prodrugs to cytotoxic radical metabolites. Metronidazole was developed primarily as an antiprotozoal agent against infections caused by T. vaginalis. However, its antimicrobial spectrum was subsequently expanded to cover anaerobic bacterial infections. It has been shown that mutations in the genes encoding PFOR result in inherent resistance of T. vaginalis and anaerobic bacteria to metronidazole. Aims: To analyze the phylogenetic distribution of PFOR in selected protozoa and bacteria using proteins encoded by housekeeping genes as controls. Using comparative bioinformatics to test the hypothesis that PFOR was most likely acquired through horizontal gene transfer from bacteria, proteome-wide analysis and gene expression analysis to identify other genes that were putatively acquired through horizontal gene transfer from bacteria to protozoa. Methods: Sequence similarity queries were performed using the proteins of interest against the NCBI non-redundant protein sequence database with BLASTP version 2.12.0+ from the NCBI website. Multiple sequence alignments were performed with MEGA version X software using the Muscle algorithm. These were then exported in Mega format to construct phylogenetic trees using the neighbor-joining algorithm and the Poisson substitution model. Complete proteomes of representative protozoan and bacterial species were downloaded in fasta format from the ensemblgenomes database. HMM profile libraries were used to screen the proteomes with hmmscan of the HMMer package. Whole proteome BLAST searches were performed between protozoan species of interest against closely related protozoa. The results were compared to the proteome BLAST against the intestinal bacteria Desulfovibrio vulgaris. Gene enrichment analysis was performed between the exclusively present proteins in the protozoa and D. vulgaris. Only results with p-values <0.05 were considered for analysis. Results and conclusions: A plausible explanation for the restricted occurrence of PFOR in protozoa is based on the hypothesis that bacteria serve as potential sources of genes that enhance optimal adaptation of protozoa in hostile environments. The expanded cladograms of Entamoeba and Cryptosporidium with their closely related genera substantiated this hypothesis. The exclusively expressed proteins obtained from E. histolytica and the putative bacterial gene donor, D. vulgaris, showed an over-representation of eleven genes involved in small molecule metabolism, generation of precursor metabolites, and carbohydrate metabolism. If these results can be reproduced in other PFOR-possessing protozoa, it would provide a more validated evidence to support the horizontal transfer of pfor from bacteria. Subsequent syntenic analyses of the significantly enriched genes would be required to provide further information regarding the positional relatedness of these genes at the chromosomal level. Since metronidazole is an established and well tolerated drug for treating infections caused by PFOR-possessing pathogens, it can be considered as a potential drug candidate for the treatment of infections caused by Cryptosporidium, Spironucleus and Blastocystis.

Deep learning has been applied in many areas that have had a significant impact on applications that improves real-life challenges. The success of deep learning in a wide range of areas is due in part to the use of activation functions, which are particularly effective at solving non-linear problems. Activation functions are a key focus for researchers in artificial intelligence who aim to improve the performance of neural networks. This article provides a comprehensive explanation and comparison of different activation functions, with a focus on the arc tangent and its variations specifically. The paper presents experimental results that show that variations of the arc tangent using irrational numbers such as pi, the golden ratio, and Euler’s number, as well as a self-arctan function, produce promising results. Since we experimented with promising activation functions on two different problems, and datasets, we reached a result that different irrationals work well for different problems. In other words, arctan ϕ gives the best results mostly for multiclass classification and arctan e gives the best results for time series prediction problems. The paper focuses on a multiclass classification problem applied to the Reuters Newswire dataset and a time-series prediction problem on Türkiye energy trade value to show the impacts of activation functions.

This work aims to investigate the influence of reaction time and catalyst-to-residual fat ratio by catalytic upgrading from pyrolysis vapors of residual fat at 400 °C and 1.0 atmosphere, on the yields of reaction products, physicochemical properties (density, kinematic viscosity, and acid value) and chemical composition of bio-oils, over a catalyst fixed bed reactor of activated carbon pellets impregnated with 10.0 M NaOH, in semi pilot scale. The experiments were carried out at 400 °C and 1.0 atmosphere, using a process schema consisting of a thermal cracking reactor of 2.0 L coupled to a catalyst fixed bed reactor of 53 mL, without catalyst and using 5.0, 7.5, and 10.0% (wt.) activated carbon pellets impregnated with 10.0 M NaOH, in batch mode. Samples of liquid phase products were withdrawn during the course of reaction at 50, 60, 70, 80, 90, 100 and 120 minutes in order to investigate the process kinetics. The physicochemical properties (density, kinematic viscosity, and acid value) of bio-oils were determined by official methods. The chemical composition of bio-oils determined by GC-MS. The thermal catalytic cracking of residual fat show bio-oils yields from 55.55 to 30.22 (wt.%), aqueous phase yields between 2.83 and 3.19 (wt.%), solid phase yields between 13.56 and 9.75 (wt.%), and gas yields from 27.89 to 55.60 (wt.%). The yields of bio-oil decreases from 74.41 to 30.22% (wt.) with increasing catalyst-to-Tallow kernel oil ratio, while that of gaseous phase increases from 12.87 to 55.60% (wt.). For all the thermal and thermal catalytic cracking experiments, the density, kinematic viscosity, and acid value of bio-oils decreases as the reaction time increases varying from 0.9266 to 0.8220 g/cm³, 8.10 to 2.24 mm²/s, and 144.14 to 2.37 mg KOH/g. The GC-MS of liquid reaction products identified the presence of hydrocarbons (alkanes, alkenes, ring-containing alkanes, ring-containing alkenes, and aromatics) and oxygenates (carboxylic acids, ketones, esters, alcohols, and aldehydes). For all the pyrolysis and catalytic cracking experiments, the hydrocarbon selectivity in bio-oil increases with increasing reaction time, while those of oxygenates decrease, reaching concentrations of hydrocarbons up to 95.35% (area.). The best results for the physicochemical properties density, kinematic viscosity, and acid value were 0.8220 g/cm³, 3.03 mm2/s, and 2.37 mg KOH/g, respectively, with a maximum hydrocarbon concentration of 97.194% (area.) and 2.806% ketones (area.) were obtained at 400 °C and 1.0 atmosphere, 80 minutes, without catalyst. For the catalytic cracking experiments, the maximum hydrocarbon content of 75.763% (area.) and 17.041% (area.) carboxylic acids, 4.702% (area.) ketones (area.), and 2.494% (area.) non-identified oxygenates was obtained at 400 °C and 1.0 atmosphere, 90 minutes, using a catalyst fixed bed reactor, with 10.0% (wt.) activated carbon pellets impregnated with 10.0 M NaOH as catalyst.

Ceramic samples based on b-calcium pyrophosphate b-Ca2P2O7 were prepared using firing at 900, 1000, and 1100 oC from powders of g-calcium pyrophosphate g-Ca2P2O7 with preset molar ratios Ca/P=1; 0,975 and 0,95. To prepare powders of g-calcium pyrophosphate g-Ca2P2O7 with preset molar ratio Ca/P=1; 0,975 and 0,95 powder mixtures based on calcium lactate pentahydrate Ca(C3H5O3)2⋅5H2O and, monocalcium phosphate monohydrate Ca(H2PO4)2⋅H2O were treated in an aqua medium in mechanical activation conditions, dried, disaggregated in acetone, and heat-treated at 600 oC. The phase composition of powder mixtures after treatment if planetary mill in aqua medium included both brushite CaHPO4⋅2H2O or monetite CaHPO4, and starting salts. The phase composition of all powder mixtures after disaggregation in acetone in planetary mill included monetite CaHPO4 and starting salts. After heat treatment at 600 oC according to the XRD data phase composition of all powder mixtures was presented by g-calcium pyrophosphate g-Ca2P2O7. The grain size of ceramics increased both with the growth of firing temperature and with decreasing of molar ratio Ca/P of powder mixtures. Calcium polyphosphate (t melt =960–968 oC) formed from monocalcium phosphate monohydrate Ca(H2PO4)2⋅H2O acted like a liquid phase sintering additive. It was confirmed by tests in vitro, that prepared ceramic materials with preset molar ratio Ca/P=1; 0,975 and 0,95 and phase composition presented by b-calcium pyrophosphate b-Ca2P2O7 according to XRD data were biocompatible and could maintain bone cells proliferation.

Creep deformation behaviour in single phase γ-TiAl alloy has been an extensively studied topic since the late 1970s. A lot of literatures have reported creep behaviour of γ-TiAl alloys, manufactured using different processing techniques [1]–[7]. The present discussion revisits the original work on understanding the tensile creep deformation behaviour of wrought single-phase γ-TiAl alloy by Hayes et al. [8] and is aimed to develop an understanding of steady state creep, through strain vs strain rate and strain vs ln(strain rate) plots. Besides, it also attempts to study the variation of stress exponent with temperature between 760-900⁰C and also, to determine activation energies using the two most common approaches, namely: Zener-Hollomon (Z-H) [9] and Sherby-Dorn (S-D, temperature compensated time approach) [10] for stress levels of 69 and 103.4 MPa between 760-900⁰C.

Understanding of the decisive role of the interaction mechanism and kinetics in the combustion processes is highly relevant for the elaboration of optimal conditions for obtaining Mo-Cu composite powders. From this perspective, the efficient delivery of the reduction mechanism of copper and molybdenum oxides with combined Mg + C reducing agents at high heating rates is crucial to develop a valuable approach for the combustion synthesis of Mo-Cu composite powders. Herein, we shed light on the mechanism of the reactions in all the studied binary, ternary and quaternary systems contemporaneously demonstrating the effect of the heating rate on the conversion degree. The combination of two highly exothermic and speedy reactions (MoO3+3Mg and CuO+Mg vs MoO3+CuO+4Mg) led to a slow interaction with weak self-heating (dysynergistic effect) due to a change in the reaction mechanism. On the other hand, it has been shown that during the simultaneous utilization of the Mg and C reducing agents, the process begins exclusively with carbothermic reduction, and at relatively high temperatures it continues with magnesiothermic one. The effective activation energy values of the magnesiothermic stages of the studied reactions were determined by Kissinger isoconversional method.

In the author's opinion, many global problems that face humanity - in the fields of education, medicine, management etc can be tackled more effectively if the cyclic nature of self-reproducing systems – including living beings – is taken into account. Summarizing the main physiological findings of the last decades on "adaptation reactions", one can very roughly say that the way of action which is effective in the sense of productive activity of people happens at the same time to be healthy, and it gives the participants of the process the feeling of happiness. The present paper represents a very short overview of the contemporary concepts of the adaptation reactions based on the fundamental understanding of their cyclic nature due to general properties of self-reproducing systems. One interesting feature of self-reproduction cycles is its first "phase of orientation" which was not discussed in detail in the past but plays a key role in the whole cycle.

The positional cloning of single nucleotide polymorphisms (SNPs) of the neutrophil cytosolic factor 1 (Ncf1) gene, advocating that a low oxidative burst drives autoimmune disease, demands an understanding of the underlying molecular causes. A cellular target could be T cells, which have been shown to be regulated by reactive oxygen species (ROS). However, the pathways by which ROS mediate T cell signaling remain unclear. The adaptor molecule linker for activation of T cells (LAT) is essential for coupling T cell receptor-mediated antigen recognition to downstream responses, and it contains several cysteine residues that have previously been suggested to be involved in redox regulation. To address the possibility that ROS regulate T cell-dependent inflammation through LAT, we established a mouse strain with cysteine-to-serine mutations at positions 120 and 172 (LATSS). We found that redox regulation of LAT through C120 and C172 mediate its localization and phosphorylation. LATSS mice had reduced numbers of double-positive thymocytes and naïve peripheral T cells. Importantly, redox insensitivity of LAT enhanced T cell-dependent autoimmune inflammation in collagen-induced arthritis (CIA), a mouse model of rheumatoid arthritis (RA). This effect was reversed on an NCF1-mutated (NCF1m1j), ROS-deficient, background. Overall, our data shows that LAT is redox-regulated, acts to repress T cell activation, and is targeted by ROS induced by NCF1 in antigen-presenting cells (APCs).

This research examines the fire resistance of geopolymer composites (GCs), formulated using alka-li-activated metakaolin and aluminum powder. The production method involves spray-coating carbon steel plates with fresh GCs, followed by a 28-day curing period at room temperature. Sub-sequently, fire performance and aging tests are conducted to evaluate fire resistance. The study investigates GC properties, including apparent density, bending strength, compression strength, thermal conductivity, porosity, and production cost. Morphological changes before and after fire and aging tests are analyzed using scanning electron microscopy (SEM). Results demonstrate GC foams' outstanding thermal insulation, providing up to 75 minutes of fire resistance with a 6 mm coating, reducing temperatures by 300 °C compared to uncoated steel. GCs exhibit a density of 670 kg/m³, thermal conductivity of 0.166 W/m·K, 68% porosity, and cost efficiency at 250 dollars per cubic meter. This study underscores the potential of foamed geopolymer coatings for effective and economical surface protection.

Ubiquitin-Specific-peptidase 22 (Usp22) cleaves ubiquitin moieties from numerous proteins, in particular transcription factors. Recently, it was reported that Usp22 acts as negative regulator of interferon-dependent responses. In the current study, we investigated the role of Usp22 deficiency upon acute viral infection with lymphocytic choriomeningitis (LCMV) virus. We found that lack of Usp22 on bone marrow derived cells (Usp22 fl/fl Vav1-Cre mice) reduced induction of type I and II interferons. Limited type I interferon response did not influence virus replication. However, restricted expression of PD-L1 led to increased frequencies of functional virus-specific CD8+ T cells and rapid death of Usp22 deficient mice. CD8+ T cell depletion experiments revealed that accelerated CD8+ T cells were responsible for enhanced lethality in Usp22 deficient mice. In conclusion, we found that the lack of Usp22 generated a pathological CD8+ T cell response, which gave rise to severe disease in mice.

Weathering and erosion transport minerals and organics toward the sea or lake bottoms over geologic time. The finest solids are deposited in lower, less turbulent areas, such as lake bottoms and continental shelves. They sometimes stack up to thicknesses of kilometers, and begin compacting. These sediment sections are called shales, and as initially deposited in water, shales can have porosities up to 50-80{\%} water, As they are buried, many alteration products from oil to slate are produced due to overburden and temperature increasess, making them important to study. A preceeding paper \cite{1} showed that pressure solution is the primary mechanism for porosity reduction, with possible mechanical compaction at shallow depths. Without naming the mineral(s) involved, it postulated that the greater the product of the water and pore interfaces, the faster the reaction would proceed. This term is $ \varphi^{4m/3}(1-\varphi)^{4n/3}$ , where $\varphi$ is porosity and m and n are numbers close to unity. The large exponents, {\em 4/3}, recognize that the reaction occurs at the molecular scale at which the surfaces are rough. A second term, $\exp^{(-E/RT)}$ , indicates that the reaction is impeded by a quantum energy barrier, E, with diminished impeding power as increased available thermal energy, represented by the absolute temperature, T, becomes available at greater depths in the Earth. These two factors combine to allow porosity $\varphi$ to reduce with time, or equivalently for the fraction of solids, $(1-\varphi)$, to increase with time,$\left. \frac{\partial(ln(1-\varphi) ) }{\partial t } \right |_{\sigma} = (\varphi )^{4m/3}( 1-\varphi )^{4n/3}Ae^{-E/(RT)}$. { \em Here it is shown that this equation can cover quantitatively any actual deposition rates which may have been experienced by the six sections studied, the actual deposition rates being unknown for these cases. Hence a time-depth depositional history for any new shale section, known in detail, would allow determination of the parameters m, n, E and a lumped proportionality constant A. This was accomplished by showing that, for a wide range of depositional rates, r, the range of E for any of the studied sections is small compared to laboratory measurements of quartz solution\cite{2}, 24+-15kJ/mol. Results were obtained over this range of r's using the previously determined m and n, and porosity and temperature profiles. The presently existing porosity profiles necessarily incorporate any overpressure or underpressure conditions that may have existed in the past or currently, as the net difference between overburden and pore pressure is a primary driving force for pressure solution. $SiO_2$ usually comprises 20-50{\%} of shales. In conclusion, pressure solution of quartz can account for vertical compaction of shales quantitatively in the studied examples. Separately, a quasi-eqivalent method for discussing reduced porosities in Macron 2 versus Macron 1 as increased vertical stress, rather than additional horizontal stress, is illustrated. Experiments are suggested to clarify the pressure solution mechanism. The role of horizontal forces is discussed.

Deep learning has been applied in many areas that have had a significant impact on applications that improves real-life challenges. The success of deep learning in a wide range of areas is due in part to the use of activation functions, which are particularly effective at solving non-linear problems. Activation functions are a key focus for researchers in artificial intelligence who aim to improve the performance of neural networks. This article provides a comprehensive explanation and comparison of different activation functions, with a focus on the arc tangent and its variations specifically. The paper presents experimental results that show that variations of the arc tangent using irrational numbers such as pi, the golden ratio, and Euler’s number, as well as a self-arctan function, produce promising results. Since we experimented with promising activation functions on two different problems, and datasets, we reached a result that different irrationals work well for different problems. In other words, arctan ϕ gives the best results mostly for multiclass classification and arctan e gives the best results for time series prediction problems. The paper focuses on a multi-class classification problem applied to the Reuters Newswire dataset and a time-series prediction problem on Türkiye energy trade value to show the impacts of activation functions.

Scrub typhus is a neglected tropical disease predominantly occurring in Asia. The causative agent is a bacterium transmitted by the larval stage of mites found in rural vegetation in endemic regions. Cases of scrub typhus frequently present as acute undifferentiated febrile illness, and without early diagnosis and treatment, the disease can develop fatal complications. We retrospectively reviewed de-identified data from a 23-year-old woman who presented to an emergency department with complaints of worsening abdominal pain. On presentation, she appeared jaundiced and toxic-looking. Other positive findings on abdominal examination were a positive Murphey’s sign, abdominal guarding and hepatosplenomegaly. Magnetic resonance cholangiopancreatography demonstrated acalculous cholecystitis. Additional findings included eschar on the medial aspect of the left thigh with inguinal regional lymphadenopathy. Further, positive results were obtained for immunoglobulins M and G, confirming scrub typhus. Workups for other infectious causes of acute acalculous cholecystitis detected human herpesvirus 4 (Epstein-Barr virus). Whether that represented acute infection or re-activation of the Epstein-Barr virus could not be determined. As other reports have described acute acalculous cholecystitis in adult scrub typhus patients, we recommend doxycycline to treat acute acalculous cholecystitis in endemic regions while awaiting serological confirmation.

Diabetes mellitus (DM) is one of the principal manifestations of metabolic syndrome and its prevalence with modern lifestyle is increasing incessantly. Chronic hyperglycemia can induce several vascular complications that were referred to be the major cause of morbidity and mortality in DM. Although several therapeutic targets have been identified and accessed clinically, the imminent risk of DM and its prevalence are still ascending. Substantial pieces of evidence revealed that histone deacetylase (HDAC) isoforms can regulate various molecular activities in DM via epigenetic and post-translational regulation of several transcription factors. To date, 18 HDAC isoforms have been identified in mammals that were categorized into 4 different classes. Classes I, II, and IV are regarded as classical HDACs, which operate through a Zn-based mechanism. In contrast, class III HDACs or Sirtuins depend on nicotinamide adenine dinucleotide (NAD+) for their molecular activity. Functionally, most of the HDAC isoforms can regulate β cell fate, insulin release, insulin expression and signaling, and glucose metabolism. Moreover, the roles of HDAC members have been implicated in the regulation of oxidative stress, inflammation, apoptosis, fibrosis, and other pathological events, which substantially contribute to diabetes-related vascular dysfunctions. Therefore, HDACs could serve as the potential therapeutic target in DM towards developing novel intervention strategies. This review sheds light on the emerging role of HDACs/isoforms in diabetic pathophysiology and emphasized the scope of their targeting in DM for constituting the novel interventional strategies for metabolic disorders/complications.

Geminiviruses possess single-stranded, circular DNA genomes, and control the transcription of their late genes, including BV1 of many bipartite begomoviruses, through transcriptional activation by the early expressing AC2 protein. DNA binding by AC2 is not sequence-specific, hence the specificity of AC2 activation is thought to be conferred by plant transcription factors (TFs) recruited by AC2 in infected cells. However, the exact TFs AC2 recruits are not known for most viruses. Here we report a systematic examination of the BV1 promoter (PBV1) of mungbean yellow mosaic virus (MYMV) for conserved promoter motifs. We found that MYMV PBV1 contains three abscisic acid (ABA)-responsive elements (ABREs) within its first 70 nucleotides. Deleting these ABREs, or mutating them all via site-directed mutagenesis, abolished the capacity of PBV1 to respond to AC2-mediated transcriptional activation. Furthermore, ABRE and other related ABA-responsive elements were prevalent in more than a dozen Old World begomoviruses we inspected. Together these findings suggest that ABA-responsive TFs may be recruited by AC2 to BV1 promoters of these viruses to confer specificity to AC2 activation. These observations are expected to guide the search for the actual TF(s), furthering our understanding of the mechanism of AC2 action.

We asked whether the level of peripheral fatigue would differ when three consecutive exercise trials were completed to task failure, and whether there would be delayed recovery in maximal voluntary contraction (MVC) force, neuromuscular activation and peripheral fatigue following task failure. Ten trained sport students performed three consecutive knee extension isometric trials (T1, T2, T3) to task failure without breaks between trials. T1 and T2 consisted of repeated 5-s contractions followed by 5-s rest. In T1, contractions were performed at a target force at 60% pre-exercise MVC. In T2, all contractions were MVCs, and task failure occurred at 50% MVC. T3 was a sustained MVC performed until force fell below 15% MVC. Evoked force responses to supramaximal electrical femoral nerve stimulation were recorded to assess peripheral fatigue. Electromyography signals were normalized to M-wave amplitude to assess neuromuscular activation. Lower levels of evoked peak forces were observed at T3 compared to T2 and T1. Within 5 s of task failure in T3, MVC force and neuromuscular activation recovered substantially without any recovery in evoked peak force. Neuromuscular activation 5-10 s after T3 was unchanged from pre-exercise values, but evoked peak forces were substantially reduced. These results challenge the existence of a critical peripheral fatigue threshold that reduces neuromuscular activation. Since neuromuscular activation changed independently of any change in evoked peak force, immediate recovery in force production after exercise is due to increased central recruitment and not to peripheral mechanisms.

Thrombosis is the pathological clot formation under abnormal hemodynamic conditions, which can result in vascular obstruction, causing ischemic strokes and myocardial infarction. Thrombus growth under moderate to low shear (<1000 s^-1) relies on platelet activation and coagulation. Thrombosis at elevated high shear rates (>10,000 s-1) is predominantly driven by unactivated platelet binding and aggregating mediated by von Willebrand factor (VWF), while platelet activation and coagulation are secondary in supporting and reinforcing the thrombus. Given the molecular and cellular level information it can access, multiscale computational modelling informed by biology can provide new pathphysiological mechanisms that are otherwise not accessible experimentally, holding promise for novel first-principle-based therapeutics. In this review, we summarize the key aspects of platelet biorheology and mechanobiology, focusing on the molecular and cellular scale events and how they build up to thrombosis through platelet adhesion and aggregation in the presence or absence of platelet activation. In particular, we highlight recent advancements in multiscale modeling of platelet biorheology and mechanobiology and how they can lead to better prediction and quantification of thrombus formation, exemplifying the exciting paradigm of digital medicine.

Malignant melanoma is a lethal skin cancer containing melanoma-initiating cells (MIC), implicated in tumorigenesis, invasion, and drug resistance, and characterized by elevated expression of stem cell markers, such as CD133. We previously showed that siRNA knockdown of CD133 enhances apoptosis induced by the MEK inhibitor trametinib in melanoma cells. The current study investigates underlying mechanisms of CD133’s anti-apoptotic activity in patient-derived BAKP and POT cells, harboring difficult-to-treat NRASQ61K and NRASQ61R drivers, after CRISPR-Cas9 CD133 knockdown or Dox-inducible expression of CD133. To maintain stable expression of CD133, MACS-sorted CD133(+) positive cells were expanded by ROCK-mediated conditional reprogramming of BAKP melanoma cells (BAKR). BAKR showed increased survival via reduced apoptosis after exposure to trametinib or DTIC, compared to BAKP. CRISPR-Cas9- mediated CD133 knockdown in BAKR cells (BAKR-T3) re-sensitized the cells, while CRISPR-Cas9 knockdown of CD133 in parental BAKP and POT cells even further increased trametinib-induced apoptosis (cleaved PARP) by reducing levels of anti-apoptotic BCL-xL, p-AKT, and p-BAD, and increasing pro-apoptotic BAD and active BAX. Dox-induced CD133 overexpression had the opposite effect, and blocked trametinib-induced apoptosis in both cell lines, coincident with elevated p-AKT, p-BAD, BCL-2 and BCL-xL and decreased levels of the active form of BAX and caspases-3 and -9. The roles of CD133 in AKT and BAD phosphorylation, or in the upregulation of anti-apoptotic BCL-2 family members, was further investigated by AKT knockout with siRNA, or inhibition of BCL-2 family members with navitoclax (ABT-263). Similar to CD133 knockdown, AKT1/2 siRNA knockdown in BAKP cells also reduced p-BAD. CD133 knockdown (T3)-mediated reduction of pBAD levels was equivalent in AKT-knockdown or AKT control cells indicating that CD133 may be upstream of AKT signaling. In BAKP cells treated with trametinib and/or ABT-263, effects of ABT-263 mirrored CD133 knockdown, since levels of active BAX and cleaved-PARP in BAKP-SC (CD133-) cells increased to the same level as that exhibited by BAKP-T3 cells (CD133+). CD133 may therefore activate a survival pathway where 1) increased phosphorylation of AKT induces 2) phosphorylation and inactivation of BAD, 3) decrease in the active form of BAX, and 4) reduction in caspase-mediated PARP cleavage, indicating apoptosis suppression leading to drug resistance in melanomas. Targeting survival pathways by which CD133 may confer chemoresistance in MICs can contribute to development of more effective treatments for patients with high-risk melanoma.

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.

Clients are increasingly looking for fast and effective means to quickly and frequently survey and communicate the condition of their buildings so that essential repairs and maintenance work can be done in a proactive and timely manner before it becomes too dangerous and expensive. Traditional methods for this type of work commonly comprise of engaging building surveyors to undertake a condition assessment which involves a lengthy site inspection to produce a systematic recording of the physical condition of the building elements, including cost estimates of immediate and projected long-term costs of renewal, repair and maintenance of the building. Current asset condition assessment procedures are extensively time consuming, laborious, and expensive and pose health and safety threats to surveyors, particularly at height and roof levels which are difficult to access. We propose a method for automated detection and localisation of key building defects from images using deep learning and convolution neural networks. The proposed model is based on a pre-trained VGG-16 classifier with Class Activation Mapping (CAM) for object localisation. The model has proven to be robust and able to accurately detect and localise mould growth, stains, and paint deterioration defects arising from dampness in buildings. The approach is being developed with potentials to scale-up to support automated detection of defects and deterioration of buildings in real-time using mobile devices and drones.

In this short review paper we have assembled the main characteristics of partial oxidation reactions (oxidative dehydrogenation and selective oxidation to olefins or oxygenates, as aldehydes and carboxylic acids and nitriles), as well as total oxidation, particularly for depollution, environmental issues and wastewater treatments. Both gas-solid and liquid-solid media have been considered with recent and representative examples within these fields. We have also discussed about their potential and prospective industrial applications. Particular attention has been brought to new raw materials stemming from biomass and to liquid-solid catalysts cases. This review paper also summarizes the progresses made in the use of unconventional activation methods for performing oxidation reactions, highlighting the synergy of these technologies with heterogeneous catalysis. Focus has been centered on usual catalysts activation methods but also on less usual ones, such as the use of ultrasounds, microwaves, grinding (mechanochemistry) and photo-activated processes, as well as their combined use.

Structural self-organizing and pattern formation are universal and key phenomena observed during growth and cluster-assembling of the carbyne-enriched nanostructured metamaterials at the ion-assisted pulse-plasma deposition. Fine tuning these universal phenomena opens access to designing the properties of the growing carbyne-enriched nano-matrix. The structure of bonds in the grown carbyne-enriched nano-matrices can be programmed by the processes of self-organization and auto-synchronization of nanostructures. We propose the innovative concept, connected with application of the universal Cymatics phenomena during the predictive growth of the carbyne-enriched nanostructured metamaterials. We also propose the self-organization approach for increase stability of the long linear carbon chains. The main idea of suggested concept is manipulating by the self-organized wave patterns excitation phenomenon and their distribution by the spatial structure and properties of the nanostructured metamaterial grows region through the new synergistic effect. Mentioned effect will be provided through the vibration-assisted self-organized wave patterns excitation along with simultaneous manipulating by their properties through the electric field. We propose to use acoustic activation of the plasma zone of nano-matrix growing. Interaction between the inhomogeneous electric field distribution generated on the vibrating layer and the plasma ions will serve as the additional energizing factor controlling the local pattern formation and self-organizing of the nano-structures. Suggested concept makes it possible to provide precise predictive designing the spatial structure and properties of the advanced carbyne-enriched nanostructured metamaterials.

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

Egg activation is a cellular transition of an arrested mature oocyte into a developing embryo through a coordinated series of events. Previous studies in Hymenoptera have indicated that mechanical pressure can induce egg activation. In this study, we developed the first egg activation protocol for the haplodiploid insect pest, Sirex noctilio (Hymenoptera: Siricidae), from two climatically different regions in South Africa. In addition, activated eggs were exposed to three treatments involving water, pine sawdust, and the fungal symbiont of S. noctilio, Amylostereum areolatum (Russulales: Amylostereaceae), to confirm the hypothesised prerequisite of the symbiotic fungus for egg development. A rearing protocol was developed for emerged first instar larvae using a modified Anoplophora glabripennis (Coleoptera: Cerambycidae) artificial diet. A significant difference between mean survival rates of activated eggs from the two different regions was observed. Amylostereum areolatum was shown to be unnecessary for egg survival and adversely affected egg eclosion. Maximum larval survival duration on the artificial diet was 92 days. The egg activation and rearing protocol developed in this study enables opportunities for research on the physiology, ecology, symbioses, and genetics of S. noctilio, which can be exploited for new genetic pest management strategies.

Optical characterization and thermal aging tests are performed on a sputter-deposited coating, consisting of SiO₂/Cr₂O₃/Cr/Cr₂O₃ layers, designed and developed as a selective solar absorber to be used for unconcentrated solar thermal applications. Both measurements are performed by using a home-made apparatus, which mimics a flat plate collector under high vacuum. A Performance Criterion (PC_η(T)), based on absorber efficiency is proposed, and a forecast of service lifetime is obtained. As a result of the thermal aging tests, the selective solar absorber under study appears to be highly efficient at mid temperatures (up to 573 K) and thermally stable at temperatures (up to 690 K).

Unlike electron microscopy, which can achieve very high resolutions, but to date can only be used to study static structures, time-resolved X-ray diffraction from contracting muscles can, in principle, be used to follow the molecular movements involved in force generation on a millisecond timescale albeit at moderate resolution. However, previous X-ray diffraction studies of resting muscles have come up with structures for the head arrangements in resting myosin filaments that are different from the apparently ubiquitous interacting heads motif (IHM) found by single particle analysis of electron micrographs of isolated myosin filaments from a variety of muscle types. This head organization is supposed to represent the super-relaxed state of the myosin filaments where ATP usage is minimized. Here we have tested whether the interacting heads motif structures will satisfactorily explain the observed low-angle X-ray diffraction patterns from resting vertebrate (bony fish) and invertebrate (insect flight) muscles. We find that the interacting heads motif does not, in fact, explain what is observed. Previous X-ray models fit the observations much better. We conclude that the X-ray diffraction evidence has been well interpreted in the past and that there is more than one ordered myosin head state in resting muscle. There is, therefore, no reason to question some of the previous X-ray diffraction results on myosin filaments; time-resolved X-ray diffraction should be a reliable way to follow crossbridge action in active muscle and may be one of the few ways to follow molecular changes in myosin heads on a millisecond timescale as force is actually produced.

Post-training quantization is pivotal in deploying convolutional neural networks for mobile applications. Block-wise reconstruction with adaptive rounding, as employed in prior works like BrecQ and Qdrop, facilitates acceptable 4-bit quantization accuracy. However, adaptive rounding is time-intensive, and its constraint on weight optimization space curtails the potential for quantization performance. The optimality of block-wise reconstruction hinges on the quantization status of subsequent network blocks. In this investigation, we delve into the theoretical underpinnings of the limitations inherent in adaptive rounding and block-wise reconstruction. Our exploration leads to the development of a post-training quantization methodology, designated as AE-Qdrop. This algorithm operates in two distinct phases: block-wise reconstruction and global fine-tuning. The block-wise reconstruction phase introduces a progressive optimization strategy, superseding adaptive rounding, which not only augments quantization precision but also significantly improves quantization efficiency. To mitigate the risk of overfitting, we introduce a random weighted quantized activation mechanism. During the global fine-tuning phase, we account for interdependencies among quantized network blocks. The weight of each network block will be corrected with logit matching and feature matching. Extensive experiments validate that AE-Qdrop achieves high-precision and efficient quantization. For instance, in the case of 2-bit MobileNetV2, AE-Qdrop outperforms Qdrop by achieving a 6.26% enhancement in quantization accuracy and quintupling the quantization efficiency.

The present study aimed to investigate the effect of cold deformation on the precipitation kinetics of a binary CuSc alloy containing 0.4 wt.% scandium using the experimental analysis method of differential scanning calorimetry (DSC). Non-deformed and 75% cross-section reduced cold-rolled, supersaturated specimens were tested at non-isothermal DSC runs at up to five different heating rates. The DSC results showed that cold deformation significantly accelerated the precipitation process in the binary alloy, leading to a decrease in the initial and peak temperatures of the exothermic reactions. The activation energies calculated with the Kissinger method, indicated that the precipitation activation energy decreased with increasing cold deformation. The findings of this study provide worthy implications to further optimize the processing of Cu-Sc alloys with improved mechanical properties.

The X-ray induced spin crossover transition of an Fe(II) molecular thin film in the presence and absence of a magnetic field has been investigated. The thermal activation energy barrier in the soft X-ray activation of the spin crossover transition for [Fe{H2B(pz)2}2(bipy)] molecular thin films is reduced in the presence of an applied magnetic field, as measured through X-ray absorption spectroscopy at various temperatures. The influence of a 1.8 T magnetic field is sufficient to cause deviations from the expected exponential spin state transition behavior that is measured in the field free case. We find that orbital moment diminishes with increasing temperature, relative to the spin moment in the vicinity of room temperature.

Abstract: Viremia in coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is often only discussed in passing and there are very few references detailing its structural mechanisms. In addition to viremia in the classic closed cardiovascular system, the lymphatic system is discussed in relation to a possible “lympho-viremia”. The cells that comprise each of these separate but interacting systems will be examined and include endothelial cells, erythrocytes, leukocytes (monocytes/monocyte-derived macrophages and resident tissue macrophages) (lymphocytes) (neutrophils) and thrombocytes -platelets. The SARS-CoV-2 virus has been identified in multiple extrapulmonary target organs at autopsy in those with severe COVID-19 requiring intensive care. Vulnerable COVID-19 patients may suffer from multiple storms including viral/virion storm, redox storm, cytokine storm and thrombo-embolic storm. Therefore, it is important that the possible mechanisms of viremia be explored in greater detail and how these mechanisms might affect intravascular blood components, extracellular tissue interstitium and organ structural remodeling and function. While the co-morbidity of T2DM does not increase the risk of acquiring COVID-19, it is commonly accepted that T2DM increases the risk for COVID-19 admissions to hospitals, assisted ventilation, morbidity and mortality. Importantly, the co-existence of T2DM and COVID-19 may have synergistic detrimental outcomes.

Poland is the 3^rdproducer of mushrooms in the world. Mushroom production in Poland accounts for nearly 25% of the total production in the EU, and it is still growing. One type of waste generated during mushroom production is mushroom spent compost (MSC), with a 5:1 (MSC: mushrooms) production rate. We investigated valorizing the MSC to produce fuel via torrefaction (‘roasting’, a.k.a. low-temperature pyrolysis). Specifically, we developed models for the MSC torrefaction kinetics using thermogravimetric analyses (TGA) and the effects of torrefaction temperature (200~300 °C) and process duration time (20~60 min) on the resulting biochar (fuel) properties. The estimated activation energy value of MSC torrefaction was 22.3 kJ^.mol^-1. The highest higher heating value(HHV) = 17.9 MJ^.kg^-1d.m. was found for 280 °C (60 min torrefaction time). The temperature of torrefaction significantly (p<0.05) increased the HHVfor constant process duration. The torrefaction duration time significantly (p<0.05) increased the HHVfor 220 °C and decreased HHVfor 300 °C. The highest mass yield 98.5% was found for 220 °C (60 min), while the highest energy yield was found for 280 °C (60 min). In addition, estimations of the value (€132.3·Mg^-1d.m. or 27.7 €·Mg^-1w.m) and quantity of resulting biochar (from torrefied MSC with 65.3% moisture content) were made based on the 280°C (60 min) torrefaction variant, assuming the price of commercially available coal fuel. We have shown a concept for an alternative utilization of abundant biowaste (MSC). The initial economic evaluation showed that MSC torrefaction might be profitable. This research provides a basis for alternative use of an abundant biowaste and can help charting improved, sustainable mushroom production.

This paper presents a comprehensive investigation into the applicability and performance of two prominent growth models, namely the Verhulst model and the Montroll model, in the context of modeling tumor cell growth dynamics. Leveraging the power of Physics-Informed Neural Networks (PINNs), we aim to assess and compare the predictive capabilities of these models against experimental data obtained from the growth patterns of tumor cells. We employ a dataset comprising detailed measurements of tumor cell growth to train and evaluate the Verhulst and Montroll models. By integrating PINNs, we not only account for experimental noise but also embed physical insights into the learning process, enabling the models to capture the underlying mechanisms governing tumor cell growth. Our findings reveal the strengths and limitations of each growth model in accurately representing tumor cell proliferation dynamics. Furthermore, the study sheds light on the impact of incorporating physics-informed constraints on the model predictions. The insights gained from this comparative analysis contribute to advancing our understanding of growth models and their applications in predicting complex biological phenomena, particularly in the realm of tumor cell proliferation.

In recent times, using image-based deep learning techniques has been very useful for classifying fruits. However, mango is a particular challenge because its shelf life is directly related to the degree of maturity at the time of harvest, which is determined mainly through the visual assessment of the operators when sorting them, doing it incorrectly, coupled with the blows and compressions exposed during storage and transport, trigger the deterioration in their quality, hence the importance of this operation. In this sense, the purpose of this study focuses on designing a computational model based on Deep Learning that uses a convolutional neural network (CNN) parameterized to select mangoes according to their color tone based on their maturity stage. A dataset was established from 201 labeled images, then a CNN architecture was built, obtaining a model on which 3 criteria were evaluated: the number of convolution and grouping layers, the resolution of the input images and the number of training epochs required. As a result, an input image resolution of 32 x 32 pixels was achieved, the process included a convolution layer followed by pooling that fed another layer that processed the results and ended in an output layer with 2 neurons under the One Hot Encoding representation. The model required 20 epochs to perfect its training, achieving 96.04 % accuracy in mango image selection. This study supports the potential of CNNs in quality analysis through mango color selection, even in uncertainty scenarios.

Autism spectrum disorder (ASD) is a neuropsychiatric condition characterized by impaired social interactions and repetitive stereotyped behaviors. Growing evidence highlights an important role of the gut-brain-microbiome axis in the pathogenesis of ASD. Research indicates an abnormal composition of the gut microbiome and the potential involvement of bacterial molecules in neuroinflammation and brain development disruptions. Concurrently, attention is directed towards the role of short-chain fatty acids (SCFAs) and impaired intestinal tightness. This comprehensive review emphasizes the potential impact of maternal gut microbiota changes on the development of autism in children, especially considering maternal immune activation (MIA). The following paper evaluates the impact of the birth route on the colonization of the child with bacteria in the first weeks of life. Furthermore, it explores the role of pro-inflammatory cytokines, such as IL-6 and IL-17a and mother’s obesity as potentially environmental factors of ASD. The purpose of the present analysis is to advance our understanding of ASD pathogenesis, while also searching for the positive implications of the latest therapies, such as probiotics, prebiotics or fecal microbiota transplantation, targeting the gut microbiota and reducing inflammation. This review aims to provide valuable insights that could instruct future studies and treatments for individuals affected by ASD.

Adult-onset Still's disease (AOSD) is a rare systemic inflammatory disorder. Diagnosis can take a long time, especially in the presence of confounding factors, and it is, at least in part, of exclusion. AOSD is generally mild, however a small percentage of patients can develop a fearsome as well potentially fatal complication, the macrophage activation syndrome (MAS), which is also referred to as hemophagocytic lymphohistocytosis (HLH). This condition is correlated with a cytokine storm production and monocyte/macrophage overactivation, and typically occurs with rash, pyrexia, pancytopenia, hepatosplenomegaly and systemic involvement. Exitus occurs in approximately 10% of cases. The Histiocyte Society, which is a nonprofit organization committed to improving the lives of patients with histiocytic disorders, currently suggests etoposide in combination with dexamethasone for the treatment of HLH/MAS, although a multidisciplinary collaboration using the resources and expertise of several specialists (e.g. rheumatologist, infectiologist, critical care medicine specialist) is always recommended. Hereby we propose the detailed description of the clinical case of a previously healthy young woman in which MAS was the dramatic onset manifestation of AOSD and whose diagnosis posed a real clinical challenge.

Fluorinated compounds and co-enzymes are being widely researched and employed throughout research community because of their versatile physical, chemical and biological properties. In this work, we synthesized NiS-NiO/S-g-C3N4, a highly effective photocatalyst for C(sp3)-F bond activation and the regeneration of coenzyme (1,4-NADH) employing a new and ecologically acceptable route. The obtained photocatalyst exhibited important photocatalytic properties, such as good solar light harvesting ability, suitability of the optical band-gap, and facilitating efficient charge migrations. As a result, the newly designed NiS-NiO/S-g-C3N4 photocatalyst shows the excellent yield for regenerations of 1,4-NADH (51%). Further, a method of combining C(sp3)-F bond activation with photocatalysis has been demonstrated that represents a very powerful and sustainable approach, that can be a major breakthrough for the field of pharmaceutical.

This paper presents work done as part of a transformation effort towards a greener and more sustainable Aluminium manufacturing plant. The effort includes reducing the carbon footprint by minimising waste and increasing operational efficiency. The contribution of this work includes the reduction of waste through the implementation of autonomous, real-time quality measurement and classification at an Aluminium casthouse. Data is collected from the MV20/20 which uses ultrasound pulses to detect molten Aluminium inclusions, which degrade the quality of the metal and cause subsequent metal waste. The sensor measures cleanliness, inclusion counts and distributions from 20 - 160 microns. The contribution of this work is in the development of business analytics to implement condition-based monitoring through anomaly detection, and to classify inclusion types for samples that failed. For anomaly detection, multivariate K-Means and DBSCAN algorithms are compared as they have been proven to work in a wide range of datasets. For classification, a two-stage classifier is implemented. The first stage classifies the success or failure of the sample, while the second stage classifies the inclusion responsible for the failed sample. The algorithms considered include logistic regression, support vector machine, multi-layer perceptron and radial basis function network. The multi-layer perceptron offers the best performance using k-fold cross-validation, and is further tuned using grid search to explore the possibility of an even better performance. The results reveal that the model has achieved a global maximum in performance. Recommendations include the integration of additional sensor systems and the improvements in quality assurance practices.

: In the last years, materializations of neuromorphic circuits based on nanophotonic arrangements have been proposed, which contain complete optical circuits, laser, photodetectors, photonic crystals, optical fibers, flat waveguides, and other passive optical elements of nanostructured materials, which eliminate the time of simultaneous processing of big groups of data, taking advantage of the quantum perspective and thus highly increasing the potentials of contemporary intelligent computational systems. This article is an effort to record and study the research that has been conducted concerning the methods of development and materialization of neuromorphic circuits of Neural Networks of nanophotonic arrangements. In particular, an investigative study of the methods of developing nanophotonic neuromorphic processors, their originality in neuronic architectural structure, their training methods and their optimization has been realized along with the study of special issues such as optical activation functions and cost functions.

Understanding platelet functionality has undergone a sea change in the last decade. No longer are platelets viewed simply as regulators of haemostasis; they are now acknowledged to be pivotal in coordinating the inflammatory and immune responses. This expanded role for platelets brings new opportunities for controlling a range of health conditions, targeting platelet activation and their interactions with other vascular cells. Antiplatelet drugs may be of wider utility than ever expected but often cause too strong a platelet suppression to be used out of clinical settings. Dietary antiplatelets represent a nutritional approach that can be efficacious while safe for general use. Here we review potential new uses for dietary antiplatelets outside the field of cardiovascular health, with specific reference to the water-soluble tomato extract Fruitflow®. Uses in different aspects of inflammation and immune function are discussed, highlighting exercise-induced inflammation, mediating the effects of air pollution, and controlling thrombotic aspects of the immune response. Potential future developments in women’s health, erectile dysfunction, and the allergic response give an indication of how wide-ranging the utility of dietary antiplatelets can possibly be.

Reversed Flow Gas Chromatography (R.F.G.C.) was employed to assess the impact of genetic modification on Saccharomyces cerevisiae yeast strains during the process of alcoholic fermentation, utilizing fig syrup. Multiple fermentations were carried out at various temperatures to evaluate the influence of genetic modifications on yeast strain efficiency. The study involved a wild-type yeast strain, W303, as a control, and two genetically modified strains, W_M4_533 and W_M4_558, sharing the same genetic background as the wild type. Notably, the genetic modifications in the Msn4p transcription factor involved the substitution of serine residues with alanine at positions 533 and 558, resulting in the development of psychrophilic or ethanol-resistant strains. Utilizing the R.F.G.C. method enabled the differentiation of the duration of alcoholic fermentation phases, providing insights correlated to the yeast cell life cycle. The values of rate constants (k) for each phase, conducted with both wild-type and genetically modified cells using RFGC, aligned with existing literature. Additionally, the calculation of activation energies for distinct phases revealed lower values for genetically modified strains compared to wild-type strains. This decrease in activation energies suggests enhanced efficiency in the alcoholic fermentation process for the genetically modified strains.

Surface processes such as coatings, corrosion, photocatalysis, and tribology are greatly diversified by acid-base interaction at the surface overlayer. This study focuses on the action of metallic copper surface as an electron donor/acceptor related to inactivation of viruses; it was found that regarding Cu2O or Cu materials electrostatic interaction plays a major role in virus inactivation. We applied TPPE method to clarify the mechanism of electron transfer (ET) occurring at light irradiated copper surfaces. The TPPE characteristics was strongly influenced by the environments, which correspond to the temperature and environment dependence of the total count of emitted electrons in the incident light wavelength scan (PE total count, NT), the photothreshold, and further the activation energy (E) analyzed from Arrhenius plot of NT values obtained in the temperature-increase and subsequent temperature-decrease processes. In this study we reexamined the dependence of the TPPE data from two types of Cu metal surfaces: Sample A, which was mechanically abraded in alcohols, water, and air, and Sample C, which was only ultrasonically cleaned in these liquids. The NT for both Samples slowly increased with increasing temperature, reached a maximum (NTmax) at 250C (maximum temperature, Tmax), and after that decreased. For Sample A the NTmax value decreased in the order H2O > CH3OH > C2H5OH > (CH3)2CHOH > C3H7OH, although the last alcohol gave Tmax = 100C, while with Sample C the NTmax value decreased in the order: C3H7OH > (CH3)2CHOH > C2H5OH > CH3OH > H2O. Interestingly, both orders of the liquids were completely opposite: this means that Cu surface can possess two-way character. The NT intensity was found to be strongly associated with the change of the hydroxyl group (Cu-OH) to the oxide oxygen (O2) in the O1s spectra in the XPS measurement. The difference between the above orders was explained by the acid-base interaction mode of the Cu-OH group with the adsorbed molecule on the surfaces. The H2O adsorbed on Sample A produces the electric dipole Cu-OH+---:OH2 (--- hydrogen bond), while the C3H7OH and (CH3)2CHOH adsorbed on Sample C produce ROH+---:O(H)-Cu (R = alkyl groups). Gutmann’s acceptor number (AN) representing the basicity of the liquid molecules was found to be related to the TPPE characteristics: (CH3)2CHOH (33.5), C2H5OH (37.1), CH3OH (41.3), H2O (54.8) (the AN of C3H7OH could not be confirmed). With Sample A the values of NTmaxa and EaUp1 both increased with increasing AN (Up1 means the 1st temperature-increase process). On the other hand, with Sample C the values of NTmaxc and EcUp1 both decreased with increasing AN. These findings suggest that Sample A acts as an acid, while Sample C functions as a base. However, in the case of both types of Samples A and C the NTmax values were found to increase with increasing EUp1. It was explained that the EUp1 values depending on the liquids originate from the difference in the energy level of the hydroxyl group radical at the surface denoted. This is able to attract electrons in the neighborhood of the Fermi level of the base metal by tunnelling. After that due to Auger emission electrons are released, leading to the ET in the overlayer. These electrons are considered to have a strong ability of reducibility.

Fibroblast activation protein (FAP) is a membrane-tethered serine protease overexpressed in the reactive stromal fibroblasts of &gt; 90% human carcinomas, which makes it a promising target for developing radiopharmaceuticals for imaging and therapy of carcinomas. Here, we synthesized two novel (R)-pyrrolidin-2-yl-boronic acid-based FAP-targeted ligands; SB02055 (DOTA-conjugated (R)-(1-((6-(3-(piperazin-1-yl)propoxy)quinoline-4-carbonyl)glycyl)pyrrolidin-2-yl)boronic acid) and SB04028 (DOTA-conjugated ((R)-1-((6-(3-(piperazin-1-yl)propoxy)quinoline-4-carbonyl)-D-alanyl)pyrrolidin-2-yl)boronic acid). natGa- and 68Ga-complexes of both ligands were evaluated in preclinical studies and compared to previously reported natGa/68Ga-complexed PNT6555. Enzymatic assays showed that FAP binding affinities (IC50) of natGa-SB02055, natGa-SB04028 and natGa-PNT6555 were 0.41±0.06, 13.9±1.29 and 78.1±4.59 nM, respectively. PET imaging and biodistribution studies in HEK293T:hFAP tumor-bearing mice showed that while [68Ga]Ga-SB02055 presented with a nominal tumor uptake (1.08±0.37 %ID/g), [68Ga]Ga-SB04028 demonstrated clear tumor visualization with ~1.5-fold higher tumor uptake (10.1±0.42 %ID/g) compared to [68Ga]Ga-PNT6555 (6.38±0.45 %ID/g). High accumulation in the bladder indicated renal excretion of all three tracers. [68Ga]Ga-SB04028 displayed low background level uptake in most normal organs, and comparable to [68Ga]Ga-PNT6555. However, since its tumor uptake was considerably higher than [68Ga]Ga-PNT6555, the corresponding tumor-to-organ uptake ratios for [68Ga]Ga-SB04028 were also significantly greater than [68Ga]Ga-PNT6555. Our data demonstrate that (R)-(((quinoline-4-carbonyl)-D-alanyl)pyrrolidin-2-yl)boronic acid is a promising pharmacophore for the design of FAP-targeted radiopharmaceuticals for cancer imaging and radioligand therapy.

Coccomyxa subellipsoidea KJ (C-KJ) is a green alga with unique immunoregulatory characteristics. Here, we investigated the mechanism underlying the modification of T cell function by C-KJ components. The water-soluble extract of C-KJ was fractionated into protein (P) and sugar (S) fractions [acidic (AS), basic (BS), and neutral (NS)]. These fractions were used for the treatment of peripheral blood mononuclear cells stimulated with toxic shock syndrome toxin-1. Transcriptome analysis revealed that both P and AS enhanced the expression of the genes encoding metallothionein (MT) family proteins, inflammatory factors, and T helper (Th) 17 cytokine and suppressed that of those encoding Th2 cytokines in stimulated T cells. The kinetics of MT1 and MT2A gene expression showed a transient increase in MT1 and maintenance of MT2A mRNA after T cell stimulation in the presence of AS. The kinetics of Th17-related cytokine secretion in the early period were comparable to those of MT2A mRNA. Furthermore, our findings revealed that static, a STAT-3 inhibitor, significantly suppressed MT2A gene expression. These findings suggest that the expression of MTs is involved in the immune regulatory function of C-KJ components, which is partially regulated by Th17 responses, and may help develop innovative immunoregulatory drugs or functional foods.

Specific proteolytic cleavages turn on, modify, or turn off the activity of vascular endothelial growth factors (VEGFs). Proteolysis is most prominent among the lymph­angiogenic VEGF-C and VEGF-D, which are synthesized as precursors that need to undergo enzymatic removal of their C- and N-terminal propeptides before they can activate their receptors. The activating cleavage of VEGF-C is mediated by at least five different proteases: plasmin, ADAMTS3, prostate-specific antigen, cathepsin D, and thrombin. All of these proteases except for ADAMTS3 can also activate VEGF-D. Processing by different proteases results in distinct forms of the "mature" growth factors, which differ in affinity and receptor activation potential. The “default” VEGF-C-activating enzyme ADAMTS3 does not activate VEGF-D and therefore, VEGF-C and VEGF-D do function in different contexts. VEGF-C itself is also regulated in different contexts by different proteases. During embryonic development, ADAMTS3 activates VEGF-C. In contrast, thrombin and plasmin likely activate VEGF-C/-D during tissue injury-induced lymphangiogenesis, and PSA and cathepsin D perhaps during tumor-associated pathological lymphangio­genesis. Additionally, cathepsin D from saliva might activate latent VEGF-C/-D upon wound licking, thereby accelerating healing. Similar to tyrosine kinase receptors and VEGFs themselves, these activating proteases could be targeted to modulate angiogenesis and lymphangiogenesis in relevant diseases.

COVID-19 sepsis immune response remains unclear. Here we propose a new perspective in host response against pathogenic proteins that may lead to a vaccine design by polymerization of antigens of <70 kDa. In COVID-19, initial Th1 response kills infected cells releasing viral proteins. SARS-CoV-2 viral structural proteins are Spike (140 kDa), Nucleocapsid (50 kDa), Membrane (25 kDa) and Envelope (10 kDa). B cell receptor cannot capture antigens >70 kDa. The Spike protein (140 kDa) cannot be captured by B cells and triggers inflammatory Th1 response via the macrophages. Only proteins with a size <70 kDa can activate B cell receptor and trigger Th2 adaptative humoral response. Moreover, M-25 kDa and E-12 kDa glycoproteins can activate IgM-BCR like oligovalent or monovalent antigens. The sustained infected cells lysis overfeeds high levels of viral proteins <70 kDa, increases B cells activation and, in the shift from Th1 to Th2 immune response, triggers the cytokine storm. The continuous BCR activation increases IL-10 releasing and may lead to immune paralysis.

Perhaps the greatest challenge in the graft copolymerization of acrylic acid onto starch initiated by Fenton’s is the selectivity of the grafting reaction. Low selectivity means that too much of unwanted homopolymer polyacrylic acid is produced. In this paper, it has been analyzed why with this reaction system, involving a water soluble monomer and indirect initiation, the graft selectivity is such a challenge. Several other grafting reactions, especially with monomers of low water solubility or when direct initiation is applied, show a better grafting performance. A scheme is presented based on reaction engineering principles, that supports an explanation of the observed differences. A more selective activation of starch is a factor, but perhaps even more important is a low monomer to starch ratio at the starting sites of graft reactions. Based on these insights, several methods to improve the graft selectivity are evaluated, with the help of literature data but mostly by experimental explorations in our laboratory. Most promising appears to be a dedicated dosage method, to add monomer in portions over time, tested in a batch reactor with gelatinized cassava starch. This way, both grafting percentage and graft selectivity could be improved. Such could not be realized with the more conventional dosage, which is to add all monomer before the start of the reaction. This can be considered a principal breaktrough. Still, more research and development would be needed to refine the method and to implement the idea also in a continuous reactor at larger scale.