We previously described a model of deep intrinsic resistance of breast cancer wherein we used a function-based approach to selection of cancer cells that can survive a variety of challenges in prolonged but reversible quiescence. Our experimental results suggested that resistant cancer cells possess a variety of mechanisms, including modifications of the epigenome and transcriptome, for generating a high degree of cellular heterogeneity. In the present study, we evaluated JIB-04, a small-molecule epigenetic inhibitor initially discovered to inhibit cancer growth, to determine its ability to affect deep intrinsic resistance in our breast cancer model. We found that long pretreatment with JIB-04 sensitized resistant triple-negative inflammatory breast cancer cells and their parental cell line SUM149 to the chemotherapeutic drugs doxorubicin and paclitaxel. Resistant cancer cells derived from another inflammatory breast cancer cell line, FC-IBC02, were considerably more sensitive to JIB-04 than was the parental cell line. Investigating a mechanism of sensitization, we found that JIB-04 exposure increased the expression of PD-L1 in resistant cells, suggesting that JIB-04 may also sensitize resistant breast cancer cells to anti-PD-L1 immune therapy. Finally, these results support the usefulness of our experimental strategy for evaluating anticancer agents such as JIB-04 that may halt cancer evolution and prevent development of cancer resistance to currently used therapies.

Chymotrypsin is an important proteolytic enzyme in human digestion system that cleaves milk proteins, through hydrolysis reaction, which makes it interesting subject to study activity of milk proteases. In this work, we compared detection of chymotrypsin by spectrophotometric, dynamic light scattering (DLS) and quartz crystal microbalance (QCM) methods and determined the limit of chymotrypsin detection (LOD), 0.15 ± 0.01 nM for spectrophotometric, 0.67 ± 0.05 nM for DLS and 1.40 ± 0.30 nM for QCM methods, respectively. We discuss peculiarities and give perspective for implementation of detection methods and note that while the optical detection methods are simple to implement, the QCM method is more robust for sample preparation. We give an overview on methods and instruments for detection of chymotrypsin and other milk proteases.

Boundary behavior of a given important function or its limit values are essential in the whole spectrum of mathematics and science. We consider some tractable cases of limit values in which either a difference of two ingredients or a difference equation is used coupled with the relevant functional equations to give rise to unexpected results. This involves the expression for the Laurent coefficients including the residue, the Kronecker limit formulas and higher order coefficients as well as the difference formed to cancel the inaccessible part, typically the Clausen functions. We also state Abelian results which yield asymptotic formulas for weighted summatory function from that for the original summatory function

The toxin-antitoxin (TA) systems have been attracting attention due to their role in regulating prokaryotic cell responses to stress and their biotechnological potential. Much recognition has been given to type II TA system of mesophiles, but so far, limited attention has been given to thermophiles. Here, we are presenting the putative type II TA families encoded on the genomes of four Geobacillus strains. We employed the TA finder tool to mine for TA-coding genes and manually curated the results using various tools. We identified 28 putative TA pairs, distributed over 8 TA families. Among the identified TAs, 15 represent putative novel toxins and antitoxins that have been overlooked or annotated as hypothetical proteins in their genome records. We also identified a potentially new TA composite, AbrB-ParE. Furthermore, we are suggesting the Geobacillus acetyltransferase toxin-antitoxin (GacTA) family which potentially represents one of the unique TA families that has a reverse gene order. Moreover, we are proposing a hypothesis on the regulation of the xre-cog2856 gene expression, which seems to involve c-di-AMP. This study aims for highlighting the significance of studying TAs in Geobacillus, since they have special features. It also aims for facilitating future experimental research.

We propose a model for medium-term hydropower scheduling (MTHS) with variable head and uncertainty in inflow, reserve capacity, and energy price. With an increase of intermittent energy sources in the generation mix, it is expected that a flexible hydropower producer can obtain added profits by participating in other markets than just the energy market. To capture this added potential the hydropower system should be modeled with a higher level of details. In this context, we apply an algorithm based on stochastic dual dynamic programming (SDDP) to solve the nonconvex MTHS problem, and show that the use of Strengthened Benders (SB) cuts to represent the expected future profit (EFP) function provide accurate scheduling results for slightly nonconvex problems. A method to visualize the EFP function in a dynamic programming setting is provided, serving as a useful tool for a priori inspection of the EFP shape and its nonconvexity.

A lack of data reproducibility (“reproducibility crisis”) is debated across many scientific and medical disciplines. A systematic analysis of the available evidence on the reliability of scientific data revealed that, although the existence of a reproducibility crisis is widely perceived, conclusive data on the scale of the problem are lacking. Most importantly we found that, although the debate is largely focused on methodological issues, researcher conduct defines research standards and in turn data reliability. The availability of reliable methods itself does not guarantee good practice. Moreover, research is typically characterised by a lack of established methods due to its immanent novelty. Despite the crucial importance of researcher conduct, research and conclusive data on the determinants of researcher behaviour are missing. In conclusion, meta-research is urgently needed that establishes an understanding of the factors that determine researcher behaviour. This knowledge can then be used to implement and iteratively improve measures, which incentivise researchers to apply the highest standards resulting in high quality data.

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

Granulomatous mastitis is a benign disease with a clinical presentation similar to that of breast cancer, and is most commonly observed in women of childbearing age. Although it has been suggested that autoimmune diseases are involved in its pathogenesis, no specific treatments have been established. The occurrence of this disease during pregnancy has rarely been reported. Our patient was a 37-year-old woman. She was pregnant and manifested a dichorionic, diamniotic placenta. At 24 weeks of gestation, the patient experienced a sensation of hardness in her left breast. Mastitis was suspected, and she was treated with cephem antibiotics. Simultaneously, she was diagnosed with erythema nodosum in the extremities. As her symptoms did not improve, an incisional drainage was performed. Bacterial cultures were obtained at 31 weeks of gestation, and Corynebacterium kroppenstedtii was detected. An elective cesarean section was performed at 37 weeks of gestation, and the baby was delivered safely. After delivery, a needle biopsy was performed, and the patient was diagnosed with granulomatous mastitis. She was completely cured with prednisolone after weaning. In this case, the patient's condition was maintained through incision and drainage; and antibiotic, anti-inflammatory, and analgesic drugs during pregnancy. This approach was chosen, taking into consideration the potential side effects of steroids. After delivery, breastfeeding and steroidal therapy proved to be effective in treating the condition.

We introduce a number of techniques in quantitative convergent-beam electron diffraction under development by our group and discuss the basis for measuring interatomic electrostatic potentials (and therefore also electron densities), localised at sub-nanometre scales, with sufficient accuracy and precision to map chemical bonds in and around nanostructures in nanostructured materials. This has never before been possible as experimental measurements of bonding in quantum crystallography have hitherto always been restricted to homogeneous single-phased crystals.

Dengue virus (DENV) and chikungunya virus (CHIKV) are reemergent arboviruses that are transmitted by mosquitoes of the Aedes genus. During the last several decades, these viruses have been responsible for millions of cases of infection and thousands of deaths worldwide. Therefore, several investigations were conducted over the past few years to find antiviral compounds for the treatment of DENV and CHIKV infections. One attractive strategy is the screening of compounds that target enzymes involved in the replication of both DENV and CHIKV. In this review, we describe advances in the evaluation of natural products targeting the enzymes involved in the replication of these viruses.

Pigs are a social species and they stablish hierarchies for a better use of resources and to reduce conflicts. However, in pig production, the opportunities for growing can differ in dominant and subordinate animals. In the present study a system was tested to perform a Dominance versus Subordinate test in growing pigs to investigate how the hierarchy affects feeding behaviour, growth and gut microbiota assessed in faeces. 64 animals housed in eight different pens were used, with four castrated males and four females in each one, weighing 18kg at arrival and maintained during the whole growing period, until 140 kg. Three stool samplings were obtained from the animals directly from the anus to avoid contamination of the faeces on 58, 100 and 133 days after the start of the study to investigate the microbiota composition. The dominant animals had higher gains during the growing period that the subordinate. In addition, they were performing more visits to the feeder throughout the day. Differential abundance patterns were observed in five bacterial genera, Oliverpabstia, Peptococcus, and Faecalbacterium being more abundant in dominant animals and Holdemanella and Acetitomaculum being overrepresented in subordinate ones. This microbial biomarker accurately classified dominant versus subordinate groups of samples with an AUC of 0.92.

The whimsical Las Vegas/Monte Carlo cubic dice are generalized to construct the combinatorial problem of enumerating all n-dimensional hypercube dice, and dice of other shapes that exhibit cubic, icosahedral and higher symmetries. By utilizing powerful generating function techniques for various irreducible representations, we derive the combinatorial enumerations of all possible dice in n-dimensional space with hyperoctahedral symmetries. Likewise a number of shapes that exhibit icosahedral symmetries such as a truncated dodecahedron and a truncated icosahedron are considered for the combinatorial problem of dice enumerations with the corresponding shapes. We consider several dice with cubic symmetries such as truncated octahedron, dodecahedron and Rubik’s cube shapes. It is shown that all enumerated dice are chiral and we provide the counts of chiral pairs of dice in the n-dimension space. During the combinatorial enumeration, it was discovered that two different shapes of dice exist with the same chiral pair count culminating into the novel concept of isochiral polyhedra. The combinatorial problem of dice enumeration is generalized to multi-coloring partitions. Applications to chirality in n-dimension, molecular clusters, zeolites, mesoporous materials, cryptography and biology are also pointed out. Applications to nonlinear n-dimensional hypercube and other dicey encryptions are exemplified with romantic, clandestine messages; “I love U” and “V Elope at 2”.

Recently, attention mechanisms have developed into an important tool for performance improvement of deep neural networks. In computer vision, attention mechanisms are generally divided into two main branches: spatial and channel attention. Both attention categories have their own advantages. The fusion of both attentions achieves higher performance, on the cost of the computational load. This paper introduces an innovative and lighter n-shifted sigmoid channel and spatial attention (CSA) module to reduce the computational cost and to improve the 3D scene relevant features selection. To validate the proposed attention module, 3D scene object detection in the deep Hough voting point sets is considered as the testing application. The proposed attention module with its piecewise n-shifted sigmoid activation function improves the network’s learning and generalization capacity which effectively predict bounding box parameters directly from 3D scenes and detect objects more accurately. This advantage is achieved by selectively attending to more relevant features of the input data. When used in the deep Hough voting point sets, the proposed attention module outperforms state-of-the-art 3D detection methods on the sizable SUNRGBD dataset. Experiments conducted showed an increase of 12.02 mean accuracy precision (mAP) when compared to the celebrated VoteNet (without attention). It also got 9.92 mAP higher compared to the MLVCNet, and 10.32 mAP higher than the Point Transformer. The proposed model not only decreases the sigmoid vanishing gradient problem but also brings out valuable features by fusing channel-wise and spatial information while improving accuracy results in 3D object detection.

N-Acetyl-L-glutamate kinase (NAGK) catalyzes the rate-limiting step in the ornithine/arginine biosynthesis pathway in eukaryotic and bacterial oxygenic phototrophs. NAGK is the most highly conserved target of the PII signal transduction protein in Cyanobacteria and Archaeplastida (red algae and Chlorophyta). However, yet there is still much to be learnt on how NAGK is regulated in vivo. The use of unicellular green Chlamydomonas reinhardtii as a model system has already been instrumental in identifying several key regulation mechanisms that control nitrogen (N) metabolism. With a combination of molecular-genetic and biochemical approaches, we show the existence of the complex CrNAGK control at transcriptional level, which is dependent on N source and N availability. In growing cells, CrNAGK requires CrPII to properly sense the feedback inhibitor arginine. Moreover, we provided primary evidence that CrPII is only partly responsible for regulating CrNAGK activity to adapt to changing nutritional conditions. Collectively, our results suggest that in vivo CrNAGK is tuned at transcriptional and post-translational levels, and CrPII and additional as yet unknown factor(s) are integral parts of this regulation.

In the present study we tested the effect of small molecular weight redox molecules on collagen-induced platelet aggregation. We used N-acetylcysteine amide (AD4), the amide form of N-acetylcysteine (NAC), a thiol antioxidant with improved lipophilicity and bio-availability compared to NAC, and the thioredoxin mimetics (TXM) peptides, TXM-CB3, TXM-CB13, and TXM-CB30. All compounds significantly inhibited platelet aggregation induced by collagen, with TXM-peptides and AD4 being more effective than NAC. The levels of TxB2 and 12-HETE, the main metabolites derived from the cyclooxygenase and lipoxygenase pathways following platelet activation, were significantly reduced in the presence of AD4, TXM-peptides, or NAC, when tested at the highest concentration (0.6 mM). The effect of AD4, TXM-peptides, and NAC was tested also on the clotting time (CT) of whole blood. TXM-CB3 and TXM-CB30 showed the highest increase of CT. Furthermore, two representative compounds, TXM-CB3, and NAC, showed an increase in the an-ti-oxidant free sulfhydryl groups of plasma detected by Ellman’s method, suggesting a contribution of plasma factors to the antiaggregating effects. Our results suggest that these small molecular weight redox peptides might become useful for the prevention and/or treatment of oxidative stress conditions associated with platelet activation.

Firstly, we present a more explicit formulation of the complete system $D(N)$ of representatives of Manin's symbols over $\mathbb{Q}$, which was initially given by Shimura. Then we establish a bijection between $D(M)\times D(N)$ and $D(MN)$ for $(M,N)=1$, which reveals a recursive structure between Manin's symbols of different levels. Based on Manin's complete system $\Pi (N)$ of representatives of cusps on $X_0(N)$ and Cremona's characterization of the equivalence between cusps, we establish a bijection between a subset $C(N)$ of $D(N)$ and $\Pi (N)$, and then establish a bijection between $C(M)\times C(N)$ and $C(MN)$ for $(M,N)=1$. We also provide a recursive structure for elliptical points on $X_0(N)$. Based on these recursive structures, we obtain recursive algorithms for constructing Manin symbols over $\mathbb{Q}$, cusps and elliptical points on $X_0(N)$. This gives rise to a more efficient algorithms for modular elliptic curve. As direct corollaries of these recursive structures, we present a recursive version of the genus formula and an elementary proof of formulas of the numbers of $D(N)$, cusps and elliptical points on $X_0(N)$.

In this paper, new N-way Wilkinson power dividers (WPDs) are represented by using slow-wave structures such as narrow slits loaded and meandered transmission lines. The slit loaded and meandered lines are used to represent the quarter wavelength transmission lines of a conventional WPD for size reduction. Based on the proposed approaches, 2-, 4- and 8-way power dividers are designed, simulated and fabricated. The fabricated -, 4- and 8-way circuits have been measured at the center frequencies of 2.03, 1.77, and 1.73 GHz in an excellent agreement with the predicted ones. The meandered transmission lines are also used to design new types of WPDs having novel input/output port arrangements. For this purpose, two 3-way WPDs are located at both sides of the same board so as to have different power splitting ratios at different inputs and outputs to provide alternative solutions for antenna arrays. Furthermore, a 5-way dual layer WPD is introduced by locating the meandered transmission lines to two layers. The proposed 3- and 5-way WPDs allow halving the input power at the next output port in the order of P/2, P/4, P/8, P/16, and P/16. All of the designed power halving WPDs have been simulated, fabricated and successfully tested.

We present improvements in n-best rescoring of code-switched speech achieved by n-gram augmentation as well as optimised pretraining of long short-term memory (LSTM) language models with larger corpora of out-of-domain monolingual text. In addition, we consider the application of large pretrained transformer-based architectures. Our experimental evaluation is performed on an under-resourced corpus of code-switched speech comprising four bilingual code-switched sub-corpora, each containing a Bantu language (isiZulu, isiXhosa, Sesotho, or Setswana) and English. We find in our experiments that, by combining n-gram augmentation with the optimised pretraining strategy, speech recognition errors are reduced for each individual bilingual pair by 3.51% absolute on average over the four corpora. Importantly, we find that even speech recognition at language boundaries improves by 1.14% even though the additional data is monolingual. Utilising the augmented n-grams for lattice generation, we then contrast these improvements with those achieved after fine-tuning pretrained transformer-based models such as distilled GPT-2 and M-BERT. We find that, even though these language models have not been trained on any of our target languages, they can improve speech recognition performance even in zero-shot settings. After fine-tuning on in-domain data, these large architectures offer further improvements, achieving a 4.45% absolute decrease in overall speech recognition errors and a 3.52% improvement over language boundaries. Finally, a combination of the optimised LSTM and fine-tuned BERT models achieves a further gain of 0.47% absolute on average for three of the four language pairs compared to M-BERT. We conclude that the careful optimisation of the pretraining strategy used for neural network language models can offer worthwhile improvements in speech recognition accuracy even at language switches, and that much larger state-of-the-art architectures such as GPT-2 and M-BERT promise even further gains.

In this review, we provide an overview of the most common majority and minority charge carrier traps in n-type 4H-SiC material. We focus on the results obtained by different applications of junction spectroscopy techniques. The basic principles behind the most common junction spectroscopy techniques are given. These techniques, namely, deep level transient spectroscopy (DLTS), Laplace DLTS (L-DLTS) and minority carrier transient spectroscopy (MCTS) have led to recent progress in identifying and better understanding of the charge carrier traps in n-type 4H-SiC material.

It is unclear how important it is to reduce fluoroquinolone consumption in the general population to prevent the spread of fluoroquinolone resistance in Neisseria gonorrhoeae (bystander selection). Methods We assessed bystander selection by using Spearman’s correlation to assess if the country-level prevalence of fluoroquinolone resistance in N. gonorrhoeae was correlated with the prevalence of fluoroquinolone resistance in four other gram-negative species - Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa. Results Fluoroquinolone resistance in N. gonorrhoeae was positively associated with homologous resistance in all 4 species - A. baumanii. (ρ=0.61, P=0.0003, E. coli (ρ=0.67, P<0.0001), K. pneumoniae (ρ=0.52, P=0.0004) and P. aeruginosa (ρ=0.40, P=0.0206). Positive associations were also found between the national prevalence of fluoroquinolone resistance and fluoroquinolone consumption in the general population in the preceding year for 4 of the 5 species. Conclusions Gonococcal fluoroquinolone resistance can be productively viewed as being part of a syndemic of fluoroquinolone resistance. Strengthening antimicrobial stewardship programs may help retard the spread of fluoroquinolone resistance in N. gonorrhoeae.

This study numerically analyzed the effect of composition and temperature and oxygen concentration changes on the selfignition characteristics of n-heptane/methane blended fuels in order to cope with development of alternative fuels and international environmental regulations. CHEMKIN-PRO is used as the analysis program and the LLNL model is used as the reaction model. The numerical results revealed that on autoignition and ignition delay time were sensitive to changes in fuel composition and oxygen concentration. As the methane ratio increases, OH radicals causing ignition are delayed in generation and the concentration is lowered, thus longer the ignition timing. The oxygen concentration in the mixed fuels are changed to simulate the exhaust gas recirculation and a numerical analysis in then performed. As the oxygen concentration decreases, the ignition delay time longer because the nitrogen gas acts as a thermal load in the combustion chamber.

The infections caused by Chikungunya virus (CHIKV), genus Alphavirus, have become a health problem around the world, due to this virus’s widespread occurrence and high morbidity rate and the absence of vaccines or antiviral drugs. In this study, we analyzed a competitive inhibitor of ornithine decarboxylase—an enzyme that is key in the biosynthesis of polyamines (PAs), N-ω-chloroacetyl-L-ornithine (NCAO), which is a possible inhibitor of CHIKV replication because intracellular polyamines participate in the in vitro transcription and translation of CHIKV. NCAO does not have any cytotoxic effect on C6/36 cells even at 1000 μM at 72 h post-exposure. However, in Vero cells, a cytotoxic effect was present above 380 μM at 48 h post-exposure, which was considered when determining the inhibitory effect on viral replication. In this work, we demonstrate that NCAO inhibits the replication of CHIKV in Vero and C6/36 cells in a dose-dependent manner, causing a decrease in the PFU/mL of at least 4 logarithms (p <0.01) in both cell lines. Viral yields were restored by the addition of exogenous polyamines, mainly putrescine. The HPLC analyses showed that NCAO decreases the content of intracellular PAs, even though mainly spermidines and spermines are present in infected cells. NCAO inhibits CHIKV replication by depleting the intracellular polyamines in Vero and C6/36 cells, suggesting that this compound is a possible antiviral for CHIKV infections.

Group IV phospholipase A₂α (cPLA₂α) regulates the production of prostaglandins and leukotrienes via the formation of arachidonic acid from membrane phospholipids. The targeting and membrane binding of cPLA₂α to the Golgi involves the N-terminal C2 domain whereas the catalytic domain produces arachidonic acid. Although most studies of cPLA₂α concern its catalytic activity, it is also linked to homeostatic processes involving the generation of vesicles that traffic material from the Golgi to the plasma membrane. Here we investigate how membrane curvature influences the homeostatic role of cPLA₂α in vesicular trafficking. The cPLA₂α C2 domain is known to induce changes in positive membrane curvature, a process which is dependent on cPLA₂α membrane penetration. We show that cPLA₂α undergoes C2 domain-dependent oligomerization on membranes in vitro and in A549 cells. We found that the association of the cPLA₂α C2 domain with membranes is limited to membranes with positive curvature, and enhanced C2 domain oligomerization was observed on vesicles ~50 nm in diameter. We demonstrated that the cPLA₂α C2 domain generates cholesterol enriched Golgi-derived vesicles independently of cPLA₂α catalytic activity. Our results therefore provide novel insight into the molecular forces that mediate C2 domain-dependent membrane localization in vitro and in cells.

This study investigated the removal characteristics of N-nitrosamines and their precursors at three pilot-scale water reclamation plants. These plants applies different integrated membrane systems: (1) microfiltration (MF) / nanofiltration (NF) / RO; (2) sand filtration/three-step RO; and (3) ultrafiltration (UF) / NF and UF / RO. Variable removal of N-nitrosodimethylamine (NDMA) by the RO membrane processes could be attributable to membrane fouling and feed water temperature. The effect of membrane fouling on N-nitrosamines removal was extensively evaluated at one of the plants by conducting one month of operation and chemical cleaning of the RO membrane element. Membrane fouling enhanced N-nitrosamines removal by the pilot-scale RO membrane process. This finding contributes to better understanding of variable removal of NDMA by RO membrane processes. This study also investigated the removal characteristics of N-nitrosamines precursors. The NF and RO membrane processes greatly reduced NDMA formation potential (FP), but the UF process had little effect. The contributions of MF, NF, and RO membrane processes for reducing FPs of NDMA, N-nitrosopyrrolidine (NPYR) and N-nitrosodiethylamine (NDEA) were different, suggesting different size distributions of their precursors.

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

This paper presents a novel segmentation algorithm specially developed for applications in 3D point clouds with high variability and noise, particularly suitable for heritage building 3D data. The method can be categorized within the segmentation procedures based on edge detection. In addition, it uses a graph-based topo-logical structure generated from the supervoxelization of the 3D point clouds, which is used to make the clo-sure of the edge points and to define the different segments. The algorithm provides a valuable tool for generating results that can be used in subsequent classification tasks and broader computer applications dealing with 3D point clouds. One of the characteristics of this segmentation method is that it is unsupervised, which makes it particularly advantageous for heritage applications where labelled data is scarce. It is also easily adaptable to different edge point detection and supervoxelization algorithms. Finally, the results show that the 3D data can be segmented into different architectural elements, which is important for further classification or recognition. Extensive testing on real data from historic buildings demonstrates the effectiveness of the method. The results show superior performance compared to three other segmentation methods, both globally and in the segmentation of planar and curved zones of historic buildings.

Background: breastfeeding is the optimal nourishment for infants and recommends that children commence breastfeeding within the first hour of birth and be exclusively breastfed for the initial 6 months of life. Our objective was to determine which factors related to mothers could influence the degree of exclusive breastfeeding during hospitalization, as well as to assess breastfeeding mothers' attitudes towards breastfeeding. Methods: A multicenter cross-sectional study was undertaken in the healthcare area of Santiago de Compostela, Spain. The reduced Iowa Infant Feeding Attitude Scale (IIFAS-s) was employed to gauge maternal attitudes toward feeding their baby. Results: 64 women were studied. The overall score of IIFAS-s (mean ± standard deviation) was 36.95 ± 5.17. No use of pacifier by the newborn was associated with a positive attitude for breastfeeding. Having previous children (ORa=6,40; IC95% 1,26 – 32,51) and previous experience with breastfeeding (ORa=6,70; IC95% 1,31 – 34,27) increase the likelihood of exclusive breastfeeding during admission. Conclusions: It is important to identify the factors that contribute to increasing the probability that mothers choose exclusive breastfeeding. We must guide our training efforts to these factors.

Kombucha is a two-stage fermented sweetened-tea beverage that uses yeast and lactic acid bacteria (LAB) to convert sugars into ethanol and lactate, and acetic acid bacteria (AAB) to oxidize ethanol to acetate. Its popularity as a beverage grew from claims of health-benefits derived from this vibrant microbial bioconversion. While recent studies have shed light on the diversity of cultures during a Kombucha fermentation, there is limited information on the diversity, and especially viability, of cultures in retail beverages that advertise the presence of Kombucha and probiotic cultures. In this study, 12 Kombucha beverages produced by different manufacturers throughout the US were purchased and microbially characterized. Eight of the beverages contained viable Kombucha cultures, while 3 of the remaining 4 had viable Bacillus cultures as added probiotics. Amplicon profiling revealed all contained Kombucha yeast and bacteria cells. The dominant yeast detected were Lachancea cidri (10/12), Brettanomyces (9/12), Malassezia (6/12) and Saccharomyces (5/12). Dominant LAB included Liquorilactobacillus and Oenococcus oeni, and AAB were Komagataeibacter, Gluconobacter and Acetobacter. One beverage had a significant amount of Zymomonas mobilis, an ethanol producing bacterium from Agave cactus. While Kombucha beverages differ in the types and viability of cultures, all except one beverage contained detectable viable cells.

An electrothermal analysis for barium titanate based ceramics is presented combining the Heywang–Jonker model for the electric resistivity with a heat dissipation mechanism based on natural convection and radiation in a one dimensional model on the device level with voltage as the control parameter. Both PTC and NTC effects are accounted for through the double Schottky barriers at the grain boundaries of the material. The problem formulated in this way admits uniform and non–uniform multiple steady state solutions that do not depend on the external circuit. The numerical bifurcation analysis reveals that the PTC effect gives rise to several multiplicites above the Curie point, whereas the NTC effect is responsible for the thermal runaway (temperature blowup). The thermal runaway phenomenon as a potential thermal shock could be among the possible reasons for the observed thermomechanical failures (delamination fracture). The theoretical results for the NTC regime and the thermal runaway are in agreement with experimental flash sintering results obtained for 3% and 8% yttria stabilized zirconia.

Lie algebra plays an important role in the study of singularity theory and other field of sciences. Finding numerous invariants linked with isolated singularities is always a main interest in the classification theory of isolated singularities. Any Lie algebra that characterizes simple singularity produces a natural question. The study of properties such as to find the dimensions of newly defined algebra is a remarkable work. Hussain, Yau and Zuo \cite{HYZ10} have been found a new class of Lie algebra \texorpdfstring{ $ \mathcal{L}_ k (V)$}{LG}, \texorpdfstring{$k\geq 1$}{LG} i.e., Der ($M_{k}(V), M_{k}(V)$) and purposed a conjecture over its dimension $\delta_{k}(V)$ for $k\geq0$. Later they proved it true for $k$ up to $k=1,2,3,4,5$. In this work, the main concern is whether it's true for a higher value of $k$. According to this, we calculate first, the dimension of Lie algebra \texorpdfstring{$\mathcal{L}_ k (V)$}{LG} for $k=6$ and then compute the upper estimate conjecture of fewnomial isolated singularities. Along with, we also justify the inequality conjecture: \texorpdfstring{$\delta_{k+1}(V) < \delta_{k}(V)$}{LG} for $k=6$. Our calculated results are innovative and a new addition to the study of singularity theory.

Nucleobase-containing molecules are compounds essential in biology due to the fundamental role of nucleic acids, and in particular G-quadruplex DNA and RNA in life. Moreover, some molecules different from nucleic acids isolated from different vegetal sources or microorganisms show nucleobase moieties in their structure. Nucleoamino acids and peptidyl nucleosides belong to this molecular class. Closely related to the above, nucleopeptides also known as nucleobase-bearing peptides are chimeric derivatives of synthetic origin and more rarely isolated from plants. Herein the self-assembly properties of a vast number of structures, belonging to the nucleic acid and nucleo amino acid/nucleopeptide family, is explored in the light of the recent scientific literature. Moreover, several technologically relevant properties such as the hydrogelation ability of some of the nucleobase-containing derivatives are reviewed in order to open the door to future experimental investigations of newly-inspired nucleobase-driven hydrogels. Nucleobase-containing molecules, such as mononucleosides, DNA, RNA, quadruplex (G4)-forming oligonucleotides and nucleopeptides, are paramount in gel and hydrogel formation owing to their distinctive molecular attributes and ability to self-assemble in biomolecular nanosystems with the most diverse applications in different fields of biomedicine and nanotechnology. In fact, these molecules and their gels present numerous advantages, underscoring their significance and applicability in both material science and biomedicine. Their versatility, capability for molecular recognition, responsiveness to stimuli, biocompatibility, and biodegradability collectively contribute to their prominence in modern nanotechnology and biomedicine. In this review, we emphasize the critical role of nucleobase-containing molecules of different nature in pioneering novel materials with multifaceted applications highlighting their potential in therapy, diagnostics, and new nanomaterials fabrication as required in order to address the numerous current biomedical and nanotechnological challenges.

In this work, we propose a Fog-enabled UAV-as-a-Service (FU-Serve) architecture to address the issues of data transmission delay for serving time-critical Internet of Things (IoT) applications. Traditionally, in a UAV-as-a-Service (UaaS) platform, different UAVs host heterogeneous sensors, which sense the physical phenomenon and transmit the sensed data to a centralized entity. Transmission of data from the sensors to the centralized entity and making any decision for an application consumes a significant amount of time. Consequently, the traditional UaaS architecture is unsuitable for serving time-critical IoT applications such as transportation, healthcare, and industries. To address these issues of service latency for time-critical IoT applications, we present the FU-Serve architecture by introducing the concept of fog computing in the UaaS platform. We discuss all the components of FU-Serve elaborately in this paper. Additionally, we architect optimal and dynamic fog node selection mechanisms for FU-Serve, which reduce the transmission delay in the networks. The simulation results show that the FU-Serve outperforms by $75\%$ compared to the traditional UaaS platform.

Single Image Super Resolution (SSIR) is a problem in computer vision where the goal is 1 to create high-resolution images from low-resolution ones. It has important applications in fields 2 such as medical imaging and security surveillance. While traditional methods such as interpolation 3 and reconstruction-based models have been used in the past, deep learning techniques have recently 4 gained attention due to their superior performance and computational efficiency. This article proposes 5 an Autoencoder based Deep Learning Model for SSIR, in particular, a light model that uses fewer 6 parameters without compromising performance. The down-sampling part of the Autoencoder 7 mainly uses 3 by 3 convolution and has no subsampling layers. The up-sampling part uses transpose 8 convolution and residual connections from the down sampling part. The model is trained using a 9 subset of the VILRC ImageNet database. The model is evaluated using quantitative metrics PSNR, 10 SSIM as well as qualitative measures such as perceptual quality. PSNR and SSIM figures as high as 11 76.06 and 0.93 are reported.

This review article is devoted to the colloidal properties of fullerene solutions. According to generally accepted understanding, all solvents in relations to fullerenes are divided into “good” (or “strong” or “high-solubility” ones), “poor” (usually polar) and “reactive”. Water occupies a special place, close to “poor” solvents. We have consistently considered and discussed the state of fullerenes in these systems. In "good", predominantly non-polar aromatic solvents and CS2, nonequilibrium dissolution methods lead to the formation of colloidal aggregates, whereas utilization of equilibrium methods results in the formation of molecular solutions. The latter, however, have some unusual properties; new results confirm previously expressed ideas about colloidal properties of these solutions. Both experimental and theoretical methods devoted to such systems are considered. In “poor” (polar) solvents, typical lyophobic colloidal systems appear. Both “bottom-up” and “top-down” methods of preparation are now well documented in the literature. However, some of these polar solvents dissolve fullerenes rather easily and with less energy consumption. In addition to N-methylpyrrolidin-2-one, which has been well studied for fullerenes, DMSO and DMF have now been described. These solvents can be considered a subset of poor solvents that have some features of being “reactive” at the expense of basic (“cationophilic”) properties. Room temperature ionic liquids are also used to dissolve fullerenes, but there is little experimental research. Hydrosols and aqueous suspensions of fullerenes are typical hydrophobic colloids that obey the Schulze–Hardy rule and other regularities in the presence of electrolytes. New experimental data confirm the previously obtained results. Organosols in acetonitrile and methanol are much less stable with respect to electrolytes; the difference in critical coagulation concentrations of electrolytes reaches two to three orders of magnitude. This allows us to conclude that there is an additional, so-called non-DLVO, stabilizing factor in the hydrosols. Accordingly, the value of the Hamaker constant of fullerene-fullerene interaction may be higher than that derived from coagulation data in water. Contrary to the mentioned “poor” polar solvents, the stability of fullerene sols in DMSO is even higher than in water. These results, as well as data obtained with DMF demonstrate strong solvation of fullerenes with basic solvents.

The composite coatings prepared by mixing the 5 wt.% of polyaniline with commercial alkyd-based paint are applied on carbon steel. The polyaniline emeraldine chloride salt is prepared by procedure recommended by IUPAC, deprotonated by ammonia hydroxide, and reprotonated with the sulfamic, succinic, citric, and acetic acids with different doping degrees or oxidation states. The steel samples with base and composite coatings are immersed in 3% NaCl and the corrosion current density is determined after 96 h in-site using ASTM 1,10-phenanthroline method. The samples are also inspected by the optical microscope. It is shown that composite coatings reduce the possibility of blister formations and delamination. The corrosion current density and the appearance of the corrosion products, which area is determined by ImageJ softer, closely follow the initial oxidation state of the polyaniline. The role of the initial state of the polyaniline is discussed. It is suggested that such behavior could be connected with the oxygen reduction reaction mechanism that proceeds mainly via two electron paths on the polyaniline particles, releasing a much smaller amount of hydroxyl ions, responsible for the delamination and blister formations of the commercial coatings.

Functional gastrointestinal disorders (FGIDs) are common in children and adolescents. In recent years, interest in the role of diet in the treatment of FGIDs has increased. Currently, interest focus-es on the low-FODMAP diet (LFD), the fructose- or lactose-restricted diet (FRD or LRD), the glu-ten-free diet (GFD), and the Mediterranean diet (MD). In this review, we focus on the role of these dietary patterns in the FGIDs most commonly diagnosed in clinical practice, namely irritable bowel syndrome (IBS), functional abdominal pain (FAP), functional dyspepsia (FD), and func-tional constipation (FC). Fifteen clinical trials were systematically reviewed (both RCTs and sin-gle arm clinical trials). We demonstrated the lack of high-quality intervention trials. Based on current evidence, low-FODMAP diet, LRD, FRD, or GFD have no place in daily practice for the management of children and adolescents with FGIDs. Nevertheless, some patients with IBS or RAP may have some benefit from the use of a low-FODMAP diet or FRD/LRD. Limited data sug-gest that MD may be promising in the management of FGIDs, especially in IBS patients, but more data are required to investigate the mechanisms of its protective effects.

NMR spin relaxation times have been an instrumental tool in deciphering the local en-vironment of ionic species, the various interactions they engender and the effect of these interactions on their dynamics in conducting media. Of particular importance has been their application in studying the wide range of electrolytes for energy storage, on which this chapter is based. Here we highlight some of the research carried out on electrolytes in recent years using NMR relaxometry techniques. Specifically, studies on liquid electro-lytes, such as ionic liquids and organic solvent; on semi-solid-state electrolytes, such as ionogels and polymer gels, and solid electrolytes such as glasses, glass ceramics and polymers. Although this chapter focuses on a small selection of materials, we believe they demonstrate the breadth of application and the invaluable nature of NMR relaxometry.

Cisplatin (CDDP), carboplatin (CP), and oxaliplatin (OXP) are three platinating agents clinically approved worldwide for use against a variety of cancers. They are canonically known as DNA damage inducers; however, that is only one of their mechanisms of cytotoxicity. CDDP mediates its effects through DNA damage-induced transcription inhibition and apoptotic signalling. In addition, CDDP targets the endoplasmic reticulum (ER) to induce ER-stress, the mitochondria via mitochondrial DNA damage leading to ROS production, and the plasma membrane and cytoskeletal components. CP acts in a similar fashion to CDDP by inducing DNA damage, mitochondrial damage, and ER stress. Additionally, CP is also able to upregulate micro-RNA activity, enhancing intrinsic apoptosis. OXP, on the other hand, at first induces damage to all the same targets as CDDP and CP, yet it is also capable of inducing immunogenic cell death via ER stress and can decrease ribosome biogenesis through its nucleolar effects. In this comprehensive review, we provide detailed mechanisms of action for the three platinating agents, going beyond their nuclear effects to include their cytoplasmic impact within cancer cells. In addition, we cover their current clinical use and limitations, including side effects and mechanisms of resistance.

COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), is estimated to have caused over 6.5 million deaths to date worldwide. The emergence of fast-evolving SARS-CoV-2 variants of concern alongside increased transmissibility and/or virulence as well as immune and vaccine escape capabilities highlight the urgent need for more effective antivirals to combat the disease in the long run along with regularly updated vaccine boosters. One of the early risk factors identified during the COVID-19 pandemic was that men are more likely to get infected by the virus, more likely to develop severe disease and exhibit higher likelihood of hospitalisation and mortality rates compared to women. An association exists between SARS-CoV-2 infectiveness and disease severity with sex steroid hormones and in particular androgens. Several studies underlined the importance of the androgen-mediated regulation of the host protease TMPRSS2 and the cell entry protein ACE2 as well as the key role of these factors in the entry of the virus into target cells. In this context, modulating androgen signalling is a promising strategy to block viral infection and antiandrogens could be used as a preventative measure at the pre- or early-hospitalisation stage of COVID-19 disease. Different antiandrogens, including commercial drugs used to treat metastatic castration-sensitive prostate cancer and other conditions, have been tested as antivirals with varying success. In this review, we summarise the most recent updates concerning the use of antiandrogens as prophylactic and therapeutic options for COVID-19.

The recent development of the Internet has boosted the extension of online food services by enabling people to search, compare prices and conveniently access these services. Because, only with an online system, small and medium-sized economic actors can compete with established food company such as McD and KFC. Therefore, it is important to know consumer behavior patterns from online food ordering systems for developing marketing strategies. Exploring online consumer behavior provides a better understanding of consumer segmentation in food demand and thus helps to lay the foundation for developing an online marketing strategy for competitive advantage. The purpose of this study is to finding factors affecting attitude towards online food retailing. This study uses a quantitative approach by involving respondents who often use online food ordering systems (Go-Food) applications in Bandung. The results showed that hedonic motivation and price saving orientation had no significant effect on behavior intention toward OFD services by Go-Food, while time saving orientation, prior online purchase experience and convenience motivation had a significant effect on behavior intention toward OFD services.

Intramammary infections (mastitis) of dairy cows, along with other periparturient diseases, have become problematic within the dairy industry as they lead to loss of milk production. The main objective of this study was to determine whether elevated somatic cell counts (SCC) in cows prior to drying off are related to the incidence of other periparturient diseases. Additionally, we de-termined whether milk composition and milk yield are affected by a high SCC prior to drying off. Somatic cell counts of milk samples were determined prior to dry off (n = 140) and were used to classify cows in the study as high (>200,000 cells/mL) or low (<200,000 cells/mL) SCC. The com-position of milk was analyzed before drying off and at 1 and 2 weeks after calving. The results showed that an elevated SCC before drying off was related to the incidence of ketosis. Cows with a high SCC at drying off also showed an increased likelihood of retained placenta, metritis, and lameness postpartum; however, it was not statistically significant. Milk lactose was lower in cows with high SCC, while protein content was lower after parturition. Milk production was lower for cows with pre-drying elevated SCC, particularly for cows with retained placenta, keto-sis, and mastitis. In conclusion, cows with pre-drying elevated SCC were more likely to develop disease after parturition and produce less milk and with lower lactose and protein content.

In this work, we introduce a generalized measure of cumulative residual entropy and study its properties. We show that several existing measures of entropy such as cumulative residual entropy, weighted cumulative residual entropy and cumulative residual Tsallis entropy, are all special cases of the generalized cumulative residual entropy. We also propose a measure of generalized cumulative entropy, which includes cumulative entropy, weighted cumulative entropy and cumulative Tsallis entropy as special cases. We discuss generating function approach using which we derive different entropy measures. Finally, using the newly introduced entropy measures, we establish some relationships between entropy and extropy measures.

Databases are by far the most valuable asset of companies. Since the need was seen not only to count but also to have some type of record of elements such as crops, animals, money, properties and that this record could be consulted and modified according to the situation, that is where the first database was born. , and after that, these databases cannot be disorganized, they also need to be managed and administered under established standards that facilitate their understanding and management not only by their creators but by the other people who subsequently administer them. Databases and database management systems have an interesting evolutionary history that deserves to be analyzed and this is the objective of this document, where it is sought to understand. Along with databases and their management systems, data mining or Data mining arises that in order not to extend ourselves so much, it is the job of finding common patterns in various data sources and in what way they can be used to predict situations or results of various circumstances; We also focus on the other topic that we will present, Oracle data mining, which roughly is to merge data mining with Oracle, which makes it a powerful tool for obtaining information and predicting results based on statistics.In this article we will study and analyze the ideas, concepts and basic examples that make up SGBD and Data Mining and, we will try to go deeper into this topic, the use of decision techniques such as advanced statistical algorithms. We also present a fictitious example of the application of these techniques: predicting which products can be sold based on their relationship with others. we will give a brief explanation of association rules, data mining cycle and the types of learning and the evolution that data mining has had.

This paper deals with developing a new class of quaternions, called hyper-dual Horadam quaternions which are constructed from the quaternions whose components are hyper-dual Horadam numbers. We investigate the algebraic properties of these quaternions.

Metal nanoparticles are used to modify/enhance the properties of a polymer matrix for a broad range of applications in bio-nanotechnology. Here, we study the properties of polymer/gold nanoparticle (NP) nanocomposites through atomistic molecular dynamics, MD, simulations. We probe the structural, conformational and dynamical properties of polymer chains at the vicinity of a gold (Au) NP and a functionalized (core/shell) Au NP, and compare them against the behavior of bulk PE. The bare Au NPs were constructed via a systematic methodology starting from ab-initio calculations and an atomistic Wulff construction algorithm resulting in the crystal shape with the minimum surface energy. For the functionalized NPs the interactions between gold atoms and chemically adsorbed functional groups change their shape. As a model polymer matrix we consider polyethylene of different molecular lengths, from the oligomer to unentangled Rouse like systems. By computing the different properties the concept of the interface, and the interphase as well, in polymer nanocomposites with metal NPs are critically examined. Results concerning polymer density profiles, bond order parameter, segmental and terminal dynamics show clearly that the size of the interface / interphase, depends on the actual property under study. In addition, the anchored polymeric chains change the behavior/properties, and especially the chain density profile and the dynamics, of the polymer chain at the vicinity of the Au NP.

Intensive application of synthetic pesticides was the routine practice of commercial agriculture during the Green Revolution to boost agricultural productivity to meet global food demand. Alongside this, the application of chemical pesticides caused adverse effects on the environment and its ecoreceptors including human health. Negative externalities arising from conventional farming instigated the call for sustainable development during the sixties to promote and balance the nexus between socially acceptable economic growth and environmental protection. Consequently, a blueprint of 17 Sustainable Development Goals (SDGs) and 169 targets including ecological stewardship and food security was drafted. Eight out of the 17 SDGs are directly linked to sustainable agriculture based on the direct impact of agriculture, judicious use of critical resources and conservation and the Principles of green chemistry. As a green chemical agent, biopesticides have been shown to have the potentials to substitute chemical pesticides with equal agricultural productivity. The adoption of bio-based pesticides via integrated pest management (IPM) has proven to be the most effective option to influence most dimensions of sustainable agriculture. Therefore, biopesticide-driven IPM if utilized with requisite education, skills and research would boost sustainable agriculture. This chapter reviews the prospects, importance, and limitations of biopesticides to sustainable agriculture and how sustainable agriculture is connected to sustainable development, Green Chemistry, and integrated pest management.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing pandemic of coronavirus disease 2019 (COVID-19). The worldwide transmission of COVID-19 from human to human is spreading like wildfire, affecting almost every country in the world. In the past 100 years, the globe did not face microbial pandemic similar in scale to COVID-19. Taken together, both previous outbreaks of other members of the coronavirus family (SARS-CoV and MERS-CoV) did not produce even 1% of the global harm already inflicted by COVID-19. There are also four other CoVs capable of infecting humans (HCoVs), which circulate continuously in the human population, but their phenotypes are generally mild, and these HCoVs received relatively little attention. These dramatic differences between infection with HCoVs, SARS-CoV, MERS-CoV, and SARS-CoV-2 raise many questions, such as: Why is COVID-19 transmitted so quickly? Is it due to the some specific features of the viral structure? Are there some specific human (host) factors? Are there some environmental factors? The aim of this review is to collect and concisely summaries the possible and logic answers to these questions.

We propose a new estimator for creating expansion factors for survey plots in the USDA Forest Inventory and Analysis program. This is a regularized version of the raking estimator widely used in sample surveys. The regularized raking method differs from other predictive modeling methods for integrating survey and ancillary data in that it produces a single set of expansion factors that can have general purpose use to produce small area estimates and wall-to-wall maps of any plot characteristic. This method also differs from other more widely used survey techniques, such of GREG estimation, in that it is guaranteed to produce positive expansion factors. We extend the previous method here to include cross-validation, and provide a comparison to expansion factors between the regularized raking and ridge GREG survey calibration.

It is important for enterprises to decide their environmental policies after carefully examining their future paths based on the relationship between the environment and the economy. This study focused on Japanese minimum administrative divisions (municipalities) and attempted to quantify the annual environmental efficiency of production activities within each division according to the theory of life-cycle impact assessment (LCIA). This study leverages the assessment theory LIME2, which is an endpoint-type LCIA method developed in 2010 that integrates environmental loads for certain impact categories, such as global warming and land use into a simple indicator by monetary unit. First, annual environmental impact assessments were conducted for all Japanese municipalities based on statistical information that was reliable, verifiable, and comparable. Next, the environmental efficiency of productivity for each division was conceptualized by dividing the gross domestic product by the environmental damage amounts as calculated above. Assessment results for each municipality were placed on a map of Japan in order to visualize the regionality of each indicator. The findings revealed in this study will aid public administrators in their decision-making process with respect to environmental policies.

This study evaluates inequalities in the use of dental services according to place of birth before and after the economic crisis in Spain. A cross-sectional study was performed in the population aged 18 to 65 years in Spain. We used data from three Spanish National Health Surveys for years 2006 (before the crisis), 2014 and 2017 (after the crisis). Log-binomial regression was used to quantify the association between region of origin and use of dental care services before and after controlling for the selected covariates. In 2006, we found a greater probability of not using dental care services in immigrants from Asia (PR:1.36, 95% CI:1.10–1.67) and Africa (PR:1.16; 95% CI:1.05–1.28) compared to the natives. For 2014, the probability of not using dental care services was greater for all immigrants compared to the natives, with the greatest odds for those from Africa (PR:1.71; 95% CI:1.46–2.01) and Asia (PR:1.3; 95% CI:1.23–1. 47). The associations for 2017 were weaker in magnitude than the ones observed for 2014, although stronger than for 2006. This study suggests that the economic recovery did not have the same impact for natives and immigrants regardless of regions of origin, given the observed inequalities in use of dental services.

Introduction: Child undernutrition remains a challenge globally and in the geographically diverse country of Ethiopia. Improving dietary diversity and consumption of animal source foods are important for improving child nutrition and corresponding health outcomes. Objective: The objective of the study was to identify household and community factors associated with consumption of animal source foods among 6 to 36-month-old children from four regions of Ethiopia. Methods: A cross-sectional survey using multistage probability sampling in eight geographic zones and four regions of Ethiopia took place in 2015 with parents/caretakers of 6 to 36-month-old children. Data was collected on demographic information, proxy indicators of socioeconomic status, and food consumed by the child the day before the survey. Results: Increased child age, pastoral livelihood, Muslim religion, and participation in the Productive Safety Net Program were associated with increased consumption of animal source foods. Odds of animal source foods consumption increased 8% with each 3-month age increase. Children from pastoralist households were the most likely to have consumed animal source foods in the preceding 24 hours as compared with those in agro-pastoralist households (0.21 times as likely) or those in agriculturalist/farming households (0.15 times as likely). The odds of consumption of animal source foods for families with food aid or safety net support was 1.7 times greater among those receiving traditional support from the Productive Safety Net Program and 4.5 times greater for those in the direct support arm of the program. Conclusions: The findings illustrate the importance of accounting for local context and community characteristics, such as livelihood and religion, when undertaking programming designed to improve diversity of children’s diets through increasing animal source foods. In addition, the Productive Safety Net program may be a critical determinant of dietary diversity for young children in these regions.

The research sought to investigate the long term characteristics of wind in the Kisii region (elevation 1710m above sea level, 0.68^oS, 34.79^o E). Wind speeds were analyzed and characterized on short term (per month for a year) and then simulated for long term (ten years) measured hourly series data of daily wind speeds at a height of 10m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent; the mean wind speed, diurnal variations, daily variations as well as the monthly variations. The wind speed frequency distribution at the height 10 m was found to be 2.9ms^-1 with a standard deviation of 1.5. Based on the two month’s data that was extracted from the AcuRite 01024 Wireless Weather Stations with 5-in-1 Weather Sensor experiments set at three sites in the region, averages of wind speeds at hub heights of 10m and 13m were calculated and found to be 1.7m/s, 2.0m/s for Ikobe station, 2.4m/s, 2.8m/s for Kisii University stations, and 1.3m/s, 1.6m/s for Nyamecheo station respectively. Then extrapolation was done to determine average wind speeds at heights (20m, 30m, 50m, and 70m) which were found to be 85.55W/m², 181.75W/m², 470.4W/m² and 879.9W/m² respectively. The wind speed data was used statistically to model a Weibull probability density function and used to determine the power density for Kisii region.

The effect of hybrid carbon fillers of multi-walled carbon nanotubes (CNT) and carbon black (CB) on the electrical and morphological properties of polystyrene (PS) nanocomposites were systematically investigated in microinjection molding (μIM). The polymer nanocomposites with three different filler concentrations (i.e. 3, 5 and 10 wt%) at various weight ratios of CNT/CB (100/0, 30/70, 50/50, 70/30, 0/100) were prepared by melt blending, then followed by μIM under a defined set of processing conditions. A rectangular mold insert which has three consecutive zones with decreasing thickness along the flow direction was adopted to study abrupt changes in mold geometry on the properties of resultant microparts. The distribution of carbon fillers within microparts was observed by scanning electron microscope, which was correlated with electrical conductivity measurements. Results indicated that there is a flow-induced orientation of incorporated carbon fillers and this orientation increased with increasing shearing effect along the flow direction. High structure CB is found to be more effective than CNT in terms of enhancing the electrical conductivity, which was attributed to the good dispersion of CB in PS and their ability to form conductive networks via self-assembly. Morphology observations indicated that there is a shear-induced depletion of CB particles in the shear layer, which is due to the marked difference of shear rates between the shear and core layers of the molded microparts. Moreover, an annealing treatment is beneficial to enhance the electrical conductivity of CNT-containing microparts.

Star block-copolymers (SBCs) are macromolecules formed by a number of diblock copolymers anchored to a common central core, being the internal monomers solvophilic and the end monomers solvophobic. Recent studies have demonstrated that SBCs constitute a self-assembling building blocks with specific softness, functionalization, shape, and flexibility. Depending on different physical and chemical parameters the SBCs can behave as flexible patchy particles. In this paper, we study the rotational dynamics of isolated SBCs using a hybrid mesoscale simulation technique. We compare three different approaches to analyse the dynamics: the laboratory frame, the non-inertial Eckart's frame, and a geometrical approximation relating the conformation of the SBC to the velocity profile of the solvent. We find that the geometrical approach is adequate when dealing with very soft systems while in the opposite extreme, the dynamics is best explained using the laboratory frame. On the other hand, the Eckart frame is found to be very general and to reproduced well both extreme cases. We also compare the rotational frequency and the kinetic energy with the definitions of the angular momentum and inertia tensor different from recent publications.

Aegilops columnaris Zhuk. is tetraploid grass species (2n=4x=28, UcUcXcXc) closely related to Ae. neglecta and growing in Western Asia and a western part of the Fertile Crescent. Genetic diversity of Ae. columnaris was assessed using C-banding, FISH, nuclear and chloroplast (cp)DNA analyses, and gliadin electrophoresis. Cytogenetically Ae. columnaris was subdivided into two groups, C-I and C-II, showing different karyotype structure, C-banding and FISH patterns. Group C-I was more similar to Ae. neglecta. All types of markers revealed significant heterogeneity of the C-II group, although group C-I was also polymorphic. Two chromosomal groups were consistent with plastogroups identified in a current study based on sequencing of three chloroplast intergenic spacer regions. The similarity of group C-I of Ae. columnaris with Ae. neglecta and their distinctness from C-II indicate that divergence of the C-I group was associated with minor genome modifications. Group C-II could emerge from C-I relatively recently, probably due to introgression from another Aegilops species followed by a reorganization of the parental genomes. Most C-II accessions were collected from the very narrow geographic region, and they might originate from a common ancestor. We suggest that the C-II group is at the initial stage of species divergence and undergoing an extensive speciation process.

Background: Peloids are therapeutic agents used in thermal and thalasso centers for curative, preventive, and skin care purposes. Marine peloids are those that include seawater and algae, both macro and/or microalgae. The aim of this study is to investigate the suitability of a marine peloid composed by seawater, clay and microalgae for thalasso-wellness and dermocosmetic uses; Methods: the thermophysical properties of the marine peloid were determined and compared with a non-marine peloid using different techniques as densimetry, conductimetry, calorimetry, and viscometry; skin hydration was also measured by means of Corneometry; Results: marine peloid has been shown to be suitable for thermotherapy and thalaso-wellness treatments as its thermophysical properties were similar to other peloids used for this purpose; marine peloids also showed to improve skin hydration after seven days of treatment; Conclusions: this research provides a comprehensive study of the thermophysical properties of a marine peloid composed by clay, seawater and microalgae for thalasso-wellness and cosmetic uses, as well as its moisturizing properties, highlighting its potential as a valuable natural product for skin care applications as well as for wellness treatments in form of cataplasm, poultices and/or wraps.

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

With the widespread use of the Internet of Things, underwater control and monitoring systems for purposes such as ocean data sampling, natural disaster prevention, underwater surveillance, submarine exploration, and the like have become a popular and challenging topic in computers. So far, various topology control and routing solutions have been proposed for these networks. However, as technology expands and applications grow, so does the need for a stable underwater communication platform. On the other hand, underwater communication is associated with challenges such as node mobility, long propagation delays, low bandwidth, limited resources, and high error rates. In this research, for the first time, a topology control platform based on the RPL tree is modelled by applying its structural changes underwater. The proposed RPLUW methods in the case of RPLUWM fixed nodes are introduced to support the mobility of nodes underwater. Flexible objective functions, utilisation of decision-making systems, and application of control schedules in these methods have increased network life, reduced overhead, and increased node efficiency. The simulation results of the proposed method, in comparison with recent methods in this field, show an increase in network efficiency.

We construct hypergraphs to analyze functional brain connectivity, leveraging event-related coherence in magnetoencephalography (MEG) data during the visual perception of a flickering image. Principal network characteristics are computed for delta, theta, alpha, beta, and gamma frequency ranges. Employing a coherence measure, a statistical estimate of correlation between signal pairs across frequencies, we generate edge time series, depicting how an edge evolves over time. This forms the basis for constructing an edge-to-edge functional connectivity network. Emphasizing hyperedges as connected components in an absolute-valued functional connectivity network, we focus on exploring these hyperedges in the context of individual variability. Our coherence-based hypergraph construction specifically addresses functional connectivity among four brain lobes: frontal, parietal, temporal, and occipital. This approach enables a nuanced exploration of individual differences within diverse frequency bands, providing insights into the dynamical nature of brain connectivity during visual perception tasks. The results furnish compelling evidence supporting the hypothesis of cortico-cortical interactions occurring across varying scales. The derived hypergraph illustrates robust activation patterns in specific brain regions, indicative of their engagement across diverse cognitive contexts and different frequency bands. Our findings suggest potential integration or multifunctionality within the examined lobes, contributing valuable perspectives to our understanding of brain dynamics during visual perception.

The vehicular ad hoc network (VANET) when augmented with internet is called internet of vehicles (IoV). In the IoV, vehicles have on board units (OBUs), use communication technologies and customized software to communicate with infrastructure around them. The vehicles can have permanent connectivity and global network awareness based on cloud computing. IoV technologies are still being assessed to ensure that the network is protected from attacks, supports a dynamic vehicular mobility scenarios and meets the low latency communication requirements between the vehicles and the surrounding infrastructure. To meet these strict Quality of Service (QoS) demands, Unmanned Aerial Vehicles (UAVs) play a vital role in IoV ecosystems. An UAV can serve as a mobile roadside unit (mRSU) to transmit data between vehicles, stationery RSUs and other UAVs. The UAVs have better line of sight (LOS) connections which result in better channel states and lower path loss than fixed RSUs. Although the inclusion of UAVs in vehicular networks has improved the system performance by providing better resource management and routing solutions, the traditional optimization techniques with their limitations are often not applicable. Therefore, in recent years, research community is integrating Artificial Intelligence (AI) and Machine Learning (ML) into UAV based IoV ecosystem to better manage resource allocation, routing and mobility management issues to optimize the overall network performance. In this survey paper we review the existing research done in AI/ML based UAV-IoV networks and communications with focus on resource management and routing from year 2019 to 2023. We have studied different AI techniques, their training attributes and architectures in various research works. The limitations of AI-based approaches in terms of required computational resources, availability of real world data and AI models’ complexity for the UAV-IoV environment are also discussed. Finally, the future directions for UAV-IoV research opportunities that can leverage the full potential of AI are presented.

As the problem of air pollution becomes more urgent, the precise determination of the characteristics of air pollution and the associated mechanisms of transport of pollutants becomes an increasingly urgent task. The simulation results of the Copernicus Atmospheric Monitoring Service (CAMS) [18] were used as initial data sets. The area of the Crimean Peninsula (within coordinates 44.50 latitude, 33.50 longitude) in 23 - 26 January, 2019 was chosen for the study. That time concentrations of pollutants (aerosol particles with a diameter of 2.5 (PM2.5) and 10 micrometers (PM10)) steadily increased and reached the maximum value. Four kinds of meteorological data sets were used in the work. The first and second data sets were the global NCEP/NCAR and (ERA-5) re-analyses. The third and fourth meteorological data sets were obtained using the Weather tracking and Forecasting model (WRF) as domains on high-resolution grids: 9 km and 2 km. The analysis of meteorological data sets was carried out to analyze the nature of the air masses movement in the studied region. Using the HYSPLIT model simulation was carried out to determine area of the sources of negative impact. The emissions transfer from the supposed sources of negative impact on the Crimea region is analyzed. The sensitivity of simulation the inverse and direct trajectories of air masses transfer was studied based a set of simulation results. On the basis of HYSPLIT model the simulation was carried out separately using meteorological data sets having different spatial and temporal resolutions. In general, the simulation results allowed us to conclude that the HYSPLIT model in combination with high-resolution meteorological input data of the WRF model are good to identify the sources of possible negative effects on atmospheric air located at long distances from the study site.

This study aimed to evaluate and compare the mechanical properties of three CAD-CAM monolithic esthetic zirconia (Ceramill® Zolid FX Multilayer (ZF), IPS e.max® ZirCAD MT Multi (ZM), and KATANATM STML (KS)) with a CAD-CAM lithium disilicate glass-ceramic (IPS e.max® CAD LT (MC)) as control. 80 samples (20/group) were milled, sintered, and subjected to a three-point bending test (3-PBT) to measure flexural strength and elastic modulus; Vickers indentations were used to measure microhardness. The numerical outcomes were analyzed using one-way ANOVA with a statistical significance set at <0.05. Zirconia showed superior mechanical properties compared with lithium disilicate (P<0.05). ZM had the highest values of flexural strength (P<0.05), KS and ZM showed significantly higher elastic modulus values than ZF (P<0.05), and ZF and KS microhardness values were significantly higher than ZM (P<0.05). Monolithic multi-layered zirconia had enhanced mechanical properties when compared with lithium disilicate and can be a predictable replacement in clinical applications.

This paper presents a study of human blood sera samples, collected in various regions of the Russian Federation, with regard to both vaccine and pandemic avian influenza viral strains. Just before the 2022-2023 epidemic season, herd immunity to seasonal influenza A viruses was reportedly lower than before the COVID-19 pandemic. Since no stable circulation of A/H5Nx and A/H9N2 influenza in the human population was observed during this period, we believe 100% vaccination against seasonal influenza is necessary for employees of poultry farms and other organizations, closely connected to the breeding and processing of poultry. In addition to protection against seasonal influenza, vaccination can hamper the emergence of new viral variants, driven by genome reassortment, during simultaneous infection of humans with seasonal human and animal influenza viruses.

The study is devoted to analyzing the economic sustainability of the town of Amherst, MA. The city's top employer and core enterprise is the University of Massachusetts Amherst, with over 32,000 students and almost 2,000 staff members. Based on a literature review, a hypothesis was put forward that a university city should have a high level of economic sustainability. To assess economic sustainability, the USCESI Index was developed. It evaluates sustainability in three groups of parameters: society, economy, and ecology. The first group includes the level of racial diversity, the level of education of the population, and the access to medical services. The second group consists of the Gini coefficient by income level, the median cost of housing, and the unemployment rate. The environmental situation is assessed according to the Air Quality Index developed by the US Environmental Protection Agency. For comparison, the town of Braintree, MA, was taken. The USCESI was calculated for both locations. The analysis showed that both Amherst and Braintree have a high degree of economic sustainability. However, it was revealed that proximity to a significant economic center has a more powerful positive impact on economic sustainability than the location of a large university.

Complexes of triply positive europium ion with organic ligands are popular objects for studying photophysical properties. This is related not only to the bright red emission of this 4f element, but also to some spectroscopic peculiarities of its luminescence: the first excited spin-orbit level (7F1) lies only about 300 cm−1 above the ground state (7F0), so that at room temperature its population is around 25–30%. However, such electronic structure of Eu(III) provides its paramagnetism under ordinary conditions. This fact is often ignored by researchers, which is shortsighted from the materials science point of view. A comprehensive and systematic study of the magnetic behavior for the Eu(III) molecular coordination compounds is a challenging task for the development of new polyfunctional materials. The present work presents synthesis, single crystal XRD analysis results, and a magnetic study for the firstly prepared europium(III) complexes with two neutral scorpionate ligands: trispyrazolylmethane (HCPz3) and its methylated analog, tris(3,5-dimethyl-1-pyrazolyl)methane (HC(PzMe2)3). The values of the spin-orbit coupling parameter obtained for Eu-trication by a theoretical approximation of the experimental magnetic susceptibility data are compared with those known for the scarce amount of the magnetically studied molecular compounds.

SARS-CoV-2, the virus that causes theCOVID-19 disease, has been demonstrated to cause immune suppression in certain individuals. This can manifest as a reduced ability for the host's immune system to effectively control the infection. Studies have reported that patients with COVID-19 can exhibit a decline in white blood cell counts, including natural killer cells and T cells, which are integral components of the immune system's response to viral pathogens. These cells play critical roles in the immune response to viral infections, and their depletion can make it harder for the body to mount an effective defense against the virus. Additionally, the virus can also directly infect immune cells, further compromising their ability to function. Some individuals with severe COVID-19 pneumonia may develop a "cytokine storm," an overactive immune response that may result in tissue damage and organ malfunction. The underlying mechanisms of immune suppression in SARS-CoV-2 are not entirely comprehended at this time, and ongoing research is being conducted to gain a more comprehensive understanding. Research has shown that severe SARS-CoV-2 infection promotes the synthesis of IgG4 antibodies. In this work, we propose the hypothesis that the IgG4 antibody produced by B cells in response to infection by SARS-CoV2 generates immunological tolerance that prevents its elimination, and leads to persistence and chronic infection. In sum, we believe that this constitutes another immune evasion mechanism that bears striking similarities to that developed by cancer cells to evade immune surveillance.

Characteristics of artificial waveguide lines composed of finite size artificial cells are analyzed and discussed with relation to designing the travelling wave parametric amplifiers. From this point of view, flux driven amplifier suggested recently can be considered as the most successful amplifier design. To increase dynamic range of the amplifier, dc SQUID cells of the artificial line in use can be substituted for bi-SQUID cells. The 1-dB compression points of the amplifier gain are calculated and compared for both types of the cells.

The microwave field is used for drying and disinfection of grain, during pre-sowing seed treat-ment. The use of a microwave field in these installations leads to an increase in their productivity and a decrease in the energy consumed by them. One of the principal problems of microwave field use for treatment of dense grain layers is to insure sufficient distribution uniformity of the field. In this article, waveguide design options have been discussed that serve to introduce microwave radiation into the grain layer. Mathematical simulation of the electromagnetic field distribution was performed with the use of CST Microwave Studio software in order to evaluate and compare horn-type, rectangular and semicircular waveguides. The data on the standing wave ratio and radiation efficiency for these types of waveguides have been reported. Specific features of the microwave electromagnetic field distribution and radiation power in the output of those wave-guides have been described. Results of mathematical simulations enabled to make out that sem-icircular waveguides with slot-type radiators are preferable for processing dense grain layers.

The use of artificial intelligence (AI) is becoming more prevalent across industries as diverse as healthcare, finance, and transportation. Artificial intelligence is based on the analysis of large data sets and requires a continuous supply of high-quality data. However, using data for AI is not without its challenges. This paper comprehensively reviews and critically examine the challenges of using data for AI, including data quality, data volume, privacy and security, bias and fairness, interpretability and explainability, ethical concern, and technical expertise and skills. This paper examines e these challenges in details and offers advices on how companies can address them. By understanding and addressing these challenges, organizations can harness the power of AI to make smarter decisions and gain a competitive advantage in the digital age.

The increased interest in space activities, structural health monitoring, and terrestrial monitoring in hostile and inaccessible zones places a high demand for energy sources for autonomous systems. Conventional electrochemical batteries that could be used are plagued by low energy storage density, short life, disposal of unwanted batteries, and related undesired recharging or replacement maintenance requirements, which endangers the environment. Fuel cells and solar energy sources being exploited to mitigate the adverse effect of environmental threats posed by batteries and fossil fuels are costly to acquire and maintain. The availability of energy sources derived from waste heat from radioactive decay for domestic appliances and industrial equipment will also help alleviate the effects of climate change, which continues to threaten the environment due to fossil fuel energy-based sources that emit harmful carbon monoxide into the atmosphere. A combination of energy from waste heat, harvested via thermoelectricity and existing battery technology to produce a hybrid energy source, can guarantee secured energy for an extended period. Based on the Seebeck effect, thermoelectric energy generation may considerably contribute to sustainable energy development and meet the power demand for spacecraft applications. Modeling of the energy from waste heat, the Li-ion battery, and a hybrid energy source are considered, and their performances are established using the MATLAB/Simulink environment. Results confirmed the comparative advantage of the hybrid energy source over and above the respective electrochemical batteries and waste heat energy sources regarding effectiveness and performance efficiency. Since batteries are required to operate in a constantly changing environment, the effects of temperatures on batteries were investigated. The results show that the performances of batteries decrease with a decrease in ambient temperature and that the higher the maximum operating capacity, the higher the battery's internal temperature.

With covid infection having a periodic occurrence and each wave affecting millions of people, there is an urgent need for healthcare providers to develop readily available biological markers to predict the severity and mortality of COVID-19 infection at an early stage of the disease to predict the most optimal management. The Neutrophil – lymphocyte Ratio (NLR) and Platelet-lymphocyte ratio (PLR), are novel inflammatory markers suggested to predict the severity of illness in COVID -19 patients. We evaluated a retrospective cohort of 224 patients with covid 19 illnesses from August 2020 to October 2020. We categorized the patients into 'mild' and 'moderate to severe as per the severity of their illnesses. The optimal cut-off values of the continuous NLR, PLR, and Age were calculated by applying the receiver operating characteristic (ROC) curve analysis. Sensitivity, specificity, and likelihood ratios were calculated from ROC analysis. The results showed that Age, Hb, and NLR are significant predictors of the severity of illness. So we quantified the predictive contribution of those variables by its Z- score and showed that NLR is the strongest predictor followed by Age.ROC curve analysis revealed NLR to be an excellent predictor of disease severity (sensitivity 88.30% and specificity 82.60%) at a cut-off of > 4.24. A cut-off of 165.63 was obtained for PLR, which showed good predictive value for the severity of illness. A NLR > 6 was used as a predictor for mortality due to covid illness with good sensitivity and specificity. Conclusion: NLR and PLR can be used as prognostic markers to identify the severity of covid illness and the probability of mortality in the future in low-resource settings. Given its low cost, easily available, accessible, and reproducible data, it can be used as a useful marker to assist the physician in early referral and treatment of covid 19 infected patients.

Contemporary research has found that people with autism spectrum disorder (ASD) exhibit aberrant immunological function, with a shift toward increased cytokine production and unusual cell function. Microglia and astroglia were found to be significantly activated in immuno-cytochemical studies, and cytokine analysis revealed that the macrophage chemoattractant protein-1 (MCP-1), interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), and transforming growth factor β-1 (TGFB-1), all generated in the neuroglia, constituted the most predominant cytokines in the brain. Taurine (2-aminoethanesulfonic acid) is a promising therapeutic molecule able to increase the activity of antioxidant enzymes and ATPase, which may be protective against aluminum-induced neurotoxicity. It can also stimulate neurogenesis, synaptogenesis, and reprogramming of proinflammatory M1 macrophage polarization by decreasing mitophagy (mitochondrial autophagy) and raising the expression of the markers of the anti-inflammatory and pro-healing M2 macrophages, such as macrophage mannose receptor (MMR, CD206) and IL-10, while lowering the expression of the M1 inflammatory factor genes. Taurine also induces autophagy, which is a mechanism that is impaired in microglia cells and is critically associated with the pathophysiology of the ASD. We hypothesize here that taurine could reprogram the metabolism of M1 macrophages that are overstimulated in the nervous system of people suffering from ASD, thereby decreasing the neuroinflammatory process, neuronal death, and improving cognitive functions. Therefore, we think that taurine can serve as an important lead for the development of novel drugs for the ASD treatment.

For the first time in history, we have witnessed the origin and development of a pandemic. To handle the accelerated accumulation of viral mutations and to comprehend the virus' evolutionary adaptation in humans, an unparalleled program of genetic sequencing and monitoring of SARS-CoV-2 variants has been undertaken. Several scientists have theorized that, with the Omicron surge producing a more contagious but less severe disease, the end of COVID-19 is near. However, by analyzing the behavior shown by this virus for 2 years, we have noted that pandemic viruses do not always show a decreased virulence. Instead, it appears there is an evolutionary equilibrium between transmissibility and virulence. We have termed this concept “intermittent virulence”. The present work analyzes the temporal and epidemiological behavior of SARS-CoV-2 and suggests that there is a high possibility that new virulent variants will arise in the near future, although it is improbable that SARS-CoV-2´s virulence will be the same as was seen during the pandemic phase.

Currently, old-style personal medicare techniques rely mostly on traditional methods, such as cumbersome tools and complicated processes, which can be time-consuming and inconvenient in some circumstances. Furthermore, such old methods need the use of heavy equipment, blood draws, and traditional bench-top testing procedures. Invasive ways of acquiring test samples can potentially cause patients discomfort and anguish. Wearable sensors, on the other hand, may be attached to numerous body areas to capture diverse biochemical and physiological characteristics as a developing analytical tool. Physical, chemical, and biological data transferred via the skin is used to monitor health in various circumstances. Wearable sensors can assess the aberrant conditions of the physical or chemical components of the human body in real-time, exposing the body state in time, thanks to unintrusive sampling and high accuracy. Most commercially available wearable gadgets are mechanically hard components attached to bands and worn on the wrist, with form factors ultimately constrained by the size and weight of the batteries required for the power supply. Wearable gadgets with “skin-like” qualities are a new type of automation that is only starting to make its way out of research labs and into pre-commercial prototypes. In this paper, we studied the recent advancement in battery-powered wearable sensors established on optical phenomena and skin-like battery-free sensors which brings a breakthrough in wearable sensing automation.

Virtual Reality(VR) is an emerging technology with a broad range of application in training, entertainment, and business. To maximize the potentials of virtual reality as a medium, the unwelcome feeling of simulation sickness needs to be minimized. Even with advancements in VR, the usability concerns are barriers for a wide-spread acceptance. Several factors (hardware, software, human) play a part towards a pleasant VR experience. The reviewed scientific articles are mostly part of documents indexed in digital libraries. In this paper, we review the potential factors which cause simulation sickness and minimize the usability of virtual reality systems. We review the best practices from a developer’s perspective and some of the safety measures a user must follow while using the VR systems from existing research. Even after following some of the guidelines and best practices VR environments do not guarantee a pleasant experience for users. Limited research in VR environments towards requirement specification, design, and development for maximum usability and adaptability was the main motive for this work.

Osteoarthritis and rheumatoid arthritis are two of the most common chronic inflammatory joint diseases, for which there remains a great clinical need to develop safer and more efficacious pharmacological treatments. The pathology of both osteoarthritis and rheumatoid arthritis involves multiple tissues within the joint, including the synovial joint lining and the bone, as well as the articular cartilage in osteoarthritis. In this review, we discuss the potential for the development of oligonucleotide therapies for these disorders by examining the evidence that oligonucleotides can modulate the key cellular pathways that drive the pathology of the inflammatory diseased joint pathology as well as evidence in preclinical in vivo models that oligonucleotides can modify disease progression.

This study demonstrated that antibiotic residue in milk can be reduced when dairy farmers use Ethno-veterinary Practices (EVP) based on herbal alternatives to prevent and cure common clinical conditions in cattle instead of antibiotics. Of the 220 farmers selected for the study, 140 were trained and motivated to use validated herbal formulations, 80 were kept as control. Milk samples from the selected farmers (except Thirukanurpatti milk society) tested positive for antibiotic residue in the baseline survey. One year after interventions, the milk from 123 (87.86%) farmers out of 140, were without any detectable antibiotic residue, while samples from 11 farmers (7.85%) were low positive for either Beta-lactams or sulphonamides and 6 (4.29%) were positive for Beta lactams and/or sulphonamides. These 17 (11 + 6) farmers had used antibiotics along with herbal formulations. The milk samples from the control groups were positive for beta lactam and sulphonamide. There was suggestive significance of change in knowledge, attitude and practice of EVP among the farmers from Kerala and Tamil Nadu. A progressive reduction in the incidence of mastitis, enteritis, repeat breeding and cowpox were observed from 2016 to 2019 among the cows treated with EVP. Use of herbal alternative also resulted in a significant reduction in health care expenditure of cattle.

In India the first case of coronavirus disease 2019 (COVID-19) reported on 30 January 2020, and thereafter cases were increasing daily after the last week of Feb. 2020. COVID-19 identified as family member of coronaviridae where previously Middle East Respiratory Syndrome MERS and Severe Acute Respiratory Syndrome SARS belongs to same family. The COVID-19 attacks on respiratory system signing fever, cough and breath shortness, in severe cases may cause pneumonia, SARS or some time death. The aim of this study work is to develop model which predicts the epidemic peak for COVID-19 in India by using the real-time data from 30 Jan to 10 May 2020. There are uncertainties while identifying the population information due to the incomplete and inaccurate data, we initiate the most popular model for epidemic prediction i.e Susceptible, Exposed, Infectious, & Recovered SEIR initially the compartmental model for the prediction. Based on the solution of the state estimation problem for polynomial system with Poisson noise, we estimate that the epidemic peak may reach the early-middle July 2020, initializing recovered R0 to 0 and Infected I0 to 1. The outcomes of the model will help epidemiologist to isolate the source of the disease geospatially and analyze the death. Also government authorities will be able to target their interventions for rapidly checking the spread of the epidemic.

Since the first case of 2019 novel coronavirus disease (COVID-19) detected on Jan 30, 2020, in India, the number of cases rapidly increased to 3819 cases including 106 deaths as of 5 April 2020. Taking this into account, in the present work, we are studying a Bats-Hosts-Reservoir-People transmission fractional-order COVID-19 model for simulating the potential transmission with the thought of individual social response and control measures by the government. The real data available about infectious cases from $14^{th}$ March to $26^{th}$ March 2020 is analysed and accordingly various parameters of the model are estimated or fitted. The Picard successive approximation technique and Banach's fixed point theory have been used for verification of the existence and stability criteria of the model. Numerical computations are done utilizing the iterative Laplace transform method. In the end, we illustrate the obtained results graphically. The purpose of this study is to estimate the effectiveness of preventive measures, predicting future outbreaks and potential control strategies using the mathematical model.

In the modern world, the problem of antibiotic therapy is acute. Despite the diversity of existing antibiotic drugs, their efficacy decreases as new, resistant forms of pathogenic microorganisms emerge. It is extremely difficult to control such processes and even more difficult to treat severe bacterial infections. In such situations, an individual approach to each patient is required and physicians need parameters to estimate the efficacy of antibiotic therapy. This review discusses the significance of monitoring the content of antibiotics in the blood for this purpose, in combination with the content of inflammatory markers, such as C-reactive protein and procalcitonin. The basic principles of antibiotic therapy, and factors in the resistance of microorganisms to antibiotics, are examined. Approaches to assess the efficacy of antibiotic therapy, as well as methods to detect antibiotics and inflammatory markers in the blood of patients, and comparative assessment of their capabilities and limitations, are described.

The epidermal growth factor receptor (EGFR) plays vital roles in cellular processes including cell proliferation, survival, motility and differentiation. Dysregulated activation of the receptor is often implicated in human cancers. EGFR is synthesized as a single-pass transmembrane protein, which consists of an extracellular ligand-binding domain and an intracellular kinase domain separated by a single transmembrane domain. The receptor is activated by a variety of polypeptide ligands such as epidermal growth factor and transforming growth factor α. It has long been thought that EGFR is activated by ligand-induced dimerization of the receptor monomer, which brings intracellular kinase domains into close proximity for trans-autophosphorylation. An increasing number of diverse studies, however, demonstrate that EGFR is present as a pre-formed, yet inactive, dimer prior to ligand binding. Furthermore, recent progress in structural studies has provided insight into conformational changes during the activation of a pre-formed EGFR dimer. Upon ligand binding to the extracellular domain of EGFR, its transmembrane domains rotate or twist parallel to the plane of the cell membrane, resulting in reorientation of the intracellular kinase domain dimer from a symmetric inactive configuration to an asymmetric active form (the “rotation model”). This model is also able to explain how oncogenic mutations activate the receptor in the absence of ligand without assuming that the mutations induce receptor dimerization. In this review, we discuss mechanisms underlying ligand-induced activation of the preformed EGFR dimer, as well as how oncogenic mutations constitutively activate the receptor dimer, based on the rotation model.

The use of artificial intelligence algorithms (AI) has gained importance for dental applications in recent years. Analyzing using IA information from different sensor data such as images or X-ray radiographs can help to improve medical decisions and to achieve early diagnosis of different dental pathologies. In particular, the use of deep learning (DL) techniques based on convolutional neural networks (CNNs) has obtained promising results in dental applications based on images, in which approaches based on classification, detection, and segmentation are being studied with growing interest. However, there are still several challenges to be tackled, such as the data quality and quantity, the variability among categories, and the analysis of the possible bias and variance associated with each dataset distribution. In this work, we compare three different DL object detection models, which are Faster R-CNN, YOLO V2, and SSD. Each object detection architecture was trained, calibrated, validated, and tested with three different feature extraction CNNs which are ResNet-18, ResNet-50, and ResNet-101, which were the networks that best fit our dataset distribution. Based on such detection networks, we detect four different categories of angles in third molars using X-ray panoramic radiographs by using Winter's classification criterion. This criterion characterizes the third molar's position regarding the second molar's longitudinal axis. The detected categories for the third molars are distoangular, vertical, mesioangular, and horizontal. For training, we used a total of 644 panoramic X-ray images. The results obtained in the testing dataset reached up to 99% mean average accuracy performance, demonstrating the YOLOV2 obtained higher effectiveness in solving the third molar angle detection problem. These results demonstrate that the use of CNNs for object detection in panoramic X-rays represents a promising solution in dental applications.

Klebsiella pneumoniae (KP) is an important gram-negative zoonotic conditional pathogen. It can infect humans and a variety of farm animals, leading to infections such as pneumonia, meningitis and even sepsis. thereby posing a significant threat to public health. OmpX acts as a virulence protein that can participate in bacterial pathogenesis, mediates bacterial adhesion to and invasion of epithelial cells, and is involved in bacterial adaptation to the osmotic pressure of the external environment. In this study, MBs-SELEX was used as the main strategy for screening aptamers. Omp X was used as the target protein and Omp A as the counter-screening target. qPCR and flow cytometry were used to determine the nature and specificity of the obtained aptamers for the Omp X protein. The analysis showed that among the obtained aptamers, three aptamers, Apt-1, Apt-2 and Apt-3, were selected with Kd values of 62.50 nM, 22.05 nM and 7.9 nM, respectively. In addition, total internal reflection fluorescence microscopy (TIRFM) was used for the characterization of KP in complex with specific FITC-labeled aptamers (FITC-Apt-3) and AuNCs. The complexes were characterized by observing blue fluorescent dots from AuNCs and green fluorescent dots from FITC-labeled aptamers overlapping with bacterial presence. These results suggest that AuNCs and aptamers can specifically bind to target bacteria, forming complexes. Furthermore, in vitro results demonstrated that Apt-1, Apt-2 and Apt-3 inhibited bacterial growth, with Apt-3 having the most significant inhibitory effect. The results suggest that aptamers can selectively recognize membrane proteins, thereby disrupting bacterial cell membrane formation and effectively inhibiting bacterial growth. Aptamers have a potential mechanism to inhibit bacterial growth.

The present article describes the synthesis of an isonicotinate-derived meso-arylporphyrin, that has been fully characterized by spectroscopic methods (including fluorescence spectroscopy), as well as by elemental analysis and by HR-MS. The structure of a n-hexane monosolvate has been determined by single crystal X-ray diffraction analysis. The radical scavenging activity of this new porphyrin against the 2,2-diphenyl-1-picrylhydrazyl (DDPH) radical has been measured. Its antifungal activity against three yeast strains (C. albicans ATCC 90028, C. glabrata ATCC 64677 and C. tropicalis ATCC 64677) has been tested, using the disk diffusion and the microdilution methods. Whereas the measured antioxidant activity was low, the porphyrin showed moderate but encouraging antifungal activity. Finally, a study of its effect on the germination of lentil seeds revealed interesting allelopathic properties.

In this work a new method is proposed to tackle down the multiple objective optimization problem of the calculation of cation distribution in spinels structure, through the difference of intensity ratios between experimental and calculated intensities of cation sensitive Bragg planes, by introducing a new factor, Rabs, in Bertaut method. This factor is introduced as the sum of absolute R factors, and it is minimized by varying cation distribution. To test this method aluminate manganese spinel where synthesized though modified Pechini method and characterized though XRD. The results show to be in agreement with literature for the aluminum inversion in tetrahedral sites, which is near to the reported value of 10%. Also, it was noticed that the manganese atoms are present in octahedral sites with a mixed valence state of +2 and +3. Which might be an indicator that oxygen vacancies are present in the structure, so the vacancies value of oxygen is proposed considering the total charge of cations and thus proposing the value of 3.678 mol per formula unit of the spinel, thus having the next stoichiometry considering normalized Al and Mn, MnAl2O3.678. Finally, the last cation distribution proposed was [Mn0.867^(+2) Al0.129^(+3) ][Mn0.034^(+2) Mn0.098^(+3) Al1.871^(+3) ] O3.678 with a Rabs factor value of 0.6466, which considers the cation distribution and oxygen vacancies.

Agricultural crops productivity is heavily influenced by the strength of their seeds. Current methods for testing seed vigor, such as the germination rate and tetrazolium test, rely on time-consuming human visual inspections. Computer Vision, a crucial technology in smart production processes, offers an automated alternative and is increasingly applied in digital agriculture processes. Here we propose a method that combines YOLOv8 and morphological analysis of seeds using X-ray images to aid seed quality analysts in classifying seed lots based on their physiological potential. We examined the internal morphology of three seed lots and generated X-ray images to train a YOLOv8-based model with a post-segmentation module. This model assessed various parameters such as the total seed area, area filled by the embryo and endosperm, length, width, and calculated the percentage occupied by the embryo and endosperm in relation to the total seed area. Subsequently, seeds were classified into four categories based on the internal area occupied by the endosperm and embryo. Our findings reveal the robust performance of the YOLOv8 model in segmenting and classifying despite the challenges posed by a relatively small dataset. Notably, the proposed model achieved an impressive accuracy of up to 95.6% in identifying and segmenting the endosperm over 1,500 epochs with just 15 training images. The endosperm/seed area ratio, particularly within the 50-60% range covering over 50% of the samples, emerged as a significant metric for evaluating the viability of seed batches.

Stable half-sandwich iron(II) dihalido complexes of the type [Fe(5-Cp’)X2] are extremely scarce, being limited to congeners containing the bulky C5H2-1,2,4-tBu3 ligand. We have extended this to homologues [Fe(5-Cp*)X2] (X = Cl – I) containing the particularly popular C5Me5 (Cp*) ligand. Corresponding ionic compounds ER4[Fe(5-Cp*)X2] are easily accessible from FeX2, MCp* (M = Li, K) and a suitable halide source R4EX (E = N, P) in THF. The new compounds NnPr4[Fe(5-Cp*)X2] (X = Cl, Br), NnPr4[Fe(5-Cp*)BrCl] and PPh4[Fe(5-Cp*)X2] (X = Cl, Br, I) have been structurally characterised by single-crystal X-ray diffraction. NnPr4[Fe(5-Cp*)Cl2] reacts readily with CO to afford [Fe(5-Cp*)Cl(CO)2], indicating the synthetic potential of ER4[Fe(5-Cp*)X2] in FeCp* half-sandwich chemistry.

Extracellular vesicles (EVs) are membrane-bound particles released from cells, and their cargo can alter the function of recipient cells. EVs from X-irradiated cells have been shown to play a likely role in non-targeted effects. However, EVs derived from proton irradiated cells have not yet been studied. We aimed to investigate and compare the proteome of EVs and their cell of origin after proton or X-irradiation. The EVs were derived from a human oral squamous cell carcinoma (OSCC) cell line exposed to 0, 4, or 8 Gy with either protons or X-rays. The EVs and irradiated OSCC cells underwent liquid chromatography-mass spectrometry for protein identification. Interestingly, we found different protein profiles both in the EVs and in the OSCC cells after proton irradiation compared to X-irradiation. In the EVs, we found that protons cause a downregulation of proteins involved in cell growth and DNA damage response compared to X-rays. In the OSCC cells, proton and X-irradiation induced dissimilar cell death pathways and distinct DNA damage repair systems. These results are of potential importance for understanding how non-targeted effects in normal tissue can be limited and for future implementation of proton therapy in the clinic.

Fragile X Syndrome (FXS) is a pervasive developmental disorder and the most common monogenic cause of autism spectrum disorder (ASD). Female heterozygous (HET) carriers play a major role in the transmission of the pathology and present several FXS- and ASD-like behavioral alterations. Despite their clear genetic origins, FXS symptoms are known to be modulated by environmental factors, e.g., the exposure to chronic stress, especially during critical life periods, such as pregnancy. Pregnancy, together with pups’ care, constitutes maternal experience, i.e., another powerful environmental factor affecting several neurobehavioral functions in females. Here we investigated the impact of maternal experience on the long-term effects of stress in Fmr1-HET female mice. Our findings demonstrated that the behavioral abnormalities of HET females, i.e., hyperactivity and memory deficits, were unaffected by stress or maternal experience. In contrast, stress, independently of maternal experience, induced the appearance of cognitive deficits in WT mice. Maternal experience increased anxiety levels in all mice and enhanced their corticosterone levels, concomitantly promoting the effects of stress on social communication and adrenal glands. Our results advance our understanding of the environmental modulation of the behavioral alterations observed in FXS mice and highlight the long-term impact of maternal experience and its interactions with chronic stress.

The purpose of this work was to achieve non-destructive detection of the internal defects of in-shell walnuts using X-ray radiography technology based on improved Faster R-CNN network model. First, the FPN structure was added to the feature extraction layer to extract richer image information. Then ROI Align was used to instead of ROI Pooling for eliminating the localization bias problem caused by quantization operation. Finally, the Softer-NMS module was introduced to the final regression layer with the predicted bounding box for improving the localization accuracy of the candidate boxes. The results indicated that the internal defects in intact walnuts with shells could be identified effectively using the proposed improved network model in this study. Specifically, the discrimination accuracy of the in-shell sound, shriveled and empty-shell walnuts were 96.14%, 91.72% and 94.80% respectively, and the highest overall accuracy can reach 94.22 %. Contrasted with original Faster R-CNN network model, the mAP and F1-value of the improved Faster R-CNN model increased by 5.86% and 5.65%, respectively. Consequently, the proposed method can be applied for the in-shell walnuts with shriveled and empty-shell defects.

X-band dual-polarization phased array radar (XPAR-D) possesses high temporal-spatial resolutions and plays a significant role in detecting meso- and micro-scale convective systems. However, the precipitation attenuation it endures necessitates an effective correction method. This study selected radar data from XPAR-D at the peak of Maofeng Mountain in Guangzhou during May 16-17, 2020 from three precipitation stages after quality control. Attenuation coefficients are calculated for different precipitation types through scattering simulations of raindrop size distribution (RSD) data. Drawing upon this, an attenuation correction algorithm (MZH-KDP method) is proposed for radar reflectivity factor (ZH) according to different raindrop types, and is compared to the ZH-KDP method currently in use. The results indicate that the attenuation amount of XPAR-D echoes depends on the attenuation path and echo intensity. When the attenuation path is shorter and the echo intensity is weaker, the amount of attenuation and correction is smaller. Difficulties arise when there are noticeable deviations in such a situation, which are challenging to solve via attenuation correction methods. Longer attenuation paths and stronger echoes highlight the advantages of the MZH-KDP method, while the ZH-KDP method tends to overcorrect the bias. The MZH-KDP method outperforms the ZH-KDP method for different precipitation types. The superior correction capability of the MZH-KDP method provides a significant advantage in improving the performance of XPAR-D for the detection of extreme weather.

In this work, Gd-filled skutterudite GdxCo4Sb12 has been prepared in one-step method under high-pressure conditions in a piston-cylinder press at 3.5 GPa and moderate temperature of 800 °C. A detailed structural characterization was performed using synchrotron X-ray diffraction (SXRD), revealing a filling fraction of x = 0.066(4) and an average &lt;Gd–Sb&gt; bond length of 3.3499(3) Å. The lattice thermal expansion accessed via temperature-dependent SXRD led to a precise determination of a Debye temperature of 322(3) K, from the fitting of the unit-cell volume expansion using the second order Grüneisen approximation. Such parameter, when evaluated from the mean square displacements of Co and Sb, displayed a value of 265(2) K, meaning that the application of the harmonic Debye theory underestimates the Debye temperature in skutterudites. Regarding the Gd atom, its intrinsic disorder value is ~5× and ~25× higher than those of Co and Sb, respectively, denoting that Gd has a strong rattling behavior with an Einstein temperature of θE = 67(2) K. As a result, an ultra-low thermal conductivity of ~0.89 W/m·K at 773 K was obtained, leading to a thermoelectric efficiency zT of ~0.5 at 673 K.

We describe the design and fabrication of an industrial injection moulding system which can be mounted and used on the NCD-SWEET Small-angle X-Ray Scattering Beamline at ALBA. We show how highly useful time-resolved data can be obtained using this system. We are able to evaluate the fraction of material in the mould cavity and identify the first material to solidify and how this varies with the injection tem-perature. The design follows current industrial practice and provides opportunities to collect time-resolved data at several points within the mould cavity so we can build up a 4D perspective of the morphology and its temporal development. The quantitative data obtained will prove invaluable for the optimisation of the next generation of in-jection moulding techniques. This preliminary work used results from the injection moulding of a general purpose isotactic polypropylene.

21-hydroxylase deficiency (21OHD), the most common form of congenital adrenal hyperplasia (CAH), is associated with pathogenic variants in CYP21A2 gene. The clinical form of the disease ranges from classic or severe to non-classic (NC) or mild late onset. The CYP21A2 gene is located on the long arm of chromosome 6, within the RCCX region, one of the most complex loci in the human genome. The 3’untranslated sequence of CYP21A2 exon 10 overlap the last exon of TNXB gene (these genes lie on the opposite strands of DNA and have the opposite transcriptional direction) that encodes an extracellular matrix glycoprotein tenascin-X (TNX). A recombination event between TNXB and its pseudogene TNXA causes a 30-kb deletion producing a chimeric TNXA/TNXB gene (CAH-X chimera) where both CYP21A2 and TNXB genes are impaired. This genetic condition characterizes a subset of patients with 21OHD who display the hypermobility phenotype of Ehlers Danlos Syndrome (hEDS) (CAH-X Syndrome). The aim of this study was to assess the prevalence of CAH-X syndrome in an Italian cohort of patients with 21OHD. At this purpose, 196 probands were recruited. Multiplex ligation-dependent probe amplification (MLPA) and Sanger sequencing were used to identify the CAH-X genotype. Twenty-one individuals showed the heterozygous continuous deletion involving the CYP21A2 and part of the TNXB gene. EDS-related clinical manifestations were identified in most patients carrying the CAH-X chimera. A CAH-X prevalence of 10.7% was estimated in our population.

For many decades, X-ray diffraction (XRD) has been used for material characterization. With the recent development in material science understanding and technology, various new materials are being developed, which requires upgrading the existing analytical techniques such that intricate problems can be solved. Although, XRD is a well-established non-destructive technique, it still requires further improvements in its characterization capabilities, especially when dealing with complex mineral structures. The present review conducts comprehensive discussions on atomic crystal structure, XRD principle, its applications, uncertainty during XRD analysis, and required safety precautions, all in one place. It further discusses the future research directions, especially the use of artificial intelligence and machine learning tools for improving the effectiveness and accuracy of XRD technique for mineral characterization. It has been focused that how XRD patterns can be utilized for a thorough understanding of the crystalline structure, size, and orientation, dislocation density, phase identification, quantification, and transformation, information about lattice parameters, residual stress, and strain, and thermal expansion coefficient of materials. All these important discussions on XRD for mineral characterization are compiled in this short yet comprehensive review that would benefit specialists and engineers in the chemical, mining, iron, metallurgy, and steel industries.

Dual energy X-ray absorptiometry (DEXA) measuring tool is a reliable and accurate technology to measure bone density and bone mineral composition. This research examined the composition and bone density (bone mineral composition and bone mineral density) of the whole body and representative body parts using DEXA. The participants were 240 healthy adult men and women who were divided into three groups based on age. The total bone mineral density (BMD) of women amounted to an average of 1.14 g/㎠ in Group A, 1.14 g/㎠ in Group B, and 0.98 g/㎠ in Group C. For men, the average BMD was 1.25 g/㎠ in Group A, 1.20 g/㎠ in Group B, and 1.17 g/㎠ in Group C. As a result, the reduction of age-specific BMD was shown to have a correlation with aging and body mass index(BMI), and it is determined that exercising on a regular basis can prevent reduction in BMD by maintaining appropriate muscle mass.

The developed microstructure features a long with mechanical properties in vacuum brazing of commercially pure Ti-alloy using Ti₂₀Zr₂₀Cu_60-x-Ni_x (x=10, 20, 30, 40 and 50) metallic filler. Brazing temperatures and holding times employed in this study were 1240-1279 K (967-1006^oC) for a period of 10 min, respectively. The mechanical properties of brazed joints were evaluated by nanoindention at a constant peak load of 5000 μN and tensile tests. The number of intermetallic phase, such as NiTi₂, Ti₂Cu, (Ti, Zr)₂Cu, (Ti, Zr)₂Ni, β(Ti, Zr), α-Ti and NiTi. The solid solution matrix have been identified at 1279 K out of these different regions the NiTi₂ rich region had the highest nanohardness of 17 GPa, It is interesting to note that among five different glasses, the Ti₂₀Zr₂₀Cu₁₀Ni₅₀ has the highest yield strength of 17 GPa, which is mainly due to NiTi₂ phase. Based on the tensile test results all cracks propagate along the brittle intermetallic compounds like NiTi₂ in the reaction layer the reduction of the strength of the joints and fracture behaviour upon propagation of the crack, which shows the morphological cleavage including facets characteristics.

The Sunyaev-Zeldovich effect (SZe) is a global distortion of Cosmic Microwave Bckground (CMB) spectrum as result of its interaction with a hot electron plasma in the intracluster medium for large gravitational virialized structures such as galaxy clusters. Furthermore, this hot gas of electrons emits X-Rays due to its fall in the gravitational potential well of the cluster. The analysis of SZe and X-Ray data, provide a method for calculating distances to galaxy clusters at any redshift (Angular diameter distance (d_A) and gas mass fraction (f_gas)). On the other side, many of these galaxy clusters produce a Strong Gravitational Lens effect (SGL), which has become an useful astrophysical tool for cosmology. We use these cosmological tests, in addition to the more traditional ones (SNIa, CMB, BAO), to constraint alternative models of dark energy (ωCDM, CPL, IDE, EDE) and study the history of expansion through the cosmographic parameters (H(z), q(z), j(z)). Using Akaike and Bayesian Information Criterion (AIC, BIC) we find that the ωCDM and ΛCDM models are the most favored by the observational data. In addition, we found that at low redshift appears an peculiar behavior of slowdown of aceleration, which occurs only on dynamical dark energy models using only galaxy clusters (d_A,clusters + f_gas).

SET protein carries out multiple functions including those for protein phosphatase 2A (PP2A) inhibition, histone modification, DNA repair and gene regulation. SET overexpression has been detected in brain neurons of Alzheimer's disease patients, follicle theca cells of Polycystic Ovary Syndrome (PCOS) patients, and ovarian cancer cells, indicating that SET may play a pathological role for these disorders. SET transcript 2, produced by a specific promoter, represents a major transcript variant in different cell types. In this study, we characterized the transcriptional activation of human SET transcript 2 promoter in HeLa cells. Promoter deletion experiments and co-transfection assays indicated that ZFX, the Zinc finger and X-linked transcription factor, was able to transactivate the SET promoter. A proximal promoter region containing four ZFX-binding sites was found to be critical for the ZFX-mediated transactivation. Mutagenesis study indicated that the site located closest to the transcription start site accounted for most of the ZFX-mediated transactivity. Manipulation of ZFX levels by overexpression or siRNA knockdown confirmed the significance and specificity of the ZFX-mediated SET promoter activation. Chromatin immunoprecipitation results verified the binding of ZFX to its cognate site in the SET promoter. These findings have led to identification of ZFX as an upstream factor regulating SET gene expression. More studies are required to define the in vivo significance of this mechanism, and specifically, its implication for several benign and malignant diseases related to SET dysregulation.

Hepatitis B virus (HBV) is the dominant risk factor for hepatocellular carcinoma (HCC). HBV X protein (HBx) plays crucial roles in HCC carcinogenesis. HBx interferes with several signaling pathways including Notch1 pathway in HCC. In our study, we found that Notch1 was highly expressed in HCC especially in large HCC. Notch1 and HBx co-localized in HCC and their levels were positively correlated with each other. Notch1 expression was more elevated in HepG2.2.15 than that in HepG2. HBx activated Notch1 pathway in HepG2.2.15. Repression of HBx and Notch1 pathway attenuated the growth of HepG2.2.15. Notch1, ERK and AKT pathways were inhibited after a γ-secretase inhibitor treatment. Dual-specificity phosphatase 1 (DUSP1) and phosphatase and tensin homolog (PTEN) were up-regulated after the γ-secretase inhibitor treatment and Hes1 inhibition. Luciferase reporter assays showed that Hes1 repressed the promoters of DUSP1 and PTEN and this was reverted by γ-secretase inhibitor treatment. Western blotting demonstrated that DUSP1 dephosphorylated pERK and PTEN dephosphorylated pAKT. Collectively, we reported a link among HBx, Notch1 pathway, DUSP1/PTEN, and ERK/AKT pathways, which influenced HCC cell survival and could be a therapeutic target for HCC.