Food safety is a significant issue that affects people worldwide and is tied to their lives and health. The issue of pesticide residues in food is just one of many issues related to food safety, which leave residues in crops and are transferred through the food chain to human consumption. Foods contaminated with pesticide residues pose a serious risk to human health, including carcinogenicity, neurotoxicity and endocrine disruption. Although traditional methods including gas chromatography, high-performance liquid chromatography, chromatography and mass spectrometry can be used to achieve quantitative analysis of pesticide residues, the disadvantages of these techniques, such as being time-consuming and costly and requiring specialist staff, limit their application. Therefore, there is a need to develop rapid, effective and sensitive equipment for the quantitative analysis of pesticide residues in food. Microfluidics is rapidly emerging in a number of fields due to its outstanding strengths. This paper summarizes the application of microfluidic techniques to pyrethroid, carbamate, organochlorine and organophosphorus pesticides, as well as to commercial products. Meanwhile, the paper also outlines the development of microfluidics in combination with 3D printing technology and nanomaterials for the detection of pesticide residues in food.

The market for microfluidic chips is experiencing significant growth; however, their development is hindered by a complex design process and low efficiency. Enhancing microfluidic chips’ design quality and efficiency has emerged as an integral approach to foster their advancement. Currently, the existing structural design schemes lack careful consideration regarding the impact of chip area, microchannel length, and the number of intersections on chip design. This inadequacy leads to redundant chip structures resulting from the separation of layout and wiring design. This study proposes a structural optimization method for microfluidic chips to address these issues utilizing a simulated annealing algorithm. The simulated annealing algorithm generates an initial solution in advance using the fast sequence pair algorithm. Subsequently, an improved simulated annealing algorithm is employed to obtain the optimal solution for the device layout. During the wiring stage, an advanced wiring method is used to designate the high wiring area, thereby increasing the success rate of microfluidic chip wiring. Furthermore, the connection between layout and routing is reinforced through an improved layout adjustment method, which reduces the length of microchannels and the number of intersections. Finally, the effectiveness of the structural optimization approach is validated through six sets of test cases, successfully achieving the objective of enhancing the design quality of microfluidic chips.

We report on the occurrence of natural Magnesium Alumina Silicate Hydrate (M-(A)-S-H) cement at Feragen and Leka in eastern and western Trøndelag Norway, respectively. Both occurrences are located in the sub-arctic climate zone and form in glacial till and moraine material deposited on ultramafic rock during the Weichselian glaciation. Weathering of serpentinized peridotite dissolve brucite and result in a relative high pH alkaline fluid that subsequently reacts with the felsic minerals of the till (quartz, plagioclase, K-feldspar) to form a cement consisting of an amorphous material or a mixture of nanocrystalline Mg-rich phyllosilicates, including illite. The presence of plagioclase in the till results in the enrichment of alumina in the cement, i.e., forms M-A-S-H instead of the M-S-H cement. Dissolution of quartz results in numerous etch-pits and negative quartz crystals filled with M-A-S-H cement. Where the quartz dissolution is faster that the cement precipitation, a honeycomb-like texture is formed. Compositionally the cemented till (tillite) contains more MgO and has a higher loss of ignition than the till, suggesting that the cement is formed by a MgO fluid that previously reacted with the peridotite. The M-(A)-S-H cemented till represent a new type of duricrust, coined magsilcrete. The study of natural Mg-cement provides information on peridotites as a Mg-source for Mg-cement and as a feedstock for CO2 sequestration.

How did life begin on Earth? And is there life elsewhere in the Cosmos? Challenging questions, indeed. The series of conferences established by NoR CEL in 2013, addresses these very same questions. The basis for this paper is the summary report of oral presentations that were delivered by NoR CEL’s network members during the 2018 Athens conference and, as such, disseminates the latest research which they have put forward. More in depth material can be found by consulting the contributors referenced papers. Overall, the outcome of this conspectus on the conference demonstrates a case for the existence of “probable chemistry” during the prebiotic epoch.

A dogma is normally considered as a principle or a belief accepted as an indisputable truth by some individuals and/or groups. Theoretically there can be no dogmas in science, but it has been demonstrated that scientific thought operates by conceptual changes. A dogma therefore can be understood as a concept present at the heart of some contemporary research programmes that need to be altered to overcome paradigms. Here we argue that two ideas relating to emergence of the biological system research need to be re-evaluated. First, is the idea that research programmes about the emergence of the biological system are the same as those of the origin of cells. Cells are strikingly important biological entities, hard core concepts for the entire field of biology. The emergence of the biological system happened much earlier than the origin of cells and thus the First Universal Common Ancestor (FUCA) should be viewed as a great-grandfather to the Last Universal Cellular Ancestor (LUCA); i.e. the latter is the first cellular life form. Second, RNA-world theories are the focus of mainstream research programmes for the origin of life stricto sensu. In the RNA-world view, self-replication of nucleic acids is seen as one of the most relevant events in the pre-biotic world. Without denying the relevance of self-replication, we argue here that the most germane event which occurred in the pre-biotic world was the crosstalk between nucleic acids and peptides. When these two macromolecules started to interact, the singularity that aggregated the complexity required to produce life emerged. Thus, comprehension of the early origins of the translation machinery and the assembly of the genetic code is key. Therefore, the relevance of cell theory and self-replication should be re-evaluated as well as the concept of life itself.

From a differential geometric perspective, information geometry (IG) aims to characterise the structure of statistical geodesic models. The research done for this paper offers a novel method for modelling the information geometry of a queuing system. From the perspective of IG, the manifold of the transient M/M/infinity queue is described in this context. The Fisher Information matrix (FIM) as well as the inverse of (FIM), (IFIM) of transient M/M/infinity QM are devised. In addition to that, new results that uncovered the significant impact of stability of QM on the existence of (IFIM) are obtained. Moreover, the Geodesic equations of motion of the coordinates of the underlying transient are obtained. Also, it is revealed that stable QM is developable (i.e., has a zero Gaussian curvature) and has a non-zero Ricci Curvature Tensor (RCT). Novel stability dynamics of transient M/M/iInfinity queue manifold is revealed by discovering the mutual dual impact between the behaviour of (RCT) and the stability(instability) phases of M/M/Infinity QM. Furthermore, a new discovery that presents the significant impact of stability of queue manifold and the continuity of the unique representation between M/G/1 queue manifold and Ricci Curvature Tensor (RCT). The information matrix exponential (IME) is devised. Also, it is shown that stability of the devised (IME) enforces the instability of M/M/ Infinity QM. More interestingly, novel relativistic info-geometric queueing theoretic links are revealed .

Juvenile Polyposis Syndrome (JPS) is a rare autosomal dominant disorder characterized by multiple juvenile polyps in the gastrointestinal tract, often associated with mutations in genes such as Smad4 and BMPR1A. This study explores the impact of Smad4 knockout on the development of intestinal polyps using Collaborative Cross (CC) mice, a genetically diverse model. Our results reveal a significant increase in intestinal polyps in Smad4 knockout mice across the entire population, emphasizing the broad influence of Smad4 on polyposis. Sex-specific analyses demonstrate higher polyp counts in knockout males and females compared to their WT counterparts, with distinct correlation patterns. Line-specific effects highlight the nuanced response to Smad4 knockout, underscoring the importance of genetic variability. Multimorbidity heat maps offer insights into complex relationships between polyp counts, locations, and sizes. Heritability analysis reveals a significant genetic basis for polyp counts and sizes, while machine learning models, including k-Nearest Neighbours and Linear Regression, identify key predictors, enhancing our understanding of juvenile polyposis genetics. Overall, this study provides a comprehensive understanding of the intricate genetic interplay in the context of Smad4 knockout, offering valuable insights into potential therapeutic targets for juvenile polyposis and related diseases.

This paper discusses domestic problem of waiting hot water for the shower use till it reaches satisfactory temperature, which result a lot of wastage in fresh water. The outcome from research survey shows that there is no satisfactory solution till now as all solutions were either expensive or with no effective results. Local small inline electric heater equipped with fuzzy logic controller is proposed in this paper to be installed just before the showerhead to measure the water temperature and flow before the showerhead, as control input-variables, and decide the operating voltage of the heater, as control output-variable (MISO). MATLAB Simulink is used to model the proposed system. Different test cases are simulated to prove the performance and the safe operation of the system. Techno-economic study is carried out to determine the “Direct Benefits” and “Indirect Benefits” that can be achieved if such system is implemented in wide range. Azerbaijan data is taken as an example to calculate the economic benefits. The results show important benefits not only for economy but also for climate and the reduction of CO₂ gas emission. Different economic indices are provided to be an easy reference for decision makers and project managers.

In this work, we derive the spectral efficiency, secrecy outage probability, and bit error rate of a communication system assisted by a large intelligent surface (LIS). We consider a single-antenna user and an array of antennas at the transmitter side and the possibility of a direct link between transmitter and receiver. Additionally, there is a single-antenna eavesdropper with a direct link to the transmitter, which is modeled as a Nakagami-m distributed fading coefficient. The channels from transmitter to the LIS and from the LIS to the user may or may not have the line-of-sight (LoS) and are modeled by the Nakagami- m distribution. Moreover, we assume that the LIS elements perform non-ideal phase cancellation leading to a residual phase error that assumes a Von Mises distribution. We show that the resulting channel can be accurately approximated by a Gamma distribution whose parameters are analytically estimated using the moments of the equivalent signal-to-noise ratio. We also provide an upper bound for the error probability for M-QAM modulations. With the derived formulas, we analyze the effect of the strength of the LoS link by varying the Nakagami parameter, m.

Nonlinear thermal transport of non-Newtonian polymer flows is an increasingly important area in materials engineering. Motivated by new developments in this area which entail more re-fined and mathematical frameworks, the present analysis investigates the boundary layer ap-proximation and heat transfer persuaded by a symmetrical cylindrical surface positioned hori-zontally. To simulate thermal relaxation impacts the bioconvection cross nanofluid flow Buongiorno model is deployed. The impact of the magnetic field applied on the nanofluid using the heat generation and melting phenomena are inspected. The nonlinear effect of thermosolutal buoyant forces is incorporated into the proposed model. The novel mathematical equations comprise thermophoresis and Brownian diffusion effects. Via robust transformation techniques, the primitive resulting partial equations for momentum, energy, concentration, and motile living microorganism are rendered into nonlinear ordinary equations with convective boundary postulates. An explicit and efficient numerical solver procedure in Mathematica 11.0 programming platform is developed to engage the nonlinear equations. The consequence of multiple governing parameters on dimensionless fluid profiles is inspected through plotted visuals and tables. Finally, outcomes declared on the surface drag force, heat, and mass transfer coefficients are exhibited through 3D visuals via different influential parameters.

Soil-borne Trichoderma spp. have been extensively studied for their biocontrol activities against pathogens and growth promotion ability with plants. However, the beneficial effect of Trichoderma on inducing resistance against insect herbivores has been considered only recently. Among diverse Trichoderma species, consistent with previous reports, we showed that root colonization by T. virens triggered induced systemic resistance (ISR) to leaf-infecting fungal pathogens. Whether T. virens induces ISR to insect pests has not been tested before. In this study, we investigated whether T. virens affects jasmonic acid (JA) biosynthesis and defense against fall armyworm (FAW) and western corn rootworm (WCR). Unexpectedly, the results showed that T. virens colonization of maize seedlings grown in autoclaved soil suppressed wound-induced production of JA, resulting in reduced resistance to FAW. Similarly, the bacterial endophyte Pseudomonas chlororaphis 30-84 suppressed systemic resistance to FAW due to reduced JA. Further comparative analyses of the systemic effects of these endophytes when applied into sterile or non-sterile field soil showed that both T. virens and P. chlororaphis 30-84 triggered ISR against hemibiotrophic fungal pathogen Colletotrichum graminicola in both soil conditions, but only suppressed resistance to FAW in sterile soil. In contrast to the effect on FAW defense, T. virens colonization of maize roots suppressed WCR larvae survival and weight gain. This is the first report suggesting the potential role of T. virens as a biocontrol agent against WCR.

This work presents the results of three connection types in double-shear with dowel fasteners, using the simplified equations from the Eurocode 5. All design parameters were established and compared using three different wood strength and density properties, which constitute the members connections. Eighty-one connections were obtained, allowing to conclude about the number of fasteners needed to the applied tensile load. An increase in the number of dowels was obtained with the increased applied tensile load, lower dowel diameter, lower wood density, and lower strength material in all connection types in the study. The design characteristic load-carrying capacity per shear plane and fastener also decrease with the previously considered parameters.

During chronic liver injury, inflammation leads to liver fibrosis— particularly due to the activation of hepatic stellate cells (HSCs). However, the involvement of inflammatory cytokines in HSC activation and the relationship among different liver cells is unclear. To examine their interactions, many in vitro liver models are performed in organoid or spheroid culture with random 3D structure, complicating analysis. Herein, we demonstrated the hierarchical coculture of primary rat hepatocytes with non-parenchymal cells such as the human-derived HSC line (LX-2) and liver sinusoidal endothelial cell line (TMNK-1). The cocultured tissue had high usability with simple operation of separating solid and liquid phases with improved liver functions such as albumin production and hepatic cytochrome P450 3A4 activity. We also studied the effects of stimulation by both oxygen tension and the key pro-fibrogenic cytokine, transforming growth factor beta (TGF-β), on HSC activation. Gene expression analysis revealed that lower oxygen tension and TGF-β1 stimulation enhanced collagen type I and alpha-smooth muscle actin expression from LX-2 cells in the hierarchical coculture. Therefore, this hierarchical in vitro cocultured liver tissue could provide an improved platform as a disease model for elucidating the interactions of various liver cell types and biochemical signals in future liver fibrogenesis studies.

The emergence of novel coronavirus (SARS-CoV-2) in marked as the highest pathogenic coronavirus that has crossed from the hosts to the human population in the twenty-first century. The spreading of COVID-19 in different chinese cities and around the world is travel-related viral spread with the unprecedented nosocomial outbreaks. It has also shown with high case-fatality rates, indeed to urgent prophylactic and therapeutic settings. Scientific advancements of the SARS-CoV-2 pandemic allowed for rapid progress to understand the epidemiology and pathogenesis of SARS-CoV-2. This review highlights the the genomic structure of SARS-CoV-2 with the proposed roles of genotype and phenotype of SARS-CoV-2 in pathogenesis and discuss recent results supporting treatment strategies of COVID-19 with a special focus on how these new insights may facilitate rational development of SARS-CoV-2 for targeted therapies in the future.

This research work investigates the possibility of shielding gravity. The ultimate purpose of this work is to understand the reality behind the concept of Gravitational Shielding (GS) and time dilation. Since the 19th century, scientists have tried to arrive at an understanding of GS via the use of various experiments. Unfortunately, some experiments failed to prove the existence of gravitational shielding, whereas some results proclaimed the possibility of attaining GS. The original phenomenon exhibited by nature cannot easily be understood, but some experiments have demonstrated that the answer may lie behind the mysterious GS. If GS is proved, then in the future, it would be possible to travel across black holes by defying gravity or through any bigger mass having high gravitational field. To unravel the mystery of GS, this work investigates the history of GS and considers the future vision of technologically advanced spacecraft or other warp drive mechanisms with appropriate gravitational shielding. Though the problem is very complex, this research work tries to come to a deeper understanding and explanation of the complexity involved in achieving gravitational shielding.

This study presents the numerical investigation of bioconvective nanofluid (NF) flow compris-ing gyrotactic microorganisms through convective boundary conditions (CBC) enclosing heat and mass transmission analysis above an inclined extending cylinder. Via appropriate transfor-mation, the set of Partial Differential Equations is transformed into a scheme of nonlinear ODEs. A new set of variables are presented in the directive to get the first-order convectional equations and, then solved numerically by using bvp4c. The influence of several factors on velocity, ener-gy, concentration, and the density of motile microorganisms (DMM) is investigated and exam-ined. The analysis describes and addresses all physical measures of concentration such as Skin Friction (SF), Sherwood number (SN), DMM, and Nusselt number (NN). The present conse-quences display a validation with published. For confirmation of bvp4c, the ND-solve approach is also applied. Error analysis is also examined for the confirmation of the mathematical model.

Pulmonary infections with Mycobacterium avium occur in susceptible individuals following exposure to the bacterium in the environment, where it often persists in biofilms. Many methods have been used to generate biofilms of M. avium, and it is unknown whether different approaches generate similar structures and cell phenotypes. To make a parallel comparison of in vitro biofilm ultrastructure, extracellular matrix (ECM) composition, and drug susceptibility of biofilm resident bacteria, we used two published methods to generate M. avium biofilms: four week incubation in M63 medium or 24 hour exposure to dithiothreitol (DTT). Scanning electron microscopy revealed differences in biofilm ultrastructure between the two methods, including variation in appearance of ECM materials and morphology of resident cells, while light microscopy and staining with calcofluor white indicated that both biofilms contained polysaccharides characteristic of cellulose. Measuring susceptibility of biofilms to degradation by enzymes suggested differences in structurally important ECM molecules, with DTT biofilms having important protein and, to a lesser extent, cellulose components, and M63 biofilms having moderate protein, cellulose, and DNA components. Both biofilms conferred resistance to the bactericidal effects of amikacin and clarithromycin, with resident cells being killed at >10-fold lower rates than planktonic cells at almost all concentrations. Though these comparisons indicate differences in biofilm responses by M. avium under differing conditions, they also suggest common features of biofilm formation including cellulose production and antimicrobial resistance.

The current work reports the upper bound of the state variable of the of the Pointwise Steady Fluid Flow Approximation (PSFFA) model of non-stationary M/Ek/1 queueing system.

Extensive genome structure variation, such as copy number variations (CNVs) and presence/absence variations, is the basis for the remarkable maize genetic diversity; however, the effect of CNVs on maize herbivory defense remains largely underexplored. Here, we report that the naturally occurring duplication of the maize 9-lipoxygenase gene, ZmLOX5, leads to increased resistance of maize to herbivory by fall armyworms (FAW). Previously, we showed that ZmLOX5-derived oxylipins are required for defense against chewing insect herbivores and identified several inbred lines, including Yu796, that contained duplicated CNVs of ZmLOX5, referred to as Yu796-2×LOX5. To test whether introgression of the Yu796-2×LOX5 locus into the herbivore-susceptible B73 background that contains a single ZmLOX5 gene is a feasible approach to increase resistance, we generated a series of near-isogenic lines that contained either 2, 1 or 0 copies of the Yu796-2×LOX5 locus in the B73 background by six back crosses (BC6). Droplet digital PCR (ddPCR) confirmed the successful introgression of the Yu796-2×LOX5 locus in B73. The resulting B73-2×LOX5 inbred line displayed increased resistance against FAW associated with increased expression of ZmLOX5, increased wound-induced production of its primary oxylipin product, the α-ketol, 9-hydroxy-10-oxo-12(Z),15(Z)-octadecadienoic acid (9,10-KODA), and the downstream defense hormones regulated by this molecule, 12-oxo-phytodienoic acid (12-OPDA) and abscisic acid (ABA). Surprisingly, wound-induced JA-Ile production was not increased in B73-2×LOX5, resulting from the increased JA catabolism. Furthermore, B73-2×LOX5 displayed enhanced drought tolerance likely due to increased ABA and 12-OPDA content. Taken together, this study revealed that the duplicated CNV of ZmLOX5 quantitively contributes to maize antiherbivore defense and presents proof-of-concept evidence that the introgression of naturally occurring duplicated CNVs of a defensive gene into the productive, but susceptible, crop varieties is a feasible breeding approach for enhancing plant resistance to herbivory and tolerance to abiotic stress.

Coronavirus disease 2019 (COVID-19) is a high contagious respiratory infectious disease that has afiected millions of people worldwide. Initially, basic public health measures were implemented to control specially the spread of such virus. However, vaccination has emerged as a highly efiective strategy in combating COVID-19 and reducing its transmission. Several efiective and safe vaccines have been approved to prevent the inadvertent spread of the disease. In this study, a modeling approach is used to analyze the impact of these vaccines on the dynamics of COVID-19. By applying a higher-order numerical method, the model is solved based on reported cases in Pakistan. A spectral method is employed for the numerical solution, and the model is simulated to assess the efiects of vaccination. The Next-generation method is used to calculate the threshold quantity, known as R0, which indicates the potential for disease transmission. The study also includes a detailed stability analysis, examining the invariance properties of the model solution and discussing equilibrium points and their stability in disease-free and endemic states. Furthermore, the study presents graphical representations of the influence of special parameters on the dynamics of the pandemic.

The World Health Organization(WHO) in 2016 considered mHealth as: “the use of mobile wireless technologies including smart devices such as smartphones and smartwatches for public health” as an important resource for health services delivery and public health given their ease of use, broad reach and acceptance. WHO emphasizes the potential of this technology to increase access to health information, services and skills as well as promoting positive changes in health behaviors and management of diseases. In this regard, the capability of smartphones and smartwatches for m-health monitoring as well as verification of the patient the signal has become an important component of mHealth system. Most of the smartwatches could extract more than one bioelectrical signal therefore, therefore they provide suitable platform for extracting health data for e-monitoring. The existing approaches have not considered the integrity of data obtained from these smart devices. Therefore, it is important that the integrity of the collected data be verified continuously through user authentication. This could be done using any of the bioelectrical signals extracted and transmitted for e-monitoring. In this article, a smartwatch is used for extracting bioelectrical signal before decomposing the signal into sub-bands of Detail and Approximation Coefficient for user authentication. To select suitable features using biorthogonal wavelet decomposition of signal from a non-intrusive extraction, a detailed experiment is conducted extracting suitable statistical features from the bioelectrical signal from 30 subjects using different biorthogonal wavelet family. Ten features are extracted using Biorthogonal wavelet to decompose the signal into three levels of sub-band Detail and Approximation Coefficient and features extracted from each level the decomposed Detail and Approximation Coefficients. Comparison analysis is done after the classification of the extracted features based on the Equal Error Rate (EER). Using Neural Network (NN) classifier, Biorthogonal Wavelet Detail Coefficient Sub-band level 3 of bior1.1 achieved the best result of EER 13.80% with the fusion of the best sub-band three levels of bior1.1 achieving a better result of 12.42% EER.

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

.Various synthetic nematicides are currently used effectively in the control of plant parasitic nematodes. However, these nematicides have adverse effects on humans and the environment. Neem oil is eco-friendly alternatives to synthetic nematicides. The effectiveness of repeated neem oil application in suppressing the root-knot nematodes infestation in figs seedlings was therefore examined in this study, both in its natural form (10 ml/L) and in its nano-emulsion form (5 and 7 ml/L). The recorded reduction parameters of M. incognita were J2/250g soil, galls and egg masses / 5g roots of infected fig seedlings were measured at that time, and the effects of these natural additives were compared with the Fosthiazate (Krenkel 75%EC). The impact of such soil amendments on some typical plant parameters, the total microbial count of soil, and the overall enzymatic activity of the fig rhizosphere were also included. Obtained results revealed that the soil population density of root knot nematode suppressed by 80.3% , reduction of nematode egg masses (60.4%) due to the application of nano-emulsion of neem oil (at 7ml/L). Present work recommend the use of nano-emulsion of neem oil as one of the effective and eco-friendly means to reduce the root- knot nematode on fig .

The current study characterizes the transient M/M/1 queue manifold info-geometrically, through devising Fisher Information matrix(FIM) and its inverse(IFIM). Additionally, the impact of stability on the existence of IFIM and explore the geodesic equations of motion has been revealed. More potentially, the paper discusses some info-geometric applications to Machine Learning are highlighted. Closing remarks with some challenging open problems combined with the next phase of research are given.

Increased CO2 emissions and air pollution impact the environment and human health. In this manner, new functionalized polyaminal-based polymers are synthesized via a one-pot polycondensation reaction of melamine with aldehyde monomers 2-bromo-1-naphthaldehyde and 2-hydroxy-1-naphthaldehyde to yield bromine- hydroxyl- functionalized polymer networks PAN-BrNA and PAN-HNA, respectively. The polyaminals porosity parameters were investigated and applied as an adsorbent for CO2 capture. FTIR, solid-state 13C NMR, and X-ray diffraction verified the PANs structure development. A scanning electron microscope and N2 adsorption-desorption methods were utilized to identify the porous properties of the polymers at 77 K. The Brunauer-Emmett-Teller (BET) surface area of PAN-BrNA and PAN-HNA is (16.6990 m2/g) and (716.7568 m2/g), respectively. At 273 K, PAN-BrNA and PAN-HNA can take CO2 gas up to (4.42786 cm3/g) and (47.55 cm3/g), respectively. The findings show that inserting functional groups has a significant impact on surface area and porosity parameters, as well as CO2 uptake.

Titania is one of the most comprehensively studied nanostructures due to its widespread applications in production of catalytic, gas- sensing and corrosion- resistance materials [1]. M-polynomial of nanotubes has been vastly investigated as it produces many degree-based topological indices which are numerical parameters capturing structural and chemical properties. These indices are used in the development of quantitative structure-activity relationships (QSARs) in which the biological activity and other properties of molecules are correlated with their structure like boiling point, stability, strain energy etc of chemical compounds. In this paper, we determine M-polynomials of single-walled titanium (SW TiO2) nanotubes and recover important topological degree based indices of them to theoretically judge these nanotubes. We also use Maple to plot surfaces associated to different types of single-walled titanium (SW TiO2) nanotubes.

The research was undertaken to study the way deformation behaves in ultrafine-grained (UFG) conducting Al-Zr alloys doped with Sc, Hf, and Yb. All in all, 8 alloys were studied with zirconium partially replaced by Sc, Hf, and/or Yb. Doping elements (X = Zr, Sc, Hf, Yb) in the alloys total 0.4 wt.%. The choice of doping elements is conditioned by possible precipitation of Al3X particles with L12 structure while annealing these alloys. Such particles provide higher thermal stability of a nonequilibrium UFG microstructure. Initial coarse-grained samples were obtained by induction casting. The UFG microstructure in the alloys was formed by Equal Channel Angular Pressing (ECAP) at 225°C. Superplasticity tests were carried out at temperatures ranging from 300 to 500 °C and strain rates varying between 3.310-4 and 3.310-1 s-1. The highest values of elongation to failure are observed in Sc-doped alloys. A UFG Al-0.2%Zr-0.1%Sc-0.1%Hf alloy has maximum ductility: at 450 °C and a strain rate of 3.310-3 s-1, relative elongation to failure reaches 765%. At the onset of superplasticity, stress–strain curves are characterized by a stage of homogeneous strain and a long stage of localized plastic flow. The dependence of homogeneous strain (eq) on test temperature in UFG Sc-doped alloys is increasing uniformly, which is not the case for other UFG alloys with eq(T) dependence peaking at 350-400 оС. Strain rate sensitivity coefficient of flow stress m is small and does not exceed 0.26-0.3 at 400-500 °C. In UFG alloys containing no scandium, m coefficient is observed to go down to 0.12-0.18 at 500 оС. It has been suggested that lower m values are driven by intensive grain growth and pore formation in large Al3X particles, which develop specifically at the ingot crystallization stage.

The segmentation and de-noising are basic operations, required in every signal processing and classification system. The classical segmentation and de-noising approaches are time-invariant. Consequently, it results in the post processing of an unnecessary information and causes an increase in the system processing activity and power consumption. In this context, an efficient event-driven segmentation and de-noising technique is proposed. It is founded on the principles of level crossing and activity selection. Therefore, it can adapt its sampling frequency, segmentation window length and position along with the filter order by analyzing the input signal local characteristics. As a result, the computational complexity and the power consumption of the proposed system is reduced compared to the counter ones. The suggested system performance is compared with the classical one. It is done for the case of a multi-channel Electroencephalogram (EEG) signals. Results show a noticeable compression gain with an effective adaptation of the de-noising filters order. It aptitudes a significant computational gain, transmission data rate reduction and power consumption reduction of the proposed technique, compared to the counter ones. It shows that the proposed solution is an attractive candidate to embed in the new generation EEG wearables.

This study introduces and demonstrates a comprehensive, accurate, unbiased approach to robust quantitative comparison of Electronic Nicotine Delivery Systems (ENDS) appropriate for establishing substantial equivalence (or lack thereof) between tobacco products. The approach is demonstrated across a family of thirteen pen- and pod-style ENDS products. Methods employed consist of formulating a robust emissions surface regression model, quantifying the empirical accuracy of the model as applied to each product, evaluating relationships between product design characteristics and maximum emissions characteristics, and presenting results in formats useful to researchers, regulators, and consumers. Results provide a response surface to characterize emissions (total particulate matter and constituents thereof) from each ENDS appropriate for use in a computer model and for conducting quantitative exposure comparisons between products. Results demonstrate that emissions vary as a function of puff duration, flow rate, E-Liquid composition, and device operating power. Further, results indicate that regulating design characteristics of ENDS devices and consumables may not achieve desired public health outcomes; it is more effective to regulate maximum permissible emissions directly. Three emissions outcome measures (yield per puff, mass concentration and constituent mass ratio) are recommended for adoption as standard quantities for reporting by manufacturers and research laboratories. The approach provides a means of (a) quantifying and comparing maximal emissions from ENDS products spanning their entire operating envelope, (b) comparative evaluation of ENDS devices and consumable design characteristics, and (c) establishing comparative equivalence of maximal emissions from ENDS. A consumer-oriented product emissions dashboard is proposed for comparative evaluation of ENDS exposure potential. Maximum achievable power dissipated in the coil of ENDS is identified as a potentially effective regulatory parameter.

An adaptive deep neural network is used in an inverse system identification setting to approximate the inverse of a nonlinear plant with the aim of constituting the plant controller by copying to the latter the weights and architecture of the converging deep neural network. This deep learning (DL) approach to the adaptive inverse control (AIC) problem is shown to outperform adaptive filtering techniques and algorithms normally used in adaptive control, especially when the plant is nonlinear. The deeper the controller the better the inverse function approximation, provided that the nonlinear plant have an inverse and that this inverse can be approximated. Simulation results prove the feasibility of this DL-based adaptive inverse control scheme. The DL-based AIC system is robust to parameter change of the nonlinear plant in that, under such change, the plant output reassumes the value of the reference signal considerably faster than with the adaptive filter counterpart of the deep neural network. Settling times and rise times of the step response are shown to improve in the DL-based AIC system.

This work combines compressive sensing and short word-length techniques to achieve localization and target tracking in wireless sensor networks with energy-efficient communication between the network anchors and the fusion center. Gradient descent localization is performed using time-of-arrival (TOA) data which are indicative of the distance between anchors and the target thereby achieving range-based localization. The short word-length techniques considered are delta modulation and sigma-delta modulation. The energy efficiency is due to the reduction of the data volume transmitted from anchors to the fusion center by employing any of the two delta modulation variants with compressive sensing techniques. Delta modulation allows the transmission of one bit per TOA sample. The communication energy efficiency is increased by RⱮ, R≥1, where R is the sample reduction ratio of compressive sensing and Ɱ is the number of bits originally present in a TOA-sample word. It is found that the localization system involving sigma-delta modulation has a superior performance to that using delta-modulation or pure compressive sampling alone, in terms of both energy efficiency and localization error in the presence of TOA measurement noise, owing to the noise shaping property of sigma-delta modulation.

Frequency estimation of a single sinusoid in colored noise has received a considerable amount of attention in the research community. Taking into account the recent emergence and advances in compressive covariance sensing (CCS), the aim of this work is to combine the two disciplines by studying the effects of compressed measurements of a single sinusoid in moving-average (MA) colored noise on its frequency estimation accuracy. CCS techniques can recover the second-order statistics of the original uncompressed signal from the compressed measurements, thereby enabling correlation-based frequency estimation of single tones in colored noise using higher-order lags. Acceptable accuracy is achieved for moderate compression ratios and for a sufficiently large number of available compressed signal samples. It is expected that the proposed method would be advantageous in applications involving resource-limited systems such as wireless sensor networks.

Training data for a deep learning (DL) neural network (NN) controller are obtained from the input and output signals of a conventional digital controller that is designed to provide the suitable control signal to a specified plant within a feedback digital control system. It is found that if the DL controller is sufficiently deep (four hidden layers), it can outperform the conventional controller in terms of settling time of the system output transient response to a unit-step reference signal. That is, the DL controller introduces a damping effect. Moreover, it does not need to be retrained to operate with a reference signal of different magnitude, or under system parameter change. Such properties make the DL control more attractive for applications that may undergo parameter variation, like sensor networks.

Chenodeoxycholic acid (CA) is a naturally occurring bile acid that is produced in the liver from cholesterol. Three CA complexes using Zn(II), Mg(II), and Ca(II) ions were synthesized to examine the chelation tendencies of CA towards these metal ions. The complexation reaction of CA with the metal ions under investigation was conducted with a 1:1 molar ratio (CA to metal) at 60-70°C in natural media (pH 7-8), which consisted of a binary solvent of MeOH and H2O (1:1). The resulting CA complexes were characterized using analytical data (metal, H, C, and Cl, analysis) and spectral data (UV-visible, FT-IR, and 1H NMR) to elucidate the complexes’ structures. The results suggested that CA in anion form utilized oxygen atoms of the carboxylate group (-COO−) to capture Zn(II), Mg(II), and Ca(II) ions. This produced complexes with the general compositions of [Zn(CA)(H2O)Cl], [Mg(CA)(H2O)Cl]H2O, and [Ca(CA)(H2O)Cl]2H2O, respectively. The Kirby-Bauer disc diffusion assay was then used to explore the bioactivity of the CA complexes toward three fungal species, three Gram-positive bacteria, and two Gram-negative bacteria. The Ca(II) and Mg(II) complexes exhibited marked inhibitory effects on the cell growth of the fungal species Aspergillus niger with potency equal to 127% and 116% of the activity of the positive control, respectively. The Zn(II) and Ca(II) complexes strongly inhibited the growth of Penicillium sp., while the Zn(II) and Mg(II) complexes showed strong growth inhibition towards the Gram-negative species Pseudomonas aeruginosa.

Since the 1980s, a growing interest in goat milk was noticed due to the nutritional values and health benefits of this milk, which resulted in increasing goat populations and milk production worldwide. This comprehensive review elaborates on goat milk composition compared to other types of milk. It is also an overview of goat milk production, properties, nourishment-value, applications in dairy products, and potential health benefits. Goat milk composition and its characteristics are slightly different from other types of milk and can be utilized to manufacture many dairy products. Fresh goat milk and goat milk products (e.g., yogurt and kefir were found to provide various potential health benefits, such as anti-inflammatory, prevent cardiovascular disease, anti-diabetic and antihypertensive, strengthen bones, boost immunity, and improve metabolism.

The chemical reaction between the quinolone antibiotic oxolinic acid (OA) and Fe(III), Zn(II), Ca(II), and Mg(II) ions results in the formation of metal-based complexes with the following formulas: [Fe(OA)(H2O)2Cl2]2H2O, [Zn(OA)(H2O)Cl]2H2O, [Ca(OA)(H2O)Cl], and [Mg(OA)(H2O)Cl]. We used analytical (C, N, H, Cl, metal analysis) and spectral (FT-IR, 1H NMR, UV-visible) data to structurally characterize the synthesized metal-based complexes of the OA molecule. We found that the OA molecule utilizes the two oxygen atoms of the carboxylate group and the pyridone C=O group to bind the investigated metal ions. The morphological properties of the synthesized OA complexes were assessed using X-ray powder diffractometry (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The biological properties, specifically antibacterial and antifungal activity, of the synthesized complexes were evaluated in vitro using the Kirby-Bauer disc diffusion protocol with five bacterial and three fungal strains. The complex containing Ca(II) ions exhibited remarkable antibacterial and antifungal activity against all tested microbial strains, surpassing or equaling the potency of the standard drugs (streptomycin for antibacterial assays and ketoconazole for antifungal assays).

: Pearl millet (Pennisetum glaucum L) R. Br) is a subtropical grain and forage crop. It is privileged with several desirable forage attributes. Nevertheless, research on pearl millet is limited especially as a forage crop in the developing countries. Therefore, the objectives of this study were to investigate the field performance and stability of pearl millet genotypes for forage yield across seven environments. The study was conducted in seven environments (combination of locations and seasons) during 2016/2017-2018/2019 seasons. Twenty-five pearl millet genotypes, selected based on forage yield from a core collection of 200 accessions, were arranged in alpha lattice design with three replications. The parameters measured were fresh forage yield, days to flowering, plant height, number of culms m-2, leaf to stem ratio, and stem girth. The combined analysis revealed that environments, genotypes and their interaction had significant effects on all traits studied except the genotypic effect on stem girth. Across the seven environments, four genotypes (G14, G01, G12, and G22) out-yielded the check genotype in fresh matter yield by 20.7, 16.5, 11.0 and 9.8%, respectively. The additive main effects and multiplicative interaction (AMMI) analysis showed that the genotype, environment and their interaction were highly significant (P≤0.001) for fresh matter yield. The results of AMMI Stability Values (ASV) and the genotype selection index (GSI) combined with the AMMI estimate-based selection showed that genotypes G14, G22 and G01 were the most stable and adapted genotypes and were superior to the check genotype. These results indicate that forage pearl millet varieties could be developed directly through evaluation of the wealth available collections or indirectly through hybridization in crop breeding programs.

The present study examines the effect of SiO2 nano-additives on the performance and emission characteristics of a diesel engine fuelled with soybean biodiesel. Soybean biofuel was prepared using the transesterification process. Nano-additives characterisations were done using different tests such as FESEM, XRD, EDS, etc., to study the morphology of nano-additives. For proper blending of nano-additives with biodiesel, the ultrasonication process was used. Surfactant was used for the stabilisation of nano-additives. After making all the combinations of nano fuel blends, physicochemical properties were measured as per ASTM standards. Performance and emissions readings were taken at different load conditions. It was found that with the addition of SiO2 nano-additives, brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) was increased by 3.48-6.39% and 5.81-9.88%, respectively. Significant reduction of CO, CO2, NOx, and smoke emissions were also observed compared to baseline fule due to better combustion efficiency with the use of SiO2 nano-additive.

Alunogen, Al2(SO4)3·17H2O, occurs as an efflorescent in acid mine drainage, low-temperature fumarolic or pseudofumarolic (at coal fires) terrestrial environments. It is considered as one of the main Al-sulfates of Martian soils demanding comprehensive crystal chemical data of natural terrestrial samples. However, structural studies of natural alunogen were carried out in 1970s without localization of H atoms and have not previously been performed for samples from geothermal fields, despite the fact that these environments are considered as proxies of the Martian conditions. The studied alunogen sample comes from Verkhne-Koshelevsky geothermal field (Koshelev volcano, Kamchatka, Russia). Its chemical formula is somewhat dehydrated, Al2(SO4)3×15.8 H2O. The crystal structure was solved and refined to R1 = 0.068 based on 5112 unique observed reflections with I > 2σ(I). Alunogen crystalizes in P-1 space group, a = 7.4194(3), b = 26.9763(9), c = 6.0549(2) Å, α = 90.043(3), β = 97.703(3), γ = 91.673(3) °, V = 1200.41(7) Å3, Z = 2. The crystal structure consists of isolated SO4 tetrahedra, Al(H2O)6 octahedra and H2O molecules connected by hydrogen bonds. The structure refinement includes Al, S and O positions that are similar to previous structure determinations and thirty-four H positions localized for the natural sample first. The study also shows the absence of isomorphic substitutions in the composition of alunogen despite the iron-enriched environment of mineral crystallization. The variability of the alunogen crystal structure is reflected in the number of “zeolite” H2O molecules and their splitting. The structure complexity of alunogen and its modifications ranges from 333-346 bits/cell for models with non-localized H atoms to 783-828 bits/cell for models with localized H atoms. The higher values correspond to higher hydration state of alunogen.

Cotton is the most ubiquitous and profitable fiber with diverse industrial and domestic applications. Grown in over 100 countries, it has a global market value of about $40 billion and employs over 350 million people from fields to textile mills, contributing about 7% of total labor-force recruitment in developing economies. Cotton has an indeterminate growth habit and an extensive tap root system affected by soil physicochemical and environmental conditions. There is a consensus among experts that conventional cotton cultivation still has a long way to attain sustainability, which is essential if cotton will maintain its competitive edge over other natural and synthetic fibers like hemp, polyesters, and rayon. Despite several efforts already committed to growing cotton sustainably, sustainability has eluded cotton cultivation globally because of the intense farm inputs (freshwater, pesticides, and heavy-duty equipment) needs, especially in developing economies. Some of the technological advancements towards achieving the goal of sustainable cotton cultivation include the development of new varieties, improved irrigation and mulching and precision agriculture techniques, application of remote sensing and Unmanned Aerial Systems (UAS) combined with image processing, and the introduction of autonomous and multi-purpose robotic platforms for growing and harvesting cotton. This review attempts to evaluate the successes already achieved by stakeholders in moving cotton towards sustainable production and identify areas where efforts are still needed to reach sustainable production and improved profitability goals for cotton with projections for future research directions.

The development of magnesium calcium phosphate bone cements (MCPCs) have garnered big attention. MCPCs are bioactive and biodegradable and have appropriate mechanical and antimicrobial properties for use in reconstructive surgery. In this study, the cement powders based on a (Ca + Mg)/P = 2 system doped with Zn2+ at 0.5 and 1.0 wt.% were obtained and investigated. After the mixing with a cement liquid, structural and phase composition, morphology, chemical structure, setting time, compressive strength, degradation behavior, solubility, antibacterial activities, and in vitro behaviour of the cement materials were examined. A high compressive strength of 48 ± 5 MPa (mean ± SD) was achieved for the cement made from Zn2+ 1.0-wt.%-substituted powders. The Zn2+ introduction led to antibacterial activity against Staphylococcus aureus and Escherichia coli strains, with an inhibition zone diameter up to 8 mm. Biological assays confirmed that the developed cements are cytocompatible and promising as a potential bone substitute in reconstructive surgery.

Dietary recommendations to decrease the risk of cardiovascular disease (CVD) have focused on reducing intake of saturated fatty acids (SFA) for more than 50 years. While the 2015-2020 Dietary Guidelines for Americans advise substituting both monounsaturated and polyunsaturated fatty acids for SFA, evidence supports other nutrient substitutions that will also reduce CVD risk. For example, replacing SFA with whole grains, but not refined carbohydrates, reduces CVD risk. Replacing SFA with protein, especially plant protein may also reduce CVD risk. While dairy fat (milk, cheese) is associated with a slightly lower CVD risk compared to meat, dairy fat results in a significantly greater CVD risk relative to unsaturated fatty acids. As research continues, we will refine our understanding of dietary patterns associated with lower CVD risk.

Commonly employed methods for reversibly disrupting gene expression, such as those based on RNAi or CRISPRi, are rarely capable of achieving >80-90% downregulation, making them unsuitable for targeting genes that require more complete disruption to elicit a phenotype. Genetic deletion, on the other hand, while enabling complete disruption of target genes, often produces undesirable irreversible consequences such as cytotoxicity or cell death. Here we describe the design, development and detailed characterization of a dual-function "TRE-Lox" system for effecting either (a) doxycycline (Dox)-mediated downregulation or (b) genetic deletion of cathepsin D (CatD), based on targeted insertion of a tetracycline-response element (TRE) and two LoxP sites into the 5' end of the endogenous gene (CTSD). Using an optimized reverse-tetracycline transrepressor (rtTR) variant fused with the Krüppel-associated box (KRAB) domain, we show that CatD expression can be disrupted by as much as 98% in mouse embryonic fibroblasts (MEFs). This system is highly sensitive to Dox (IC50 = 1.46 ng/mL) and results in rapid (t1/2 = 0.57 d) and titratable downregulation of CatD. Notably, even near-total disruption of CatD expression was completely reversed by withdrawal of Dox. As expected, transient expression of Cre recombinase results in complete deletion of the CTSD gene. The dual functionality of this novel system will facilitate future studies of the involvement of CatD in various diseases, particularly those attributable to partial loss of CatD function. In addition, the TRE-Lox approach should be applicable to the regulation of other target genes requiring more complete disruption than can be achieved by traditional methods.

The Six Sigma (6σ) method is used to improve and optimize an organization’s products, services, and processes by constantly decreasing defects. In this paper we try implementing the 6σ methodology in Academia. The challenges and actuality of implementation of 6σ methodologies successfully in Academia are immense. However, the benefits of applying 6σ are equally great. The objective of this paper is to understand the evolution, benefits, and challenges of 6σ practices in academia through a case study of Presidency University situated in Bangalore, Karnataka, India. The problem statement in the paper is the poor performance of students in academics and by using the DMAIC approach of 6σ we try to identify and understand the causes and set out to improve them so the students can have better placement and academic opportunities. This paper is also an attempt to show the readers about the wide application of 6σ in fields other than manufacturing and how it can be beneficial.

In this study, we address the formidable challenge of solving large-scale Max-Cut problems (MCP). We introduce a rapid computational procedure utilizing a hybrid 1-flip/r-flip local search heuristic. This innovative strategy significantly reduces the computational time required for MCP problems while consistently generating solutions of exceptional quality. The paper presents substantial computational insights, showcasing the effectiveness of our approach on very-large-scale Max-Cut instances with varying densities. Our proposed heuristic is rigorously evaluated by comparing its performance against a quantum annealing solver, leveraging a multi-start Tabu Search framework. The results underscore the potency of this unique combination as an efficient and effective solution for large-scale QUBO problems. Notably, our hybrid heuristic consistently delivers high-quality solutions within the stringent CPU time limits of 600 seconds, demonstrating its efficacy across Max-Cut instances ranging from 10,000 to 40,000 variables. This research contributes to advancing the state-of-the-art in large-scale QUBO problem-solving, offering a powerful and time-efficient approach with broad applicability.

(S)-Atenolol ((S)-2-(4-(2-Hydroxy-3-(isopropylamino)propoxy)phenyl)acetamide) has been synthesized in >99% ee with use of Candida antarctica lipase B from Syncozymes (Shanghai, China), in a kinetic resolution of the corresponding racemic chlorohydrin. Deprotonation of the starting phenol building block was base catalyzed. The enantiopurity of the chlorohydrin building block remained unchanged upon subsequent amination. All four steps in the synthesis protocol have been optimized compared to previously reported methods, which makes this new protocol more sustainable and in accordance with green chemistry principles compared to previously reported protocols.

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

Abstract: As a low-input crop, Miscanthus offers numerous advantages that, in addition to agricultural applications, permits its exploitation for energy, fuel, and material production. Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ. Here, a comparative study is presented between lignins isolated from M. x giganteus, M. sinensis, M. robustus and M. nagara using a catalyst-free organosolv pulping process. The lignins from different plant constituents are also compared regarding their similarities and differences regarding monolignol ratio and important linkages. Results showed that the plant genotype has the weakest influence on monolignol content and interunit linkages. In contrast, structural differences are more significant among lignins of different harvest time and/or season. Analyses were performed using fast and simple methods such as nuclear magnetic resonance (NMR) spectroscopy. Data was assigned to four different linkages (A: b-O-4 linkage, B: phenylcoumaran, C: resinol, D: b-unsaturated ester). In conclusion, A content is particularly high in leaf-derived lignins at just under 70 % and significantly lower in stem and mixture lignins at around 60 % and almost 65 %. The second most common linkage pattern is D in all isolated lignins, the proportion of which is also strongly dependent on the crop portion. Both stem and mixture lignins, have a relatively high share of approximately 20 % or more (maximum is M. sinensis Sin2 with over 30 %). In the leaf-derived lignins, the proportions are significantly lower on average. Stem samples should be chosen if the highest possible lignin content is desired, specifically from the M. x giganteus genotype, which revealed lignin contents up to 27 %. Due to the better frost resistance and higher stem stability, M. nagara offers some advantages compared to M. x giganteus. Miscanthus crops are shown to be very attractive lignocellulose feedstock (LCF) for second generation biorefineries and lignin generation in Europe.

Background: Obesity and its attendant conditions have become major health problems worldwide and is currently ranked as the fifth most common leading cause of death globally. Complex environmental and genetic factors are the cause of the current obesity epidemic. Diet, lifestyle, chemical exposures, and other confounding factors are difficult to manage in humans. The mice model is helpful in researching genetics BW gain because genetic and environmental risk factors can be controlled in mice. Studies in mouse strains with various genetic backgrounds and established genetic structures provide unparalleled opportunities to find and analyze trait-related genomic loci. In this study, we used the Collaborative Cross (CC), a large panel of recombinant inbred mouse strains, to present a predictive study using CC mice SMAD4 knockout profiles to understand and effectively identify predisposition to body weight gain. Materials and Methods: Male C57Bl / 6J Smad4+/- mice were mated with female mice from 10 different CC lines to create F1 mice (Smad4+/- x CC). Body weight (BW) was measured weekly until week 16, then monthly until the end (week 48). The heritability H2 of the assessed traits was estimated and presented. Comparative analysis of various machine learning algorithms for predicting the BW changes and genotype of mice was conducted. Results and conclusions: Our data showed that the body weight records of F1 mice with different CC lines differed between wildtype and mutant Smad4 mice during the experiment. Genetic background affects weight gain and some lines gained more weight in the presence of Smad4 knockout, while others gained less, but in general, the mutation caused overweight mice, except for a few lines. In both control and mutant groups, female %BW had a higher heritability H2 value than males. Additionally, both sexes with wildtype genotypes showed higher heritability values than the mutant group. Logistic Regression provides the most accurate mouse genotype predictions using machine learning. We plan to validate the proposed method on more CC lines and mice per line to expand machine learning for BW prediction.

The aim of our study was a comprehensive comparative assessment of the effect of consumption of 1 and 2% cholesterol as part of a standard diet with and without regular moderate physical activity on the main biomarkers of lipid and cholesterol metabolism, as well as the intestinal microbiota of male Wistar rats. The animals were randomly divided into 5 groups according to body weight and Open Field test results: Control (n=10), 1% Chol (n=10), 2% Chol (n=10), 1% Chol + RUN (n=10) and 2% Chol + RUN. The cholesterol was additionally added in the amount of 1g or 2g/100g, respectively, to the diet of animals. The rats of experimental groups 1% Chol + RUN and 2% Chol + RUN were subjected to regular (2 days a week) physical activity on a Treadmill. In rats of four experimental groups, when compared to the Control, a response of 39 indicators was revealed. The largest number of changes in biomarkers - 29 (statistically significant, p

New antiviral agents are essential to improving treatment and control of SARS-CoV-2 infections that can lead to the disease COVID-19. Antimicrobial peptoids are sequence-specific oligo-N-substituted glycine peptidomimetics that emulate the structure and function of natural antimicrobial peptides but are resistant to proteases. We demonstrate antiviral activity of a new peptoid (TM9) against the coronavirus, murine hepatitis virus (MHV), as a closely related model for the structure and antiviral susceptibility profile of SARS-CoV-2. This peptoid mimics the human cathelicidin LL-37, which has also been shown to have antimicrobial and antiviral activity. In this study TM9 was effective against three murine coronavirus strains, demonstrating the therapeutic window is large enough to allow use of TM9 for treatment. All three isolates of MHV generated infection in mice after 15 min of exposure by aerosol using the Madison aerosol chamber and all three viral strains could be isolated from the lungs throughout the 5-day observation period post-infection, with the peak titers on day 2. MHV-A59 and MHV-A59-GFP were also isolated from liver, heart, spleen, olfactory bulbs, and brain. These data demonstrate that MHV serves as a valuable natural murine model of coronavirus pathogenesis in multiple organs, including the brain.

Mastitis-causing bacteria can establish persistent infections in the mammary gland of commercially important dairy animals despite the presence of strong specific humoral and cellular immune mechanisms. The aim of this study was to encapsulate vitamin D3 by complex coacervation with sulfur-saturated bovine lactoferrin-alginate using microbial transglutaminase-catalyzed crosslinking and investigate the oral administration of encapsulated vitamin D3 in blood serum biomarkers of the immune response in late-lactating dairy goats. Dairy goats (n = 18) in late lactation were randomly assigned to three experimental groups (n = 6), after balancing weight. Dairy goats were orally administered with 0.35 mg vitamin D3/day in the unencapsulated form and 0.35 mg vitamin D3/day in the encapsulated powder form. Another group received the basal diet. The experimental period lasted 6 weeks. The blood serum concentrations of 25-hydroxyvitamin D3 [25-(OH)-D3], lactoferrin, immunoglobulin A (IgA), and interferon-gamma (INF-γ) were measured. The delivery of vitamin D3 to dairy goats resulted in a marked increase of 25-(OH)-D3 concentration in serum while the serum level of lactoferrin also increased. Alternatively, the serum levels of IgA and the immunomodulatory cytokine INF-γ were elevated following supplementation with the encapsulated vitamin D3. Overall, the capsules in the powder form used in this study kept vitamin D3 highly bioavailable.

Schinus terebinthifolius Raddi is a plant native to Brazil. The objective of this work was to analyze the chemical composition, antioxidant and antibacterial potential of essential oils (EOs) from the leaves, fruits and twigs of S. terebinthifolius aiming for their application in food safety. EOs were obtained by hydrodistillation and the chemical composition was determined by gas chromatog-raphy coupled to mass spectrometry. Phenolic compounds were quantified and antioxidant ac-tivity was evaluated using three different methods. The antibacterial activity was determined by the broth microdilution method against foodborne bacteria. In the chemical analysis, 22 com-pounds were identified in the leaves, 13 compounds in the fruits and 37 compounds in the twigs, revealing the presence of the main compounds germacrene D, caryophyllene, α-pinene, β-pinene and γ-gurjunene. EOs showed better antioxidant potential using the β-carotene/linoleic acid method with 40.74, 61.52 and 63.65% oxidation inhibition for leaves, fruits and twigs, respectively. The EO from the leaves showed greater antibacterial potential against Escherichia coli and Staphy-lococcus aureus with a minimum inhibitory concentration (MIC) of 0.62 mg mL-1, values lower than the MIC of sodium nitrite (5.00 mg mL-1), antimicrobial standard synthetic. The activities of pink pepper EOs suggest their potential as a biopreservative in foods.

This paper analyses the application of deep learning techniques for predicting wave overtopping events in port environments using sea state and weather forecasts as inputs. The study was conducted in the outer port of Punta Langosteira, A Coruña, Spain. A video recording infrastructure was installed to monitor overtopping events from 2015 to 2022, identifying 3709 overtopping events. The data collected was merged with actual and predicted data for the sea state and weather conditions during the overtopping events, creating three datasets. We used these datasets to create several machine learning models to predict whether an overtopping event would occur based on sea state and weather conditions. The final models achieved a high accuracy level during the training and testing stages: 0.81, 0.73, and 0.84 average accuracy during training and 0.67, 0.48, and 0.86 average accuracy during testing, respectively. The results of this study have significant implications for port safety and efficiency, as wave overtopping events can cause disruptions and potential damage. Using deep learning techniques for overtopping prediction can help port managers take preventative measures and optimize operations, ultimately improving safety and helping to minimize the economic impact that overtopping events have on the port's activities.

Central adiposity is one of the significant determinants of obesity-related hypertension risk, which may arise due to the abdominal fat depot's pathogenic inflammatory nature. Pro-inflammatory cytokines and adipokines up-regulation through nuclear factor-kappa B (NF-κB) activation in adipose tissue has been considered an essential function in the pathogenesis of obesity-related hypertension. This study aimed to ascertain the NF-κB inhibitor (SN50) effect on TNF-α and angiotensinogen (AGT) secretion and expression in mediating the anti-inflammatory effect through its impact on NF-κB activity in humans adipose tissue. Primary human adipocytes were isolated from 20 subjects among 10 overweight and 10 obese with and without hypertension and treated with 10ng/ml LPS in the presence and absence of NF-κB inhibitor, SN50 (50μg/ml). TNF-α secretion and NF-κB p65 activity were detected in supernatants extracted from cultured cells treated and untreated with LPS (10ng/ml) and SN50 (50μg/ml) using enzyme-linked immunosorbent assay (ELISA). The western blot technique detected the protein of NF-κB p65 and AGT. Gene expression of TNF-α and AGT was detected in cells and performed using quantitative real-time polymerase chain reaction (RT-PCR). Treatment of AbdSc adipocytes with LPS (10ng/ml) caused a significant increase in NF-κB p65 among overweight and obese subjects with and without hypertension (P= 0.001) at 24 hours incubation. In contrast, SN50-NF-κB inhibitor causes a reduction of NF-κB p65 in overweight (P= <0.001) and obese subjects with and without hypertension (P= 0.001) at 24 hours incubation. Treatment of AbdSc adipocytes with 10ng/ml LPS caused a significant increase in TNF-α secretion in overweight and obese subjects at all-time points (P= <0.001), whereas SN50 leads to a decrease in TNF-α secretion at 3 and 12 hours incubation. Treatment of AbdSc adipocytes with LPS (10ng/ml) caused increased TNF-α and AGT gene expression twofold compared with untreated cells, whereas, in the presence of SN50, it reduces mRNA AGT levels in both groups. Taken together, these adipokines with NF-κB activation may represent essential biomarkers to evaluate hypertension risk and to provide insight into the pathogenesis of obesity-related hypertension.

The stress testing methodology should be implemented and applied to the entity's overall financial system at least annually, and if the organization operates in a volatile economy, it should be performed at least twice a year. Finally, managers should include regular training and development sessions for relevant employees of their organization to be fully informed and more informed and informed, considering the evolving science, theory and practicality of a discrete range of stress testing mechanisms that can be appropriately applied to overall financial framework and system of multiple financial institutions and banks. In addition, stress testing is essentially a methodology that collects and analyzes certain future macro-prudential and micro-prudential economic drivers and indicators, the primary purpose of which is to assess the future financial and economic well-being, level of growth and status quo of a financial institution, bank, organization, credit institution or economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. with the primary intention of assessing the future financial and economic well-being, level of growth and status quo of a group of financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically targeted and incorporated into a paper that substantially and broadly discussed and summarized the importance of the feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. with the primary intention of assessing the future financial and economic well-being, level of growth and status quo of a group of financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. the level of growth and status quo of the financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. the level of growth and status quo of the financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries.

Heavy metal accumulation in soils used for agricultural purposes is a major issue as it can affect the growth of plants and contain health risks as plants containing heavy metals are taken as food. This study provided the potential of three Bacillus pumilus strains (C-2PMW-8, C-1 SSK-8, and C-1PWK-7) for mitigation of the health factors related to heavy metals on lettuce (Lactuca sativa) grown in chromium contaminated soil from activities related to mining. Lettuce seeds inoculated with B. pumilus strains were grown in pots with garden soil amended with varying amount of chromite mine soil (2.27%, 4.65%, 7.14%). Growth indicators like days to germination, percentage of germination, leaf weight, leaf area and rate of survival decreased with incremental soil chromium levels but improved highly with inoculation of B. pumilus compared to uninoculated controls. When B. pumilus strains were provided, there was also a decreased level in the buildup of chromium in soil as well as lettuce shoots. The results explains that plant growth-promoting B. pumilus strains may be able to lower down the detrimental effects of chromium on lettuce development, hence increment in the effectiveness of phytoremediation.

Background: Chronic kidney disease, one of the most common diseases in the world, is characterized by irreversible impairment of the kidney’s metabolic, excretory, and endocrine functions. During end-stage renal disease, patients require renal replacement therapy, such as hemodialysis (HD). Protein-energy wasting is a common health problem among HD patients. However, this study aims to assess the nutritional status of HD patients at two HD centers in Jeddah, Saudi Arabia, and to determine its associated factors. Methods: A cross-sectional study was conducted at two different Dialysis Centers in Jeddah, Saudi Arabia; 211 female and male HD patients. Malnutrition was recognized using the Modified-SGA (M-SGA) comprising two parts: medical history and physical examination. Sociodemographic and health status for all patients were also determined. Patients were classified based on their M-SGA score into two groups: normal and malnourished. Results: Overall, 54.5% of the participants showed malnutrition. Unemployment, low muscle strength and mass, high level of medication use, and high dialysis vintage were positively (P&lt;0.05) associated with malnutrition. Conclusion: The M-SGA score indicates a high prevalence of malnutrition among HD patients. These results show the importance of regular assessment and follow-ups for HD patients ensuring better health and nutritional status.

Sensing Technology (ST) plays a key role in Structural Health Monitoring (SHM) systems. ST focuses on developing sensors, sensory systems or smart materials that monitor a wide variety of materials properties aiming to create smart structures and smart materials, using Embedded Sensors (ESs), and allowing continuous and permanent measurements of the structural integrity. The integration of ESs is limited to the processing technology to embed the sensor due to its high-temperature sensitivity and the possibility of damage during its insertion into the structure. In addition, the technological process selection is dependent on the base material composition, either metallic or composite parts. The selection of smart sensors or the technology underlying them is fundamental to the monitoring mode. This paper presents a critical review of the fundaments and applications of sensing technologies for SHM employing ESs, focusing on the actual developments and innovation of these, as well as analysing the challenges that these technologies present, to build a path that allows a connected world through distributed measurement systems.

In this paper we use the conformable fractional derivative to discuss some fractional linear differential equations with constant coefficients. By applying some similar arguments to the theory of ordinary differential equations, we establish a sufficient condition to guarantee the reliability of solving constant coefficient fractional differential equations by the conformable Laplace transform method. Finally, we analyze the analytical solution for a class of fractional models associated with Logistic model, Von Foerster model and Bertalanffy model is presented graphically for various fractional orders and solution of corresponding classical model is recovered as a particular case.

Artificial intelligence is dramatically transforming medical imaging. We assessed the levels of artificial intelligence use among radiology trainees and explored their perceived impact of artifi-cial intelligence on the radiology workflow and radiology profession, in correlation with the perceived ease of use and behavioral intention to use artificial intelligence. This cross-sectional study enrolled radiology trainees from Saudi Arabia, and an online 5-part-structured question-naire was disseminated via online networks to trainee in July 2021. We included 98 participants (51 male; age 27.59±2.02 years). Level of use was low; few used it in routine practice (7%). The impact of artificial intelligence on the radiology workflow was positively perceived in all radi-ology workflow steps (3.64–3.97 out of 5). A positive impact on the radiology profession was more frequently perceived for technical and performance aspects (81%–85%) compared with prestige and legal aspects (64%–71%). Perceived ease of use and behavioral intention to use arti-ficial intelligence was associated with the current professional activity, level of use artificial in-telligence use, and perceived impact on the profession as well as on radiology workflow (p<0.05). Levels of artificial intelligence use in radiology are very low. The perceived positive impact of ar-tificial intelligence on radiology workflow and profession is correlated with an increase in be-havioral intention to use artificial intelligence. Thus, increasing awareness about the favorable impact can improve the behavioral use.

The goal of our study was to examine the effect of regional characteristics of living environment on individual a priori and a posteriori dietary patterns of the Russian population. For the analysis, we used cross-sectional data from the Epidemiology of Cardiovascular Diseases in the Regions of the Russian Federation study of 2013-2014. The sample included 18,054 men and women 25-64 years of age from 12 regions. Based on the frequency of consumption of basic foods, four a posteriori empirical dietary patterns (EDPs), along with an a priori cardioprotective dietary pattern (CPDP) were identified. To describe the regional living environment, 5 regional indices were used. The adherence to the meat-based EDP was directly associated with deterioration of social living conditions and the more northerly location of the region of residence. The probability of CPDP increased with deterioration of social living conditions, an aggravation of demographic crisis, higher industrial development of the region, as well as with a decline in the economic development of the region, income and economic inequality of the population. We detected some gender-dependent differences in associations. The revealed patterns reflect the national dietary preferences of Russians, and regional indices characterize the effect of living environment.

The current work reveals the fine tuning between stability zones and randomness of GI/M/1 Pointwise Stationary Fluid Flow Approximation (PSFFA) model of the non-stationary D/M/1 queueing system. More specifically, this clearly provides more insights into developing a contemporary PSFFA theory that unifies non-stationary queueing theory with chaos theory and fields in both theoretical physics and chaotic systems. This opens new grounds for stability analysis of non-stationary queueing systems. A notable application of GI/M/1 queueing model to achieve ultra-low latency of autonomous driving service is highlighted. Concluding remarks associated with future avenues of research are given.

The present work was aimed at the investigation of effect of High Energy Ball Milling (HEBM) time on the sintering kinetics, structure, and properties of heavy tungsten alloy (HTA) W-7%Ni-3%Fe. The HTA samples were obtained from the nanopowders (20-80 nm) by conventional liquid phase sintering (LPS) in hydrogen and by Spark Plasma Sintering (SPS) in vacuum. The HTA density was shown to depend on the HEBM time non-monotonously that originates from the formation of non-equilibrium solid solutions in the W-Ni-Fe systems during HEBM. The SPS kinetics of the HTA nanopowders was shown to have a two-stage character, the intensity of which depends on the Coble diffusion creep rate and on the intensity of diffusion of the tungsten atoms in the crystal lattice of the -phase. The kinetics of sintering of the initial submicron powders have a single-stage character originating from the intensity of the grain boundary diffusion in the -phase. The dependencies of the hardness and of the yield strength on the grain sizes were found to obey the Hall-Petch relation. The hardness, strength, and dynamic strength in the compression tests of the fine-grained tungsten alloys obtained by SPS and LPS were studied.

Otolith morphology analysis is one of the main tools used for fish or fish stock identification. Moreover, otolith shape can also be used in fish dietary studies (stomach content) for the identification of prey fishes and their size according to the relationship between fish and otolith sizes. In the present study, the relationship between fish length and otolith morphological dimensions was investigated for the sabre squirrelfish, Sargocentron spiniferum (Forsskål, 1775) (family: Holocentridae). Samples of 185 fish were collected from the coast of the Red Sea, Egypt. To analyze the relationship between fish and otolith, otolith morphometric measurements (length, width, area, perimeter, weight, sulcus, and ostium) and shape factors (aspect ratio, compactness, form factor, rectangularity, roundness, ellipticity, squareness) describing outline shape were extracted using image analysis. Generalized linear models were applied for the relationship between body length and each otolith morphology feature. From the relationships between the total length of fish and fourteen morphology features, only otolith length, caudal length, and squareness were significantly correlated with fish size. Our results provide more information for the relationship between fish length and otolith morphometric features.

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

As abiotic stress, drought limits plant growth and minimizes productivity. The increased request for valuable essential oil extracted from geranium (Pelargonium graveolens L.) is mainly associated with plant growth, which is adversely affected by drought. Melatonin (MT) has been used to enhance plant growth under abiotic stress, however, its impact to overcome drought stress of aromatic plants including geranium is poorly investigated. In the current investigation, MT application at 100 µM was applied under 100 % (well-watered) or 50 % (drought stress) of FC to verify this role. Drought stress markedly reduced growth parameters, herb yield, and total chlorophyll; however, MT alleviated these effects. In contrast, drought enhanced the essential oil percentage in geranium leaves. Despite the reduction in oil yield caused by drought, MT application mitigated this reduction and improved both oil yield and oil components. Besides, MT treatment enhanced the accumulation of total phenols, glutathione, and proline and improved the activity of ascorbate peroxidase, catalase, and glutathione reductase with possible alleviation of drought-induced oxidative damage. Therefore, it reduced both H2O2 and malondialdehyde accumulation, and finally maintained membrane integrity. Overall, this is the first report that reveals that MT application can improve geranium resistance to drought by enhancing the antioxidant potential and protecting the cell membrane from oxidative damage.

Primary materials supply is the heart for engineering and sciences; depletion of natural resources and an increase in the human population by a billion in 13 to 15 years pose a critical concern on the sustainability of the materials. Therefore, functionalizing renewable materials, such as nanocellulose, possibly exploiting its properties for various practical applications, has been undertaken worldwide. Nanocellulose has emerged as a dominant green natural material with attractive and tailorable physicochemical properties, renewable, sustainable, biocompatibility, and tunable surface properties. Nanocellulose is derived from cellulose, the most abundant polymer in nature with remarkable properties of nanomaterials. This article provides a comprehensive overview of the methods used for nanocellulose preparation, structure-property and processing-property correlations, and the application of nanocellulose and its nanocomposite materials. This article differentiates the classification of nanocellulose, provides a brief account of the production methods that have been developed for isolating nanocellulose, highlights a range of unique properties of nanocellulose that have been extracted from different kinds of experiments and studies; and elaborates on nanocellulose potential applications in various areas. The present review is anticipated to provide the readers regarding the progress and knowledge related to nanocellulose. Pushing the boundaries of nanocellulose further into cutting edge applications will be of particular interest for the future, especially as cost-effective commercial sources of nanocellulose continue to emerge.

Chemoinformatics is the combination of physical chemistry theory with computer and information science techniques "in silico techniques" to a variety of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular areas. On the other hand, machine learning has become a vital tool for drug designers to mine chemical information from enormous compound databases in order to build medications with important biological features. In Egypt, chemoinformatics were used recently in different applications. For example; the development of new antimicrobial agents like tetracycline analog B (Iodocycline). Another area of application in bioinformatics included heart disease classification based on hybrid ensemble stacking technique. In the era of COVID-19, hybrid approach for COVID-19 detection from chest radiography was applied. Furthermore, bio/chemoinformatics methods were used to compare antimicrobial medications in order to choose an effective nose-to-brain formulation targeting meningitis infection by using differences in the drugs' primary structural, topological, and electronic characteristics. An example for this included cefotaxime and ceftriaxone that were examined at three levels: at formulation level, by comparing the loading in gelatin and tripalmitin matrices as basis for the production of nanoparticulate systems, at biopharmaceutical level, through interaction with mucin and the P-gp efflux pumps, and at therapeutic level, through studying the interaction with S. pneumoniae bacterial receptors.

The aim of this paper is to develop an intelligent event-driven Electrocardiogram (ECG) processing module in order to achieve an efficient solution for diagnosis of the cardiac diseases. The suggested method acquires the signal with an event-driven A/D converter (EDADC). The output of EDADC is passed through the activity selection and interpolation blocks. It allows focusing only on the important signal parts and resampling it uniformly. Later on, the signal is de-noised. The autoregressive (AR) method is used to extract the classifiable features of the de-noised signal. Afterwards, the output is classified by employing different robust classification techniques such as support vector machines (SVMs), K- Nearest Neighbor (KNN) and Artificial Neural Network (ANN). The event-driven feature enables to adapt the system processing load according to the signal temporal variations. This interesting feature of the devised system aptitudes a drastic reduction in its processing activity and therefore in the power consumption as compared to the traditional ones. A comparison of the performance of different classifiers is also made in terms of accuracy. Results show that the proposed system is a potential candidate for an automatic diagnosis of the cardiac diseases.

A single tree topology is a commonly employed topology for wireless sensor networks (WSN) to connect sensors to one or more remote gateways. However, its many-to-one traffic routing pattern imposes heavy burden on downstream nodes, as the same routes are repeatedly used for packet transfer, from one or more upstream branches. The challenge is how to choose the most optimal routing paths that minimizes energy consumption across the entire network. This paper proposes a proactive energy awareness-based many-to-one traffic routing scheme to alleviate the above said problem referred to as Energy Balance-Based Energy Hole Alleviation in tree topology (EBEHA-T). This protocol combines updated status of variations in energy consumption pattern around sink-hole zones and distribution of joint nodes among the trees. With this approach, EBEHA-T proactively prevents sink-hole formation instead of just a reactive response after they have occurred. Performance evaluation of EBEHA-T against benchmark method RaSMaLai shows increased energy saving across the entire network and a marked improvement in energy consumption balance in energy-hole zones. This precludes energy hole formation and the consequent network partitioning, leading to improved network lifetime beyond that of the RasMaLai. OMNET++ network simulation software has been used for the evaluation.

Cardiovascular disease (CVD) is the leading cause of death worldwide. Cardiac rehabilitation (CR) has proven to be effective in reducing the rate of recurrence and disease as secondary prevention (evidence-based intervention) in patients who have suffered from myocardial infarction (MI). CR is a multidisciplinary path in which the patient is followed pharmacologically, from a psychological, nutritional, nursing and physiotherapy point of view. Post-MI patients present a reduction in the performance of the diaphragm muscle, the main inspiratory muscle, and this condition can become a risk factor for further relapses or for the onset of heart failure. Despite the solidity of the international guidelines for CR, the latter are lacking in specifically indicating an evaluation and training path regarding the inspiratory muscles in post-MI patients who have not undergone cardiac surgery. The article reviews the information on the adaptation of the diaphragm post-MI and highlights the need for clearer indications for a rehabilitation process that gives importance to the diaphragm.

Zika virus (ZIKV) has been characterized as one of the potential pathogens and placed under future epidemic outbreaks by the WHO. However, lack of potential therapeutics can result in uncontrolled pandemic like other human pandemic viruses; therefore, prioritized effective therapeutics development has been recommended against ZIKV. In this context, the present study adopted the strategy to explore the lead compounds from Azadirachta indica against ZIKV via concurrent inhibition of the ZIKVpro and ZIKVRdRp proteins using molecular simulations. Initially, structure-based virtual screening of 44 bioflavonoids reported in Azadirachta indica against the crystal structures of targeted ZIKV proteins resulted in the identification of top four common bioflavonoids, viz. rutin, nicotiflorin, isoquercitrin, and hyperoside. These compounds showed substantial docking energy (-7.9 to -11.01 kcal/mol) and intermolecular interactions with essential residues of ZIKVpro (His51, Asp74, and Ser135) and ZIKVRdRp (Asp540, Ile799, and Asp665) by comparison to the reference compounds, O7N inhibitor (ZIKVpro) and Sofosbuvir inhibitor (ZIKVRdRp). Long interval molecular dynamics simulation (500 ns) on the selected docked poses reveals the stability of respective docked complexes contributed by intermolecular hydrogen bonds and hydrophobic interactions. The predicted complex stability was further supported by calculated end-point binding free energy using molecular mechanics generalized born surface area (MM/GBSA) method. Consequently, the identified common bioflavonoids are recommended as promising therapeutic inhibitors of ZIKVpro and ZIKVRdRp for further experimental assessment.

Astrocytes perform a wide variety of essential functions defining normal operation of the nervous system, and are active contributors to the pathogenesis of neurodegenerative disorders such as Alzheimer among others. Recent data provide compelling evidence that distinct reactive astrocyte states are associated with specific stages of Alzheimer´s disease. The advent of transcriptomics technologies enables rapid progress in the characterisation of such pathological astrocyte states. In this review, we provide an overview of the origin, main functions, molecular and morphological features of astrocytes in physiological as well as pathological conditions related to Alzheimer´s disease. We will also explore the main roles of astrocytes in the pathogenesis of Alzheimer´s disease and summarize main transcriptional changes and altered molecular pathways observed in astrocytes during the course of the disease.

Drug functionalization through formation of hydrophilic groups is the norm in phase I metabolism of drugs for modification of drug action. The reactions involved are mainly oxidative catalyzed mostly by CYP isoenzymes. The benzene ring, as phenyl or fused with other rings, is the most common hydrophobic pharmacophoric moiety in drug molecules. On the other hand the alkoxy group (mainly methoxy) bonded to the benzene ring assumes an important and sometimes essential pharmacophoric status in some drug classes. Upon metabolic oxidation, both moieties, i.e. the benzene ring and the alkoxy group, produce hydroxy groups; the products are arenolic in nature. Through a pharmacokinetic effect, the hydroxy group enhances the water solubility and elimination of the metabolite with the consequent termination of drug action. However, through hydrogen bonding, the hydroxy group may modify the pharmacodynamics of the interaction of the metabolite with the site of parent drug action (i.e. the receptor). Accordingly, the expected pharmacologic outcome will be enhancement, retaining, attenuation, or loss of activity of the metabolite relative to the parent drug. All the above issues have been presented and discussed in this review using selected members of different classes of drugs with inferences regarding mechanisms, drug design and drug development.

Al-6%Mg-Sc-Zr alloys with the total ratio of Sc + Zr = 0.32 wt.% make up the target of this research. The content of scandium and zirconium varied with an increment of 0.02%. The alloys were produced by induction casting. Their ultrafine-grained (UFG) microstructure was formed with Equal Channel Angular Pressing (ECAP). Such cast alloys have a homogeneous macrostructure formed by small equiaxed grains in the central part of the ingot and columnar crystals along the edges of the cross section. After ECAP, the average grain size in the alloy specimens is 0.5–1 µm. The average grain size does not depend on the ratio of Sc and Zr in these alloys. Superplasticity tests were performed at temperatures ranging from 300 to 500 °C and at a strain rate varying between 3.3·10-3 and 3.3·10-1 s-1. UFG Al-6%Mg-0.20%Sc-0.12%Zr and Al-6%Mg-0.18%Sc-0.14%Zr alloys exhibit the highest superplasticity. It was suggested that changes in Sc:Zr ratio affect spatial distribution and composition of the following precipitating particles: Al3Sc, Al3Zr, Al3(ScxZr1-x). An increase in Zr concentration is shown to reduce the susceptibility of UFG alloys to cavitation fracture.

As the coronavirus disease 2019 (COVID-19), which is caused by the novel SARS-CoV-2, continues to spread rapidly around the world, there is a need for well validated serological assays that allow the detection of viral specific antibody responses in COVID-19 patients or recovered individuals. In this study, we established and used multiple indirect Enzyme Linked Immunosorbent Assay (ELISA)-based serological assays to study the antibody response in COVID-19 patients. In order to validate the assays we determined the cut off values, sensitivity and specificity of the assays using sera collected from pre-pandemic healthy controls, COVID-19 patients at different time points after disease-onset, and seropositive sera to other human coronaviruses. The developed SARS-CoV-2 S1 subunit of the spike glycoprotein and nucleocapsid (N)-based ELISAs not only showed high specificity and sensitivity but also did not show any cross-reactivity with other CoVs. We also show that all RT-PCR confirmed COVID-19 patients tested in our study developed both virus specific IgM and IgG antibodies as early as week one after disease onset. Our data also suggest that the inclusion of both S1 and N in serological testing would capture as many potential SARS-CoV-2 positive cases as possible than using any of them alone. This is specifically important for tracing contacts and cases and conducting large-scale epidemiological studies to understand the true extent of virus spread in populations.

In recent years, Blockchain has been favorably adopted in the Supply Chain industry as it provides guaranteed transparency and traceability. The flexibility of Blockchain allows different applications to enable to exchange information; a significant middleweight layer is responsible for information transfer in the Agricultural Sector. The products that are manufactured at a global level in the agriculture industry are improved in safety, validation of some criteria, and quality. In the agriculture industry, the increasing number of complications associated with food safety and impurity risks needs high-level effective traceability solutions that act as necessary quality management tools to make sure satisfactory safety of crops. The agricultural supply chain today has complex ecosystems, consisting of several stockholders to authenticate criteria which are important like crop development stages, monitoring and validation, and compliance with the quality standard. In this proposed research, a systematic literature review will be done that includes smart contracts, Blockchain, and business transactions exclusively for crop production traceability across the agricultural and food supply chain. By using Blockchain in the agriculture sector, productivity, consistency, safety, reliability, and advanced security are increased. All transactions are kept and recorded on the immutable record of Blockchain associates with a decentralized system. Thus, it provides more traceability and clarity in the agriculture system in asafe, trustworthy, and effective way. A systematic literature review is thus enforced to classify the papers which are selected by the following classification: crop traceability, contribution type, research type, and their approach. For this systematic review, the papers which extracted are classified according to defined criteria. The purpose of this study is to fill the gap by collecting and analyzing studies available within the literature aiming to firstly, gain complete insight on the integration of Blockchain in the agriculture sector. Secondly, provide a summary of the present state of research on this area and identify gaps in existing studies. To achieve this aim an SLR was conducted. The findings of this SLR are discussed and researchers were provided with suggestions on possible directions for future research.

We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

Competition between cotton, winter, and summer crops is the greatest obstacle for plant breeders in Egypt. Breeders are thus seeking early maturing, high-yielding cultivars that are suited for planting following winter crops. This study was conducted during the 2016 and 2018 growing seasons at the Sakha agriculture research station, Egypt's agricultural research facility. This research used breeding material from the F2, F3, and F4 generations that resulted from crossing Giza 94 and Uzbekistan. During the 2016 growing season, the F2 population was cultivated, and the top 5% of the F2 population (75 plants) were chosen based on the selection criteria. In the summer of 2017, the F3 families were cultivated, and 5% of the superior F3 families were chosen to become the F4 fam-ilies, which were planted in the summer of 2018 at the single plant and bulk studies in a randomised full block design with three replications. The average performance of the characteristics boll weight, seed cotton yield, lint percentage, and lint index increased as generations passed from F2 to F4. In the meanwhile, the characteristic value of the first flower to open decreased, showing the accu-mulation of advantageous alleles. For all examined characteristics, the phenotypic coefficient of variance was greater than the genotypic coefficient of variation. In addition, the data demonstrated that heritability in a broad sense was greater in F4 populations than in F3 and F2 populations. With a few exceptions, the phenotypic and genotypic associations for all investigated characteristics were positive and very significant. According to the data, initial opening flowering and boll weight had a substantial impact on seed cotton output per feddan. In general, five superior families No. 9, 13, 18, 19, and 20 were chosen from the F4 population, which were more significant for yield and yield component than the commercial variety, and these genotypes may be promising for the breeding programme to develop new genotypes with superior yield.

In an attempt to improve the quality of the agricultural drain in Egypt for its reuse again in the irrigation, low cost solution such as sand filter along with/ without other filtration media have been used in this research, As a result of that, pilot plant of sand filter mixed with other filtration media was tested for its ability to improve the sand performance in removing the suspended solids and organic matters from agricultural drain water of the Belbeis drain (in Sharkia governorate in Egypt). Only sand compared with sand with sponge and sand with Liyan Nanfang activated carbon (L.N.A.C) have been tested to find the optimum mixing sand/ medium ratio &optimum infiltration rate. The work has been done on four runs. It was found that sand mixed with sponge gave the best removal efficiency compared to that of the sand only and the sand mixed with L.N.A.C. The results presented that the concentration of CODt, CODsol and TSS was reduced from 125, 47 and 162 mg/l to 44, 34 and 28 mg/l respectively at optimum infiltration rate of 2 m³/m²/d for sand mixed with sponge.

Lomefloxacin (F1) and pefloxacin (F2) have a broad spectrum of antimicrobial activities against Gram-positive and Gram-negative bacteria. In this study, we investigated the complexation mode, morphological and biological properties of four metal-based complexes of F1 and F2 molecules with Mg(II), Ca(II), Zn(II), and Fe(III) metal ions. These complexes were prepared at ~60–70°C in a neutral medium using a 5% NH3 solution at pH ~7-8 with a 1:1 ratio. Multiple physicochemical methods were employed to characterize the binding mode between F1 and F2 with the metal ions under investigation. The results of these methods suggested that the gross formula of the complexes obtained with the metal ions were [MgF1(H2O)Cl]2H2O, [CaF1(H2O)Cl]3H2O, [ZnF1(H2O)Cl], [FeF1(H2O)2Cl2]Cl2H2O, [MgF2(H2O)Cl]2H2O, [CaF2(H2O)Cl]3H2O, [ZnF2(H2O)Cl], and [FeF2(H2O)2Cl2]Cl2H2O. The microscopic characterizations indicated that the Ca(II)-F1 complex had an interesting surface topography. Its particles had a homogenous, short, rod-like shaped structure that clustered together to form a tree shape. Using the Kirby-Bauer disc diffusion protocol, the synthesized metal-based complexes were screened in vitro against different Gram-positive and Gram-negative bacterial and fungal species. The antimicrobial profile of the Fe(III)-F1 complex indicated that it had remarkable inhibitory activity against all the tested bacterial and fungal species with potency equal to that of the standard drugs (streptomycin and ketoconazole).

This study aims to characterize the molecular profile of hepatitis B virus (HBV) among socially vulnerable immigrants residing in Brazil to investigate the introduction of uncommon HBV strains into the country. Serum samples from 102 immigrants with positive serology for HBV core antibody (anti-HBc) were tested for the presence of HBV DNA by PCR assays. Among these, 24 were also positive for the HBV surface antigen (HBsAg). The full or partial genome was sequenced to determine genotype by phylogenetic analysis. Participants were from Haiti (79.4%), Guinea Bissau (11.8%), Venezuela (7.8%), and Colombia (1%). Of the 21 HBV DNA-positive samples, subgenotypes A1 (52.4%), A5 (28.6%), E (9.5%), F2 (4.8%), and F3 (4.8%) were identified. Among the 78 HBsAg-negative participants, four were positive for HBV DNA, resulting in an occult HBV infection rate of 5.1%. Phylogenetic analysis suggested that most strains were likely introduced to Brazil by migration. Importantly, 80% of A5 sequences had the A1762T/G1764A double mutation, linked to an increased risk of hepatocellular carcinoma development. In conclusion, this study is the first report of HBV subgenotype A5 in Brazil, shedding new light on the diversity of HBV strains circulating in the country. Understanding the genetic diversity of HBV in immigrant communities can lead to better prevention and control strategies, benefiting both immigrants and the broader society.

Brushless Synchronous Machines (BSM) are replacing conventional synchronous machines with static excitation in generation facilities due to the absence of sparking and lower maintenance. However, this excitation system makes challenging measuring electric parameters in the rotor. This fact highly difficult the detection of ground faults, which are the most common type of electrical fault in electric machines. In this paper, a ground fault detection method for BSM is proposed. It is based on an inductive AC/DC rotating current sensor installed in the shaft. In case of a ground fault in the rotating parts of the BSM, a fault current will flow through the rotor’s sensor, inducing voltage in its stator. Analyzing the frequency components of the induced voltage the detection of a ground fault in the rotating elements is possible. The ground faults detection method proposed covers the whole rotor and discern between DC and AC sides. To corroborate the detection method, experimental tests have been performed using a prototype of this sensor connected to laboratory synchronous machines achieving satisfactory results.

This study reports the synthesis and characterization of novel per-fluorinated organic polymers with azo- and azomethine-based linkers using nucleophilic aromatic substitution. The polymers reveal variations in the fluorine content via the incorporation of decafluorobiphenyl and hexafluorobenzene linkers, which enhanced their hydrophobic nature. The rich fluorine polymers were slightly soluble in THF and have shown molecular weights between 4886 to 11948 g/mol. All polymers exhibit thermal stability in the range of 350-500°C, with varying thermal stability depending on the fluorine and nitrogen content. Conjugation of the polymers was confirmed through changes in the UV-Vis spectra, with a hypsochromic shift observed in all cases, more pronounced in azo-based fluorinated chains due to H-bonding on the nitrogen sites, chain conformations, and planarity. The optical band gap (Eg) of the polymers was determined from the UV-Vis data, with the Eg values of the azo-based fluorinated polymers being 1 eV higher than those of their corresponding linkers. The cross-linking formation was characterized by porosity measurements, with the azo-based polymer exhibiting the highest surface area of 770 m²/g with a pore volume of 0.35 cm³/g, while the open-chain azomethine-based polymer exhibited the lowest surface area of 285 m²/g with a pore volume of 0.0872 cm³/g. Porous structures with varied hydrophobicities were investigated as adsorbents for separating water-benzene and water-phenol mixtures and selectively binding methane/carbon dioxide gases from the air. The most hydrophobic polymers containing the decafluorbiphenyl linker were suitable for benzene separation, while the best methane uptake values were 6.14 and 3.46 mg/g for DAB-Z-1O and DAB-A-1O, respectively. DAB-Z-1h, with the highest surface area and rich in nitrogen sites, exhibited the highest CO₂ uptake at 298 K (17.25).

Conventional diagnostic techniques are based on utilization of analyte sampling, sensing and signalling on separate platforms for detection purposes, that must be evaded and integrated to a single step procedure in point of care (POC) testing devices. Therefore, the trend has been shifted towards utilization of microfluidic platforms for detection of analytes in biochemical, clinical and food technology due to its being expeditious. Microfluidic systems moulded with polymer substances or glass offer specific and sensitive detection of infectious and non-infectious diseases by providing innumerable benefits including less cost, good biological affinity, strong capillary action and simple process of fabrication. In the case of nucleic acid-based nanosensors, there are some challenges that need to be addressed such as cellular lysis, isolation and amplification of nucleic acid required to be accomplished prior to its detection. To avoid utilization of laborious steps for executing these steps, advances have been deployed in this perspective for on-chip sample preparation, amplification and detection which not only improves sensitivity and selectivity but also saves time and resources. This review emphasizes the significance of microfluidic technology for nucleic acid detection of infectious and non-infectious diseases. The implementation of isothermal amplification in concomitance with lateral flow assay greatly increases the binding efficiency of nanoparticles and biomolecules, improves limit of detection and sensitivity. Most importantly deployment of paper-based material made of cellulose reduces the overall cost. Microfluidic technology in nucleic acid testing has been discussed by explicating its applications in different fields. This review concludes with the prospects and proposes future directions in microfluidic based methods in disease diagnosis.

The ability to simulate realistically the electronic structure of superconducting materials is important to understand and predict various properties emerging in both the superconducting topological and spintronics realms. We introduce a tight-binding implementation of the Bogoliubov-de Gennes method, parameterized from density functional theory, which we utilize to explore the bulk and thin films of Nb, known to host a significant superconducting gap. The latter is useful for various applications such as the exploration of trivial and topological in-gap states. Here, we focus on the simulations aspects of superconductivity and study the impact of temperature, Cooper-pair coupling and dimensionality on the size of the superconducting order parameter.

The objective of this study was to correlate the binding of drugs on a very popular nanoparticulate polymeric matrix; PLGA nanoparticles with their main constitutional, electronic and physico-chemical descriptors. Gaussian Processes (GPs) was the artificial intelligence machine learning method that was utilized to fulfil this task. The method could successfully model the results where optimum values of the investigated descriptors of the loaded drugs were deduced. A percentage bias of 12.68 % ± 2.1 was obtained in predicting the binding energies of a group of test drugs. As a conclusion, GPs could successfully model the drugs-PLGA interactions associated with a good predicting power. The GPs-predicted binding energies (ΔG) can easily be projected to the drugs loading as was previously proven. Adopting the “Pharmaceutics Informatics” approach can save the pharmaceutical industry and the drug delivery scientists a lot of exerted resources, efforts and time.

The COVID-19 outbreak has focused attention on the use of social distancing as the primary defence against community infection, yet forcing social animals to maintain that physical distance has presented significant challenges for health authorities and law enforcement. Anecdotal media reports suggest widespread dissatisfaction with social distancing as a policy, yet there is little prior work aimed at measuring community acceptance of social distancing. In this paper, we propose a new approach to measuring attitudes towards social distancing by using social media and sentiment analysis. Over a 4 month period, we found 82.5% of tweets were in favour of social distancing. The results indicate a widespread acceptance of social distancing in the community. We conclude by examining options for estimating the optimal (minimal) social distance required at scale, and the implications for securing widespread community support and acceptance of public health messaging.

The present study was aimed at revealing the influence of the mechanical stress induced by water molecules adsorption on the composition of crystalline phases in the ZrO2–3mol%Y2O3-nanoparticles. Three basic methods have been used to determine the phase transition: neutron diffraction, Raman microspectroscopic scanning, and X-ray diffraction. The fact of phase-structural β → α transformation and the simultaneous presence of two polymorphic structural modifications (β is the phase of the tetragonal syngony and α of monoclinic syngony in nanosized particles (9nm)) under normal physical conditions was established by these methods. Satisfactory consistency was achieved between the results obtained using different techniques.

In the software development process, the decision-maker (DM) has a range of problems inherent to its function. Wrong choices during software planning can bring great risk to the project. Therefore, the planning of software releases to be delivered to the customer should be well done. This is not an easy task because releases are made up of many requirements that contain complex variables that must be considered, such as precedence, cost, requirement stability, among other features that make the requirements-selection process challenging. To make this process less exhaustive, DM can use tools that facilitate this work. In software engineering, we can find fields of research specialists in this context, such as Search-Based Software Engineering (SBSE). The SBSE makes use of advanced metaheuristics to search for optimal solutions or the closest to it. In this work, we try to use another field of research to solve this same problem type, the Verbal Decision Analysis (VDA). To do this, we elaborate a workflow that will use the same source data, execute two solutions using the two search fields (SBSE and VDA) and compare the results. In the end, we evaluated and commented on the results.

The paper proposes a mechanism for the impact of changes in the key rate on the volume of newly issued loans. The volume depends on the price (interest rates on loans), and the price depends on the key rate and the actual consumption of loans in the previous period (generalized cobweb cycle). The model was estimated by a Kalman filter, adequacy was confirmed by simulation. It is possible to forecast the average rate on loans for a month in advance according to the information published by the Central Bank of the Russian Federation (CB). By playing various scenarios for changing the key rate, it was found that in quiet periods of economic development, the usual laws of supply and demand operate in the loan market and by raising the key rate, you can reduce inflation. In the turbulent (overheated) state of the economy, an increase in the key rate can, on the contrary, provoke an increase in the issuance of loans and unconventional manipulations with the key rate are required.

Many years and $$$ spent for research did not yet produced a universally effective gene therapy of prostate cancer (PCa). Our studies indicated that not only each human, but even each cancer nodule in the same tumor has unique and dynamic gene expression profile, control and coordination. The tumor heterogeneity of the transcriptome topology is a strong argument in favor of personalized gene therapies, tailored on patients’ primary tumor unique characteristics. Here, we propose a bioinformatics procedure by which to identify the Gene Master Regulators (GMR) of cancer cells from transcriptomic data and predict consequences of their experimental manipulation. The procedure, based on our Genomic Fabric Paradigm (GFP), can determine the most important gene in each cancer nodule whose controlled alteration would selectively kill the cancer cells. In this report, the method is applied to our microarray data on two men PCs (each with three distinct cancer nodules) and two standard human PCa cell lines (DU145 and LNCaP). We expect the industry to produce ready-to-use CRISPR constructs for all genes allowing the clinical oncologist to prescribe the adequate personalized CRISPR cocktail for his/her patient. Thus, the GMR approach may provide the most effective, yet affordable solution in fighting cancer.

Tdp1 and Tdp2 are DNA repair enzymes that repair DNA damages caused by various agents, including anticancer drugs. Thus, these enzymes resist anticancer therapy and could be the reasons of resistance to such widely used drugs as topotecan and etoposide. In the present work, we found compounds capable of inhibiting both enzymes among derivatives of (-)-usnic acid. Both (+)- and (-)-enantiomers of compounds act equally effectively against Tdp1, and only (-)-enantiomers inhibited Tdp2. Surprisingly, the compounds protect HEK293FT wild type cells from the cytotoxic effect of etoposide but potentiate it against Tdp2 knockout cells. We assume that the sensitizing effect of the compounds in the absence of Tdp2 is associated with effective inhibition of Tdp1, which could take over the functions of Tdp2.

Mining is an important industry, accounting for 6.9% of global GDP. However, global development promotes accelerated demand, resulting in the accumulation of hazardous waste in land, sea, and air environments. It reached 7 billion tonnes of mine tailings generated yearly worldwide, and 19 billion solid tailings will be accumulated by 2025. Adding to this, the legacy of environmental damage from abandoned mines is worrying; in Canada there are around 10,000 abandoned mines, 50,000 in Australia, 6,000 in South Africa, and 9,500 coal mines in China, reaching 15,000 by 2050. In this scenario, restoration techniques from mining tailing have become increasingly discussed among scholars due to their potential to offer benefits towards reducing tailings levels, thereby reducing environmental pressure for the correct management and adding value to previously discarded waste. This review paper explores available literature on the main techniques of mining tailing recycling and reuse and discusses leading technologies, including the benefits and limitations, as well as emerging prospects. The findings of this review serve as a supporting reference for decision-makers concerning the related sustainability issues associated with mining, mineral processing, and solid waste management.

This paper based on systems - theoretic approach to the definition of a country's GDP as not directly observable characteristic of system state. Leontief dynamic model is generalized to take into account the stimulating effect of consumption on GDP growth. In consumption, apart from final consumption, terms are considered: balance of foreign trade, fictitious investments and hidden costs. The Kalman filter uses Rosstat's gross output (for system output) and final consumption (for system control) data from 1995 to 2015. It is concluded that if in the years 2014, 2015 it was possible to increase consumption by 5% by, say, price cuts or some increase in money supply, then GDP would be greater by about 2.5%. GDP real values in recent years are most likely greater than official values. Fictitious investments and hidden costs are found in the amount of up to third the value of final consumption. The accuracy of one-year forecasts of true GDP by the methodology of this article is approximately 1.5%.

Base excision repair (BER) is the predominant pathway to remove most forms of hydrolytic, oxidative and alkylative DNA damage. The precise functioning of BER is achieving by the regulation of each step by regulatory/accessory proteins, with the most important of which being poly(ADP-ribose) polymerase 1 (PARP1). The PARP1 regulatory functions extend to many cellular processes including regulation of mRNA stability and decay. PARP1 can therefore affect BER both at the level of the BER proteins and at the level of their mRNAs. Systematic data on how the PARP1 content affects the activities of key BER proteins and the levels of their mRNAs in human cells are extremely limited. In this study the CRISPR/Cas9 based technique has been used to knocked out the PARP1 gene in the human HEK 293FT line. The obtained cell clones with putative PARP1 deletion were characterized by several approaches including: PCR analysis of deletions in genomic DNA, Sanger sequencing of genomic DNA, qPCR analysis of PARP1 mRNA, western-blot analysis of whole-cell-extract proteins with anti-PARP1 antibodies, and the PAR synthesis in the whole-cell-extracts. qPCR analysis of mRNAs coding the BER related proteins: PARP2, uracil DNA glycosylase 2, AP endonuclease 1, DNA polymerase β, DNA ligase III and XRCC1 did not reveal crucial influence of PARP1 knockout. The corresponding catalytic activities in the whole-cell extracts (WCEs) evaluated in parallel did not differ significantly between mutant and parental cell lines. No considerable influence of poly(ADP-ribose) synthesis on the activity of the above WCE enzymes was revealed.

The research that we are referring to examines the morphological, structural, and optical characteristics of kesterite (Cu1-xAgx)2ZnSnS4 (CAZTS) thin films, which are produced using a process known as thermal evaporation (TE). The study's main goal was to determine how different Ag contents affect the characteristics of CAZTS systems. X-ray diffraction (XRD) and Raman Spectroscopy: were used to confirm the crystal structure of the CAZTS thin films. Using a mathematical model of spectroscopic ellipsometry, the refractive index (n) represented the part of the complex refractive index, the extinction coefficient (k) portrayed the imaginary one, and also the energy band gap of the fabricated films were all calculated. The energy band gap of the thin films was also calculated. This is a crucial parameter for solar cell applications, as it determines the wavelength of light that the material can absorb. The energy band gap was found to decrease from 1.74 eV to 1.55 eV with increasing Ag content. The ITO/n-CdS/p-CAZTS/Mo heterojunction was well constructed, and the primary photovoltaic characteristics of the n-CdS/p-CAZTS junctions were examined for use in solar cells. Different Ag contents of the CAZTS layers were used to determine the dark and illumination (current-voltage) characteristics of the heterojunctions. The study's findings collectively point to CAZTS thin layers as potential absorber materials for solar cell applications.

The treatment of petroleum refinery wastewater (PRWW) is of great interest in the field of industrial wastewater management. The wastewater contains a diverse concentration of contaminants such as oil and grease, petroleum hydrocarbons, phenol, ammonia, sulfides, as well as other organic and inorganic composites etc. The treatment of refinery wastewater has been treated through various processes including; physical, biological, chemical or hybrid methods which combine two or more techniques. Hence, the objective of this review is to summarize the recent research studies applied in the treatment of petroleum refinery wastewater using conventional, advanced as well as integrated treatment techniques. Furthermore, critically highlight the efficiencies and major limitations of each technique as well as prospects for improvement. Several conventional treatment techniques (basically, the physicochemical and biological processes) were discussed. In this context, advanced oxidation processes (AoPs) especially electrochemical oxidation and photocatalysis as well as the integrated/hybrid processes are found effective to remove the recalcitrant fraction of organic pollutants because of their various inherent mechanisms. These techniques could effectively remove COD and phenols concentration with an average removal efficiency exceeding 90%. Hence, the review also presented an elaborate discussion of the photocatalytic process as one of the advanced techniques and highlighted some basic concepts to optimize the degradation efficiency of a photocatalyst. Finally, a brief recommendation for research prospects is also presented.

Electric vehicles (EV) are getting more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace the internal combustion engine (ICE) vehicles in near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system can face huge instabilities with enough EV penetration; but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of smart grid. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emission from the transportation sector. However, there are some major obstacles for EVs to overcome before replacing the ICE vehicles totally. This paper is focused on reviewing all the useful data available on EV configurations, energy sources, motors, charging techniques, optimization techniques, impacts, trends, and possible directions of future developments. Its objective is to provide an overall picture of the current EV technology and ways of future development to assist in future researches in this sector.