Deciding when to replace dairy bulls presents a complex challenge for artificial insemination (AI) companies. These decisions encompass multiple factors, including a bull's age, predicted semen production, and estimated genetic merit. This study's purpose was to provide a practical, objective tool to assist in these decisions. We utilized a Markov Chain model to calculate the economic valuation of dairy bulls, incorporating key factors such as housing costs, collection and marketing expenses, and the bull's probable tenure in the herd. Data from a leading AI company were used to establish baseline values. The model further compared a bull's net present value to that of a potential young replacement, establishing a relative valuation (BullVal$). The range of BullVal$ observed spanned from -$316,748 to $497,710. Interestingly, the model recommended culling for 49% of the bulls based on negative BullVal$. It was found that a bull's net present value was primarily influenced by market allocation and pricing, coupled with the interaction of semen production and genetic merit. This study offers a robust, data-driven model to guide bull replacement decisions in AI companies. Key determinants of a bull's valuation included market dynamics, semen production rates, and genetic merit.

Anaerobic digestion has emerged as an increasingly popular method for the effective management of organic waste and wastewater with the potential to generate renewable energy. However, efficient digestion depends heavily on the complex and diverse microbial communities mediating this process. This review paper delves into the complex microbiome that exists within anaerobic digestion digesters, playing a critical role in the efficient and sustainable conversion of organic waste into biogas. Its primary focus falls within the scope of how various operational and environmental factors, including temperature, pH, hydraulic retention time, substrate loading rates, and the presence of inhibitory compounds, can substantially impact the microbiome of these systems. Through an extensive analysis of the existing literature, the microbial ecology of anaerobic digestion, including the composition and function of the microbial community, their interactions, and responses to different stressors, are evaluated. By offering critical insights into the distribution patterns of active microbial populations upon alterations in various process parameters, a better understanding of the microbial dynamics within these systems is provided, enhancing their efficiency. Overall, this paper emphasizes the importance of unraveling the microbial evolution within AD reactors to optimize biogas production and sustainable waste management and proposes future perspectives in this direction.

Biogas production from organic waste is a promising renewable energy source, but achieving optimal production and digester stability can be challenging. This study investigated the impact of the Evogen microbial additive on biogas production and digester quality through microbial abundance and physicochemical parameter analysis. Two biogas plants, BG01 and BG02, were examined using 16S rRNA profiling to assess microbial abundance. Simultaneously, physicochemical parameters, including FOS/TAC ratio, total solids, volatile solids, biogas production, and VFA profile, were measured to evaluate digester performance. Results revealed distinct microbial community shifts in Evogen-treated digesters. Increased abundance of methanogenic archaea and hydrolytic bacteria indicated improved anaerobic digestion. Evogen supplementation also positively affected digester performance, with higher FOS/TAC ratios indicating enhanced acidification and methanogenesis. Reductions in total solids and volatile solids demonstrated improved organic matter degradation. Significantly higher biogas production was observed in Evogen-treated digesters, highlighting its potential as a microbial additive. Furthermore, VFA profiling demonstrated improved process stability and reduced substrate inhibition in Evogen-treated digesters. In summary, Evogen microbial additive positively influenced microbial dynamics, improving biogas production and digester quality. These findings contribute to optimizing biogas production systems and understanding the complex microbial interactions within anaerobic digesters.

Additives can improve the efficiency of anaerobic digestion by increasing biogas production, reducing air pollution, and preventing total ammoniacal nitrogen (TAN) inhibition. Biological or chemical supplementation can also improve the economic efficiency of anaerobic digestion. However, the effects of specific additives on biogas production can vary depending on the type of supplement used. This research utilizes the additives on an industrial scale and monitors the optimization of the anaerobic digestion operating parameters after their addition. The various AD additives were examined in a sufficient cycle of operation for three biogas plants located in northern Greece. In this manner, the effectiveness was investigated in multiple initial feeds and unstable operating situations caused by the seasonality of specific feedstocks. The existing operation state in the three biogas plants was recorded before and after adding the supplements. In all three cases, lower concentration levels were observed in many of the examined trace elements. Introducing additives proved to be a stabilization factor in AD performance and inhibition mediator.

Almost two decades ago, Ernesto P. Borges and Bruce M. Boghosian embarked on the intricate task of composing a manuscript to honor the profound contributions of Constantino Tsallis to the realm of statistical physics, coupled with a concise exploration of q-Statistics. Fast forward to Constantino Tsallis’ illustrious 80th birthday celebration in 2023, where Deniz Eroglu and Ugur Tirnakli delved into Constantino’s collaborative network, injecting renewed vitality into the project. With hearts brimming with appreciation for Tsallis’ enduring inspiration, Eroglu, Boghosian, Borges and Tirnakli proudly present this meticulously crafted manuscript as a token of their gratitude.

For this research, a comparative evaluation was performed in which the addition of 3D-printed biocarriers fabricated with 13X and Halloysite (13Χ-Η) and commercial Kaldnes K1 biocarriers were evaluated as opposed to the non addition of biocarriers in a semi-pilot scale MBBR-MBR unit. For the evaluation of the MBBR-MBR efficiency, various physicochemical parameters were measured while static light scattering and optical microscopy observations were additionally used. Biofilm extracted from the biocarriers was also evaluated. It was observed that in the MBBR-MBR K1 unit, the membrane filtration improved while in the MBBR-MBR 13X-H unit the membrane fouling rate was the same as in the control MBBR-MBR unit. This is due to the production of large amount of SMP which resulted from the large amount of biofilm created in the 13X-H biocarriers. An optimal biodegradation of the organic load was concluded for all three MBBR-MBR units. The nitrification and denitrification processes were improved at the MBBR-MBR units using 13X-H and K1. The dry mass produced on the 13X-H biocarriers was three orders of magnitude larger than that produced on the K1. Finally, it was observed that mostly EPS was produced in the biofilm of K1 biocarriers while in the biofilm of 13X-H mostly SMP.

The physiological characteristics of liquid digestate retrieved from various biogas plants based in northern Greece are presented. Preliminary photocatalysis experiments on inoculated liquid di-gestate sampled showed that disinfection is possible when pre-treated digestate with a combination of centrifuge-flocculation-μFiltration after 5.5 hours of 0.7g/L suspended TiO2 under UVA illumination for the experimental conditions is used. A novel design photocatalytic nanofiltration reactor was implemented for disinfection experiments on pre-treated liquid digestate, giving promising results. This work sets the basis for the efficient operation and engineering application of technology collaboration with photocatalysis as the final step for liquid digestate sanitation and reusable water recovery.

Organic wastes and by-products from several activities, including food industries, farming, and animal husbandry, are a hygiene threat when aerobically decomposed. Therefore, their manage-ment is crucial for public health. In this direction, anaerobic digestion (AD) systems may be the solution by transforming waste into energy, which may decrease the environmental impact. However, their efficacy should be carefully examined. In this innovative study, we evaluated the physicochemical and microbial characteristics of liquid digestate (LD) retrieved from organic animal wastes in northern Greece using nanofiltration. Using treatment technologies including physical (solid-liquid separation, microfiltration and nanofiltration) and biological (anaerobic digestion), heavy metals and microbial (i.e., Salmonella spp., Escherichia coli, Enterococcus faecalis) concentrations reduced and nutrients were recovered. This work sets the basis for the efficient management of liquid digestate. Our method may enable the use of treated liquid digestate for unlimited irrigation water and other industrial applications of water. Apart from the sanitation process, the recovery of nutrients for soil fertilization seems to be a more sustainable way for fu-ture agricultural practices.

The field of applied behavior analysis has been directly involved in both research and applications of behavioral principles to improve the lives of captive zoo animals. Thirty years ago, Forthman and Ogden (1992) wrote one of the first papers documenting some of these efforts. Since that time, considerable work has been done using behavioral principles and procedures to guide zoo welfare efforts. The current paper re-examines and updates Forthman and Ogden’s original points, with attention to the five categories they detailed: (1) promotion of species-typical behavior, (2) reintroduction and repatriation of endangered species, (3) animal handling, (4) pest control, and (5) animal performances. In addition, we outline three current and future directions for behavior analytic endeavors: (i) experimental analyses of behavior and the zoo, (ii) applied behavior analysis and the zoo, and (iii) within-subject methodology and the zoo. The goal is to provide a framework that can guide future behavioral research in zoos, as well as create applications based on these empirical evaluations.

The number of children diagnosed with autism spectrum disorder (ASD) has increased substantially over the past two decades with current research unable to fully account for this dramatic increase in prevalence. One explanation proposes that both intrinsic (e.g., genetic) and extrinsic (e.g., environmental) risk factors may be involved in the etiology of ASD. The goal of this review paper is to explore modifiable pathways for intervention in children at risk for ASD, specifically examining how early social experience may be correlated with epigenetic change in genes associated with autism. We present an innovative model which proposes that polygenic risk and social experience (via epigenetic mechanisms) may both contribute to the observed ASD phenotype. Previous research on genetic, environmental, and epigenetic mechanisms implicated in the etiology of ASD will be reviewed, with an emphasis on the oxytocin receptor gene, which is epigenetically altered by early social experience, plays a crucial role in mammalian social and cognitive development, and is associated with both genetic and epigenetic risk for ASD. Identifying intrinsic (e.g., genetic) and extrinsic (e.g., social experience) risk markers for ASD, a combination of which has not previously been examined, would transform our understanding of this condition, facilitate earlier identification of ASD risk, and guide early intervention efforts. This may have a far-reaching impact on individuals with ASD, their families, and society.

Many corporations have now revised their value statements to showcase their commitment to sustainable development and green business due to the pressing issues of climate and environmental damage. Despite the importance of value statements that can direct companies to achieve sustainable goals, what kind of values can be perceived as organizational orientations to sustainability remains unknown. This study explores how the general public views the inclusion of sustainable components in value statements from the listed companies in Hong Kong by using Q-sort methodology (n = 30). Analyzing the final sample of 40 value statements extracted from 27 listed companies, we identified three factors related to sustainability, namely, Empowering business process management, Empowering customer-centric excellence, and Empowering sustainable progress. This study provides an additional component to the traditional triple bottom line by suggesting that internal operation of a company is an emerging idea to understand corporate sustainability.

As modern systems are becoming more complex their control strategy cannot longer relay only on measurement information that usually comes from probes but also from mathematical models. Those systems models can lead to unbearable computation times due to their own complexity, turning the control process non-viable, which leads to the implementation of surrogate models that enable to achieve estimates within acceptable time to take decisions. A control trained with Deep Reinforcement Learning algorithm, using a Physics-Informed Neural Network to obtain the temperature map on the following time step, replaces the need of running Direct Numerical Simulations. On this work we considered an 1D heat conduction problem, which temperature distribution feeds a control system to activate a heat source aiming to obtain a constant, previously defined, temperature value. With this approach, control training becomes much faster without the need of performing numerical simulations or laboratory measurements, as well the control is taken based on Neural Network enabling its implementation on simple processors to edge computing.

The potential agricultural use of metal nanoparticles (NPs) for slow-release micronutrient fertilizers is beginning to be investigated by both industry and regulatory agencies. However, the impact of such NPs on soil biogeochemical cycles is not clearly understood. In this study, impacts of a commercially-available copper NPs on the soil nitrification kinetics was investigated via batch experiments. The X-ray absorption near edge structure spectroscopy analysis showed that the NPs readily oxidized to Cu(II) and strongly retained in soils with minimum dissolution (<1% of total mass). The Cu2+ (aq) at 1mg/L showed the beneficial effect on the nitrification, an increase in the rate of nitrification kinetics (Vmax). However Vmax was negatively impacted by ionic Cu at 10-100mg/L and CuNP at 1-100 mg/L. The trace metal toxicity of soil nitrifiers seems to be critical in the soil nitrification processes. Among CuNPs, the suppressed nitrification kinetics was concentration dependent at >10mg/L. The reaction products of surface oxidation such as the release of ionic Cu seem to play an important role in suppressing the nitrification process. Considering the potential use of copper NPs as a slow-release micronutrient fertilizer, further studies are needed in heterogeneous soil systems.

Pneumatic nebulizers (as variations based on the Collison nebulizer) have been widely used for producing fine aerosol droplets from a liquid material. The basic working principle of those nebulizers has been qualitatively described as utilization of the negative pressure associated with an expanding gas jet to syphon liquid into the jet stream, then to blow and shear into liquid sheets, filaments, and eventually droplets. Detailed quantitative analysis based on fluid mechanics theory is desirable, to gain in-depth understanding of the liquid aspiration mechanism among other aspects of the Collison nebulizer behaviour. The purpose of present work is to investigate the nature of negative pressure distribution associated with compressible gas jet flow in the Collison nebulizer by a computational fluid dynamics (CFD) analysis, using an OpenFOAM® compressible flow solver. The value of the negative pressure associated with a gas jet flow is examined by varying geometric parameters of the jet expansion channel adjacent to the outlet of jet orifice. Such an analysis can provide valuable insights into fundamental mechanisms for liquid aspiration, helpful for designing improved pneumatic atomizer in the Aerosol Jet® direct-write system for micro-feature, high-aspect-ratio material deposition

The Affordable Care Act (ACA) is at the crossroads. It is important to evaluate the effectiveness of the ACA in order to make rational decisions about the ongoing healthcare reform, but existing research into its effect on health insurance status in the United States is insufficient and descriptive. Using data from the National Health Interview Surveys from 2009 to 2015, this study examines changes in health insurance status and its determinants before the ACA in 2009, during its partial implementation in 2010–2013, and after its full implementation in 2014 and 2015. The results of trend analysis indicate a significant increase in national health insurance rate from 82.2% in 2009 to 89.4% in 2015. Logistic regression analyses confirm the similar impact of age, gender, race, marital status, nativity, citizenship, education, and poverty on health insurance status before and after the ACA. Despite similar effects across years, controlling for other variables, youth aged 26 or below, the foreign-born, Asians, and other races had a greater probability of gaining health insurance after the ACA than before the ACA; however, the odds of obtaining health insurance for Hispanics and the impoverished rose slightly during the partial implementation of the ACA but somewhat declined after the full implementation of the ACA starting in 2014. These findings should be taken into account by the U.S. government in deciding the fate of the ACA.

In Los Angeles, at one point, the Covid-19 testing positivity rate was 6.25%, or one in sixteen. This translates to, on average, one in sixteen specimens testing positive and the vast majority testing negative. Usually, we run sixteen tests on sixteen specimens to identify the positive one(s). This process can be time consuming and expensive. Since a group of negative specimens pooled together for testing will produce a negative result, one single test could potentially eliminate many specimens. Only when the pooled specimen tests positive do we need further testing to identify the positive one(s). Based on this concept, we designed a strategy that will identify the positive specimen(s) efficiently. Assuming one in sixteen specimens is positive, we find that only four tests are needed. Furthermore, we can run them simultaneously, saving both resources and time. Although, in the real world, we cannot make the assumption of only one positive specimen, the same strategy works with slight modification and proves to be much more efficient than the conventional testing. Our strategy returns an answer 48% of the time in four tests and one time cycle. Overall, the average number of tests is seven or eight depending on the follow-up testing, and the average time cycle is about one and a half.

Precipitation patterns are critical for understanding the hydrological and climatological dynamics of any region. Sicily, the largest island of the Mediterranean sea, with its diverse topography and climatic conditions, serves as an ideal case study for analyzing precipitation data to gain insights into regional water resources, agricultural productivity, and climate change impacts. This paper employs advanced statistical physics methods, particularly Tsallis q-statistics, to analyze sub-hourly precipitation data from 2002 to 2023, provided by the Sicilian Agrometeorological Informative System (SIAS). We investigate several critical variables related to rainfall events, including duration, depth, maximum record, and inter-event time. The study spans two decades (2002-2012 and 2013-2023), analyzing the distributions of relevant variables. Additionally, we examine the simple returns of these variables to identify significant temporal changes, fitting these returns with q-Gaussian distributions. Our findings reveal the scale-invariant nature of precipitation events, the presence of long-range interactions and memory effects, characteristic of complex environmental processes.

Biomechanics is a branch of biophysics that deals with mechanics applied to biology. The biomechanics of the cornea plays a significant role in managing patients with glaucoma. While evidence suggests a higher risk of glaucoma in patients with thin and stiffer corneas, it also affects the measurement of intraocular pressure (IOP). We reviewed the pertinent literature to help the understanding of corneal biomechanics and how it can help optimize clinical and surgical treatments and a better approach to diagnosing and managing patients with glaucoma.

In the present work, a comparative evaluation of an MBBR unit performance was carried out for the following cases: when adding 3D-printed biocarriers fabricated with 13X and bentonite, when using K1 commercial biocarriers and when not adding biocarriers at all. For the evaluation of the MBBR efficiency, various physicochemical parameters were measured, while static light scattering and optical microscopy observations were additionally used. Finally, biofilm extracted from the biocarriers was evaluated. The findings suggest that there is an optimal biodegradation of the organic load in all MBBR units. The nitrification and denitrification process were improved at the 3D MBBR as compared to the control MBBR and MBBR K1. The dry mass of the biofilm in the 3D-printed biocarriers was two orders of magnitude larger than the one in the K1 biocarriers. What is more, in the K1 biocarriers the mass of the biofilm varied in relation to time, due to the fact that it could not be kept inside the holes, something that was not observed to happen with the 3D-printed biocarriers. Finally, it was observed, mostly in the 3D MBBR and less in the K1 MBBR, that the growth of nitrifying bacteria and heterotrophs inside the units increased the biomass production in the form of SMP, which in turn favored the adhesion of biomass on the surface of biocarriers.

ME/CFS (Myalgic Encephalomyelitis / Chronic Fatigue Syndrome) is a chronic, complex, heterogeneous disease that affects millions and lacks both diagnostics and treatments. Big data, or the collection of vast quantities of data that can be mined for information, has transformed the understanding of many complex illnesses like cancer (1,2) and multiple sclerosis (3,4), by dissecting heterogeneity, identifying subtypes, and enabling the development of personalized treatments. It is possible that big data can reveal the same for ME/CFS. Solve M.E. developed and launched the You + ME Registry to collect longitudinal health data from people with ME/CFS, people with Long COVID (LC) and control volunteers using rigorous protocols designed to harmonize with other groups collecting data from similar groups of people. The Registry is an invaluable resource because it integrates with a symptom tracking app, as well as a biorepository, to provide a robust and rich dataset that is available to qualified researchers. Accordingly, it facilitates collaboration that may ultimately uncover causes and help accelerate the development of therapies.

The addition of biocarriers can improve the biological processes appearing in a bioreactor since their surface allows the immobilization, attachment, protection, and growth of microorganisms. In addition, the development of a biofilm layer allows the colonization of microorganisms in the biocarriers. The structure, composition, and roughness of the biocarriers' surface are crucial factors that affect the development of the biofilm. In the current work, the aluminosilicate zeolites 13X and ZSM-5 were examined as the main building components of the biocarrier scaffolds, using bentonite, montmorillonite, and halloysite nanotubes as inorganic binders in various combinations. 3D printing was utilized to form pastes into monoliths that underwent heat treatment. The 3d-printed biocarriers were subjected to a mechanical analysis, including density, compression, and nanoindentation tests. Furthermore, the 3d-printed biocarriers were morphologically and structurally characterized using nitrogen adsorption at 77 K (LN2), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The stress-strain response of the materials being studied was obtained through nanoindentation tests combined with finite element analysis (FEA). These tests were also utilized to simulate the lattice geometries under compression loading conditions to investigate their deformation and stress distribution in relation to experimental compression testing. The results indicated that the 3d-printed biocarrier 13X/halloysite nanotubes was endowed with high specific surface area and extended mesoporous structure. Due to these assets, its bulk density was one of the lowest observed amongst the biocarriers derived from the various combinations of materials. The biocarriers based on the 13X zeolite exhibited the highest mechanical stability and appropriate morphological features. The 13X/halloysite nanotubes scaffold exhibits a moderate hardness value compared to the rest, while it presents the highest value of modulus of elasticity. In conclusion, Aluminosilicate zeolites and their combination with clays and inorganic nanotubes afford 3d-printed biocarriers of various textural and structural properties, which can be utilized to improve biological processes.

Glaucoma poses a serious public health concern as it is the second leading cause of blindness after cataracts, while also being the leading cause of irreversible blindness worldwide. Glaucoma is more prevalent among Black, Latino, and Asian populations and it is essential to examine both racial and ethnic disparities that exist in treatment and prevention. As the number of people with glaucoma continues to grow, it is important to review aspects of this condition in order to better care for those affected. This article will review significant forms of glaucoma and what differentiates them in a diagnosis, treatment options, and recommendations on prevention and improving awareness

Understanding of the molecular mechanisms of prostate cancer has led to development of therapeutic strategies targeting androgen receptor (AR). These androgen-receptor signaling inhibitors (ARSI) include androgen synthesis inhibitor- abiraterone and androgen receptor antagonists- enzalutamide, apalutamide, and darolutamide. Although these medications provide significant improvement in survival among men with prostate cancer, drug resistance develops in nearly all patients with time. This could be through androgen-dependent or androgen-independent mechanisms. Even weaker signals and non-canonical steroid ligands can activate AR in the presence of truncated AR-splice variants, AR overexpression, or activating mutations in AR. AR splice variant, AR-V7 is the most studied among these and is not targeted by available ARSIs. Non-androgen receptor dependent resistance mechanisms are mediated by activation of an alternative signaling pathway when AR is inhibited. DNA repair pathway, PI3K/AKT/mTOR pathway, BRAF-MAPK and Wnt signaling pathway and activation by glucocorticoid receptors can restore downstream signaling in prostate cancer by alternative proteins. Multiple clinical trials are underway exploring therapeutic strategies to overcome these resistance mechanisms.

Cardiomyopathies are diseases of heart muscle, a significant percentage of which are genetic in origin. Cardiomyopathies can be classified as dilated, hypertrophic, restrictive, arrhythmogenic right ventricular or left ventricular non-compaction, although mixed morphologies are possible. A subset of neuromuscular disorders, notably Duchenne and Becker muscular dystrophies, are also characterized by cardiomyopathy aside from skeletal myopathy. The global burden of cardiomyopathies is certainly high, necessitating further research and novel therapies. Genome editing tools, which include zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeats (CRISPR) systems have emerged as increasingly important technologies in studying this group of cardiovascular disorders. In this review, we discuss the applications of genome editing in the understanding and treatment of cardiomyopathy. We also describe recent advances in genome editing that may help improve these applications, and some future prospects for genome editing in cardiomyopathy treatment.

This article introduces a new fractional approach to the concept of information dimension of complex networks, based on a (q,q′)-entropy proposed in the literature. The q parameter measures how far is the number of subsystems (for a given size ε) from the mean number of overall sizes. The q′ (interaction index) measures when the interactions between subsystems are greater (q′&gt;1), lesser (q′&lt;1) or equal to the interactions into these subsystems. The computations of the proposed information dimension are carried out on several real-world and synthetic complex networks. The results from the proposed information dimension are compared with those from the information dimension based on the Shannon entropy.

Leaf temperature (T_leaf) influences photosynthesis and respiration. Currently, there is a growing interest on including lianas in productivity models due to their increasing abundance, and their detrimental effects on net primary productivity in tropical environments. Therefore, understanding the differences of T_leaf between lianas and trees is important for future of forest on whole ecosystem productivity. Here we determined the displayed leaf temperature (T_d= T_leaf – ambient temperature) of several species of lianas and their host trees during ENSO and non-ENSO years to evaluate if the presence of lianas affects the T_d of their host trees, and if leaves of lianas and their host trees exhibit differences in T_d. Our results suggest that close to midday, the presence of lianas does not affect the T_d of their host trees; however, lianas tend to have higher values of T_d than their hosts across seasons, in both ENSO and non-ENSO years. Although lianas and trees tend to have similar physiological-temperature responses, differences in T_d could lead to significant differences in rates of photosynthesis and respiration based temperature response curves. Future models should thus consider differences in leaf temperature between these life forms to achieve robust predictions of productivity.

Let G be a finite group. The prime graph Γ(G) of G is defined as follows: The set of vertices of Γ(G) is the set of prime divisors of |G| and two distinct vertices p and p' are connected in Γ(G), whenever G has an element of order pp'. A non-abelian simple group P is called recognizable by prime graph if for any finite group G with Γ(G)=Γ(P), G has a composition factor isomorphic to P. In [4] proved finite simple groups ²D_n(q), where n ≠ 4k are quasirecognizable by prime graph. Now in this paper we discuss the quasirecognizability by prime graph of the simple groups ²D_2k(q), where k ≥ 9 and q is a prime power less than 10⁵.

The application of graph theory in chemical and molecular structure research far exceeds people's expectations, and it has recently grown exponentially. In the molecular graph, atoms are represented by vertices and bonded by edges. In this report, we study the silicon-carbon Si₂C₃-I[p,q] and Si₂C₃-II[p,q]. We compute several Zagreb polynomials and Redefined Zagreb indices of these silicon-carbons.

The construction industry plays a crucial role in shaping the built environment and contributes to the global economy. However, the construction process is associated with negative impacts on the environment and communities. This paper examines the environmental impacts of construction and presents strategies for mitigating them, focusing on sustainable construction practices. The research draws on a comprehensive literature review, case studies, and expert interviews to fully understand the construction industry and its environmental effects. The findings indicate that the implementation of greater supervision of every construction project phase, using alternative design practices, and the use of sustainable construction practices can reduce the negative impacts of construction on the environment and society. The study concludes that sustainable construction practices can contribute to a better environment for a better quality of life and should be embraced by the construction industry. The recommendations for future work include the adoption of green building standards, the use of renewable energy sources, the reduction of waste, and the promotion of stakeholder engagement. Future research should focus on the evaluation of the effectiveness of these strategies and their scalability.

This article aims to identify the generating function of modi…ed Apostol type q-Bernoulli polynomials. With the aid of this generating function, some properties of modi…ed Apostol type q-Bernoulli polynomials are given. It is shown that aforementioned polynomials are q-Appell. Hence, we make use of these polynomials to have applications on q-Umbral calculus. From those applications, we derive some theorems in order to get Apostol type modi…ed q-Bernoulli polynomials as a linear combination of some known polynomials which we stated in the paper.

Background: In the present study, cisplatin, artemisinin and oleanolic acid were evaluated alone and in combination, on human ovarian A2780, A2780ZD0473R and A2780cisR cancer cell lines with aim of overcoming cisplatin resistance and side effects. Methods: Cytotoxicity was assessed by MTT reduction assay. CI values were used as a measure of combined drug effect. MALDI TOF/TOF MS/MS and 2-DE gel electrophoresis were used to identify protein biomarkers in ovarian cancer and to evaluate combination effects. Results: Synergism from combinations was dependent on concentration and sequence of administration. Generally, bolus was most synergistic. 49 proteins differently expressed by 2 ≥ fold were: CYPA, EIF5A1, Op18, p18, LDHB, P4HB, HSP7C, GRP94, ERp57, mortalin, IMMT, CLIC1, NM23, PSA3,1433Z, and HSP90B were down-regulated, whereas hnRNPA1, hnRNPA2/B1, EF2, GOT1, EF1A1, VIME, BIP, ATP5H, APG2, VINC, KPYM, RAN, PSA7, TPI, PGK1, ACTG and VDAC1 were up-regulated, while TCPA, TCPH, TCPB, PRDX6, EF1G, ATPA, ENOA, PRDX1, MCM7, GBLP, PSAT, Hop, EFTU, PGAM1, SERA and CAH2 were not-expressed in A2780cisR cells. The proteins were found to play critical roles in cell cycle regulation, metabolism and biosynthetic processes and drug resistance and detoxification. Conclusion: Results indicate that appropriately sequenced combinations of cisplatin with ART and OA may provide a means to reduce side effects and circumvent platinum resistance.

We analyzed the SARS-CoV-2 spike (S) protein amino acid sequence extracted from 11,542 viral genomic sequences submitted to the Global Initiative on Sharing All Influenza Data (GISAID) database through April 27, 2020. Consistent with prior reports, we found a major S protein mutation, D614 to G614, that was represented in 56% of all the analyzed sequences. All other mutations combined were less than 10%. After parsing the data geographically, we found most of the Chinese patient samples showed D614 (97%). By contrast, most patient samples in many European countries showed G614 (51 to 88%). In the United States, the genotypic distribution in California and Washington was similar to Asian countries, while the distribution in other US states was comparable to Europe. We observed a dramatic increase in the frequency of G614 over time in multiple regions, surpassing D614 when both were present, suggesting G614 S protein virus outcompetes D614 S protein virus. To gain insight into the consequences of the D614G mutation, homology modeling using a multi-template threading mechanism with ab initio structural refinement was performed for a region of the S protein (S591 to N710) spanning the D614G mutation and the S1 furin cleavage site. Molecular models of this region containing D614 or G614 revealed a major difference in secondary structure at the furin domain (RRARS, R682 to S686). The D614 model predicted a random coil structure in the furin domain whereas the G614 model predicted an alpha helix. Critical residues in the cleavage domain of G614 model were found to better align with the PDB structure of a furin inhibitor. Thus, homology modeling studies suggest a potential mechanism whereby the D614G mutation may confer a competitive advantage at the furin binding domain that may contribute to the rise of the D614G SARS-CoV-2 mutant.

Public health agencies are increasingly using pathogen whole genome sequencing (WGS) to support surveillance and epidemiologic investigations. As access to WGS has grown, greater amounts of molecular data have helped improve our ability to detect outbreaks, investigate transmission chains, and explore large-scale population dynamics, such as the spread of antibiotic resistance. However, the wide adoption of WGS also poses challenges due to the amount of data generated and the need to transform raw data prior to analysis. This complexity means that public health agencies may need more advanced computational infrastructure, a broader technical workforce, and new approaches to data management and stewardship. As both a guide for how this development could occur, and a place to initiate discussion, we describe ten proposals for developing and supporting an informatics infrastructure for public health.

The asymptotic behavior of the analytic solutions of a family of singularly perturbed q-difference-differential equations in the complex domain is studied. Different asymptotic expansions with respect to the perturbation parameter and to the time variable are provided: one of Gevrey nature, and another of mixed type Gevrey and q-Gevrey. This asymptotic phenomena is observed due to the modification of the norm established on the space of coefficients of the formal solution. The techniques used are based on the adequate path deformation of the difference of two analytic solutions, and the application of several versions of Ramis-Sibuya theorem.

Electronic designers nowadays are facing two challenging demands for various applications: miniaturization and increased functionality. To satisfy these seemingly opposed requirements, reducing the number of mounted components—and thus solder joints—in PCB designs becomes an attractive approach by directly printing passive components such as embedded resistors into the circuit. This approach can also potentially increase the reliability, such as “mean time between failures” (MTBF), while reducing the circuit board size. With its unique capabilities for non-contact precision material deposition, the Aerosol Jet® direct-write technology has been enabling additive manufacturing of fine-feature electronics conformally onto flexible substrates of complicated shapes. The CAD/CAM controlled relative motions between substrate and print head allows convenient adjustment of the pattern and pile height of deposited material at a given ink volumetric deposition rate. To date in the printed electronics industry, additively printing embedded polymer-thick-film (PTF) resistors has mostly been done with screen printing using carbon-based paste inks. Here we demonstrate results of Aerosol Jet® printed PTF resistors of resistance values ranging from ~50 W to > 1 kW, adjustable (among several variable parameters) by the number of stacked layers (or print passes with each pass depositing a fixed amount of ink) between contact pads of around 1 mm apart with footprint line typically < 0.3 mm. In principle, any ink material that can be atomized into fine droplets of 1 to 5 microns can be printed with the Aerosol Jet® system. However, the print quality such as line edge cleanliness can significantly influenced by ink rheology which involves solvent volatility, solids loading, and so on. Our atomizable carbon ink was made by simply diluting a screen printing paste with a compatible solvent of reasonable volatility, which can be cured at temperatures below 200 ^oC. We show that Aerosol Jet® printed overlapping lines can be stacked to large pile height (to reduce the resistance value) without significant increase of line width, which enables fabricating embedded resistors with adjustable resistance values in a limited footprint space.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive neuromuscular disease prevalent in 1 in 3500 to 5000 males worldwide. As a result of mutations that interrupt the reading frame of the dystrophin gene (DMD), DMD is characterized by a loss of dystrophin protein which leads to decreased muscle membrane integrity, which increases susceptibility to degeneration. CRISPR/Cas9 technology has garnered interest as an avenue for DMD therapy due to its potential for permanent exon skipping, which can restore the disrupted DMD reading frame in DMD and lead to dystrophin restoration. An RNA-guided DNA endonuclease system, CRISPR/Cas9 allows for the targeted editing of specific sequences in the genome. The efficacy and safety of CRISPR/Cas9 as a therapy for DMD has been evaluated by numerous studies in vitro and in vivo, with varying rates of success. Despite the potential of CRISPR/Cas9-mediated gene editing for the long-term treatment of DMD, its translation into the clinic is currently challenged by issues such as off-targeting, immune response activation, and sub-optimal in vivo delivery. Its nature as being mostly a personalized form of therapy also limits applicability to DMD patients, who exhibit a wide spectrum of mutations. This review summarizes the various CRISPR/Cas9 strategies that have been tested in vitro and in vivo for the treatment of DMD. Perspectives on the approach will be provided, and the challenges faced by CRISPR/Cas9 in its road to the clinic will be briefly discussed.

The application of graph theory in chemical and molecular structure research far exceeds people's expectations, and it has recently grown exponentially. In the molecular graph, atoms are represented by vertices and bonded by edges. Closed forms of multiplicative degree-based topological indices which are numerical parameters of the structure and determine physico-chemical properties of the concerned molecular compound. In this article, we compute and analyze many multiplicative degree-based topological indices of silicon-carbon Si₂C₃-I[p,q] and Si₂C₃-II[p,q].

The goal of this work is to develop a sustainable value chain of carbonaceous adsorbents that can be produced from the solid fibrous digestate (SFD) of biogas plants and further applied in integrated desulphurisation-upgrading (CO2/CH4 separation) processes of biogas to yield high purity biomethane. On this purpose, physical and chemical activation of the SFD derived biochar was optimised to afford micro-mesoporous activated carbons (ACs) of high BET surface area (590-2300 m2g−1) and enhanced pore volume (0.57-1.0 cm3g−1). Gas breakthrough experiments from fixed bed columns of the obtained ACs, using real biogas mixture as feedstock, unveiled that the physical and chemical activation conclude to different types of ACs which are sufficient for biogas upgrade and biogas desulphurisation respectively. Performing breakthrough experiments at three temperatures close to ambient it was possible to define the optimum conditions for enhanced H2S/CO2 separation. It was also concluded that the H2S adsorption capacity is significantly affected by restriction to gas diffusion. Hence, the best performance was obtained at 50 oC and the maximum observed in the H2S adsorption capacity vs the temperature is attributed to the counterbalance between adsorption and diffusion processes.

A family of singularly perturbed q-difference-differential equations under the action of a small complex perturbation parameter is studied. The action of the formal monodromy around the origin is present in the equation, which suggests the construction of holomorphic solutions holding logarithmic terms in both, the formal and the analytic level. We provide both solutions and describe the asymptotic behavior relating them by means of q-gevrey asymptotic expansions of some positive order, with respect to the perturbation parameter. On the way, the development of a space product of Banach spaces in the Borel plane is needed to provide a fixed point for a coupled system of equations.

This study focused on the level of Phonological awareness and Word Decoding ability among second year BSED English students in the University of Southeastern Philippines in terms of critical sound. Moreover, it aimed to recognize the significant relationship between the two variables. To verify, there were tests being employed to gather the necessary data. These were: listening test for measuring the respondents' level of awareness to words with critical sounds; phonetic transcription test to identify the respondents' level of awareness to sound-symbol relationship; and spelling test to know the respondents' level of ability for transcriptions to be translated to its Standard English spelling. After the data have been gathered, it was interpreted that the students have a moderate Phonological awareness. On the other hand, their Word Decoding ability resulted to high level. As being correlated, it is being found that there is a great significant relationship between the two variables. With these marks, the researchers encourage the schools in enhancing the students' sound-word relationship knowledge by primarily utilizing speech laboratory and establishing a speech club in the school for extending their exposure about these concepts.

In this paper, we study the p-adic integral representation on Z_p of q-Bernoulli numbers arising from two variable q-Bernstein polynomials and investigate some properties for the q-Bernoulli numbers. In addition, we give some new identities of q-Bernoulli numbers.

The extensive deployment of wireless infrastructure provides a low-cost way to track mobile users in indoor environment. This paper demonstrates a prototype model of an accurate and reliable room location awareness system in a real public environment, where three typical problems arise. First, a massive number of access points (APs) can be sensed leading to a high-dimensional classification problem. Second, heterogeneous devices record different received signal strength (RSS) levels due to the variations in chip-set and antenna attenuation. Third, APs are not necessarily visible in every scanning cycle leading to missing data. This paper presents a probabilistic Wi-Fi fingerprinting method in a hidden Markov model (HMM) framework for mobile user tracking. Considering the spatial correlation of the signal strengths from multiple APs, a Multivariate Gaussian Mixture Model (MVGMM) is fitted to model the probability distribution of RSS measurements in each cell. Furthermore, the unseen property of invisible AP has been investigated in this research, and demonstrated the efficiency of differentiation between cells. The proposed system is able to achieve comparable localization performance. The filed test results present a reliable 97% localization room level accuracy of multiple mobile users in a real university campus WiFi network without any prior knowledge of the environment.

Discovery of inhibitors for endothelial-related transcription factors can contribute to the development of angiogenic therapies that treat diseases ranging from cardiovascular to cancer. The role of transcription factor Vezf1 in vascular development and regulation of angiogenesis has been defined by several earlier studies. Through construction of a computational model for Vezf1, work here has identified a novel small molecule drug capable of inhibiting Vezf1 from binding to its cognate DNA binding site. Using structure-based design and virtual screening of the NCI Diversity Compound Library, 12 shortlisted compounds were tested for their ability to interfere with the binding of Vezf1 to DNA using electrophoretic gel mobility shift assays. We identified one compound, T4, which has an IC50 of 20uM. Using murine endothelial cells, MSS31, we tested the effect of T4 on endothelial cell viability and angiogenesis by using tube formation assay. Our data show that addition of T4 in cell culture medium does not affect cell viability at concentrations lower or equal to its IC 50 but strongly inhibits the network formation by MSS31 in the tube formation assays. Given its potential efficacy, this inhibitor has significant therapeutic potential in several human diseases raging from wound healing to cancer.

This article seeks to provide an improved and more comprehensive understanding of the concept and theories on wasteland. It achieves this by focusing on the Indian context allowing us to unpack the importance of including multiple perspectives of wasteland narratives; this means including more positive narratives of the potential of wasteland to inform and improve prospects for land policies in the global south. Wasteland is commonly recognized as an underutilized category of land that may transform into a valuable resource base with proper management measures. The term waste has multiple angles that carry different notions ranging from fallow to agroforestry land in the global south and Brownfield to green space in the global north. We conduct a narra-tive review approach to qualitatively analyze the concept wastelands studied in pre-existing lit-erature from 1970 to present. The unsystematic literature review approach incorporates multiple elements of wasteland discourse, like understanding the meaning of the term on a global scale, setting out the meaning of the term waste into multiple perspectives explicitly in the Indian con-text, along with different classes and management approaches of wasteland from a national per-spective. The multiple perspectives of wasteland not only generate misconception on land resource but spawn difficulties in land use policy particularly for Indian scenario. For sustainable land use policy, reclaiming wasteland would be the best possible way for India and other countries in Global South, which requires a comprehensive methodological overview on wasteland narrative.

The main purpose of this paper is to introduce a new class of $q$-Hermite-Fubini numbers and polynomials by combining the $q$-Hermite polynomials and $q$-Fubini polynomials. By using generating functions for these numbers and polynomials, we derive some alternative summation formulas including powers of consecutive $q$-integers. Also, we establish some relationships for $q$-Hermite-Fubini polynomials associated with $q$-Bernoulli polynomials, $q$-Euler polynomials and $q$-Genocchi polynomials and $q$-Stirling numbers of the second kind.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In the present paper, we introduce (p, q)-extension of Apostol type Frobenius-Euler polynomials and numbers and investigate some basic identities and properties for these polynomials and numbers, including addition theorems, difference equations, derivative properties, recurrence relations and so on. Then, we provide integral representations, explicit formulas and relations for these polynomials and numbers. Moreover, we discover (p, q)-extensions of Carlitz's result [L. Carlitz, Mat. Mag., 32 (1959), 247–260] and Srivastava and Pintér addition theorems in [H. M. Srivastava, A. Pinter, Appl. Math. Lett., 17 (2004), 375–380].

Here, we describe the bicomplex (p,q)- Fibonacci numbers and the bicomplex (p,q)- Fibonacci quaternions that are based on these numbers and give some of their equations, including the Binet formula, generating function, Catalan, Cassini, d’Ocagne’s identities, and some summation formulas for both of them. Finally, we create a matrix for bicomplex (p,q)- Fibonacci quaternions, and we obtain a determinant of a special matrix that gives the terms of that quaternion.

We propose a notion of $(q,\sigma,\tau)$-differential graded algebra, which generalizes the notions of $(\sigma,\tau)$-differential graded algebra and $q$-differential graded algebra. We construct two examples of $(q,\sigma,\tau)$-differential graded algebra, where the first one is constructed by means of generalized Clifford algebra with two generators (reduced quantum plane), where we use a $(\sigma,\tau)$-twisted graded $q$-commutator. In order to construct the second example, we introduce a notion of $(\sigma,\tau)$-pre-cosimplicial algebra.

The COVID-19 pandemic has profoundly changed the world and human society in various ways. Infection-related figures are key indicators of the direct impact of the pandemic. In addition to the virus, many vulnerable populations (e.g. patients with complex health conditions) have suffered direct or indirect health impacts, such as delayed treatment or diagnosis of cancer and severe mental illness due to stay-at-home restrictions, or financial issues. Studying these kinds of impacts can provide the community with insights and understanding of how the pandemic has affected patients with health conditions and help inform decision-makers design policies that support various vulnerable populations. This paper surveys analytical work conducted on how COVID-19 has impacted patients with complex health conditions. We categorise vulnerable populations into three specific cohorts: patients with chronic disease, patients with cancer and patients with end-of-life care. We then investigate how each of these cohorts has been impacted by the pandemic. We also identify each cohort from an analytics perspective by leveraging various data collection strategies and analytical methods. The goals of this paper are to provide evidence on how to improve the quality of life for vulnerable populations and to inform a national response strategy for future pandemics, which seems inevitable in a highly globalised economy.

This paper presents experimental results of static and dynamic obstacle avoidance methods for a two-wheel mobile robot with independent control using a deep Q-learning (DQL) reinforcement learning algorithm. This is an alternative method that combines the Q-learning (QL) algorithm with a neural network. Neural networks in the DQL algorithm act as Q matrix table approximators for each pair (State - Action). The effectiveness of the proposed solution was verified through simulations, programming, and experimentation. This DQL algorithm is compared to the QL algorithm. First, the mobile robot communicated with the control script using the robot operating system (ROS). The mobile robot is code programmed using a Python in the ROS operating system combined with the DQL controller in Gazebo software. The mobile robot then performed experiments in a workshop with many different experimental scenarios. This DQL controller is improved in term of the computation time, convergence time, planning trajectory accuracy, and obstacles avoidance. Therefore, the DQL controller solved the path optimization problems for mobile robots better than the Q-learning controller.

Polarimetric Synthetic Aperture Radar (PolSAR) images encompass valuable information that can facilitate extensive land cover interpretation and generate diverse output products. Extracting meaningful features from PolSAR data poses challenges distinct from those encountered in optical imagery. Deep Learning (DL) methods offer effective solutions for overcoming these challenges in PolSAR feature extraction. Convolutional Neural Networks (CNNs) play a crucial role in capturing PolSAR image characteristics by leveraging kernel capabilities to consider local information and the complex-valued nature of PolSAR data. In this study, a novel three-branch fusion of complex-valued CNN named Shallow to Deep Feature Fusion Network (SDF2Net) is proposed for PolSAR image classification. To validate the performance of the proposed method, classification results are compared against multiple state-of-the-art approaches using the Airborne Synthetic Aperture Radar (AIRSAR) datasets of Flevoland, San Francisco, and ESAR Oberpfaffenhofen dataset. The results indicate that the proposed approach demonstrates improvements in OA, with 1.3% and 0.8% enhancement for the AIRSAR datasets and 0.5% improvement for the ESAR dataset. The analyses conducted on the Flevoland data underscore the effectiveness of the SDF2Net model, revealing a promising OA of 96.01% even with only 1% sampling ratio.

In this paper, we derive multifarious relationships among the two types of higher order q-Daehee polynomials and p-adic gamma function via Mahler theorem. Also, we compute some weighted p-adic q-integrals of the derivative of p-adic gamma function related to the Stirling numbers of the both kinds and the q-Bernoulli polynomials of order k.

In This paper we introduce the integration of Renormalization Group (RG) methods with Deep Q-Networks (DQNs) to improve reinforcement learning in high-dimensional state spaces. RG methods provide multi-scale analysis, enhancing state representation, learning stability, and exploration. The proposed RG-DQN algorithm uses hierarchical Q-value estimation and multi-scale representations, demonstrating superior performance on synthetic genomic data compared to traditional DQNs.}

For evaluating probabilities of arbitrary random events with respect to a given multivariate probability distribution, specific techniques are of great interest. An important two-dimensional high risk limit law is the Gauss-exponential distribution whose probabilities can be dealt with based upon the Gauss-Laplace law. The latter will be considered here as an element of the newly introduced family of (p,q)-spherical distributions. Based upon a suitably defined non-Euclidean arc-length measure on (p,q)-circles we prove geometric and stochastic representations of these distributions and correspondingly distributed random vectors, respectively. These representations allow dealing with the new probability measures similarly like with elliptically contoured distributions and more general homogeneous star-shaped ones. This is demonstrated at hand of a generalization of the Box-Muller simulation method. En passant, we prove an extension of the sector and circle number functions.

Aquaculture production is under pressure to increase its production to meet the growing demand for food from a growing population. In the Philippines, aquaculture has experienced the shift from milkfish to prawn with its attractive marketable price. Its intensification has led to negative and positive impacts making its collapse inevitable in the mid-1990s and raised a range of environmental and socioeconomic problems. This paper reviewed the environmental impacts, challenges, and disease outbreaks that overtook the industry using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. We examined gaps and changes required to revitalize the industry to properly take-off. It considers and gives details on the impacts of shrimp culture on the environment e.g. shrimp farm management, marine pollution, disease outbreaks, climate change impacts, and socioeconomic impacts. Moreover, the presence of viral diseases such as White Spot Syndrome Virus (WSSV), Monodon Baculovirus (MBV), Infectious Hypodermal and Hematopoietic Necrosis Virus (IHHNV), Hepatopancreatic Parvovirus (HPV), and Yellow Head Virus (YHV), have caused socioeconomic impacts with approximate losses of 40,080 mt in 1997 to 51,000 mt in 2014 in the shrimp industry. Recommended strategies were considered to improve the environmental management of shrimp aquaculture, including disease management, and priorities that were highlighted for future research. This management relates to adopting good aquaculture practices on shrimp culture, proper environmental monitoring and sustainable practices at the farm level.

Objectives: This study aimed to investigate and compare sleep quality between patients with chronic temporomandibular disorder and healthy controls, and to analyze the association of sleep quality with disease characteristics, obstructive sleep apnea risk factors, and excessive daytime sleepiness. Methods: Chronic temporomandibular disorder patients (n=503) and 180 age- and sex-matched healthy controls were included, who completed well-organized clinical report and answered questions on sleep quality (Pittsburgh Sleep Quality Index), sleep apnea risk factors (STOP-Bang questionnaire), and excessive daytime sleepiness (Epworth sleepiness scale). Results: Mean global Pittsburgh Sleep Quality Index scores were significantly higher in the patients (6.25±2.77) than in healthy controls (6.25±2.77) (p&lt;0.001). Poor sleep was significantly more prevalent in the patient group (56.9%) than in healthy controls (22.2%) (p&lt;0.001). Compared with healthy controls, chronic temporomandibular disorder patients had a higher likelihood of obstructive sleep apnea. (STOP-Bang total score ≥3; 7.2% vs. 16.1%; p&lt;0.01) and higher excessive daytime sleepiness (Epworth sleepiness scale score ≥10; 12.8% vs. 19.7%; p&lt;0.05). Age (odds ratio=2.551; p&lt;0.001), female sex (odds ratio=1.885; p=0.007), total Epworth sleepiness scale score (odds ratio=1.839; p=0.014), and headache attributed to temporomandibular disorder (odds ratio=1.519; p=0.049) were the most powerful predictors of poor sleep (global Pittsburgh Sleep Quality Index score ≥5) in chronic temporomandibular disorder patients. Conclusion: Chronic temporomandibular disorder patients had sleep quality impairment. Various factors, including peripheral and central factors, affect the patient's sleep quality. Therefore, in addition to sleep quality and sleep-related problems, the underlying central mechanism for poor sleep quality should be assessed when treating chronic temporomandibular disorder patients.

This paper aims to unify q-derivative/q-integral and h-derivative/h-integral in a single definition, this will be called q−h-derivative/q−h-integral. These notions are further extended on finite interval [a,b] in the form of left and right q−h-derivatives and q−h-integrals. Some inequalities are studied for q−h-integrals which are directly connected with well known results. In diverse fields of science and engineering the theory based on q-derivatives/q-integrals and h-derivatives/h-integrals can be unified by using the concept of q−h-derivative/q−h-integral.

In this paper, we consider the zero distributions of q-shift monomi-als and difference polynomials of meromorphic functions with zero order, that extends the classical Hayman results on the zeros of differential poly-nomials to q-shift difference polynomials. We also investigate problem of q-shift difference polynomials that share a common value.

Astrocytes have been implicated in a wide range of neurodegenerative diseases, with the literature indicating harmful or beneficial roles on a case-by-case basis. On such conditions, these cells are capable of secreting several inflammatory factors and also promote synapse elimination and remodeling. These responses are possible because they sense their surroundings via several receptors, including metabotropic glutamate receptor (mGluR5). However, mGluR5 activation in astrocytes under neuroinflammatory conditions can be neuroprotective or have the opposite effect. In this work, we investigated the role of mGluR5 in hiPSC-derived astrocytes subjected to pro-inflammatory stimulation by recombinant TNF-α (rTNF-α). Our results show that mGluR5 blockade by CTEP is capable of reducing pro-inflammatory cytokines (IL-6, IL-8 and TNF-α) release in rTNF-α-stimulated astrocytes, but, in contrast, leads to an augmented expression of the pan-reactive marker SERPINA3. Additionally, CTEP enhances synaptoneurosomes phagocytosis by astrocytes in both non-stimulated and TNF-α-stimulated conditions, indicating that mGluR5 blockade alone is enough to drive synaptic material engulfment. Finally, mGluR5 antagonism as well as rTNF-α stimulation leads to a reduction in the expression of synaptogenic molecules. Altogether, these data suggest a complex role for mGluR5 in human astrocytes, since its blockage may have beneficial and detrimental effects under inflammatory conditions.

A linear Cauchy problem with polynomial coefficients wich combines q-difference operators for q>1 and differential operators of irregular type is examined. A finite set of sectorial holomorphic solutions w.r.t the complex time is constructed by means of classical Laplace transforms. These functions share a common asymptotic expansion in the time variable which turns out to carry a double layers structure which couples q-Gevrey and Gevrey bounds. In the last part of the work, the problem of confluence of these solutions as q tends to 1 is investigated.

We attempted to establish an objective method to accurately evaluate the motility of bull sperm and examined the effects of media for sperm suspensions and frame rates on data of computer-assisted sperm motility analysis (CASA). Sperm incubated in Brackett and Oliphant medium (BO) more clearly showed hyperactivation-like motility than those in synthetic oviductal fluid. Sperm images captured at 150 frames per second (fps) showed a trajectory that was closer to the real pathway than those at other frame rates (30, 50, and 75 fps). We then examined the characteristics of sex-sorted and non-sorted semen using a cluster analysis followed by a discriminant analysis of sperm motility in BO at 150 fps. The results indicated that sex-sorted semen contained sperm with hyperactivation-like motility as the main subpopulation immediately after thawing and this subpopulation decreased after 2-h incubation. The main subpopulation in non-sorted semen had progressive motility that was maintained during incubation. In conclusion, usage of BO for sperm suspensions and capturing sperm motility at 150 fps by CASA were appropriate for evaluating bovine sperm motility. A discriminant analysis using data from a cluster analysis of motile sperm has the ability to accurately describe differences in the structures of sperm motility subpopulations.

Satellite-based monitoring can retrieve ground-level PM_2.5 concentrations with higher-resolution and continuous spatial coverage to assist in making management strategies and estimating health exposures. The Sichuan Basin has a complex terrain and several city clusters that differ from other regions in China: it has an enclosed air basin with a unique planetary boundary layer dynamic which accumulates air pollution. The spatiotemporal distribution of 1-km resolution Aerosol Optical Depth (AOD) in the Sichuan Basin was retrieved using the improved dark pixel method and Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The retrieved seasonal AOD reached its highest values in spring and had the lowest values in autumn. The higher correlation (r = 0.84, N = 171) between the ground-based Lidar AOD and 1-km resolution MODIS AOD indicated that the high-resolution MODIS AOD could be used to retrieve the ground-level PM_2.5 concentration. The Lidar-measured annual average extinction coefficient increased linearly with the Planetary Boundary Layer Height (PBLH) in the range of 100 ~ 670 m, but exponentially decreased between the heights of 670 ~ 1800 m. Both the correlation and the variation tendency of simulated PBLH from WRF_SHIN/CALMET were closer to the Lidar observation than that of three other Planetary Boundary Layer (PBL) schemes (the Grenier-Bretherton-McCaa (GBM) scheme, the he Total Energy-Mass Flux (TEMF) scheme and the University of Washington (UW) scheme), which suggested that the simulated PBLH could be used in the vertical correction of retrieval PM_2.5. Four seasonal fitting functions were also obtained for further humidity correction. The correlation coefficient between the aerosol extinction coefficient and the fitted surface-level PM_2.5 concentration at the benchmark station of Southwest Jiao-tong University was enhanced significantly from 0.62 to 0.76 after vertical and humidity corrections during a whole year. During the evaluation of the retrieved ground-level PM_2.5 with observed values from three cities, Yibin (YB), Dazhou (DZ), and Deyang (DY), our algorithm performed well, resulting in higher correlation coefficients of 0.78 (N = 177), 0.77 (N = 178), and 0.81 (N = 181), respectively.

This present work explores the performance of a thermal-magnetic engine of Otto type, considering as a working substance an effective interacting spin model corresponding to the q− state clock model. We obtain all the thermodynamic quantities for the q = 2, 4, 6, 8 cases in a small lattice size (3×3 with free boundary conditions) by using the exact partition function calculated from the energies of all the accessible microstates of the system. The extension to bigger lattices was performed using the mean-field approximation. Our results indicate that the total work extraction of the cycle is highest for the q=4 case, while the performance for the Ising model (q=2) is the lowest of all cases studied. These results are strongly linked with the phase diagram of the working substance and the location of the cycle in the different magnetic phases present, where we find that the transition from a ferromagnetic to a paramagnetic phase extracts more work than one of the Berezinskii–Kosterlitz–Thouless to paramagnetic type. Additionally, as the size of the lattice increases, the extraction work is lower than smaller lattices for all values of q presented in this study.

In this brief paper a quantum algorithm to calculate the Hamming distance of two binary strings of equal length (or messages in theory information) is presented. The algorithm calculates the Hamming weight of two binary strings in one query of an oracle. To calculate the hamming distance of these two strings we only have to calculate the Hamming weight of the xor operation of both strings. To test the algorithms the quantum computer prototype that IBM has given open access to on the cloud has been used to test the results.

In this paper, we introduce a new generalization of the Hermite polynomials via (p, q)-exponential generating function and investigate several properties and relations for mentioned polynomials including derivative property, explicit formula, recurrence relation, integral representation. We also de…ne a (p, q)-analogue of the Bernstein polynomials and acquire their some formulas. We then provide some (p, q)-hyperbolic representations of the (p, q)-Bernstein polynomials. In addition, we obtain a correlation between (p, q)-Hermite polynomials and (p, q)-Bernstein polynomials.

In this paper, we investigate p-adic q-integral (q-Volkenborn integral) on Z_p of p-adic gamma function via their Mahler expansions. We also derived two q-Volkenborn integrals of p-adic gamma function in terms of q-Daehee polynomials and numbers and q-Daehee polynomials and numbers of the second kind. Moreover, we discover q-Volkenborn integral of the derivative of p-adic gamma function. We acquire the relationship between the p-adic gamma function and Stirling numbers of the first kind. We finally develop a novel and interesting representation for the p-adic Euler constant by means of the q-Daehee polynomials and numbers.

Actinobacteria are known for their production of bioactive specialized metabolites, but still under-exploited due to silent biosynthetic gene clusters (BGCs) not expressed in conventional laboratory cultures conditions. In this study, three marine-derived actinobacteria were cultured using the one strain many compounds method (OSMAC) to explore the real potential of these microorganisms. Salinispora arenicola (SH-78) and two Micromonospora sp. (SH-82 and SH-57) were grown under varying parameters such as time, medium composition, and culture support. The microbial extracts produced were chemically screened by high-resolution analysis (HRMS/MS). The data were used to build ion identity molecular networks (IIMN) and annotate the specialized metabolites detected. A selection of extracts was biologically screened for their cytotoxic and antiplasmodial activities. The IIMNs and the annotations produced were used to assess the impact of culture parameters on the metabolomic diversity of the selected actinobacteria and highlight the presence of unique molecules to specific culture conditions. Micromonospora sp. SH-57 produced a greater quantity of metabolites in liquid culture, with higher associated biological activity. The method employed allowed to explore deeper the specialized metabolites production and to identify the best culture conditions to produce bioactive natural products.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive neuromuscular disorder most commonly caused by mutations disrupting the reading frame of the dystrophin (DMD) gene. DMD codes for dystrophin, which is critical for maintaining the integrity of muscle cell membranes. Without dystrophin, muscle cells receive heightened mechanical stress, becoming more susceptible to damage. An active body of research continues to explore therapeutic treatments for DMD as well as to further our understanding of the disease. These efforts rely on having reliable animal models that accurately recapitulate disease presentation in humans. While current animal models of DMD have served this purpose quite well, each comes with their own limitations. To help overcome this, clustered regularly interspaced short palindromic repeats (CRISPR)-based technology has been extremely useful in creating novel animal models for DMD. This review focuses on animal models developed for DMD that have been created using CRISPR, their advantages and disadvantages as well as their applications in the DMD field.

We examine a family of nonlinear q-difference-differential Cauchy problems obtained as a coupling of linear Cauchy problems containing dilation q-difference operators, recently investigated by the author, and quasi-linear Kowalevski type problems that involve contraction q-difference operators. We build up local holomorphic solutions to these problems. Two aspects of these solutions are explored. One facet deals with asymptotic expansions in the complex time variable for which a mixed type Gevrey and q-Gevrey structure is exhibited. The other feature concerns the problem of confluence of these solutions as q tends to 1.

In this paper, we investigate p-adic q-integral (q-Volkenborn integral) on ℤ_{p} of p-adic gamma function via their Mahler expansions. We also derived two q-Volkenborn integrals of p-adic gamma function in terms of q-Daehee polynomials and numbers and q-Daehee polynomials and numbers of the second kind. Moreover, we discover q-Volkenborn integral of the derivative of p-adic gamma function. We acquire the relationship between the p-adic gamma function and Stirling numbers of the first kind. We finally develop a novel and interesting representation for the p-adic Euler constant by means of the q-Daehee polynomials and numbers.

In this paper, we introduce a new class of $(p,q)$-analogue type of Fubini numbers and polynomials and investigate some properties of these polynomials. We establish summation formulas of these polynomials by summation techniques series. Furthermore, we consider some relationships for $(p,q)$-Fubini polynomials associated with $(p,q)$-Bernoulli polynomials, $(p,q)$-Euler polynomials and $(p,q)$-Genocchi polynomials and $(p,q)$-Stirling numbers of the second kind.

In this paper, we revisit the q-states clock model for small systems. We present results for the thermodynamics of the q-states clock model from $q=2$ to $q=20$ for small square lattices $L \times L$, with L ranging from $L=3$ to $L=64$ with free-boundary conditions. Energy, specific heat, entropy and magnetization are measured. We found that the Berezinskii-Kosterlitz-Thouless (BKT)-like transition appears for $q>5$ regardless of lattice size, while the transition at $q=5$ is lost for $L<10$; for $q\leq 4$ the BKT transition is never present. We report the phase diagram in terms of $q$ showing the transition from the ferromagnetic (FM) to the paramagnetic (PM) phases at a critical temperature T$_1$ for small systems which turns into a transition from the FM to the BKT phase for larger systems, while a second phase transition between the BKT and the PM phases occurs at T$_2$. We also show that the magnetic phases are well characterized by the two dimensional (2D) distribution of the magnetization values. We make use of this opportunity to do an information theory analysis of the time series obtained from the Monte Carlo simulations. In particular, we calculate the phenomenological mutability and diversity functions. Diversity characterizes the phase transitions, but the phases are less detectable as $q$ increases. Free boundary conditions are used to better mimic the reality of small systems (far from any thermodynamic limit). The role of size is discussed.

The prim objective of commenced article is to determine q-sumudu transforms of a product of unified family of q-polynomials with basic (or q-) analogue of fox’s H-function and q-analog of I-functions. Specialized cases of the leading outcome are further evaluated as q-sumudu transform of general class of q-polynomials and q-sumudu transforms of the basic analogues of Fox’s H-function and I-functions.

The main goal of the present paper is to construct some families of the Carlitz’s q-Bernoulli polynomials and numbers. We firstly introduce the modified Carlitz’s q-Bernoulli polynomials and numbers with weight (α, β) and investigate their some explicit properties and identities arising from the bosonic q-Volkenborn integral on ℤ_p. We then define the modified degenerate Carlitz’s q-Bernoulli polynomials and numbers with weight (α, β) and obtain some recurrence relations and other identities. Moreover, we derive some correlations with the modified Carlitz’s q-Bernoulli polynomials with weight (α, β), the modified degenerate Carlitz’s q-Bernoulli polynomials with weight (α, β), the Stirling numbers of the first kind and second kind.

The use of Information Communication Technologies (ICT) in education brings up new possibilities of promoting the learning and health experiences. In this sense, education contexts of 21st century must consider these two areas of knowledge, especially their integration. This article presents learning practices developed with mobile devices and games, in order to improve learning and well-being in children and adolescents undergoing cancer treatment in non-formal educational setting. The methodology is based on qualitative case studies with content-based data analysis, involving informal interviews and observation methods. The study considers data from 5 patients who participated in the research between 2015 and 2019. The results demonstrate a positive influence of the practices with mobile technologies and games in terms of learning and in the well-being feeling of patients during the treatment.

It was the aim of this study to examine whether the usage of the vaccine COXEVAC® (Ceva Santé Animale) could reduce the consumption of antibiotics in Q-fever-positive dairy farms. Additionally, the effects of other herd-level factors on the consumption of antibiotics were investigated. In this longitudinal cohort study, 36 farms with vaccination and 13 farms without vaccination participated. In all herds, Coxiella burnetii had been directly or indirectly diagnosed. To compare the treatment frequency of antibiotics between the vaccinated group and the non-vaccinated group, the consumption of antibiotics for each farm was collected using the veterinary documents about the application and delivery of antibiotics. To gather detailed information about herd data, nutrition, milking management, housing, and animal health, the farmers were interviewed with the help of a questionnaire. The results suggest that there might be an association between the vaccination against Q fever and a reduced consumption of antibiotics. Neither herd size nor milk yield level influenced the consumption of antibiotics in the study herds. Type of flooring and udder cluster disinfection while milking were associated with a lower and higher therapy frequency, respectively. Further studies are necessary to elucidate the cause-effect relationship between vaccination and the consumption of antibiotics.

Aquaculture is growing rapidly as a food-producing sector and in recent years, fishmeal prices have climbed by more than twofold on a global scale. This review of previous studies was performed to contribute to the extant literature on the aquaculture sector to aid cost reduction of aquafeeds by identifying substitute protein that can replace fishmeal. The review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) using the SCOPUS and WOS (Web of Science), DOAJ (Directory of Open Access Journals), Academia, and Pubmed Central databases with the following search terms: “fishmeal,” “alternative protein source” and “aquafeeds.” This resulted in 5,331 articles from the SCOPUS and WOS databases. Finally, the titles and abstracts of the articles were screened, giving a total of 162 articles that were used in the study; another 58 articles came from open databases. Results have shown that 100% replacement of fishmeal with blood meal did not affect the growth of fish as well as 75% to 100% combination of poultry-by-product (PBM), feather meal (FEM), and blood meal (BM). Moreover, a 10% replacement of fishmeal using seaweed (Gracilaria arcuata) has no adverse effect on feed efficiency and growth performance of tilapia, a 50% replacement of fishmeal using black soldier fly (Hermetia illucens), and 25% replacement using soybean (Glycine max) also showed better results for fish growth. With that, this review shows that alternative protein can be a great alternative to the aquaculture sector in reducing the cost of aquafeeds since alternative proteins are much cheaper than the usual fishmeal.

Although nanotechnology is a new and rapidly growing area of science, the impact of nanomaterials on living organisms is unknown in many aspects. In this regard it is extremely important to perform toxicological tests, but complete characterization of all varying preparations is extremely laborious. The computational technique called quantitative structure-activity relationship, or QSAR, allows reducing the cost of time- and resource-consuming nanotoxicity tests. In this review, (Q)SAR cytotoxicity studies of the past decade are systematically considered. We regard here five classes of engineered nanomaterials (ENMs): metal oxides, metal-containing nanoparticles, multi-walled carbon nanotubes, fullerenes, and silica nanoparticles. Some studies reveal that QSAR models are better than classification SAR models, while other reports conclude that SAR is more precise than QSAR. The quasi-QSAR method appears to be the most promising tool, as it allows accurately taking experimental conditions into account. However, experimental artifacts are a major concern in this case

In this article, a new class of $q$-Hermite based unified Apostol type polynomials is introduced by means of generating function and series representation. Several important formulas and recurrence relations for these polynomials are derived via different generating methods. We also introduce $q$-analog of Stirling numbers of second kind of order $\nu$ by which we construct a relation including aforementioned polynomials.

We introduce the Hermite based poly-Bernoulli polynomials with a q parameter and give someof their basic properties including not only addition property, but also derivative properties and integralrepresentations. We also de.ne the Hermite based λ -Stirling polynomials of the second kind, and thenprovide some relations. Moreover, we derive several correlations and identities including the Hermite-Kampéde Fériet (or Gould-Hopper) family of polynomials, the Hermite based poly-Bernoulli polynomials with a qparameter and the Hermite based λ -Stirling polynomials of the second kind.

For paramagnetic and elastic materials in the presence of quasi-static magnetic field, there is correspondingly quasi-static magnetic pressure, in contrast to the radiational electromagnetic pressure associated with electromagnetic momentum density. A thermodynamic pressure demagnetization is demonstrated. For the elastic dielectrics in the presence of quasi-static electrical field, its dual effect can be easily obtained by variable transformation.

By utilizing a generalized version of the Madelung quantum-hydrodynamic framework that incorporates noise, we derive a solution using the path integral method to investigate how a quantum superposition of states evolves over time. This exploration seeks to comprehend the process through which a stable quantum state ultimately emerges in the presence of fluctuations induced by the noisy gravitational background. The model defines the conditions that give rise to a limited range of interaction for the quantum potential, allowing for the existence of coarse-grained classical descriptions at a macroscopic level. The theory uncovers the smallest attainable level of uncertainty in an open quantum system and examines its consistency with the localized behavior observed in large-scale classical systems. The research delves into connections and similarities with decoherence theory and the Copenhagen interpretation of quantum mechanics. Additionally, it assesses the potential consequences of wave function decay on the measurement of photon entanglement. To validate the proposed theory, an experiment involving entangled photons transmitted between detectors on the Moon and Mars is discussed. Finally, the findings of the theory are applied to the creation of larger Q-bits systems at elevated temperatures.

We propose a new statistical analysis of the Acoustic Emissions (AE) produced in a series of triaxial deformation experiments leading to fractures and failure of two different rocks, namely, Darley Dale Sandstone (DDS) and AG Granite (AG). By means of q-statistical formalism, we are able to characterize the pre-failure processes in both types of rocks. In particular, we study AE inter-event time and AE inter-event distance distributions. Both of them can be reproduced with q-exponential curves, showing universal features which are observed here for the first time and could be important in order to understand more in detail rock fractures dynamics.

A homogenized, supersaturated Al-Zn-Mg-Zr alloy was processed by severe plastic deformation (SPD) using high-pressure torsion (HPT) technique for different revolutions at room temperature to get ultrafine-grained (UFG) microstructure. The microstructure and mechanical properties of the UFG samples were then studied by transmission electron microscopy (TEM), differential scanning calorimetry (DSC), as well as by tensile and hardness measurements. Emphasis was placed on the effect of shear strain on the evolution of microstructure of the investigated alloy. Experimental results have shown a very interesting evolution of the decomposed microstructure in a wide range of shear strains imposed by HPT. While the global properties, such as the average grain size (~200 nm) and hardness (~2.2 GPa) appeared unchanged, the local microstructure was continuously transformed. After 1 turn of HPT, the decomposed UFG structure contains relatively large precipitates inside grains. In the sample processed by 5 turns in HPT, segregation of Zn atoms into grain boundaries (GBs) can also be observed. After 10 turns, more Zn atoms have segregated into GBs and only smaller size precipitates can be observed inside grains. The intensive segregation of solute atoms into GBs may significantly affect the ductility of the materials, leading to its ultralow-temperature superplasticity. Our findings pave the way for achieving advanced microstructural and mechanical properties in nanostructured metals and alloys by engineering their precipitation and segregation by means of applying different HPT regimes.

The mobile devices caused a constant struggle for the pursuit of data privacy. Nowadays, it appears that the number of mobile devices in the world is increasing. With this increase and technological evolution, thousands of data associated with everyone are generated and stored remotely. Thus, the topic of data privacy is highlighted in several areas. There is a need for control and management of data in circulation inherent to this theme. This article presents an approach of the interaction between the individual and the public environment, where this interaction will determine the access to information. This analysis was based on a data privacy management model in public environments created after reading and analyzing the current technologies. A mobile application based on location via Global Positioning System (GPS) was created to substantiate this model, which it considers the General Data Protection Regulation (GDPR) to control and manage access to the data of each individual.

In this paper we propose the explicit formulas of Average Run Length (ARL) of Exponentially Weighted Moving Average (EWMA) control chart for Autoregressive Integrated Moving Average: ARIMA (p,d,q) (P, D, Q)_L process with exponential white noise. To check the accuracy, the ARL results were compared with numerical integral equations based on the Gauss-Legendre rule. There was an excellent agreement between the explicit formulas and the numerical solutions. Additionally, we compared the computational time between our explicit formulas for the ARL with the one obtained via Gauss-Legendre numerical scheme. The computational time for the explicit formulas was approximately one second that is much less than the numerical approximations. The explicit analytical formulas for evaluating ARL0 and ARL₁ can produce a set of optimal parameters which depend on the smoothing parameter (λ) and the width of control limit (H), for designing an EWMA chart with a minimum ARL₁.

Community pharmacists are involved in antimicrobial stewardship through self-care advice and delivering medications for uncomplicated infections. Objectives This mixed methods study aimed to identify opportunities to enhance the role of community pharmacists in the management of patients with suspected or confirmed urinary tract infection (UTI). Methods Data collection was through a service user survey (n=51) and pharmacist surveys and semi-structured interviews before (16 interviews, 22 questionnaires) and after (15 interviews, 16 questionnaires) trialling UTI leaflets designed to be shared with patients. Data were analysed inductively using thematic analysis and descriptive tabulation of quantitative data. Results Twenty-five percent (n=13/51) of service users with urinary symptoms sought help from a pharmacist first and 65% (n=33/51) were comfortable discussing their urinary symptoms with a pharmacist in a private space. Community pharmacists were confident as the first professional contact for service users with uncomplicated UTI (n=13/16, 81%), but indicated the lack of a specific patient referral pathway (n=16/16, 100%), the need for additional funding and staff (n=10/16, 62%), and the importance of developing prescription options for pharmacists (5/16, 31%). All community pharmacists reported playing a daily role in controlling antimicrobial resistance by educating service users about viral and bacterial infections and promoting a healthy lifestyle. Enhancing their role will need greater integrated working with general practices and more prescribers based in community pharmacy. Conclusion This study suggests that community pharmacists could play a greater role in the management of uncomplicated UTI. The current reconfiguration of primary care in England with primary care networks and integrated care systems could provide a real opportunity for this collaborative working with potential learning for international initiatives.

We present atomic structures and nonequilbrium synthesis of new class of materials, where the basic structural unit is a diamond tetrahedron. When units of one, two, and three tetrahedra are randomly packed, we create distinct phases of amorphous Q-carbon. Four tetrahedra in two adjacent layers lead to crystalline diamond lattice, which has four missing tetrahedra alternately. When these four missing tetrahedra are filled, we create subunit cell of crystalline Q-diamond. Theoretical calculations show that superconducting transition temperature (Tc) in 50 atomic % B-doped Q-diamond can reach near room temperature at ambient pressures. This is consistent with our earlier results using low-loss EELS measurements in 50 atomic % B-doped Q-carbon, which had mostly amorphous QB3 phase mixed with some crystalline Q-diamond phase. These EELS results showed that the Tc for these samples was in between 90K and 300K. Theoretical calculations of density of states, Eliashberg function, electron-phonon interaction parameter, and root-mean-square and logarithmic average of frequency in crystalline Q-diamond show Tc in the range of 268K to 300K, which is in a complete agreement with our EELS results in QB3.

In this paper, a new class of q-Hermite based Frobenius type Eulerian polynomials is introduced by means of generating function and series representation. Several fundamental formulas and recurrence relations for these polynomials are derived via different generating methods. Furthermore, diverse correlations including the q-Apostol-Bernoulli polynomials, the q-Apostol-Euler poynoomials, the q-Apostol-Genocchi polynomials and the q-Stirling numbers of the second kind are also established by means of the their generating functions.

In this paper, we develop the theory of the multiple q-analogue of the Heine’s binomial formula, chain rule and Leibnitz’s rule. We also derive many useful definitions and results involving multiple q-antiderivative and multiple q-Jackson’s integral. Finally, we list here multiple q-analogue of some elementary functions including trigonometric functions and hyperbolic functions. This may be a good consideration in developing the multiple q-calculus in combinatorics, number theory and other fields of mathematics.

In this paper, we introduce a new generalization of the r-Stirling numbers of the second kind based on the q-numbers via an exponential generating function. We investigate their some properties and derive several relations among q-Bernoulli numbers and polynomials, and newly de…ned (q, r, w)-Stirling numbers of the second kind. We also obtain q-Bernstein polynomials as a linear combination of (q, r, w)-Stirling numbers of the second kind and q-Bernoulli polynomials in w.

Epithelial-mesenchymal transition (EMT) networks are essential in acquiring the drug resistance and cancer malignant features in cancer stem cells (CSCs). In this regard, gene expression profiles in diffuse- and intestinal-type gastric cancer (GC) have been analyzed to reveal the network pathways in EMT and CSCs, since the diffuse-type GC has much more mesenchymal features than intestinal-type GC that has the intestinal features. The study results revealed that the activation state of several canonical pathways related to cell cycle regulation was altered. The canonical pathway on Cell cycle: G1/S checkpoint regulation was activated in diffuse-type GC, and canonical pathways on Cell cycle control of chromosomal replication and Cyclins and cell cycle regulation were activated in intestinal-type GC. Canonical pathway related to Role of BRCA1 in DNA damage response was activated in intestinal-type GC, where BRCA1, which is related to G1/S phase transition was up-regulated in intestinal-type GC. Several microRNAs (miRNAs), including mir-10, mir-17, mir-19, mir-194, mir-224, mir-25, mir-34, mir-451, and mir-605, were identified to have direct relationships of RNA-RNA interaction in Cell cycle: G1/S checkpoint regulation pathway. Additionally, cell cycle regulation may be altered in EMT conditions. The alterations in activation states of the pathways related to cell cycle regulation in diffuse- and intestinal-type GC would indicate the significance of cell cycle regulation in EMT.

Development of mucosal vaccines has been limited and could be aided by a systems vaccinology approach to identify platforms and adjuvant strategies that induce protective immune responses. Induction of local immune responses by mucosal-delivered vaccines has been difficult to evaluate from peripheral samples as systemic responses often do not correlate with the mucosal response. Here we utilized transcriptomics in combination with Gene Set Enrichment Analysis (GSEA) to assess innate immune activation by an oral probiotic Lactobacillus acidophilus-based vaccine platform in mice. The goal was to explore the earliest immune responses elicited after oral immunization at the Peyer’s patch. Twenty-four hours after oral delivery of the L. acidophilus vaccine platform, we found an overabundance of L. acidophilus at Peyer’s patches and detected expression of the vaccine viral proteins and adjuvants confirming in vivo vaccine delivery. Compared to mice orally dosed with buffer or wild-type L. acidophilus, we identified enhanced response in immune pathways related to cytokine and gene signaling, T and B cell activation, phagocytosis, and humoral responses. While more work is needed to correlate these pathways with protection from infection and/or disease, they indicate this method’s potential to evaluate and aid in the iterative development of next-generation mucosal vaccines.

Despite its growing importance as a dry beneficiation method, there is a lack of studies exploring the fundamentals aspects of dry jigging. In this sense, this study focuses on explore some essential aspects of density-based separation in dry jigs, like pulse profile, energy consumption and, especially, stratification over time, also exploring an innovative operational strategy here called “transient pulsation”. The tests were carried out using density tracers distributed across 11 density ranges (0.4-2.4 g/cm³) and employing a base bed (gravel) to analyze their segregation in a pilot-scale dry jig. Pressure drop and active power data were acquired to measure the pulse characteristics and energy consumption. The findings suggest that establishing the dry jigging cycle is more complex than in hydraulic jigs due to the compressibility of air. Stationary pulsation tests revealed an unstable behavior of stratification over time, contrasting with traditional hydraulic jigs, while transient pulsation tests unveiled varied trends in separation quality. Energy consumption analysis underscored the significant role of the blower drive. These insights have the potential to inform operational enhancements in dry jigging.

Epithelial-mesenchymal transition (EMT) plays an important role in the acquisition of cancer stem cell (CSC) feature and drug resistance, which are the main hallmarks of cancer malignancy. Although previous findings have shown that several signaling pathways are activated in cancer progression, the precise mechanism of signaling pathways in EMT and CSCs are not fully understood. In this study, we focused on the intestinal and diffuse-type gastric cancer (GC), and analyzed the gene expression of public RNAseq data to understand the molecular pathway regulation in different subtypes of gastric cancer. Network pathway analysis was performed by Ingenuity Pathway Analysis (IPA). Total 2815 probe set IDs were significantly different between intestinal- and diffuse-type GC data in cBioPortal Cancer Genomics. The 10 genes including male-specific lethal 3 homolog (Drosophila) pseudogene 1 (MSL3P1), CDC28 protein kinase regulatory subunit 1B (CKS1B), DEAD-box helicase 27 (DDX27), golgi to ER traffic protein 4 (GET4), chromosome segregation 1 like (CSE1L), translocase of outer mitochondrial membrane 34 (TOMM34), YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), ribonucleic acid export 1 (RAE1), par-6 family cell polarity regulator beta (PARD6B), and MRG domain binding protein (MRGBP) were found to have difference in gene expression in intestinal- and diffuse-type GC. Total 463 direct relationships with 3 molecules (MYC, NTRK1, UBE2M) were found in the biomarker-filtered network generated by network pathway analysis. The networks and features in intestinal- and diffuse-type GC have been investigated and profiled in bioinformatics. Our results revealed the signaling pathways networks in intestinal- and diffuse-type GC, bringing new light for the elucidation of drug resistance mechanisms in CSCs.

Read-Across Structure-Activity Relationship (RASAR) is an emerging cheminformatic approach that combines the usefulness of a QSAR model and similarity-based Read-Across predictions. In this work, we have generated a simple, interpretable, and transferable quantitative-RASAR (q-RASAR) model which can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials. The data set involves 29 TiO2-based nanomaterials which contain specific amounts of noble metal precursors in the form of Ag, Au, Pd, and Pt. The data set was rationally divided into training and test sets and the Read-Across-based predictions for the test set were generated using the tool Read-Across-v4.1 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. The hyperparameters were optimized based on the training set data and using this optimized setting, the Read-Across-based predictions for the test set were obtained. The optimized hyperparameters and the similarity approach, which yields the best predictions, were used to calculate the similarity and error-based RASAR descriptors using the tool RASAR-Desc-Calc-v2.0 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. These RASAR descriptors were then clubbed with the physicochemical descriptors and were subjected to features selection using the tool Best Subset Selection v2.1 available from https://dtclab.webs.com/software-tools. The final set of selected descriptors was used to develop multiple linear regression based q-RASAR models, which were validated using stringent criteria as per the OECD guidelines. Finally, a random forest model was also developed with the selected descriptors. The final machine learning model can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials superseding previously reported models in the prediction quality.

Attitude control of a novel regional truss-braced wing aircraft with low stability characteristics is addressed in this paper using Reinforcement Learning (RL). In recent years, RL has been increasingly employed in challenging applications, particularly, autonomous flight control. However, a significant predicament confronting discrete RL algorithms is the dimension limitation of the state-action table and difficulties in defining the elements of the RL environment. To address these issues, in this paper, a detailed mathematical model of the mentioned aircraft is first developed to shape an RL environment. Subsequently, Q-learning, the most prevalent discrete RL algorithm will be implemented in both the Markov Decision Process (MDP), and Partially Observable Markov Decision Process (POMDP) frameworks to control the longitudinal mode of the air vehicle. In order to eliminate residual fluctuations that are a consequence of discrete action selection, and simultaneously track variable pitch angles, a Fuzzy Action Assignment (FAA) method is proposed to generate continuous control commands using the trained Q-table. Accordingly, it will be proved that by defining an accurate reward function, along with observing all crucial states (which is equivalent to satisfying the Markov Property), the performance of the introduced control system surpasses a well-tuned Proportional–Integral–Derivative (PID) controller.

This paper includes some new investigations and results for post quantum calculus, denoted by (p,q)-calculus. A chain rule for (p,q)-derivative is developed. Also, a new (p,q)-analogue of the exponential function is introduced and some its properties including the addition property for (p,q)-exponential functions are investigated. Several useful results involving (p,q)-binomial coefficients and (p,q)-antiderivative are discovered. At the final part of this paper, (p,q)-analogue of some elementary functions including trigonometric functions and hyperbolic functions are considered and some properties and relations among them are analyzed extensively.