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.

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.

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.

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].

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 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].

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.

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.

Understanding pollen and ovule fertility as factors influencing fruit and seed set is important in cassava breeding. Red light (RL) and plant growth regulators (PGRs) have been used to induce or enhance flowering and fruit set in cassava without any reference to effects on pollen viability or ovule fertilizability. This study investigated effects of field-applied RL and PGR on pollen viability and ovule fertilizability. Panels of cassava genotypes, with early or moderate flowering responses were used. RL was administered from dusk to dawn. Two PGRs, a cytokinin (6-benzyl adenine, BA) and an anti‑ethylene (silver thiosulphate, STS) were applied. Pollen viability was assessed basing on pollen grain diameter, in vitro stainability, in vivo germinability, ovule fertilizability and ploidy level. Treating flowers with RL led to increased pollen diameter from 143.6 to 148.5µm, stainability from 82.9 to 93.0%, ovule fertilizability from 52.0 to 56.9% in treated female flowers and 47.7 to 64.3% on using pollen from treated male flowers. Fruit set increased from 51.5 to 71.8% in RL-treated female flowers and from 53.7 to 71.1% when pollen from RL-treated male flowers was used. Seed set followed a trend similar to that of fruit set. Ploidy level of pollen from RL-treated flowers increased slightly and positively correlated with pollen diameter (R2 = 0.09*), ovule fertilization (R2 = 0.20*), fruit (R2 = 0.59*) and seed set (R2 = 0.60*); but negatively correlated with pollen stainability. Treating flowers with PGR did not affect pollen diameter and stainability, but increased ovule fertilizability from 42.9 to 64.9% and fruit set from 23.2 to 51.9% in treated female flowers and 31.3 to 54.7% when pollen from treated male flowers was used. Application of combined BA+STS on male flowers caused the highest ovule fertilizability, fruit and seed set efficiency, though this varied among study genotypes. These results show that RL and PGR treatment of flowers increases pollen viability and ovule fertilizability. This is important for planning pollination strategies in cassava breeding programmes.

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.

Motivated by Kurt's work [Filomat 30 (4) 921-927, 2016], we first consider a class of a new generating function for (p, q)-analog of Apostol type polynomials of order a including Apostol-Bernoulli, Apostol-Euler and Apostol-Genocchi polynomials of order a. By making use of their generating function, we derive some useful identities. We also introduce (p, q)-analog of Stirling numbers of second kind of order v by which we construct a relation including aforementioned polynomials.

In this paper, some convexity properties and some inequalities for the (p,k)-analogue of the Gamma function, Г_p,k(x) are given. In particular, a (p,k)-analogue of the celebrated Bohr-Mollerup theorem is given. Furthermore, a (p,k)-analogue of the Riemann zeta function, ζ_p,k(x) is introduced and some associated inequalities are derived. The established results provide the (p,k)-generalizations of some known results concerning the classical Gamma function.

This review focuses on an extensive synopsis of the recent improvements in the field of CO2 hydrogenation over structured zeolites including their properties, synthesis methods, and characterization approaches. The role of bimodal mesoporous structures surface oxygen vacancies, and the Si/Al ratio in improving catalytic activity is highlighted. The porosity, thermal stability, and structural integrity are also discussed in the review along with how structured zeolites are affected by electrical and plasma interactions. The synthesis methods are analyzed in detail by comparing the benefits and drawbacks of the bottom-up techniques, such as hard templating, soft templating, and non-templating on the one side; and the top-down approaches, e.g. dealumination, desilication, and recrystallization on the other. This review also draws attention to the necessity of overcoming the difficulties arising from these synthesis techniques, for example, micropore-induced diffusion restrictions and morphological constraints, employing innovative approaches and optimization strategies. Conventional and advanced characterization techniques are pointed out in this respect as crucial for understanding the catalytic mechanism and the dynamic behavior, hence, beneficial in the advancements of research on structured zeolites with higher efficiency and activity. The review ends with a perspective that highlights the necessity of further research in the improvement of synthesis approaches and characterization procedures of the structured zeolites to increase their catalytic activity in CO2 hydrogenation, a critical process of paramount importance in the global effort to reduce excessive carbon emissions and combat climate change..

In this paper, we establish some inequalities bounding the ratio Г_p,k(x)/Г_p,k(y), where Г_p,k(.) is the (p,k)-analogue of the Gamma function. Consequently, some previous results are recovered from the obtained results.

In the present paper, the (p,q)-Hermite based Apostol type Frobenius-Euler polynomials and numbers are firstly considered and then diverse basic identities and properties for the mentioned polynomials and numbers, including addition theorems, difference equations, integral representations, derivative properties, recurrence relations. Moreover, we provide summation formulas and relations associated with the Stirling numbers of the second kind.

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.

This paper assessed rice farmers' perceptions of agricultural and irrigation practices through their choices. A survey was carried out among 278 rice farmers on five irrigation schemes in three agro-ecological zones of Togo, viz. the savannah region, the forest region and the coastal region. The sample of random respondents was selected from a list of rice farmers provided by the managers of these irrigated schemes. Data collected through face-to-face interviews using kobocollect software were analyzed with R 4.2 software, and the Pearson test was validated at the 5% level. The results showed that the socio-economic characteristics of the rice growers, such as access to agricultural credit, experience, non-agricultural activities, membership of a rice growers' cooperative, gender, level of education and training in growing irrigated rice, and farm labor, significantly influenced the choice of agronomic practices and irrigation management. Characteristics such as experience, training and hired farm labor enhanced paddy yields, while access to agricultural credit was unproductive. Chemical clearing combined with stump removal, tiller ploughing, transplanting and high plant density are the agricultural practices that increased paddy yields, while tiller mudding and basal mineral fertilization were inefficient. In the same way, water distribution by demand, water depth above the soil of less than 5 cm, use of water-saving technologies and farmer's knowledge of how to improve water and fertilizer use-efficiency also helped to boost paddy yields. For sustainable rice production in the context of labor shortages and the financial resources required, future studies will focus on the effectiveness of motorized mudding and agricultural credits for rice farmers. Furthermore, considering the crucial role of training in the adopting of good agricultural and irrigation practices, future research will study strategies for wide diffusion of knowledge to rice producers.

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.

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.

In many countries, governments have implemented non-pharmaceutical techniques to limit COVID-19 transmission. Restricting human mobility is one of the most common interventions, including lockdown, travel restrictions, working from home, etc. However, due to the strong transmission ability of the virus variants, further rounds of interventions, including a strict lockdown, are not considered as effective as expected. The paper aims to understand how the lockdown policy and pandemics changed human mobility in the real scenario. Here we focus on understanding the mobility changes caused by compliance with restrictions and risk perceptions, using the mobility index from the Google report during three strict lockdown periods in Leeds, the largest city in the county of West Yorkshire, England from March 2020 to March 2021. The research proposed the time-varying z-scores and Principal Component Analysis (PCA) to simulate how local people dynamically process and perceive health risk based on multi-dimensional daily COVID-19 reports first. Further modelling highlights exponentially increasing policy non-compliance through the duration of lockdown, probably attributable to factors such as mental anxiety and economic pressures. Finally, the proposed nonlinear regression model examines the mobility changes caused by the population's dynamic risk perceptions and lockdown duration. The case study at Leeds fits data well and shows that the third lockdown policy took effect much slower than the first. At the same time, the negative impact of the epidemic on population mobility decayed 40% in the third lockdown period in contrast with the first lockdown. The risk perception estimation methods could reflect that the local population became increasingly accustomed to the COVID-19 situation, and local people rationally evaluated the risks of COVID in the third lockdown period. The results prove that simulated risk perceptions and policy decay could explain urban mobility behaviour during the mobility well during lockdown periods, which could be a reference for future decision-making processes.

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.

The aim of this paper is to investigate the amenability modulo an ideal of Banach algebras with emphasis on applications to homological algebras. In doing so, we show that amenability modulo an ideal of A^** implies amenability modulo an ideal of A. Finally, for a large class of semigroups, we prove that l¹(S)^** is amenable modulo Iσ^** if and only if an appropriate group homomorphic image of S is finite where Iσ is the closed ideal induced by the least group congruence σ.

Crop production in Afghanistan suffers from limited phosphorus (P) availability, which severely hinders national agriculture sustainability. This present study hypothesized that deep fertilizer placement could significantly enhance uptake of immobile P and thus tissue P accumulation and crop yield. A two-year pot experiment growing two maize (Zea mays) hybrid cultivars (Xida-789 and Xida-211) was therefore conducted to test these hypotheses under three contrasting fertilizer placement methods (broadcast, side band, and deep band). In doing so, P concentrations in both maize tissues and soils were compared at 45, 60, and 115 days after sowing (DAS) under nine combinations of nitrogen (N) and P fertilizer rates (kg ha-1: N112P45, N112P60, N112P75, N150P45, N150P60, N150P75, N187P45, N187P60, N187P75). Results have shown that deep band placement significantly increased P uptake efficiency, leading to greater P concentration and accumulation in maize tissues compared to other two fertilization methods. This improved P uptake was attributed to several factors associated with deep placement, including reduced P fixation, enhanced root access to P, and moisture availability for P uptake. Additionally, deep band placement combined with higher N application rates (N187 and N150) further enhanced plant P uptake by promoting P availability and utilization mechanisms. Deep band placement also resulted in significantly higher total soil P, Olsen-P, and P use efficiency than broadcast and side band methods, indicating a more efficient P fertilization strategy for maize that can improve growth and yield. This present study also found positive correlations between P concentration in plant organs and soil Olsen-P, highlighting the importance of adequate soil P levels for optimal plant growth. Overall, our results have showed that deep band fertilizer placement emerged as a superior strategy for enhancing P uptake efficiency, utilization, and maize productivity compared to broadcast and side band placement. This approach can potentially optimize P fertilizer utilization, improve maize growth and yield, while minimizing environmental P losses associated with broadcast applications.

In this paper, we investigate several relations for p-adic gamma function by means of their Mahler expansion and fermionic p-adic q-integral on ℤ_{p}. We also derive two fermionic p-adic q-integrals of p-adic gamma function in terms of q-Boole polynomials and numbers. Moreover, we discover fermionic p-adic q-integral of the derivative of p-adic gamma function. We acquire a representation for the p-adic Euler constant by means of the q-Boole polynomials. We finally develop a novel, explicit and interesting representation for the p-adic Euler constant including Stirling numbers of the first kind.

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.

Selecting drought-tolerant and more water-efficient wheat genotypes is a research priority, spe-cifically in regions with irregular rainfall or areas where climate change is expected to result in reduced water availability. The objective of this work was to use high-throughput measurements with morphophysiological traits to characterize wheat genotypes in relation to water stress. Field experiments were conducted from May to September 2018 and 2019, using a sprinkler bar irriga-tion system to control water availability to eighteen wheat genotypes: BRS 254; BRS 264; CPAC 01019; CPAC 01047; CPAC 07258; CPAC 08318; CPAC 9110; BRS 394 (irrigated biotypes) and Aliança; BR 18_Terena; BRS 404; MGS Brilhante; PF 020037; PF 020062; PF 120337; PF 100368; PF 080492; TBIO Sintonia (rainfed biotypes). The water regimes varied from 22 to 100% of the crop evapotranspiration replacement. Water stress negatively affected gas exchange, vegetation indices and grain yield. High throughput variables TCARI, NDVI, OSAVI, SAVI, PRI, NDRE and GNDVI had higher correlation with yield and morphophysiological measurements. The drought re-sistance index indicated that genotypes Aliança BRS 254, BRS 404, CPAC 01019, PF 020062, and PF 080492 were more drought tolerant.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

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.

This work deals with aerofoil aerodynamic features optimization, not only to improve flight features, but also to improve economy, ecology and safety of parameters of flight technique. In cruise mission, occupying the most flight time, the most important parameter is aerodynamic drag, which directly influences the aeroplane operational economy of transportation. Drag reduction is adequately reflected in the fuel consumption reduction. Consumption reduction is also adequately reflected in the flight ecology. In take-off and landing mission, the safety is priority and directly influences the aerofoil geometry. For cruise mission the new modified evolutionary algorithms (EA) are used to parameters incoming to Bezier-PARSEC 3434 parametrization. Such aerofoil is processed and evaluated by the Xfoil program. The change of model parameters results to optimal aerofoil shape. The DCAG (Direct Control Aerofoil Geometry) is unique developed mechanical device, makes possible the change of curvature of aerofoil, and also aerofoil geometry. DCAG is based on the rotary principle, which makes it possible to define the curvature of aerofoil for every roll as well as defining the geometry in the variable parts of aerofoil. For take-off and landing mission the best combination of slots and flaps is choosed. To improve of laminarity and reduce turbulent flow the DCAG is used. The work results to optimization, which is 50 times faster in comparison to ordinary optimization, with minimum of input parameters (flight speed, chord length, range of angles of attack and fitness function). The optimized aerofoil can achieve savings in fuel consumption up to 44% in comparison with unoptimized aerofoil, the aerodynamic drag reduction up to 44%. The output was checked by ANSYS Fluent simulation.

Limited availability of expensive alloying elements elevates low-alloyed steels to a unique position in the field of lightweight construction and mass production. Quenching and partitioning (Q&P) heat treatments of low-alloyed steels with exceptional property combinations are particularly promising. In this study, we characterize for the first time a new low-alloyed steel to be processed by Q&P heat treatments. In combined experimental and numerical studies, we design a novel approach that effectively combines the short cycle times of press hardening with the excellent property profiles of Q&P-treated steels. We identify appropriate transformation parameters for Q&P heat treatments by dilatometric studies and we adjust a number of reference conditions with different isothermal holding times. By means of SEM analysis and XRD measurements, we show that different fractions of retained austenite result in different mechanical properties. Initial numerical designs of the process can identify varying temperature profiles and cooling rates depending on the position in the die. The results show that the geometry of the part plays a minor role, but the die temperature is the dominant factor for successful partitioning directly in the press hardening process.

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.

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.

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.

Fungi play important roles in the process of material cycling and energy transfers in aquatic ecosystems. Yet little is known about the fungal community in lake sediment. In this study, sediment samples from five habitat types in Baiyangdian Lake (BYD Lake) were collected across three seasons. High-throughput sequencing techniques were used to determine the compositions of fungal communities. Fungi are highly diverse in the sediment of BYD Lake, although some important fungi have not been accurately identified. The fungal diversity was highest in winter and lowest in summer, while the variations of species richness among sampling sites were not significant. The compositions of fungal community differed among seasons and habitats. Physicochemical properties of sediments were measured and the influence of the environmental factors on fungal communities were analyzed. Temperature, P, N, and heavy metals explained 48.98% of the variations of fungal communities across three seasons. Human activities have affected the species and biomass of fungi to some extent. Temperature is the most influential factor and is negative to fungal diversity. Nutrient element in different forms have different effects on shaping the fungal community. The effect of heavy metals is not clear.

1) Background: carbapenem-resistant Acinetobacter baumannii (CRAB) is an opportunistic Gram-negative pathogen that has a significant role in healthcare-associated infections. Unlike several studies on the antibiotic-resistant epidemiology of A. baumanni, virulence molecular epidemiology was less studied. This study aimed to investigate CRAB virulence genes and their ability to form biofilms, and to correlate their biofilm formation ability with both; biofilm-encoding virulence genes and carbapenemase-encoding resistance genes. 2) Methods: 107 CRAB clinical isolates were collected from two hospitals in Jordan between 2018 and 2019 and were screened for virulence genes using PCR. In addition, biofilm formation ability was assessed using the microtiter plate method. 3) Results: the frequencies of the bap, OmpA, surA, PLD, paaE, basD, and traT virulence genes were 99.10%, 98.20%, 98.20%, 95.50%, 89.10%, 86.40%, and 8.20%, respectively. Overall, 86.4% of the tested isolates were biofilm formers with varying degrees; weak (28.2%), moderate (36.4%) and strong (21.8%). A significant relationship was found between the carbapenemase-encoding gene (OXA-23 gene) and biofilm production. 4) Conclusion: to the best of our knowledge, this is the first study in Jordan that inspected CRAB virulence genes and highlighted the importance of improving infection control measures to avoid CRAB outbreaks.

The cassava whitefly, Bemisia tabaci, causes direct damage to cassava in the tropics by feeding on the phloem of leaves, inducing leaf chlorosis and abscission which can result in considerable yield loss of up to about 50% on susceptible varieties. The pest is also known to impart its indirect damage through sooty mold formation. Most of the improved cassava varieties in Uganda were developed for CMD resistance and CBSD tolerance and little is known about their reaction to whitefly infestation. A study was conducted to evaluate the reaction of 24 improved cassava varieties which were sourced from 5 different countries in the region (Uganda, Kenya, Tanzania, Malawi, and Mozambique) to whitefly infestation. These varieties were evaluated in three agro-ecological zones of Uganda, namely; North-Western Savannah Grassland, Lake Victoria Crescent and the Kyoga Plains in the second rains of 2016. Monthly data were taken on adult and nymph counts, whitefly and sooty mold damage, CMD and CBSD severities from 2 up-to 9 Months after planting (MAP). Results show that the whitefly population was highly significantly (P

The integration of deep learning methods, especially Convolutional Neural Networks (CNN), and Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has been widely deployed in the field of radar signal processing. Nevertheless, these methods are frequently regarded as black-box models due to the limited visual interpretation of their internal feature representation and parameter organization. In this paper, we propose an innovative approach named C-RISE, which builds upon the RISE algorithm to provide a post-hoc interpretation technique for black-box models used in SAR Images Target Recognition. C-RISE generates saliency maps that effectively visualize the significance of each pixel. Our algorithm outperforms RISE by clustering masks that capture similar fusion features into distinct groups, enabling more appropriate weight distribution and increased focus on the target area. Furthermore, we employ Gaussian blur to process the masked area, preserving the original image structure with optimal consistency and integrity. C-RISE has been extensively evaluated through experiments, and the results demonstrate superior performance over other interpretation methods based on perturbation when applied to neural networks for SAR image target recognition. Furthermore, our approach is highly robust and transferable compared to other interpretable algorithms, including white-box methods.

The important sampling parameters of a headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) procedure, extraction temperature, extraction time and sample volume were optimized to quantify 23 important impact odorants in reduced alcohol red and white wines. A three-factor design of Box-Behnken experiments was used to determine optimized sampling conditions for each analyte, and a global optimized condition at every ethanol concentration of interest determined using a desirability function that accounts for a low signal response for compounds. Shiraz and Chardonnay wines were dealcoholized from 13.7 and 12.2% v/v ethanol respectively, to 8 and 5% v/v, using a commercially available membrane-based technology. A sample set of the reduced alcohol wines were also reconstituted to their natural ethanol level to evaluate the effect of ethanol content reduction on volatile composition. The three-factor Box-Behnken experiment ensured an accurate determination of the headspace concentration of each compound at each ethanol concentration, allowing comparisons between wines at varying ethanol levels to be made. Overall, the results showed that the main effect of extraction temperature was considered the most critical factor when studying the equilibrium of reduced alcohol wine impact odorants. The impact of ethanol reduction upon the concentration of volatile compounds clearly resulted in losses of impact odorants from the wines. The concentration of most analytes decreased with dealcoholization compared to that of the natural samples. Significant differences were also found between the reconstituted volatile composition and 5% v/v reduced alcohol wines, revealing that the dealcoholization effect is the result of a combination between the type of dealcoholization treatment and reduction in wine ethanol content.

We consider a coded compressed sensing protocol for unsourced massive random access (URA) that concatenates a shared Patterned Reed-Muller (PRM) inner codebook to an outer error-correction code. In this paper, an iterative list PRM projection algorithm is proposed to supplant the signal detector associated with the inner PRM sequences. In particular, we first propose an enhanced paths-saving algorithm called list PRM projection detection for the single-user scenario that keeps multiple candidates for the first few layers to remedy the risk of spreading errors. On this basis, we further propose an iterative list PRM projection algorithm for the multi-user scenario. The vectors for PRM codes and channel coefficients are jointly detected in an iterative manner, which offers significant improvements regarding the convergence rate for signal recovery. Furthermore, the performances of the proposed algorithms are analyzed mathematically, and we verified that the theoretical simulations are consistent with the numerical simulations. Finally, we concatenate the inner PRM codes that employ the iterative list detection to two practical error-correction outer codes. According to the simulation results, we conclude that the packetized URA with the proposed iterative list projection detection works better than benchmarks in terms of the number of active users it can support in each slot and the amount of energy needed per bit to meet an expected error probability.

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.

Paratemporal methods based on tree expansion have proven to be effective in efficiently generating trajectories of stochastic systems. However, combinatorial explosion of branching arising from multiple choice points presents a major hurdle that must be overcome to implement such techniques. In this paper we tackle this scalability problem by developing a systems theory-based framework covering both conventional and proposed tree expansion algorithms for speeding up discrete event system stochastic simulations while preserving desired accuracy. An example is discussed to illustrate the tree expansion framework in which a discrete event system specification (DEVS) Markov stochastic model takes the form of a tree isomorphic to a free monoid over the branching alphabet. We derive the computation times for baseline, non-merging, and merging tree expansion algorithms to compute the distribution of output values at any given depth. The results show the remarkable reduction from exponential to polynomial dependence on depth effectuated by node merging. We relate these results to the similarly reduced computation time of binomial coefficients underlying Pascal’s triangle. Finally, we discuss application of tree expansion to estimating temporal distributions in stochastic simulations involving serial and parallel compositions with potential real world use cases.

In a recent paper, Sarikaya et al. introduced a new analogue of the classical Gamma function which they called, the conformable Gamma function. Motivated by their results, this paper seeks to establish some inequalities for the conformable Gamma and Polygamma functions. Among other analytical tools, the procedure relies on the generalized forms of some classical inequalities.

Since its initial characterization in 2016, the interferon stimulated gene Shiftless (SHFL) has proven to be a critical piece of the innate immune response to viral infection. SHFL expression stringently restricts the replication of multiple DNA, RNA, and retroviruses with an extraordinary diversity of mechanisms that differ from one virus to the next. These inhibitory strategies include the negative regulation of viral RNA stability, translation, and even the manipulation of RNA granule formation during viral infection. Even more surprisingly, SHFL is the first human protein found to directly inhibit the activity of the -1 programmed ribosomal frameshift, a translation recoding strategy utilized across nearly all domains of life and a several human viruses. Recent literature has shown that SHFL expression also significantly impacts viral pathogenesis in mouse models, highlighting its in-vivo efficacy. To help reconcile the many mechanisms by which SHFL restricts viral replication, we provide here a comprehensive review of this complex ISG, its influence over viral RNA fate, and the implications of its functions on the virus-host arms race for control of the cell.

Terrestrial orchid tubers are an important source of food in some parts of Africa and are traditionally included in the diets of most rural communities in Malawi. However, there is limited information on the nutritional and phytochemical content of the Malawian orchids to substantiate their traditional use. The present study evaluates the nutritional and phytochemical variation of four orchid species: Disa zombica, Satyrium buchananii, Satyrium carsonii, and Satyrium trinerve, collected from the same ecological zone of Malawi. The proximate content, minerals, phytochemicals, and functional properties were analysed using official procedures. Protein ranged from 2.19% to 4.65%, whereas carbohydrate ranged from 65.24% to 80.22%, with S. carsonii and S. trinerve registering the highest protein and carbohydrate contents, respectively. Iron and potassium were highest in D. zombica, while sodium and calcium were highest in S. buchananii. The total phenolics ranged from 228.56 to 500.00 mg GAE/100 g, with D. zombica registering the highest. The water absorption capacity ranged from 4.10 to 10.88 g/g. Albeit variable levels, the study provides evidence that orchid species contain essential nutrients and phytochemicals important for human nutrition and health. Furthermore, the functional properties can be utilised in the development of food products, such as baked products.

This research aims to develop an inexpensive ocean observation instrument with a project name is NOBEL (Nusantara Oceanography Backdoor Experiment Laboratory)-BOX. The device can be installed on all types of vessels and placed in a specific area to map the water conditions, providing accurate data for managing a marine area specifically to water quality. The principle of NOBEL-BOX is to attach sensors in a container connected to a microcontroller and then measure directly. The method employed includes experimental design, laboratory and field tests, and data evaluation to produce the necessary system and instruments. The design process involves the construction of the instrument and the fabrication of the device. This process includes creating three-dimensional sketches/drawings, designing microcontrollers and data transmission systems, and power capacity. The sensors attached to this device are surface water temperature, air temperature, salinity, dissolved oxygen, pH, and TDS. The testing phase includes data validation, testing of the device in the laboratory, and field testing. The laboratory and field tests showed that the device worked and provided data that can be used to analyze the seawater condition spatially and over time.

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

Pekalongan is one of several cities that lies in the northern coast of Java island which is often flooded due to sea level rise. This condition impacted its urban development characteristic and increase in the future. In this research both Geographical Information System based and Spatial Metric approach are used. The spatial pattern is analyzed by using spatial metric based on the exploration of land use change that occurred. In this research, the spatial pattern is focused on aggregation pattern and diversity in coastal area. The result shows that the land use of coastal area are dominated with swamp, then followed by settlement and fishpond. It is also shown that the greatest land use change occurred on paddy field and swamp areas. Based on the spatial metric calculation, the aggregation level of land use decrease periodically and has a small growth level. It is indicated from its metric value aggregation and diversity from two periods: 2003-2009 and 2009-2016. Overall the land use of Pekalongan experienced large dynamics, especially in its coastal area. The spatial pattern trend in those area tend to be more sprawl as defined by the decrease of aggregation pattern and low level of land use growth pattern.

In this paper, we use three different experimental methods (particle method, grid method and hybrid method) to model and simulate the smoke from the perspective of fluid dynamics. Through the comparison of different methods, we conclude: The particle method can avoid the numerical dissipation problem caused by grid calculation, but it also brings problems such as the distortion of the trajectory of the example. The grid method is accurate in calculation, but it is prone to numerical dissipation and loss of details. Finally, we choose the hybrid method to store the vorticity in the form of particles in vortex particles, avoiding the numerical dissipation problem caused by the use of grids, and including rich turbulence, which perfectly shows the simulation effect of smoke.

Drug nanosuspensions offer a promising approach to improve bioavailability for poorly soluble drug candidates. Such formulations often necessitate the inclusion of an excipient to stabilize the drug nanoparticles. However, a rationale to choose the correct excipient for a given drug candidate remains unclear. To gain molecular insight into formulation design, this work first utilizes molecular dynamics simulation to computationally investigate drug-excipient interactions for a number of combinations that have been previously studied experimentally. We find that hydrophobic interactions drive excipient adsorption to drug nanoparticles, and that the fraction of polar surface area serves as a predictor for experimental measurements of nanosuspension stability. To test these ideas prospectively, we applied our model to an uncharacterized drug compound, GDC-0810. Our simulations predicted that salt forms of GDC-0810 would lead to more stable nanosuspensions than the neutral form; therefore, we tested the stability of salt GDC-0810 nanosuspensions and found that the salt form readily formed nanosuspensions even without excipient. To avoid computationally expensive simulations in the future, we extended our model by showing that simple, two-dimensional properties of the single drug molecule can be used to rationalize nanosuspension design without simulation. In all, our work demonstrates how computational tools can provide molecular insight into drug-excipient interactions, and aid in rational formulation design.

Immune checkpoint inhibitors (ICI) are currently use in a wide range of tumors, but only 20-40% of patients achieve clinical benefit. Aim of our study was to find predictive biomarkers of ICI treatment. We analyzed by immunohistochemistry various cell subsets, including CD3+ cells, CD8+ cells, CD68+ cells, CD20+ cells, FoxP3+ cells, and molecules as LAG-3, IDO1, TGfβ. Comprehensive genomic profiles were analyzed. Correlation of various biomarkers with efficacy of ICI treatment in patients with advanced solid tumors was evaluated. We evaluated 56 patients treated with ICI monotherapy. Longer median progression-free survival (PFS) was found in tumors negative for nuclear FoxP3 (P = 0.002, HR 0.14) and in TMB-high tumors (P = 0.024, HR 0.38). Longer overall survival (OS) was found in patient with intraepithelial CD8 negativity (P = 0.045, HR 0.47). In malignant melanoma CD68 negativity, FoxP3 negativity and PDL TPS ≥ 1 was associated with longer PFS. In NSCLC FoxP3 was associated with longer PFS and OS. We found that absence of expression of several biomarkers such as CD68 and FoxP3 is associated with better survival. TMB-high and PD-L1 expression not universally but in certain disease could predict response.

Reinforcement learning (RL) is an extensively applied control method for the purpose of designing intelligent control systems to achieve high accuracy as well as better performance. In the present article, the PID controller is considered as the main control strategy for brushless DC (BLDC) motor speed control. For better performance, the fuzzy Q-learning (FQL) method as a reinforcement learning approach is proposed to adjust the PID coefficients. A comparison with the adaptive PID (APID) controller is also performed for the superiority of the proposed method, and the findings demonstrate the reduction of the error of the proposed method and elimination of the overshoot for controlling the motor speed. MATLAB/SIMULINK has been used for modeling, simulation, and control design of the BLDC motor.

A defining feature of a productive infection is the co-opting of host cell resources for viral replication. Despite their repertoire of molecular functions, viruses subvert host defenses to take control of cellular factors such as RNA binding proteins (RBPs). RBPs are involved in virtually all steps of mRNA life forming ribonucleoprotein complexes (mRNPs) in a highly ordered and regulated process to control RNA fate and stability in the cell. Thus, the hallmark of this viral takeover is to reshape RNA fate in the cell to modulate host gene expression and evade immune responses. Here we provide an extensive review of work in this area, particularly how the host-viral interplay influences RBP functions to modulate the host cell. Overall, in this review, we highlight the myriad of ways RBPs can regulate RNA stability in either a pro-viral or antiviral manner by gathering novel insights gained from research studies in this field.

Autonomous and cooperative vehicle systems represent a key priority in the automotive realm. Networked driving simulation can be utilized as a safe, cost-effective experimental replica of real traffic environments in order to support and accelerate the development of such systems. In networked driving simulation, different independent systems collaborate to achieve a common task: multi-driver traffic scenario simulation. Yet distinct system complexity levels are necessary to fulfill the requirements of various application scenarios, such as development of vehicle systems, analysis of driving behavior, and training of drivers. With myriad alternatives of available systems and components, developers of networked driving simulation are typically confronted with high design complexity. There are no systematic approaches to date for the design of networked driving simulation in accordance with the specific requirements of the concerned application scenarios. This paper presents a novel design method for networked driving simulation. The method consists mainly of a procedure model that is accompanied by a configuration software. The procedure model includes the necessary phases for the systematic design of application-oriented platforms for networked driving simulation. The configuration software embeds supportive decision-making processes that enable developers to apply the design method and easily create different system models. The design method was validated by generating system models and developing platforms of networked driving simulation for three different application scenarios.

Spent nuclear fuel and high-level radioactive waste can be disposed in deep horizontal drillholes in sedimentary, metamorphic, or igneous rocks. Horizontal drillhole disposal has safety, operational, and economic benefits: The repository is deep in the brine-saturated zone far below aquifers in a reducing environment of formations that can be shown to have been isolated from the surface for millions of years; its depth provides safety against inadvertent intrusion, earth¬quakes, and near-surface perturbations; it can be placed close to the reactors and interim storage facilities, minimizing transportation; disposal costs per ton of waste can be kept substantially lower than for mined repositories by its smaller size, reduced infrastructure needs, and staged imple¬mentation; and, if desired, the waste could be retrieved using “fishing” technology. In the proposed disposal concept, corrosion-resistant canisters containing unmodified fuel assemblies from commercial reactors would be placed end-to-end in up to 50 cm diameter horizontal drill¬holes, a configuration that reduces mechanical stresses and keeps the temperatures below the boiling point of the brine. Other high-level wastes, such as capsules containing 137Cs and 90Sr, can be disposed in small-diameter drillholes. We provide an overview of this novel disposal concept and its technology, discuss some of its safety aspects, and compare it to mined repositories and the deep vertical borehole disposal concept.

: Tunnel instability and lining integrity are intimately tied to the creep properties of the surrounding rock. The acquisition of rock mass creep parameters is critical in ascertaining the appropriate timing for lining construction. Nevertheless, creep tests on rock specimens conducted in a controlled setting cannot be straightforwardly extrapolated to rock mass creep analysis. This study performs laboratory-based creep tests on mudstone samples and establishes the corresponding creep constitutive model. Integration of a Mohr-Coulomb element with the Burgers model in series serves to characterise the yield creep behaviour of the rock mass. Additionally, the research outlines a series of 100 orthogonal experiments utilising randomised creep parameters, and formulates a GA-BP neural network inversion model. Employing long-term deformation measurements from the crown and sidewalls of the project site, this study deduces the creep parameters of the mudstone in the investigated tunnel section and examines the prolonged deformation traits of the surrounding rock. Drawing on the deformation traits of the surrounding rock and the forces impacting the primary support and lining structures, this paper evaluates the earliest and latest viable lining casting periods and pinpoints an optimal timing interval for lining implementation. The methodologies employed herein can serve as a benchmark for analogous endeavors internationally.

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.

In perennial fruit crops, bearing can be influenced by various factors, including environmental conditions, germplasm, rootstocks, and cultivation methods. Cherries, one of the most important and popular fruit species from the temperate climate zone, achieve high prices on the market. New agricultural technologies and environmental factors force a change in the approach to cherry cultivation. Old-type cherry orchards with their high demand for water, nutrients and manual work are replaced by orchards of self-pollinating cherry cultivars grown on dwarf rootstocks. These changes make it necessary to search for ways to regulate fruiting, in particular to thin buds, flower and fruit. In view of environmental regulations and consumer pressure, thinning methods are being sought that either do not involve the use of chemicals or that use eco-friendly chemical agents. This review examines recent progress in understanding the effect of thinning methods on the physiology, tree growth and fruit quality of cherries, discusses horticultural practices aimed to ensure regular cropping and their influence on fruit quality, and provides suggestions for future research.

The European pear is a climacteric fruit species characterized by high storability. 'Conference', a pear cultivar very popular on the market, can be stored in a CA room without major losses for half a year. However, for ‘Conference’ storage to be successful, the fruit must be harvested fully developed even before it enters the climatic maturation phase. Harvested too early or too late, pears will taste bad, have physiological disorders and will be poorly storable. Among the various methods used to determine the optimal harvest date, the degree-days method, which relies of the sum of active temperatures, seems to be relatively accurate and easy to apply. During 11 years of study, ‘Conference’ pears were harvested on 4 dates (every 4-5 days) chosen based on measurements and observations, and then, after a six-month storage period, the optimum harvest date was determined. During the growing season, temperature was measured using an automatic weather station to calculate the sum of active temperatures from full bloom to the optimal harvest date. Measurements made after storage were analysed and the sum of active temperatures needed for the proper development of ‘Conference’ pear was calculated to be 2469 degree days. The calculations are very accurate because the dispersion calculated using the standard deviation was only 20 °. The base temperature with the smallest error was 0 °. On the basis of the study results, this method can be recommended as useful for determining the optimal harvest date.

The earthquake alert of the early warning systems is based on the delay that the S waves have in reference to the P waves and on the interpretation of the P waves’ specific parameters. One of the most used parameters for estimating the moment magnitude of an earthquake is the characteristic period measured in the first 3 seconds of the appearance of the P wave. The typical method determines the characteristic period in the time domain, based on the velocity wave and the displacement wave. In the present work, we present a method for estimating the frequency of the characteristic period. This method includes zero padding of the P wave sequence, conversion of the extended sequence from the time domain to the frequency domain, the identification of local frequency maxima and the calculation of the weighted average of the frequency based on the identified maxima. Tests conducted on synthetic signals, as well as standard deviation evaluation tests for simultaneous recordings on several stations, reveal better performance to the usual method.

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.

Microsystems are key enabling technologies, with applications found in almost every industrial field, including in-vitro diagnostic, energy harvesting, automotive, telecommunication, drug screening, etc. Microsystems, such as microsensors and actuators, are typically made up of components below 1000 microns in size that can be manufactured at low-unit cost through mass-production. Yet, the development of microsystems for commercial or educational purposes, has typically been limited to upper income countries due to the initial investment costs associated with the microfabrication equipment and processes. However, recent technological advances have enabled the development of low-cost microfabrication tools. In this paper, we describe a range of low-cost approaches and equipment (below £1000), developed or adapted and implemented in our laboratories. We describe processes including photolithography, micromilling, 3D printing, xurography and screen-printing used for the microfabrication of structural and functional materials. The processes that can be used to shape a range of materials with sub-millimetre feature sizes are demonstrated here in the context of Lab-on-Chips, but they can be adapted for other applications. We anticipate that this paper, which will enable researchers to build a low-cost microfabrication toolbox in a wide range of settings, will spark a new interest in microsystems.

Celtis iguanaea is popularly used in the treatment of diabetes mellitus. However, thorough chemical and pharmacological investigations regarding its activity are lacking. In this study, we investigated the effects of the hydroalcoholic extract from C. iguanaea (CI) on markers of cardiovascular diseases and the glucose metabolism in cholesterol-fed rats. Therefore, hypercholesterolemic rats (1% cholesterol) were orally treated with CI (150, 300, or 600 mg/kg) or simvastatin (4 mg/kg) (n = 6) once a day for 30 days along with a hypercholesterolemic diet. A control group (C) was given saline solution. CI showed significant decreases in serum levels of total cholesterol, LDL-cholesterol, HMG-CoA-reductase, IL-1, IL-6, TNF-α, and IFN-γ when compared to group C (p ˂ 0.05). Hypoglycemic effects were observed along with a decrease of the activity of sucrase (CI 600), maltase (CI 150, CI 300), and an increase in muscle glycogen levels (CI 300). Antioxidant effects were observed in plasma, and the histopathological analysis showed a significant decrease in the liver fat area for CI compared to group C (p < 0.001). Our results suggest that the biological effects of CI could be related to the presence of flavonoids that possibly exert antioxidant, enzymatic inhibitory, and insulin-mimetic effects.

In this paper, we gave an attack on RSA when Euler function has small multiplicative inverse modulo "e" and the prime sum p+q is of the form p+q=2^nk_0+k_1 where n is a given positive integer and k_0 and k_1 are two suitably small unknown integers using sublattice reduction techniques and Coppersmith's methods for finding small roots of modular polynomial equations. When we compare this method with an approach using lattice based techniques, this procedure slightly improves the bound and reduces the lattice dimension.

Coronavirus disease 2019 (COVID-19) can lead to systemic coagulation activation and thrombotic complications. We investigated the incidence of objectively confirmed venous thromboembolism (VTE) in 198 hospitalized patients with COVID-19 in a single-center cohort study. Seventy-four patients (37%) were admitted to the intensive care unit (ICU). At time of data collection, 58 (29%) were still hospitalized and 14% had died. During a median follow-up of 5 days (IQR, 3-9), 33 patients (17%) were diagnosed with VTE of whom 22 (11%) had symptomatic VTE, despite routine thrombosis prophylaxis. The cumulative incidences of VTE at 7 and 14 days were 15% (95% CI, 9.3-22) and 34% (95% CI, 23-46), respectively. For symptomatic VTE, these were 11% (95% CI, 5.8-17) and 23% (95% CI, 14-33). VTE appeared to be associated with death (adjusted HR, 2.9; 95% CI, 1.02-8.0). The cumulative incidence of VTE was higher in the ICU (25% at 7 days 95% CI, 15-36, and 48% at 14 days, 95% CI, 33-61) than on the wards (any VTE and symptomatic VTE 6.5 % at 7 days (95% CI, 1.5-17) and 10% at 14 days (95% CI, 2.9-24)).The observed risk for VTE in COVID-19 is high, particularly in ICU patients, which should lead to a high level of clinical suspicion and low threshold for diagnostic imaging for DVT or PE. Future research should focus on optimal diagnostic and prophylactic strategies to prevent VTE and potentially improve survival.

The synthesis 2-tert-butyl-4-methylphenol is of great significance because of its widely application in industry, and the development of highly efficient catalyst is necessary to the alkylation of p-cresol and tert-butyl alcohol. Here, an efficient and mild method was established, caprolactam was chosen as hydrogen-bonding acceptor, p-toluenesulfonic acid was employed as hydrogen-bonding donor, and deep eutectic solvent (DES) was prepared to catalyze the alkylation reaction. The structure of the DES catalyst was characterized by 1H NMR spectra, thermogravimetric analysis and fourier transform infrared spectra (FT-IR). In addition, response surface design based on Box-Behnken method was employed to optimize the alkylation reaction process parameters, the study of reaction kinetics was also carried out subsequently. The recycle performance of the catalyst was evaluated by recovery experiments, and a good result was obtained. Comparing with the literature reported, we here provide a mild method to the synthesis of 2-tert-butyl-4-methylphenol.

Solid asperity interactions are common and inevitable under severe loading conditions for any lubricated contact. Heavy-duty machine components (gear, bearings etc.) generally operate under Mixed Lubrication, where uneven surface features contact each other when generated fluid pressure is not enough to support the external load. The Reynolds equation is commonly used to simulate smooth lubricated contacts numerically. In rough lubricated interfaces where opposite surface asperities make contact, the Reynolds equation alone cannot accurately predict pressure using the traditional numerical simulation method. In this paper, Lubrication-Contact interface conditions (LCICs) have been implemented and extended to solve the multiple asperity contact problem using the full-multigrid approach. The developed novel algorithm has significantly accelerated the solution process and improved the accuracy and efficiency of pressure calculation for fluid-solid sub-interactions that can occur under ML regions. The Finite Difference Method (FDM) results have been compared with Computational Fluid Dynamics (CFD) simulation to validate the newly developed model. Hence, the proposed optimized solution method will provide valuable insight to researchers and industry engineers interested in simulating the ML problem where the effect of the fluid-solid interface can be captured effectively to improve reliability in the calculation of the life expectancy of the lubricated parts.

For the problem of poor accuracy of the existing multi-rate simulation methods, this paper proposes a multi rate real-time simulation method based on the Norton equivalent, compared with multi-rate simulation method based on the ideal source equivalent. After the Norton equivalence of the fast subsystem and the slow subsystem, they are obtained simultaneously at the junction nodes. In order to reduce the amount of simulation calculation, the Norton equivalent circuit is obtained by incremental calculation. The data interface between the fast subsystem and the slow subsystem is realized by extrapolation method. For ensuring the real-time performance of the simulation, the method that the slow subsystem calculates ahead of the fast subsystem is given for the slow subsystem with a large amount of calculation. Finally, the AC/DC hybrid power system was simulated on the real-time simulation platform (FRTDS), and the simulation results were compared with the single-rate simulation, which verified the correctness and accuracy of the method.

This paper examines the determinants of CO2 emissions in Oman from 1990 to 2022, focusing on the impacts of energy consumption, economic growth, urbanization, financial development, and foreign direct investment. Utilizing stepwise regression, robust least squares, Fully Modified Least Squares (FMOLS), Canonical Cointegrating Regression (CCR), and various cointegration tests including the Johansen cointegration test, Engle-Granger cointegration test, and Vector Error Correction (VEC) model, the study reveals several key findings. Energy use per capita (ENGY) and real GDP per capita (RGDPC) are consistently significant positive predictors of CO2 emissions. Urbanization (URB) also significantly contributes to higher emissions. Conversely, Financial Development Index (FDX) and foreign direct investment (FDI) do not show significant effects on CO2 levels. The high R-squared values across models indicate that these variables explain a substantial portion of the variation in emissions. Cointegration tests confirm long-term equilibrium relationships among the variables, with the Johansen test identifying two cointegrating equations and the Engle-Granger test showing significant tau-statistics for FDX, ENGY, and URB. The VEC model further highlights the short-term dynamics and adjustment mechanisms. These findings underscore the importance of energy policy, economic development, and urban planning in Oman's efforts towards sustainable development and decarbonization.

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.

The advent of the era of big data will bring more convenience to people and greater development to society. But at the same time, it will also bring people the problem of 'information overload', i.e., when people are faced with huge information data, there are many redundant and worthless data. The redundant and worthless data information seriously interferes with the accurate selection of information data. Even though people can use Internet search engines to access information data, they cannot meet the individual needs of specific users in specific contexts. The personalized needs of a particular user in a particular context. Therefore, how to find useful and valuable information quickly has become one of the key issues in the development of big data. With the advent of the era of big data, recommendation systems, as an important technology to alleviate information overload, have been widely used in the field of e-commerce. Recommender systems suffer from a key problem: data sparsity. The sparsity of user history rating data causes insufficient training of collaborative filtering recommendation models, which leads to a significant decrease in the accuracy of recommendations. In fact, traditional recommendation systems tend to focus on scoring information and ignore the contextual context in which users interact. There are various contextual modal information in people's real life, which also plays an important role in the recommendation process. In this paper we achieve data degradation and feature extraction, solving the problem of sparse data in the recommendation process. An interaction context-aware sub-model is constructed based on a tensor decomposition model with interaction context information to model the specific influence of interaction context in the recommendation process. Then an attribute context-aware sub-model is constructed based on the matrix decomposition model and using attribute context information to model the influence of user attribute contexts and item attribute contexts on recommendations. In the process of building the model, the method not only utilizes the explicit feedback rating information of users in the original dataset, but also utilizes the interaction context and attribute context information of the implicit feedback and the unlabeled rating data. We evaluate our model by extensive experiments. The results illustrate the effectiveness of our recommender model.

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.

A synopsis of current knowledge of the diversity of the New Zealand landhopper fauna is provided. A combination of morphological and molecular analysis was employed on material from across New Zealand. Thirteen new endemic genera soon to be formally described have been discovered, including four belonging to the widespread families Talitridae and Arcitalitridae. These are families that had not been previously reported from New Zealand. We document the existence of at least 48 new provisional native species. This number far exceeds the 28 species currently described. Some described species are now shown to be species complexes and a few of these are very diverse with numerous cryptic species. Six changes to the existing taxonomy are proposed. Dallwitzia simularis (Hurley, 1957) is transferred from Makawidae Myers and Lowry, 2020 to Talitridae Rafinesque, 1815; Kellyduncania hauturu (Duncan, 1994) is reinstated as a member of Dana Lowry, 2011 and Kellyduncania (Lowry and Myers, 2019) is relegated to a synonym of Dana Lowry, 2011; Kanikania Duncan, 1994 is transferred from Makawidae Myers and Lowry, 2020 to Arcitalitridae Myers and Lowry, 2020; Parorchestia longicornis is transferred to Kanikania Duncan, 1994; Waematau kaitaia (Duncan, 1994) is transferred to Kohuroa Lowry, Myers and Nakano, 2019; and Waematau unuwhao (Duncan, 1994) is transferred to Omaiorchestia Lowry and Myers, 2019. This reduces the number of described genera from 17 to 16.

Large language models (LLMs) have shown impressive performance and versatility. However, their billions of parameters and high computational costs hinder the development of personalized and privacy-preserving AI assistants operating locally on user devices. In this work, we explored the potential of pruning LLMs to create lightweight models suitable for user devices, using the moderate-sized Llama-2 7B model as an example. By adopting a simple yet effective pruning method, we found that up to 60% of the weights in the Llama-2 7B model could be pruned without significantly impairing its language modeling capabilities. Furthermore, despite occasional factual inaccuracies, the pruned model at the sparsity limit generated fluent and helpful answers to daily queries, demonstrating its feasibility of on-device AI assistants. These inaccuracies might originate from forgetting or hallucination due to pruning. We proposed a simple protocol to distinguish between the two mechanisms, as well as future directions to improve the pruned models for local AI assistants.

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 evaluation of the possibility of obtaining dihaploids by the method of anther culture in vitro to accelerate selection for resistance to prolonged flooding of seeded rice with water was carried out. The object of research is rice hybrids F2 of the Rice Breeding and Seed Production Laboratory of the “Donskoy” ASC, obtained as a result of interbreeding the best economically valuable varieties with samples bearing genes of resistance to prolonged flooding with water. Basic nutrient medium with an optimal composition of nutrition elements and growth hormones stimulating callo- and morphogenesis were used. For the induction of callus formation, 12604 anthers were planted, according to 26 hybrid combinations represented by 68 plants, as a result, 716 neoplasms were obtained, including 586 non–morphogenic callus, 130 regenerating plants. Cultivation of anthers revealed large genotypic differences in the samples. According to the responsiveness to neoplasms, 60% of the panicles showed a positive result, the rest did not give callus. The most responsive to the formation of callus were hybrid combinations: 5009/2 – 84 pcs., 5010/2 – 94 pcs., 4565/3 – 85 pcs., 4641/2 – 69 pcs. They also showed the ability to morphogenesis. Androgenic plants were obtained by 14 hybrid combinations, their share was 1.03% of the total number of inoculated anthers. 30 green regenerative lines from four rice hybrids were obtained, differing in visual morphological assessment: 5009/2 - 5 pcs., 5010/2 – 5 pcs., 4565/3 – 2 pcs., 4641/2 – 18 pcs. The isolated lines are characterized by good responsiveness in the culture of anthers in vitro, carry genes for resistance to prolonged flooding, and can be used in rice breeding programs using DG technologies.

In this paper, we study the third order semilocal convergence of the Newton-like method for finding the approximate solution of nonlinear operator equations in the setting of Banach spaces. First, we discuss the convergence analysis under ω-continuity condition, which is weaker than the Lipschitz and Hölder continuity conditions. Second, we apply our approach to solve Fredholm integral equations, where the first derivative of involved operator not necessarily satisfy the Hölder and Lipschitz continuity conditions. Finally, we also prove that the R-order of the method is 2p + 1 for any p $\in$ (0,1].

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.

This work introduces a novel numerical method designed to address three-dimensional unsteady free surface flows incorporating integral viscoelastic constitutive equations, specifically, the K-BKZ-PSM (Kaye–Bernstein, Kearsley, Zapas - Papanastasiou, Scriven, Macosko) model. The new proposed methodology employs a second-order finite difference approach along with the deformation fields method to solve the integral constitutive equation, and the marker-particle method (known as \emph{Marker-and-Cell}) to accurately capture the evolution of the fluid's free surface. The newly developed numerical method has proven its effectiveness in handling complex fluid flow scenarios, including confined flows and extrudate swell simulations of Boger fluids. Furthermore, a new semi-analytical solution for velocity and stress fields is derived, considering fully developed flows of a K-BKZ-PSM fluid in a pipe.

Despite identical genetic constitution, a cancer cell population can exhibit phenotypic variations termed as non-genetic/non-mutational heterogeneity. Such heterogeneity – a ubiquitous nature of biological systems – has been implicated in metastasis, therapy resistance and tumour relapse. Here, we review the evidence for existence, sources and implications of non-genetic heterogeneity in multiple cancer types. Stochasticity/ noise in transcription, protein conformation and/or external microenvironment can underlie such heterogeneity. Moreover, the existence of multiple possible cell states (phenotypes) as a consequence of the emergent dynamics of gene regulatory networks may enable reversible cell-state transitions (phenotypic plasticity) that can facilitate adaptive drug resistance and higher metastatic fitness. Finally, we highlight how computational and mathematical models can drive a better understanding of non-genetic heterogeneity and how a systems-level approach integrating mathematical modelling and in vitro/in vivo experiments can map the diverse phenotypic repertoire, and identify therapeutic vulnerabilities of an otherwise clonal cell population.

A sustainable low cost activated carbon substitute was produced based on pretreated lignocellulosic biomass, especially spruce sawdust. A harmful liquid waste, desalination brine was used for the treatment of a solid wood industry waste, spruce sawdust. This approach is in the circular economy theory and aims to the decarbonization of the economy. The pretreated sawdust was tested as an adsorbent appropriate for the removal of a commonly used pollutant, methylene blue, from industrial wastewater. The adsorption capacity of the pretreated material was found to increased four times comparing to the untreated one in the case that the Freundlich equation was fitted to the isotherms’ data. The treatment experimental conditions with desalination brine that gave maximum adsorption capacity correspond to 1.97 combined severity factor in logarithmic form value. The same adsorption capacity was found to increase five to six times comparing to the untreated spruce sawdust in the case that the Langmuir isotherm model was applied at the same data. Moreover, kinetic experiment was cried out as regards the methylene blue adsorption process. The desalination brine pretreated sawdust adsorption capacity increased 1.4 times comparing to the untreated one, in the case of the Lagergren kinetic equation fitting. Furthermore, the adsorption capacity of the same material was increased 1.6 times when the second order kinetic model was applied to the same data. Industrial scale applications can be based on the kinetic data findings as they have to do with a very shorter adsorption period comparing to the isotherm data.

We introduce the notion of p-adic magic contraction on p-adic Hilbert space. We derive p-adic Halmos dilation, p-adic Egervary N-dilation, p-adic von Neumann inequality and p-adic Sz.-Nagy dilation for p-adic magic contraction.

Thermal analysis of a hypereutectic Al-Si alloy used for an automotive part was carried out in this research work. Solidification characteristics are recognized from the Temperature-time curve and its corresponding derivatives. This analysis was successfully used in a simulation software program with the aim of improving the resultant simulation accuracy. In this study, different types of molds, with and without cooling systems, were designed and used. The melt present in the furnaces of the factory was used to simulate the casting process. The effect of different cooling rates (1.2ºC/s, 2ºC/s, 2.3ºC/s and 2.9ºC/s) on the solidification parameters have been investigated. Differences in the resultant microstructure between wall and center of the molds have been analyzed and have been related to the T-t curve. Finally, the experimental results clearly indicate that the water-cooling rate of the molds and the melt temperature directly affects the solidification process as well as the final microstructure.

Background: Exercise is increasingly understood as an important resource for people with harmful substance use, including those in prison. Little is known about how inmates adopt various health behaviors during incarceration, without interventions. Methods: This study analyzed self-reports from 1468 inmates in Norwegian prisons, compared them according to harmful substance use pre-incarceration, and explored changes in exercise and nicotine use during incarceration. Results were presented in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results: Inmates with harmful substance use reported higher rates of smoking, smokeless tobacco, and physical inactivity pre-incarceration than inmates without harmful use. However, inmates with harmful use also exhibited more behavioral changes: they adopted exercise, ceased smoking, and adopted smokeless tobacco at higher rates during incarceration than the non-harmful group. Conclusions: Exercise is being taken up by a significant proportion of inmates, and may in particular be a replacement behavior for substance use. However, unhealthy behaviors are also begun or maintained. If prisons were used as an arena to facilitate healthy behaviors, the public health benefits to a marginalized group such as substance-using inmates could be substantial.

ω-Transaminases have been immobilized on macrocellular silica monoliths and used as heterogeneous biocatalysts in a continuous flow mode enantioselective transamination reaction. The support was prepared by a sol-gel method based on emulsion templating. The enzyme was immobilized on the structured silica monoliths both by adsorption, and by covalent grafting using amino-functionalized silica monoliths and glutaraldehyde as a coupling agent. A simple reactor set-up based on the use of a heat-shrinkable Teflon tube is presented and successfully used for the continuous flow kinetic resolution of a chiral amine, 4-bromo-α-methylbenzylamine. The porous structure of the supports ensures effective mass transfer and the reactor works in the plug flow regime without preferential flow paths. When immobilized in the monolith and used in the flow reactor, transaminases retain their activity and their enantioselectivity. The solid biocatalyst is also shown to be stable both on stream and during storage. These essential features pave the way to the successful development of an environmentally friendly process for chiral amines production.

Microbial composition across substrates in mangroves, particularly in the Middle East, remains unclear. This study characterized bacterial communities in sediment, water, Terebralia palustris snail guts, and plastic associated with Avicennia marina mangrove forests in two coastal lagoons in the Sea of Oman using 16S rDNA gene MiSeq sequencing. The genus Vibrio dominated all substrates except water, which featured unique genera Sunxiuqinia and Pseudomonas. There were significant differences in bacterial communities on different substrata, in particular plastic. Snail guts harbored the highest number of unique Operational Taxonomic Units (OTUs) in both lagoons. Plastic in the polluted Sawadi lagoon with low salinity harbored distinct genera like Vibrio, Aestuariibacter, Zunongwangia, and Jeotgalibacillus absent in Qurum lagoon with higher salinity and low pollution. Sawadi lagoon exhibited higher species diversity in sediment and plastic substrates, Qurum lagoon demonstrated lower overall species diversity. The PCA indicates that environmental factors like salinity, pH, and nutrient levels significantly influence bacterial community composition across substrates. Variations in organic matter and potential anthropogenic influences, particularly from plastics, further shape bacterial communities. This study highlights the complex microbial communities in mangrove ecosystems, emphasizing the importance of considering multiple substrates in mangrove microbial ecology studies.

Ship wave is of great interest for wave drag, coastal erosion and ship detection. In this paper, a highly-paralleled numerical scheme is proposed for simulating three-dimensional (3-D) nonlinear Kelvin ship waves effectively. First, a numerical model for nonlinear ship waves is established based on potential flow theory, boundary integral method and Jacobian-free Newton-Krylov (JFNK) method. In order to improve computational efficiency and reduce data storage of JFNK method, a banded preconditioner method is then developed by formulating the optimal bandwidth selection rule. After that, a Graphics Process Unit (GPU) based parallel computing framework is designed, and a GPU solver is developed by using Compute Unified Device Architecture (CUDA) language. Finally, numerical simulations of 3-D nonlinear ship waves under multiple scales are performed by using the GPU and CPU solvers. Simulation results show that the proposed GPU solver is more efficient than the CPU solver with the same accuracy. More than 66% GPU memory can be saved and the computational speed can be accelerated up to 20 times. Hence, the computation time for Kelvin ship waves simulation can be significantly reduced by applying the GPU parallel numerical scheme, which lays a solid foundation for practical ocean engineering.

The nature of the fracture and fragmentation process of concrete medium under blast loading is the transformation process of the medium from continuum to discontinuity, coupled with the significant rate correlation of concrete medium, its mechanical behavior presents a high degree of complexity. Problems such as grid distortion and even negative volume are often encountered in the finite element method and others when solving this problem, while the material point method can effectively avoid these problems. In addition, the widely used HJC concrete constitutive model does not take into account the segmented characteristics of the calculation function for dynamic increasing factor. Therefore, in this paper, firstly, the calculation function for dynamic increasing factor in the HJC concrete model is modified by SHPB experiment, and the improved HJC concrete model is proposed; secondly, the material point method simulation program is developed, and the improved HJC concrete model is embedded into the simulation program; finally, the simulation program is verified by numerical examples, and the results show that the developed simulation program can better simulate the fracture and fragmentation process of concrete medium under blast loading, especially the pulverization characteristics of the medium in the near zone of the load.

The calculation of echo intensity involved in the SAR image simulation is usually based on the electromagnetic formula or approximate formula derived under certain assumptions. However, the parameters used in these formulas are often difficult to obtain, and the formulas have errors with the actual situation. In this paper, a method of embedding deep neural network (DNN) into the simulation process based on ray tracing is proposed, so that the DNN model can be directly used to fit the calculation formula of echo intensity from real SAR images. Simulation results show that this method can obtain SAR images with high similarity.

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.

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.

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 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.

Polo-like kinase 1 (PLK1) plays a pivotal role in cell division regulation and emerges as a promising therapeutic target for cancer treatment. Consequently, the development of small-molecule inhibitors targeting PLK1 has become a focal point in contemporary research. The adenosine triphosphate (ATP)-binding site and the polo-box domain in PLK1 present crucial interaction sites for these inhibitors, aiming to disrupt the protein's function. However, designing potent and selective small-molecule inhibitors can be challenging, requiring a deep understanding of protein-ligand interaction mechanisms at these binding sites. In this context, our study leverages the fragment molecular orbital (FMO) method to explore these site-specific interactions in-depth. Through the FMO approach, we used the FMO method to elucidate the molecular mechanisms of small-molecule drug binding to these sites to design PLK1 inhibitors that are both potent and selective. Our investigation further entailed a comparative analysis of various PLK1 inhibitors, each characterized by distinct structural attributes. This comparison enhanced our understanding of the structure-activity relationships of these inhibitors, underscoring the efficacy of the FMO method in identifying critical binding features and predicting binding modes for small-molecule ligands. Furthermore, Our research spotlighted "hot spot" residues instrumental for selective and robust PLK1 binding. Our findings offer profound insights, priming the rational design of innovative potential PLK1 inhibitors with significant implications for developing anticancer therapeutics.

This study addresses the problem of accurately predicting azimuth and elevation angles of signals impinging on an antenna array employing Machine Learning (ML). Using the information obtained at a receiving system when a transmitter’s signal hits it, a Decision Tree (DT) model is trained to estimate azimuth and elevation angles simultaneously. Simulation results demonstrate the robustness of the proposed DT-based method, showcasing its ability to predict the Direction of Arrival (DOA) in diverse conditions beyond the ones present in the training dataset, i.e., the results display the model’s generalization capability. Additionally, the comparative analysis reveals that DT-based DOA estimation outperforms the state-of-the-art MUltiple SIgnal Classification (MUSIC) algorithm, establishing DTs as competitive alternatives for DOA estimation in signal reception systems.

Alzheimer's disease (AD) remains a significant challenge in the field of neurodegenerative disor-ders, even nearly a century after its discovery, due to the elusive nature of its causes. The develop-ment of drugs that target multiple aspects of the disease has emerged as a promising strategy to address the complexities of AD and related conditions. The immune system's role, particularly in AD, has gained considerable interest, with nanobodies representing a new frontier in biomedical research. Advances in targeting antibodies against amyloid-β (Aβ) and using messenger RNA for genetic translation have revolutionized the production of antibodies and drug development, open-ing new possibilities for treatment. Despite these advancements, conventional treatments for AD, such as Cognex, Exelon, Razadyne, and Aricept, often have limited long-term effectiveness, under-scoring the need for innovative solutions. This necessity has led to the incorporating of advanced technologies like artificial intelligence and machine learning into the drug discovery process for neurodegenerative diseases. These technologies help identify therapeutic targets and optimize lead compounds, offering a more effective approach to addressing the challenges of AD and similar conditions.

Cassava brown streak disease (CBSD) threatens cassava production in sub-Saharan Africa despite the availability of resistant varieties since extreme environmental factors weakens plant defenses hence reduce CBSD resistance. This study examined the inheritance of CBSD in cassava populations, assessed genetic variability and identified superior sources of resistance through F1, S1 and half-sib offspring of populations derived from resistant sources. The offsprings underwent field evaluation at two distinct sites from 2019 to 2021, and the symptoms free genotypes were analyzed using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Resistance to CBSD was categorized as most resistant, resistant, most tolerant and tolerant based on symptoms and virus titer. The findings of the study indicate that the resistance to Cassava Brown Streak Disease (CBSD) is highly influenced by genotypes, F1/S1 types, and environmental conditions. The analysis of combining abilities revealed significant general combining abilities (GCA) for CBSD, cassava mosaic disease (CMD), and traits associated with yield. The heritability estimates for resistance to CBSD varied between 43.4% to 63.2% for foliar symptoms and 14.6% to 57.9% for root necrosis across locations. The inheritance pattern involved a combination of additive and recessive genes and selfed (S1) populations displayed stronger and effective resistance to the disease. There was a high prevalence of cassava brown streak virus (CBSV) and a low prevalence of Ugandan cassava brown streak virus (UCBSV). Four genotypes were identified to be highly resistant to Cassava Brown Streak Disease (CBSD) that could be used as key sources of resistance to CBSD.

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.

The production of biodiesel through transesterification routes generates large amounts of glycerol, approximately 10 m3 for every 90 m3 of the biodiesel produced. Taking into account this scenario, the valorization of glycerol using chemical routes that could be operated in biodiesel industry constitutes a promising approach to achieve added-value products. An interesting option is the production of ethers, which can be used as fuel additives in diesel engines to improve the combustion efficiency, reducing soot emission and increasing cetane index. In this study, a purification route was applied to crude glycerol and its valorization by etherification was evaluated. The glycerol contents of purified samples were above 98% wt. The purified and commercial glycerol was used to obtain ethers. Etherification reactions were carried out with different alcohols (ethanol, isopropanol and 3-methyl-1-butanol) into a batch reactor, using small amount of Amberlyst 15 as a catalyst, at autogenous pressure and solvent-free conditions. The glycerol conversion, selectivity and yield to ethers were evaluated. A glycerol conversion of 97% wt. with selectivity of 80% to monoether was obtained when using ethanol. For isopropanol, the glycerol conversion was up to 95% (76% of monoether and 22% of diether). However, the selectivity to ethers for 3-methyl-1-butanol was negligible (&lt;3% wt.). A process simulation for purification and etherification steps integrated with a biodiesel production was assessed in terms of productivity and energy consumption, considering different scenarios of glycerol/alcohol molar ratios.