Product Formula Research Articles

Residue removal and nitrogen cycling in burn and non‐burn Kentucky bluegrass seed production systems

AbstractKentucky bluegrass (Poa pratensis L.) postharvest residue in northern Idaho has historically been burned to maintain stand life and profitability. Alternatives to open field burning are necessary to reduce adverse impacts of burning on air quality and several have been proposed. However, limited information is available on the impact of residue management on residue removal and nitrogen cycling. In this study, the impact of residue management on residue nutrient dynamics and nitrogen availability was evaluated within replicated full load burn (FLB), bale then burn (BB), bale then mow then harrow (BMH), and system (SYST) (BMH year 1, BB year 2, and FLB year 3) plots in Kootenai County, ID from 2002 to 2006. Standing and non‐standing residues were measured immediately following grass seed harvest and periodically thereafter in each plot. Averaged across years, non‐standing residue (thatch) removal ranged from −13% in BMH to 61% in FLB, and removal of standing biomass ranged from 6% in BMH to 92% in FLB. The combined removal of both non‐standing and standing residue was 18% with BMH, 57% with SYST, 69% with BB, and 75% with FLB. Plant N uptake ranged from 53 kg N ha−1 in FLB in 2006 to 131 in SYST (BMH) in 2003 and nitrogen use efficiency, calculated using partial factor productivity formula, ranged from 0.6 to 5.8 kg bluegrass seed per kg N fertilizer. Mean NO3−–N concentrations from lysimeters 10‐cm deep were 14 mg NO3−–N L−1 in FLB, 12 mg NO3−–N L−1 in BB, and 6 mg NO3−–N L−1 in BMH treatments for years 2003–2006. Greater concentrations of NO3−–N in burn treatments were available for plant uptake or leaching compared to the BMH treatment. The data indicate that the efficacy of any residue management system will vary from year to year and impact seed production in the following year. Nitrogen availability varied across residue management systems, suggesting N fertilizer product, rate, and timing to optimize N use efficiency may also need to vary.

Thermo-Responsive Hyaluronan-Based Hydrogels Combined with Allogeneic Cytotherapeutics for the Treatment of Osteoarthritis.

Thermo-responsive hyaluronan-based hydrogels and FE002 human primary chondroprogenitor cell sources have both been previously proposed as modern therapeutic options for the management of osteoarthritis (OA). For the translational development of a potential orthopedic combination product based on both technologies, respective technical aspects required further optimization phases (e.g., hydrogel synthesis upscaling and sterilization, FE002 cytotherapeutic material stabilization). The first aim of the present study was to perform multi-step in vitro characterization of several combination product formulas throughout the established and the optimized manufacturing workflows, with a strong focus set on critical functional parameters. The second aim of the present study was to assess the applicability and the efficacy of the considered combination product prototypes in a rodent model of knee OA. Specific characterization results (i.e., spectral analysis, rheology, tribology, injectability, degradation assays, in vitro biocompatibility) of hyaluronan-based hydrogels modified with sulfo-dibenzocyclooctyne-PEG4-amine linkers and poly(N-isopropylacrylamide) (HA-L-PNIPAM) containing lyophilized FE002 human chondroprogenitors confirmed the suitability of the considered combination product components. Specifically, significantly enhanced resistance toward oxidative and enzymatic degradation was shown in vitro for the studied injectable combination product prototypes. Furthermore, extensive multi-parametric (i.e., tomography, histology, scoring) in vivo investigation of the effects of FE002 cell-laden HA-L-PNIPAM hydrogels in a rodent model revealed no general or local iatrogenic adverse effects, whereas it did reveal some beneficial trends against the development of knee OA. Overall, the present study addressed key aspects of the preclinical development process for novel biologically-based orthopedic combination products and shall serve as a robust methodological basis for further translational investigation and clinical work.

Formula optimization and thermodynamic evolution of high-performance large-sized porcelain thin ceramic tiles mainly enhanced by contrivable multi-phases

Owing to the high expenses and numerous potential avenues for formula research in ceramic production, obtaining cost-effective and high-quality ceramic formulas for high-performance ceramics poses significant challenges. To address this issue, a flux formula optimization procedure is proposed to develop the predictive ceramic formula P18, which allows precise control of the Al/Si ratio and is compatible with standard manufacturing processes. This cost-effective method enables the visual examination of ceramics’ physical, mechanical and thermodynamic properties. It is found that sintering temperature plays a crucial role in phase and microstructure evolution by classical phenomenological kinetic theory. Moreover, the sintered sample P18 exhibits remarkable mechanical performance, with a strength of 96.82 ± 2.0 MPa and fracture toughness of 1.89 ± 0.02 MPa·m1/2. These outstanding properties can be attributed to the reinforcing effects of multiple phases, such as high-strength corundum and in situ mullite whiskers. The mechanical mechanisms of the resulting ceramic tiles include particle reinforcement, microcrack deflection, intergranular and transgranular fracture, and in situ mullite whisker bridge pull-out, which collectively contribute to increase energy consumption per unit length, thus reducing the risk of brittle fractures.

Characteristic Polynomials of the Weak Order on Classical and Affine Coxeter Groups

We find a simple product formula for the characteristic polynomial of the permutations with a fixed descent set under the weak order. As a corollary we obtain a simple product formula for the characteristic polynomial of alternating permutations. We generalize these results to Coxeter groups. We also find a formula for the generating function for the characteristic polynomials of classical Coxeter groups, which is then related to affine Coxeter groups.

Price calculation of wooden bariatric beds

Abstract In the field of interior and furniture, the pursuit of comfort has always been based on the anthropometric dimensions of the user. When optimizing the dimensions of the bed for the needs of today’s population, we start from the forecasted values of the relevant body dimensions, i.e. height and weight. Based on previous research, we can conclude that the anthropometric dimensions of the adult Slovak population after reaching the age of adulthood have increased statistically significantly by approx. 4.5–5% since the last measurements in 1987, from the point of view of the body growth process. In connection with the aforementioned findings, it is necessary for furniture companies producing bed furniture to adjust their calculation procedures for price formation depending on the needs of users, in order to forecast their financial situation. The goal of the work is to determine the cost increase for bariatric respondents, based on the determined dimensions of the wooden bed compared to a standard manufactured bed, and to determine the calculation formula for single-piece production. The results show that increasing the dimensions of the bed will increase the total costs by approximately 70%.

Two Formulas for F-Polynomials

Abstract We discuss a product formula for $F$-polynomials in cluster algebras and provide two proofs. One proof is inductive and uses only the mutation rule for $F$-polynomials. The other is based on the Fock–Goncharov decomposition of mutations. We conclude by expanding this product formula as a sum and illustrate applications. This expansion provides an explicit combinatorial computation of $F$-polynomials in a given seed that depends only on the $\textbf {c}$-vectors and $\textbf {g}$-vectors along a finite sequence of mutations from the initial seed to the given seed.

High-molecular-weight by-products of chlorine disinfection

Although drinking water chlorination has reduced the incidence of waterborne disease, the reactions of chlorine with organic matter can lead to the formation of >700 halogenated disinfection by-products (DBPs). Epidemiological studies have linked the consumption of chlorinated drinking water with bladder cancer. With studies indicating that the one- and two-carbon-atom DBPs of current interest account for only ~16% of disinfected water cytotoxicity, there is a need to identify toxicity drivers within the poorly characterized higher-molecular-weight (more than two carbon atoms) DBP fraction. In this Review, we outline the current knowledge regarding this fraction and discuss novel analytical approaches to characterizing the much wider variety of structures that it contains. We detail the products formed from the reactions of chlorine with different categories of precursor, including the characteristics of the elemental formulae of products identified by high-resolution mass spectrometry, the halogenated aromatic DBPs formed from precursors in pristine waters and the products derived from biopolymer-bound monomers in algal- or wastewater-impacted waters. Finally, we discuss the key challenges for research into this important, but until recently, mostly overlooked by-product fraction. Recent toxicological studies have indicated that the poorly characterized high-molecular-weight fraction of disinfection by-products may contribute more to toxicity than the carbon disinfection by-products of current research interest. This Review summarizes what is known about the high-molecular-weight fraction and suggests pathways for future research in this area.

Importance sampling for stochastic quantum simulations

Simulating many-body quantum systems is a promising task for quantum computers. However, the depth of most algorithms, such as product formulas, scales with the number of terms in the Hamiltonian, and can therefore be challenging to implement on near-term, as well as early fault-tolerant quantum devices. An efficient solution is given by the stochastic compilation protocol known as qDrift, which builds random product formulas by sampling from the Hamiltonian according to the coefficients. In this work, we unify the qDrift protocol with importance sampling, allowing us to sample from arbitrary probability distributions, while controlling both the bias, as well as the statistical fluctuations. We show that the simulation cost can be reduced while achieving the same accuracy, by considering the individual simulation cost during the sampling stage. Moreover, we incorporate recent work on composite channel and compute rigorous bounds on the bias and variance, showing how to choose the number of samples, experiments, and time steps for a given target accuracy. These results lead to a more efficient implementation of the qDrift protocol, both with and without the use of composite channels. Theoretical results are confirmed by numerical simulations performed on a lattice nuclear effective field theory.

State-dependent Trotter limits and their approximations

This paper gives sufficient conditions to conclude the validity of digital simulations involving the Trotter product formula for finite discretizations of continuous operators. Essentially, it depends on the state-dependent Trotter error, for which it establishes explicit bounds that are also of independent interest.

FORMULASI GEL HAND SANITIZER EKSTRAK DAUN PALIASA (Kleinhovia hospita Linn) DENGAN GELLING AGENT HPMC

Gel hand sanitizer is a novel product formula that can be utilized as a cost-effective and portable replacement for hand washing soap. One of the plants whose leaves can be used as a central component of hand sanitizer gel is the Paliasa plant (Kleinhovia hospita Linn). Staphylococcus and Escherichia coli resist the antimicrobial effects of alkaloids, tannins, and saponins. To create the hand sanitizer gel, three different concentrations of the HPMC gelling ingredient were used: 1%, 2%, and 3%. Variations in the amount of HPMC used in each formulation impact the gel's characteristics, particularly its viscosity, spreadability, and adherence. Following the cycle test, the three formulations' viscosity decreased, but their pH, spreadability, and stickiness increased. There was no significant difference between the stability test on day 0 and day 12 for pH, viscosity, spreadability, and gel adhesion, according to testing utilizing the paired sample T-test. > 0.05.

What’s new in the field of serum-based eye drops

Worldwide serum-based eye drops are successfully used in the treatment of the Dry Eye Syndrome (DES). Autologous serum eye drops (ASEDs) are most common but allogenic eye drops were introduced in many countries mostly because of the COVID-19 pandemic. Not all aspects of the product formula have however been worked out so far. Each medical entity involved in the preparation, packaging and distribution of the product performs according to its own procedures. Various actions have therefore been undertaken to standardize, harmonize and exchange the experience in this field. In 2022 the 5th edition of EDQM’s Guide to the quality and safety of tissues and cells for human application was issued. Within the EU4Health Programme a new group for Recommendations and Guidance Documents for the Management of Substances of Human Origin (SoHO) in Hospitals is being formed. International cooperation of serumbased product users lead to the establishment of working group events — Workshops on the Eye Drops of Human Origin (EDHO) and Serum eye drop manufacturer’s group. Despite the widespread use of serum-based eye drops all over the world, in almost none of the countries, EU included, are there strict legal regulations for handling the product. It is therefore necessary to come up with a universal definition of artificial tears therapy and to determine specific procedures for the product preparation.

Pengembangan Snack Bar Berbasis Tepung Talas (Colocasia esculenta) dan Tepung Kacang Hijau (Vigna radiata) dengan Penambahan Bubuk Kayu Manis (Cinnamomum)

Background: The prevalence of underweight adolescents according to Riskesdas 2018 is 16.8%, which means that it has not reached the target set by WHO, it is said to be normal if the prevalence is below 10%. The factor that causes the high prevalence of underweight in adolescents is an inappropriate diet. In adolescence, snack foods have a big contribution to the total daily caloric intake. This study aims to develop a snack bar product formula as a practical snack for energy content, proximate, and organoleptic quality. This study aims to develop a snack bar product formula as a practical snack for energy content, proximate, and organoleptic quality. Methods: The experimental research design with Completely Randomized Design (CRD) was carried out in three stages, they are (1) making taro flour, mung bean flour, and cinnamon powder, and (2) making snack bars with a ratio of taro flour: mung bean flour 75%:25%(F1), 65%:35%(F2), 55%:45%(F3), cinnamon powder for the three formulations are 1%, (3) snack bar testing consists of nutritional, energy, and organoleptic content tests. The data were analyzed descriptively for nutrient and energy content and the Kruskal Wallis test followed by the Mann-Whitney test for organoleptic analysis. Results: The results of the highest energy content showed an average of 526.36 kcal/100 g, carbohydrates 58.775 g, fat 36.04 g, and protein 7.825 g. The result of the overall organoleptic test that the panelists most favored was F3 (55% taro flour: 45% mung bean flour). Conclusion: There were differences in the calorie, carbohydrate, protein, and fat content of the three formulations, and the overall organoleptic test results were favored by the panelists.

Pengaruh Model Pembelajaran Problem Based Learning (PBL) terhadap Kemampuan Pemahaman Konsep Matematis Siswa Kelas XI SMA Swasta Kampus Nommensen Pematangsiantar

This study aims to determine whether there is an influence of the Problem Based Learning learning model on students' ability to understand mathematical concepts in Class XI of Private High School Nommensen Pematangsiantar Campus T.A 2022/2023. In this study there is a significant difference between the learning outcomes of students who use the Problem Based Learning learning model and conventional learning models. The population in this study were all students of class XI at the Nommensen Pematangsiantar Private High School, namely 64 people, and the samples in this study were two classes, namely class XI-PMIA as the experimental class and class XI-PIIS as the control class. The research instrument given to the sample is significant, because by using the moment product formula the lowest validity coefficient calculation results are obtained 0.598 (sufficient validity) and the highest validity coefficient is 0.870 (very high validity) so that each test item is valid, using the alpha formula for the test is obtained the results of the calculation of the test reliability coefficient were 0.781 and when compared with rtable with a significant level α = 0.05 and n = 32, it was obtained rtable = 0.361 it turned out that rcount > rtable then the instrument was reliable. This research was conducted on 64 students, the learning outcomes of students who used the Problem Based Learning learning model obtained an average of 64.438, variance of 41.197. The learning outcomes of students using conventional learning models obtained an average of 60.438, a variance of 39.729. From the results of the calculation of the hypothesis test, zcount > ztable is (2.515 > 1.960). Then it is concluded that H0 is rejected and Ha is accepted. This means that the Problem Based Learning learning model influences the ability to understand students' mathematical concepts.

Analysis on the Methods and Techniques of Sunscreen Enhancement

In recent years, sunscreen products have been the research focus in the field of daily chemicals. Sunscreen products with high sun protection factor (SPF), fresh skin feeling and high safety are the market hotspots of sunscreen products. This article systematically sorts out the key points of sunscreen synergistic technology from the aspects of sunscreen compound synergism, the influence of plant-derived active ingredients on sunscreen, the carrier modification of sunscreen microcapsules, the solid lipid particles and sunscreen product formulation system. This article explained the future development direction of sunscreen enhancement, hoping to provide scientific basis for the research and development of sunscreen product formula.

Mathematical modeling of experimental data in the design of formulas for dairy products

mathematical modeling methods. The author analyzed the problems in the field of food technology and concluded that mathematical modeling is used in the following areas: clarification of technological process modes, designing recipes and assessing the quality of finished products, as well as predicting the shelf life of new products when they are put into production. The use of dihydroquercetin as a drug that prevents the oxidation of milk fat in the design of dairy products is substantiated. Mathematical modeling was carried out on the basis of experimental and analytical material obtained in laboratory and production conditions. Based on the maximum value of the objective functions, the optimal normalized mixtures and the maximum allowable concentration of dihydroquercetin were selected. The analysis of the received mathematical dependences and models is carried out, the system of linear equations is made. Purpose: to study the effect of natural bioflavonoid antioxidant on the oxidative processes of milk fat and the viability of lactic acid cultures and their associations by mathematical modeling in order to use it in the technology of a new product; conduct an analysis of mathematical dependencies and models, compose a system of linear equations. Methods: the article uses the method of mathematical analysis and the matrix method. Results and their significance: a mathematical model was developed for the dependence of the viability of probiotic cultures on the mass fraction of dihydroquercetin when designing recipes for a creamy-protein curd product, a matrix of the chemical composition of dairy ingredients was presented, and a system of linear equations for basic recipes was compiled. In the course of the study, the spatial configurations of dihydroquercetin, as well as its effect on the oxidative processes of milk fat, were studied. Mathematical modeling of experimental data on the study of the effect of dihydroquercetin on the viability of microorganisms with probiotic properties was carried out. The normalization of the complex of obtained results on the study of the influence of the mass fraction of dihydroquercetin on the fermentation process was studied. Controlled factors characterizing the process of fermentation of model media with dihydroquercetin have been determined. A rationing of the dihydroquercetin complex of more than 0.50% was established; the target function decreases to its minimum value of 0.53 with a mass fraction of dihydroquercetin of 1.00%.

Solving Sturm–Liouville inverse problems by an orthogonalized enhanced boundary function method and a product formula for symmetric potential

We develop a fast convergence iterative method after transforming the Sturm–Liouville problem into the weak-form integral equations, and using sinusoidal functions as the testers as well as the bases of eigenfunction. Owing to the orthogonal property of these bases, we can obtain the expansion coefficients in closed-form. A new idea of orthogonalized and enhanced boundary function (OEBF) is introduced to compute eigenvalues. In the Sobolev space, we prove the closeness of the OEBF to the eigenfunction with their distance being reduced when the eigenvalue increases. Moreover, upon expressing the Rayleigh quotient in terms of OEBF, the unknown functions in the Sturm–Liouville operator can be recovered quickly, merely two boundary data of unknown functions and the first eigenvalue are sufficing. The OEBF is a promising method with a few iterations to obtain quite accurate estimations of the unknown potential and weight functions. Thanks to the symmetry property a symmetric matrix eigenvalue problem is derived to recover a symmetric potential. The characteristic equation endowing with a special coefficient matrix is decomposed into a product of two characteristic equations. The Newton iterative method is thus developed by relying on the product formula to reconstruct the unknown symmetric potential function with the aid of a few lower orders eigenvalues.

Effect of Low Nesquehonite Addition on the Hydration Product and Pore Structure of Reactive Magnesia Paste.

Reactive magnesia cement is considered an eco-efficient binder due to its low synthesis temperature and CO2 absorption properties. However, the hydration of pure MgO-H2O mixtures cannot produce strong Mg(OH)2 pastes. In this study, nesquehonite (Nes, MgCO3·3H2O) was added to the MgO-H2O system to improve its strength properties, and its hydration products and pore structure were analyzed. The experimental results showed that the hydration product changed from small plate-like Mg(OH)2 crystals to interlaced sheet-like crystals after the addition of a small amount of Nes. The porosity increased from 36.3% to 64.6%, and the total pore surface area increased from 4.6 to 118.5 m2/g. At the same time, most of the pores decreased in size from the micron scale to the nanometer scale, which indicated that Nes had a positive effect on improving the pore structure and enhancing the compressive strength. Combined with an X-ray diffractometer (XRD), a Fourier transform infrared spectrometer (FTIR), and a simultaneous thermal analyzer (TG/DSC), the hydration product of the sample after Nes addition could be described as xMgCO3·Mg(OH)2·yH2O. When Nes was added at 7.87 and 14.35 wt%, the x-values in the chemical formula of the hydration products were 0.025 and 0.048, respectively. These small x-values resulted in lattice and property parameters of the hydration products that were similar to those of Mg(OH)2.

A Product Formula for Homogeneous Characteristic Functions

A bounded linear operator T on a Hilbert space is said to be homogeneous if $$\varphi (T)$$ is unitarily equivalent to T for all $$\varphi $$ in the group Möb of bi-holomorphic automorphisms of the unit disc. A projective unitary representation $$\sigma $$ of Möb is said to be associated with an operator T if $$\varphi (T)= \sigma (\varphi )^* T \sigma (\varphi )$$ for all $$\varphi $$ in Möb. In this paper, we develop a Möbius equivariant version of the Sz.-Nagy–Foias model theory for completely non-unitary (cnu) contractions. As an application, we prove that if T is a cnu contraction with associated (projective unitary) representation $$\sigma $$ , then there is a unique projective unitary representation $${\hat{\sigma }}$$ , extending $$\sigma $$ , associated with the minimal unitary dilation of T. The representation $${\hat{\sigma }}$$ is given in terms of $$\sigma $$ by the formula $$\begin{aligned} {\hat{\sigma }} = (\pi \otimes D_1^+) \oplus \sigma \oplus (\pi _*\otimes D_1^-), \end{aligned}$$ where $$D_1^\pm $$ are two unitary representations (one holomorphic and the other anti-holomorphic) living on the Hardy space $$H^2({\mathbb {D}})$$ , and $$\pi , \pi _*$$ are representations of Möb living on the two defect spaces of T defined explicitly in terms of $$\sigma $$ . Moreover, a cnu contraction T has an associated representation if and only if its Sz.-Nagy–Foias characteristic function $$\theta _T$$ has the product form $$\theta _T(z) = \pi _*(\varphi _z)^* \theta _T(0) \pi (\varphi _z),$$ $$z\in {\mathbb {D}}$$ , where $$\varphi _z$$ is the involution in Möb mapping z to 0. We obtain a concrete realization of this product formula for a large subclass of homogeneous cnu contractions from the Cowen–Douglas class.

Optimal Quantum Dataset for Learning a Unitary Transformation

Unitary transformations formulate the time evolution of quantum states. How to learn a unitary transformation efficiently is a fundamental problem in quantum machine learning. The most natural and leading strategy is to train a quantum machine learning model based on a quantum dataset. Although the presence of more training data results in better models, using too much data reduces the efficiency of training. In this work, we solve the problem on the minimum size of sufficient quantum datasets for learning a unitary transformation exactly, which reveals the power and limitation of quantum data. First, we prove that the minimum size of a dataset with pure states is $2^n$ for learning an $n$-qubit unitary transformation. To fully explore the capability of quantum data, we introduce a practical quantum dataset consisting of $n+1$ elementary tensor product states that are sufficient for exact training. The main idea is to simplify the structure utilizing decoupling, which leads to an exponential improvement in the size of the datasets with pure states. Furthermore, we show that the size of the quantum dataset with mixed states can be reduced to a constant, which yields an optimal quantum dataset for learning a unitary. We showcase the applications of our results in oracle compiling and Hamiltonian simulation. Notably, to accurately simulate a 3-qubit one-dimensional nearest-neighbor Heisenberg model, our circuit only uses $96$ elementary quantum gates, which is significantly less than $4080$ gates in the circuit constructed by the Trotter-Suzuki product formula.

Close, but No Cigar

Close, but No Cigar