Nonlinear Quadratic Model Research Articles

Longitudinal changes in DNA methylation associated with clozapine use in treatment-resistant schizophrenia from two international cohorts

The second-generation antipsychotic clozapine is used as a medication for treatment-resistant schizophrenia. It has previously been associated with epigenetic changes in pre-clinical rodent models and cross-sectional studies of treatment-resistant schizophrenia. Cross-sectional studies are susceptible to confounding, however, and cannot disentangle the effects of diagnosis and medication. We therefore profiled DNA methylation in sequential blood samples (n = 126) from two independent cohorts of patients (n = 38) with treatment-resistant schizophrenia spectrum disorders who commenced clozapine after study enrolment and were followed up for up to six months. We identified significant non-linear changes in cell-type proportion estimates derived from DNA methylation data - specifically B-cells - associated with time on clozapine. Mixed effects regression models were used to identify changes in DNA methylation at specific sites associated with time on clozapine, identifying 37 differentially methylated positions (DMPs) (p < 5 × 10-5) in a linear model and 90 DMPs in a non-linear quadratic model. We compared these results to data from our previous epigenome-wide association study (EWAS) meta-analysis of psychosis, finding evidence that many previously identified DMPs associated with schizophrenia and treatment-resistant schizophrenia might reflect exposure to clozapine. In conclusion, our results indicate that clozapine exposure is associated with changes in DNA methylation and cellular composition. Our study shows that medication effects might confound many case-control studies of neuropsychiatric disorders performed in blood.

Application of Response Surface Methodology for concentration of fluorosilicic acid by extraction technique with benzyl alcohol as extractant

As a kind of alternative of natural fluorinated minerals and raw material for producing anhydrous hydrogen fluoride, fluorosilicic acid has attracted more and more attention. In order to raise its utilization rate, dilute fluorosilicic acid solution coming from chemical enterprises needs to be concentrated. The extraction technology with benzyl alcohol as extraction agent was used to concentrating fluorosilicic acid aqueous solution. In order to determine the optimizing operation conditions of the extracting process, single - factor experiments were carried out to confirm the significant affecting factors and their operating range. Then the Response Surface Methodology (RSM) was conducted to accomplish regression of a nonlinear quadratic polynomial model to the experimental data and statistical analysis. Based on these studies, the optimal technical parameters of extracting process are acquired by optimization of the model using the Design-Expert 13 software. The statistical analysis for the fitting response surface quadratic equation model indicated that the model was reliable and accurate with very low p-values (<0.0001), the predicted values with the model equation had remarkable consistency in experimental data. By a great number of optimizations carried out with the Design Expert 13 software based on the fitting model equation, the optimal extractive processing conditions for concentrating fluorosilicic acid aqueous solution were obtained: the phase ratio 7, the extraction time 120.11 min and the extraction temperature 39.70 °C. The optimal concentration of fluorosilicic acid is 26.68 %. In order to increase the concentration of fluorosilicic acid, three-stage cross-current extraction for dilute fluorosilicic acid solution was carried out at the optimizing extracting conditions, 17.43 wt% fluorosilicic acid solution can be concentrated up to 37.46 wt%. The extractant-benzyl alcohol can be recovered with vacuum distillation and recovery rate reached up to 98 %.

Determination of Motorcycle Equivalent Unit and Road Capacity: A Case Study of Selected Road Sections of Kathmandu Valley

The research focused on road congestion in Kathmandu Valley, Nepal, caused by the prevalence of small motorized vehicles, especially motorcycles. The objective of the study was to quantify the impact of different vehicle classes on congestion by calculating Motorcycle Equivalent Units (MEU) and determining roadway capacity using speed and effective space parameters. The field data collected over two locations in Kathmandu Valley were analyzed using Speed Estimation from Video Data (SEV) software that revealed a strong correlation between vehicle speed and effective space, represented by a quadratic non-linear model. MEU values were determined for different vehicle classes, and fundamental speed-flow-density relationships were used to calculate roadway capacity. Vehicles like motorcycles, standard cars, big cars, utility, minibusses, buses, light commercial vehicles, two/three-axle trucks, and multi-axle trucks had MEU values of 1, 3.32, 4.91, 4.65, 9.22, 12.22, 6.72, 13.57 and 18.04 respectively. The study indicated peak capacities during the evening hours on specific road sections. For instance, the Gatthaghar-Kaushaltar and Balkumari-Gwarko sections reached their maximum capacities at 12,335 and 20,589 (motorcycles per hour per direction), respectively. The study emphasized the significant influence of speed on effective space and roadway capacity, suggesting further exploration of additional factors like driver characteristics, gender, age, income, road geometry, and level of service using MEU, along with the potential for developing a motorcycle simulation model in Kathmandu valley.

Residue Management and Nutrient Stoichiometry Control Greenhouse Gas and Global Warming Potential Responses in Alfisols

Although crop residue returns are extensively practiced in agriculture, large uncertainties remain about greenhouse gas (GHG) emissions and global warming potential (GWP) responses to residue return (RR) rates under different residue placements and nutrient supplements. We conducted a laboratory mesocosm experiment in Alfisol in central India to investigate the responses of soil GHG emissions (CO2, N2O, and CH4) and the global warming potential to four wheat RR rates (R0: no residue; R5: 5 Mg/ha; R10: 10 Mg/ha; R15: 15 Mg/ha) and two placements (surface [Rsur] and incorporated [Rinc]) under three nutrient supplement levels (NSLs) (NS0: no nutrients, NS1: nutrients (N and P) added to balance the stoichiometry of C:N:P to achieve 30% humification in RR at 5 t/ha, NS2: 3 × NS1). The results demonstrated a significant (p &lt; 0.05) interaction effect of RR × NSL × residue placement on N2O emission. However, CH4 and GWP responses to the RR rate were independent of NSL. N2O fluxes ranged from −2.3 µg N2O-N kg−1 soil (R5 NS0 Rsur) to 43.8 µg N2O-N kg−1 soil (R10 NS2 Rinc). A non-linear quadratic model yielded the best fit for N2O emissions with RR rate (R2 ranging from 0.55 to 0.99) in all NSLs and residue placements. Co-applying wheat residue at 10 and 15 Mg/ha at NS1 reduced CH4 and N2O emissions (cf. R0 at NS1). However, increasing NSLs in NS2 reduced the nutrient stoichiometry to &lt; 12:1 (C:N) and &lt; 50:1 (C:P), which increased N2O emissions in all RR rates (cf. R0) across all residue placements. Averaged across nutrient levels and residue placements, the order of the effects of RR rates on CH4 emissions (µg C kg−1 soil) was R10 (5.5) &gt; R5 (3.8) &gt; R15 (2.6) &gt; R0 (1.6). Our results demonstrated a significant linear response of total GWP to RR rates R15 &gt; R10 &gt; R5 &gt; R0, ranging from 201.4 to 1563.6 mg CO2 eq kg−1 soil. In conclusion, quadratic/linear responses of GHGs to RR rates underscore the need to optimize RR rates with nutrient supplements and residue placement to reduce GHG emissions and GWP while ensuring optimal soil health and crop productivity.

Body surface area is a predictor of maturity status in school children and adolescents

BackgroundGenerally, Body surface area (BSA) changes significantly during growth and maturation. These increases portend a possible relationship between body size as determined by BSA with maturational status in children and adolescents.ObjectiveTo determine the relationship between maturity status (MS) obtained by non-invasive anthropometric methods and body surface area (BSA) in children and adolescents of both sexes in a regional population of Chile. Additionally, we sought to verify the type of linear or nonlinear relationship between MS and BSA in both sexes.MethodsA descriptive (cross-sectional) study was designed in 950 children and adolescents of both sexes (539 males and 411 females). The age range ranged from 6.0 to 17.9 years. Anthropometric measurements were evaluated: body weight, standing height, sitting height. MS was assessed by means of two non-invasive anthropometric techniques. Both techniques predict peak years of growth velocity (APHV) through a regression equation for each sex. BSA (m2) was estimated by means of the Haycock equation.ResultsThe R2 in the linear model is relatively lower (R2 = 0.80 to 0.89 in males and 0.74 to 0.66 in females) in relation to the nonlinear quadratic model (R2 = 0.81 in males and 0.76 to 0.69). The quadratic nonlinear quadratic model reflected an adequate fit (RMSE) for the data set, being in men (RMSE = 1.080 and 1.125), while in women (RMSE = 1.779 and 1.479).ConclusionBSA is positively associated with MS determined by two non-invasive methods in Chilean children and adolescents: The nonlinear quadratic model was a better fit to the data distribution. The results suggest the use of BSA as a possible predictor of maturity status in Chilean youth.

Exploring an Optimal Model of Cognitive, Behavioral, and Affective Recreation Specialization based on the Experience and Goods of Scuba Divers

PURPOSE Recreation specialization theory, which is characterized by a unique development process and progress, has been found to have varied pathways that develop in different patterns based on each dimension of recreation specialization. This study aimed to investigate how each sub-dimension of specialization changes as the degrees of experiential participation (frequency, period, and intensity of participation) and goods investment (expenditure) of the scuba divers increase. METHODS In the summer of 2021 (May-August), a purposive sampling method was used to collect samples from young scuba divers, and 278 copies of valid data were used for the final analysis. Frequency analysis, descriptive statistical analysis, confirmatory factor analysis, reliability analysis, correlation analysis, curve estimation analysis, and hierarchical regression analysis were performed using SPSS 24.0 and AMOS 24.0 ver. RESULTS The findings were as follows. First, the quadratic nonlinear model was identified as the optimal model for the relationships between the scuba divers’ participation intensity and cognitive, behavioral, and affective recreation specializations based on experience. Second, the cubic nonlinear model was identified as the optimal model for the relationships between the participation period, frequency of participation, and cognitive, behavioral, and affective recreation specializations of scuba divers. Third, the cubic nonlinear model was identified as the optimal model for the relationships between the expenditure cost of scuba divers and the cognitive, behavioral, and affective recreation specializations in the center of the goods. As the period, frequency, and expenditure of scuba diving participants increased, the relevant cognitive, behavioral, and affective specializations did not progress in a linear manner; instead, they went through an intermediate maintenance stage and developed to a higher level. CONCLUSIONS Progressive and meaningful consumption of experiences and goods further promotes recreation specialization. Any future follow-up study should identify a trade-off point in the development of the recreation specialization in a step by step manner.

Long-run scarring effects of meltdowns in a small-scale nonlinear quadratic model

We build a small-scale nonlinear quadratic (NLQ) model in which credit feedback and regime switches in the output gap affect the adjustment path of the economy towards a steady state. The central bank solves a finite-horizon decision problem where the policy rate also can be zero or negative. We estimate this model by nonlinear seemingly unrelated regression method (NLSUR) and using the parameters to explore policy scenarios. The latter projects long-run dynamics after a large demand contraction leading to scarring effects on the economy. We point out three main results. First, while scars are dominant when the central bank follows a standard Taylor rule, unconventional monetary policy (UMP) – such as Quantitative Easing – mitigates the output decline in both the short and the long run. Second, a zero natural interest rate curtails the central bank’s ability to adjust the economy and mitigate scars. Third, financial constraints leave the deepest scars even if UMP is active.

Relationship between body mass index and physical fitness of children and adolescents in Xinjiang, China: a cross-sectional study

BackgroundXinjiang is an economically underdeveloped area in China, but the obesity rate of children and adolescents is increasing year by year. Physical fitness and body mass index (BMI) are very important factors for healthy development, whereas few studies focus on the relationship between them in this region. This study aimed to explore the relationship between physical fitness and BMI of children and adolescents aged 7 to 18 in Xinjiang.MethodA total of 17,356 children and adolescents aged 7–18 years were involved. BMI was divided into five levels by percentiles, from very low to very high. Physical fitness was evaluated by five indicators: grip strength, standing long jump, sit-and-reach, 50 m dash, and endurance running. Single-factor analysis of variance was used to compare the Z-scores of the five physical fitness indicators among different BMI levels for the four age groups by gender. A nonlinear quadratic regression model was used to evaluate the relationship between BMI and each indicator in the four age groups.ResultThere is a significant correlation between the five health-related indicators (grip strength, standing long jump, sit and reach, 50 m dash, endurance run) at two age groups (13-15 yrs., 16-18 yrs) of children and adolescents in Xinjiang, China. The range of the Pearson coefficient is 0.048 ~ 0.744. For the other two age groups (7-9 yrs., 10-12 yrs.,) significant correlations are found only in some indicators, and the Pearson coefficient ranges from 0.002 to 0.589. The relationship between BMI and physical fitness presents an U-shaped or inverted U-shaped curve in most age groups(R2 ranges from − 0.001 to 0.182. Children and adolescents with normal BMI score higher on physical fitness tests, and boys (R2 ranges from − 0.001 to 0.182) are more pronounced than girls (R2 ranges from 0.001 to 0.031).ConclusionChildren and adolescents with a BMI above or below the normal ranges have lower physical fitness than those with normal BMI. BMI and physical fitness have an U-shaped or inverted U-shaped curve relationship, and the impact is more evident in boys than girls. Targeted actions such as improving the quality of physical education classes, advocating students to keep a balanced diet and physical exercise should be taken designedly.

Laser Welding Multimodel Quality Forecast Method Based on Dynamic Geometric Features of the Molten Pool.

Laser welding quality forecast is highly significant during the laser manufacturing process. However, extracting the dynamic characteristics of the molten pool in the short laser welding process makes predicting of the welding quality in real time difficult. Accordingly, this study proposes a multimodel quality forecast (MMQF) method based on dynamic geometric features of molten pool to forecast the welding quality in real time. For extraction of geometric features of molten pool, an improved fully convolutional neural network is proposed to segment the collected dynamic molten pool images during the entire welding process. In addition, several dynamic geometric features of the molten pool are extracted by using the minimum enclosed rectangle algorithm with an evaluation of the performance by several statistical indexes. With regard to forecasting the welding quality, a nonlinear quadratic kernel logistic regression model is proposed by mapping the linear inseparable features to the high dimensional space. Experimental results show that the MMQF method can make an effective and stable forecast of welding quality. It performs well under small data and can satisfy the requirement of real-time forecast.

Application of Parking Retribution Income Forecasting at PT Bumi Daya Plaza Bengkulu City Using Trend Method Non Linear Squadratic Model

The calculation of parking retribution income which has been managed by PT. Bumi Daya Plaza Bengkulu City used Microsoft Excel application. Data processing is only limited to revenue recapitulation. Then a forecasting application will be made that will be used to forecast future income, for the benefit of the company by using Trend Method Non-Linear Quadratic Model. Trend Method NonLinear Quadratic Model is a trend in which the value of the dependent variable increases or decreases linearly or a parabola occurs when the data is made a scatter plot (the relationship between the dependent and independent variables is quadratic) tend to be in one direction (up or down), such trends generally include movements lasting about 10 periods or more. This motion reflects the nature of continuity or a continuous state from time to time over a certain period of time, because of the nature of this continuity, the trend is considered a stable motion so that in interpreting it a mathematical model can be used, according to the circumstances and the time series data itself. Trend can be a straight line (regression/linear trend) or non-straight (regression/non-linear trend). The results obtained are derived from the processing of income for the last 12 months using Trend Method Non-Linear Quadratic Model. With data that has been processed from January 2020 to December 2020, it produces income forecasting at the T001 parking point of Rp. 467,272 and at the T002 parking point of Rp. 15,814,697 in January 2021. By using Trend Method Non-Linear Quadratic Model can determine forecasting/ prediction of parking retribution income in the future using preexisting data.

Effect of ultrasonic welding process parameters on peel strength of membranes for tents

Ultrasonic welding is a universal, clean, and secure alternative joining method. Alternative joining technologies are used increasingly to fulfill specific functional requirements of the seam, such as fluid impermeability to achieve positive bonding during the assembly of technical textiles. In this research, the effect of important ultrasonic welding parameters on peel strength and weld seam thickness was investigated for flexible and lightweight textile material, which is a valuable innovative hybrid textile for technical applications like architectural, construction, and protective textiles. Three main welding parameters with three different levels were selected based on the preliminary test results of 6 and 12 mm welding widths, and a superimposed type of seam was applied. Light scanning microscopic images were used to examine the effective weld locations and their morphology at the joining interface. The parametric influence of ultrasonic welding technique on-seam quality and their tendencies in the relationship were analyzed. Optimized peel strength yielding parametric levels were also assessed numerically. The result shows that the optimal peel strength value was obtained at a welding speed of 2.318 m/min, power of 119.382 W, and pressure force of 349.729 N for a 12 mm welding width. The weld seam thickness had an inverse relationship with the peel strength, and a higher amount of thickness was reduced to 12 mm welding width than 6 mm. Microscopic cross-sectional image of weld seam indicated that a compressed yarn between the coating material at higher welding power and pressure force in lower welding speed. A nonlinear quadratic numerical model was developed to predict the peel strength, and their results were close to the regressed diagonal line against the actual points. The statistical analysis was carried out to show the significant effect of process parameters on peel strength, whereby the obtained results were statistically significant.

Optical coherence tomography angiography vessel density parameters in primary open-angle glaucoma

BackgroundMany studies suggest the existence of an alteration of the retinal hemoperfusion in primary open-angle glaucoma. The OCT-A is a novel technique that allows to provide information on retinal microcirculation in a non-invasive way, thus it represents a possible imaging target for the early diagnosis and follow-up of glaucoma. The aim of our work is to evaluate the contribution of vascular parameters provided by OCT-A and their diagnostic abilities in the different stages of primary open-angle glaucoma. MethodThis is a prospective cross-sectional study involving 200 eyes of control subjects and 250 eyes of glaucomatous subjects divided into early glaucoma, moderate glaucoma and advanced glaucoma subgroups. They were assessed for MD, LV by visual field, RNFL and GCC thickness by SS-OCT papillary and macular vascular densities by SS-OCT A. ResultsOCT-A vessel densities determined in the optic nerve head, in the peripapillary and in the macular regions were significantly lower in glaucomatous eyes. Among the vascular parameters studied the whole image vascular density showed the best diagnostic ability in the discrimination between glaucomatous eyes and healthy eyes with an AUC of 0.949. Nevertheless, the diagnostic ability of vascular parameters remains lower than of the structural parameters RNFL (AUC: 0.981). A significant correlation was found between structural, functional and vascular parameters with r < 0.05. The quadratic non-linear model defines better the relationship between structural, vascular and functional damage in glaucoma. ConclusionThe OCT-A plays an important role in the early diagnosis and follow-up of PAOG. It also contributes to the understanding of some aspects of the vascular role in glaucoma.

Association between body mass index and blood pressure levels across socio-demographic groups and geographical settings: analysis of pooled data in Peru.

BackgroundUnderstanding the relationship between BMI and blood pressure requires assessing whether this association is similar or differs across population groups. This study aimed to assess the association between body mass index (BMI) and blood pressure levels, and how these associations vary between socioeconomic groups and geographical settings.MethodsData from the National Demographic Health Survey of Peru from 2014 to 2019 was analyzed considering the complex survey design. The outcomes were levels of systolic (SBP) and diastolic blood pressure (DBP), and the exposure was BMI. Exposure and outcomes were fitted as continuous variables in a non-linear quadratic regression model. We explored effect modification by six socioeconomic and geographical variables (sex, age, education level, socioeconomic position, study area, and altitude), fitting an interaction term between each of these variables and BMI.ResultsData from 159, 940 subjects, mean age 44.4 (SD: 17.1), 54.6% females, was analyzed. A third (34.0%) of individuals had ≥12 years of education, 24.7% were from rural areas, and 23.7% lived in areas located over 2,500 m above sea level. In the overall sample mean BMI was 27.1 (SD: 4.6) kg/m2, and mean SBP and DBP were 122.5 (SD: 17.2) and 72.3 (SD: 9.8) mmHg, respectively. In the multivariable models, greater BMI levels were associated with higher SBP (p-value < 0.001) and DBP (p-value < 0.001). There was strong evidence that sex, age, education level, and altitude were effect modifiers of the association between BMI and both SBP and DBP. In addition to these socio-demographic variables, socioeconomic position and study area were also effect modifiers of the association between BMI and DBP, but not SBP.ConclusionsThe association between BMI and levels of blood pressure is not uniform on a range of socio-demographic and geographical population groups. This characterization can inform the understanding of the epidemiology and rise of blood pressure in a diversity of low-resource settings.

Nonlinear vibrations of a rotor on nonlinear tilting-pad-journal-bearings

In this paper, the coupled equations of nonlinear vibrations of a rigid two-dimensional rotor supported on tilting-pad-journal-bearing under harmonic excitation have been studied using second-order multiple scales method. By considering a nonlinear quadratic model for tilting-pad-journal-bearings, the governing coupled nonlinear differential equations of motion are presented. The frequency response function of the system, the effect of excitation force on the response, and stability of the system are discussed in different operating conditions using the method of multiple scales and validated with a numerical method. The results show that the system may have hardening or softening behavior under different working conditions because of the different nonlinear characteristics of the system. It is shown that the solution may be multivalued depending on initial conditions; also, jump phenomena can be observed.

Estimation of Tobacco Leaf Area by a Non-destructive Method

The leaf area index (AFI) is an important variable when evaluating the growth, development and possible productivity of a crop. The objective of this article was to determine mathematical models that allow estimating the leaf area of tobacco from measurements of dimensions of length and width of tobacco leaves. The experimental design used was in blocks with four replications and two planting times. The treatments consisted of five commercial cultivars of Virginia type tobacco and Burley type. Of which the leaves were detached from the stem, and these leaves were fractionated in limbo and petiole. Its leaves were 10 models were obtained to estimate the leaf area of tobacco. All the models presented a significant test to estimate the leaf area. The power and quadratic models presented values of determination coefficients higher than linear models. It had the best results with the nonlinear power and quadratic model, using the squared width multiplied by length. Therefore, the measurements of the leaf area of tobacco can be estimated from potential, linear and quadratic equations with good precision. The models that use linear squared width measurements multiplied by leaf limbo length satisfactorily estimate the leaf area of tobacco.

Unconventional monetary policy in a nonlinear quadratic model

Abstract After the financial market meltdown and the Great Recession of the years 2007–9, the financial market-macro link has become an important issue in monetary policy modeling. We develop a dynamic model that contains a nonlinear Phillips curve, a dynamic output equation, and a nonlinear credit flow equation – capturing the importance of credit cycles, risk premia, and credit spreads. Our Nonlinear Quadratic Model (NLQ) model has three dynamic state equations and a quadratic objective function. It can be used to evaluate the response of central banks to the Great Recession in moving from conventional to unconventional monetary policy. We solve the model with a new numerical procedure using estimated parameters for the euro area. We conduct simulations to explore the (de)stabilizing effects of the nonlinearities in the model. We demonstrate that credit flows, risk premia, and credit spreads play an important role as an amplification mechanism and in affecting the transmission of monetary policy. We thereby highlight the importance of the natural rate of interest as an anchor for a central bank target and the weight it places on the credit flows for the effectiveness of unconventional monetary policy. Our model is similar in structure compared to larger scale macro-econometric models which many central banks employ.

Prediction Model of Minimum Void Ratio for Various Sizes/Shapes of Sandy Binary Mixture

The minimum void ratio is a fundamental physical index for evaluating particle properties in soil mechanics, ceramic processing, and concrete mixes. Previous research found that both particle size distribution and particle shape characteristics would affect minimum void ratio, while the current research generally uses a linear model to estimate the minimum void ratio of a binary mixture, ignoring quantitative effect of particle shape on the minimum void ratio. Based on a study of binary mixtures of natural sand from three different origins and iron particles of two different shapes, this paper analyzes the influence factors of the minimum void ratio, and a quadratic nonlinear model is proposed for estimating the minimum void ratio of binary mixture. The model contains only one undetermined coefficient, a, the value of which is correlated to the particle sphericity, particle size, and particle size ratio. A theoretical calculation formula for the coefficient a is proposed to quantitatively analyze the effects of these three factors on the size of the parameters. In the end, the model is used to estimate the minimum void ratios of sand and substitute particles from different producing areas; the average difference between the estimated values and the fitted values is about 2.03%, suggesting that the estimated values of the model fit well with the measured data.

Biomarker profiles of Alzheimer's disease and dynamic of the association between cerebrospinal fluid levels of β-amyloid peptide and tau.

ObjectiveTo investigate the relationship between cerebrospinal fluid (CSF) β-amyloid peptide (Aβ42) and CSF Tau in a large population of patients referred to memory clinics for investigation of cognitive dysfunction.MethodsWe analyzed Alzheimer’s disease (AD) biomarkers in CSF taken from 3565 patients referred to 18 French memory clinics. Patients were classified into four profiles according to levels of CSF biomarkers (A: amyloidosis, N: neurodegeneration). The association between CSF Tau and CSF Aβ42 were analyzed using general linear regression models, in the overall population and stratified by biomarkers profiles. We compared linear and quadratic models using Akaike information criterion. We also assessed change in biomarker profiles in a subset of patients who had 2 assessments of biomarkers.ResultsCSF Tau was negatively associated with CSF Aβ42 in the overall population, following a non-linear quadratic model. However, the nature of this association was different in the 4 profiles: positive association in A-N- profile, negative association in A-N+ and A+N+ profiles, lack of association in A+N- patients. When considering patients with longitudinal data on profiles, 36% of those initially classified as A-N+ evolved to an A+N+ profile.ConclusionsThe nature of the association between CSF Aβ42 and CFS Tau depends on the A/N profiles of patients. These results suggest an increase in CSF Aβ42 early in the disease before its decline while tau pathology progresses, this pattern is particularly observed in non-APOE4 subjects. This phenomenon may explain why some patients with neurodegeneration only markers convert to an AD profile (A+N+) over time.

Nonlinear Credit Dynamics, Regime Switches in the Output Gap and Supervisory Shocks

Over the last two decades the intensity of credit standards’ tightening during economic contractions has exceeded their easing during expansions among euro area banks. This mechanism is fed by the boom-bust cycle of credit that, as much research has shown, is linked to financial instability with large effects on the real economy. We build a small scale nonlinear quadratic (NLQ) model to study how credit feedback can affect the overall adjustment path of the economy towards some steady state, when the central bank solves a finite-horizon decision problem where the policy rate is allowed to also be zero or negative. Then, we estimate local projections for a super- visory shock hitting banks’ credit standards and propose a new external instrument to identify its dynamic causal impact on the real and financial sector. We find that the regime dependence reveals important information to policy makers to implement macroprudential measures.

Performance Evaluation of African Breadfruit (Treculia Africana) Seed Dehuller

Abstract This paper reports the effect of the parboiling time on dehulled kernel out-turns (DKO) of African breadfruit seeds, and the most recent effort to upgrade an existing dehuller and its performance. Two common and readily available varieties – Treculia var. africana and var. inverse were used in the study. The seeds were parboiled for 0 (control), 2, 5, 8, 11 and 14 minutes and then dehulled. The result revealed that the parboiling time had a significant effect on the DKO of the two varieties of the seed. The DKO increased from 0 to 5 min of the treatment, after which it decreased considerably up to 14 min of the parboiling time. The obtained data were used to develop a non-linear quadratic regression model to predict the DKO as a function of the parboiling time. The performance evaluation of the breadfruit seeds dehuller revealed that it was significantly influenced by the variety.