Genetic analysis of body weight and growth curve parameters in Muzaffarnagari sheep of India.

The objective of this study was to estimate genetic effects on parameters of the Brody and Richards growth curves using body weight records from birth to 12 months of age on 2287 Muzaffarnagari lamb for a period of 29 years (1976-2004). Estimated growth curve parameters were analysed using six univariate animal models, and genetic correlations among and between the parameters of each function and between parameters of the functions and observed birth and yearling weights were estimated using bivariate analyses. Significant environmental factors including birth year, sex, season, birth status and dam parity were included as fixed effects in all models. Likelihood ratio tests indicated that maternal genetic effects were significant only for birth weight (BW) and degree of maturity at birth (u0) for the Brody and Richards functions. For these traits, direct heritabilities were similar (0.21, 0.19 and 0.17, respectively), but the estimated maternal heritability for BW (0.18) was twice that of u0 for both functions. Heritabilites for yearling weight and asymptotic final body weights for the Brody and Richards functions were 0.28, 0.17 and 0.21, respectively. The remaining growth curve parameters were lowly heritable, ranging from zero for the predicted degree of maturity at the age of maximum growth rate for the Richards function to 0.08 for the maturing rate parameter of the Brody function. Genetic correlations between corresponding parameters for different growth functions exceeded 0.88. Our results showed that the Brody and Richards functions had similar genetic architecture, but the Richards function had no apparent advantages over the more easily interpreted Brody function. Failure to identify maternal genetic effects on maturing rate parameters suggested that both functions failed to identify potentially important maternal genetic effects. Therefore, there is no usefulness of estimated growth curve parameters in selection compared to the simple multi-trait genetic evaluations of individual body weights.

Modeling tumor growth using fractal calculus: Insights into tumor dynamics.

Important concepts like fractal calculus and fractal analysis, the sum of squared residuals, and Aikaike's information criterion must be thoroughly understood in order to correctly fit cancer-related data using the proposed models. The fractal growth models employed in this work are classified in three main categories: Sigmoidal growth models (Logistic, Gompertz, and Richards models), Power Law growth model, and Exponential growth models (Exponential and Exponential-Lineal models)". We fitted the data, computed the sum of squared residuals, and determined Aikaike's information criteria using Matlab and the web tool WebPlotDigitizer. In addition, the research investigates "double-size cancer" in the fractal temporal dimension with respect to various mathematical models.

Effects of intraoperative sodium oxybate infusion on post-operative sleep quality in patients undergoing gynecological laparoscopic surgery: A randomized clinical trial.

STUDY OBJECTIVE: Post-operative sleep quality is an important factor that influences post-operative recovery. Sodium oxybate has been used to treat sleep disturbances associated with various pathological conditions. However, whether intraoperative intravenous infusion of sodium oxybate improves post-operative sleep quality is unknown. This study aimed to examine the effects of sodium oxybate on the post-operative sleep quality of patients who underwent gynecological laparoscopic surgery. DESIGN: A single-center, prospective, two-arm, double-blinded randomized controlled trial. SETTING: The Shengjing Hospital of China Medical University in Liaoning, China. PATIENTS: We enrolled 180 adult patients (90 for each group) undergoing elective gynecological laparoscopic surgery, and 178 patients (89 for each group) were included in the final analysis. INTERVENTIONS: Patients were randomly allocated in a 1:1 ratio to receive either sodium oxybate (30 mg kg-1) or an equivalent volume of saline after intubation. The patients, anesthetists, and follow-up staff were blinded to group assignment. MEASUREMENTS: The primary outcome was sleep quality measured using the Richards-Campbell Sleep Questionnaire (RCSQ) on post-operative days (PODs) one and three. Secondary outcomes included post-operative pain measured using the visual analog scale, sleep quality at one and three months post-operatively measured using the Pittsburgh Sleep Quality Index, and factors associated with post-operative sleep quality. MAIN RESULTS: Analysis with generalized estimating equations showed that sodium oxybate significantly improved post-operative sleep quality, as represented by increased total RCSQ scores (mean difference (95% CI); 9 (2, 16), P = 0.010) over PODs one and three. There was no difference in post-operative pain between the two groups over PODs one and three or in post-operative sleep quality over one and three months post-operatively. Age, surgery type, start time of surgery, and use of sufentanil-based patient-controlled intravenous analgesia were significantly associated with post-operative sleep quality. CONCLUSIONS: Intraoperative sodium oxybate infusion improved post-operative sleep in patients who underwent gynecological laparoscopic surgery. TRIAL REGISTRATION: Chinese Clinical Trial Registry, Clinical trial number: ChiCTR2200061460.

A systematic review of estimation of growth curve in goats.

Growth is an economically important trait in animal production industry and is one of the subjects that can be justified mathematically. The literature recommends different non-linear model to estimate the growth of goats. The objective of this study was to systematically review the literature published on estimation of growth using non-linear models in goats. Databases such as Google Scholar, PubMed, ScienceDirect, and Web of Science were evaluated systematically using the combination of the following key terms: Non-linear growth curve models such as Brody, Richards, Gompertz, Von Bertalanffy, Logistic models. A total of 25 eligible articles were found published between 2008 and 2022 in Bangladesh, Brazil, China, Egypt, Germany, India, Indonesia, Iran, Pakistan, South Africa, Turkey, Tunisia, and Vietnam. The results showed that out of 25 articles, Gompertz growth curve model was the most used (n = 10), followed by Logistic (n = 8), then Brody growth curve model (n = 6). The findings further indicated that Janoscheck growth curve model was the least used model (n = 1) for estimation of growth in goats. One of the limitations is that some of the reviewed articles did not indicate the sex of the animals which make it difficult to draw the conclude for sexes. The systematic review concludes that Gompertz growth curve model is the most recommended for estimation of growth parameters of goats, followed by Logistic, and then Brody. Therefore, researchers should consider using these models when studying growth parameters of goats.

"Not by a Decree of Fate:" Ellen Richards, Euthenics, and the Environment in the Progressive Era.

In 1904, Ellen Richards introduced "euthenics." By 1912, Lewellys Barker, director of medicine and physician-in-chief at Johns Hopkins Hospital, would tell the New York Times that the "task of eugenics" and the "task of euthenics" was the "Task for the Nation." Alongside the emergence of hereditarian eugenics, where fate was firmly rooted in heredity, this article places euthenics into the same Progressive Era demands for the scientific management over environmental issues like life and labor, health and hygiene, sewage and sanitation. I argue that euthenics not only heralded women as leaders in the quest for what Richards and eugenicists termed "racial improvement," but also aimed to make reforms through environmental and educational changes rather than hereditary interventions. Seeking to recuperate the figure of Ellen Richards in the history of science, I place Richards and her euthenics more into the debate over eugenics rather than over the emergence of home economics. Building on the work of Donald Opitz, Staffan Bergwik, and Brigette Van Tiggelen, this article shows, first, how Richards' career threads the needle between the home and the laboratory as sites of science making, not as separate spheres but as overlapping realms, and helps recover how domestic concerns shaped the focus of the life sciences. Second, this article shows how euthenics shaped eugenics by looking at the writings of American eugenicists Charles Davenport, Paul Popenoe, and David Starr Jordan. Third, the article describes how euthenics took root in new academic departments of domestic science, home economics, and departments child welfare and family life in the 1920 and 1930s, most notably the department of euthenics at the Kansas State Agricultural College from 1926 and the Institute of Euthenics at Vassar College after 1923.

Hall Effect at the Focus of an Optical Vortex with Linear Polarization.

The tight focusing of an optical vortex with an integer topological charge (TC) and linear polarization was considered. We showed that the longitudinal components of the spin angular momentum (SAM) (it was equal to zero) and orbital angular momentum (OAM) (it was equal to the product of the beam power and the TC) vectors averaged over the beam cross-section were separately preserved during the beam propagation. This conservation led to the spin and orbital Hall effects. The spin Hall effect was expressed in the fact that the areas with different signs of the SAM longitudinal component were separated from each other. The orbital Hall effect was marked by the separation of the regions with different rotation directions of the transverse energy flow (clockwise and counterclockwise). There were only four such local regions near the optical axis for any TC. We showed that the total energy flux crossing the focus plane was less than the total beam power since part of the power propagated along the focus surface, while the other part crossed the focus plane in the opposite direction. We also showed that the longitudinal component of the angular momentum (AM) vector was not equal to the sum of the SAM and the OAM. Moreover, there was no summand SAM in the expression for the density of the AM. These quantities were independent of each other. The distributions of the AM and the SAM longitudinal components characterized the orbital and spin Hall effects at the focus, respectively.

Hospitalized Patients' Sleep Quality Compared Between Multioccupancy Rooms and Single-Patient Rooms.

OBJECTIVES: To evaluate patients' sleep quality in a former hospital with two-and four-bedded rooms compared to a new hospital that incorporated evidence-based design features, including exclusively single-patient rooms (SPRs). BACKGROUND: Hospitalized patients often report poor sleep quality due to both patient-related factors and hospital environmental factors. It is unclear if staying in an SPR in a hospital designed as a healing environment is associated with better sleep quality. METHODS: In a before-after study, sleep quality, duration, and efficiency over 72 hr were measured with a sleep diary, GENEActiv accelerometer, and the Richards-Campbell Sleep Questionnaire (RCSQ) with scores ranging from 0 to 100, with higher scores reflecting better sleep. Participants were either staying alone in the former hospital with two-and four-bedded rooms (Group 1), sharing a room with one to three fellow patients (Group 2), or staying alone in a newly designed hospital with 100% SPRs (Group 3). RESULTS: We included 17 patients in Group 1, 32 patients in Group 2, and 56 patients in Group 3. Univariable linear mixed model analysis, controlling for night number, revealed that the RCSQ total score was lowest in Group 2 compared to the other two groups. In the multivariable analysis, the RCSQ score was also the lowest in Group 2, with a significant effect from covariate "use of night medication." CONCLUSION: Self-reported sleep quality of hospitalized patients in a hospital with 100% SPRs designed as a healing environment was slightly better than that of patients staying in multioccupancy rooms with fellow patients.

A MATLAB toolbox to fit and forecast growth trajectories using phenomenological growth models: Application to epidemic outbreaks.

Background: Simple dynamic modeling tools can be useful for generating real-time short-term forecasts with quantified uncertainty of the trajectory of diverse growth processes unfolding in nature and society, including disease outbreaks. An easy-to-use and flexible toolbox for this purpose is lacking. Results: In this tutorial-based primer, we introduce and illustrate a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using phenomenological dynamic growth models based on ordinary differential equations. This toolbox is accessible to various audiences, including students training in time-series forecasting, dynamic growth modeling, parameter estimation, parameter uncertainty and identifiability, model comparison, performance metrics, and forecast evaluation, as well as researchers and policymakers who need to conduct short-term forecasts in real-time. The models included in the toolbox capture exponential and sub-exponential growth patterns that typically follow a rising pattern followed by a decline phase, a common feature of contagion processes. Models include the 2-parameter generalized-growth model, which has proved useful to characterize and forecast the ascending phase of epidemic outbreaks, and the Gompertz model as well as the 3-parameter generalized logistic-growth model and the Richards model, which have demonstrated competitive performance in forecasting single peak outbreaks.The toolbox provides a tutorial for forecasting time-series trajectories that include the full uncertainty distribution, derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance across different models, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score. Conclusions: We have developed the first comprehensive toolbox to characterize and forecast time-series data using simple phenomenological growth models. As a contagion process takes off, the tools presented in this tutorial can facilitate policymaking to guide the implementation of control strategies and assess the impact of interventions. The toolbox functionality is demonstrated through various examples, including a tutorial video, and is illustrated using weekly data on the monkeypox epidemic in the USA.

Combination of suitable planting density and nitrogen rate for high yield maize and their source-sink relationship in Northwest China.

BACKGROUND: Increasing crop yield per unit area by increasing planting density is essential to ensure food security. However, the optimal combination of planting density and nitrogen (N) application for high-yielding maize and its source-sink characteristics need to be more clearly understood. RESULTS: A 2-year field experiment was conducted combining three planting densities (D1: 70 000 plants ha-1 ; D2: 100 000 plants ha-1 ; D3: 130 000 plants ha-1 ) and three nitrogen rates (N1: 150 kg hm-2 ; N2: 350 kg hm-2 ; N3: 450 kg hm-2 ). The results showed that increasing planting density significantly increased leaf area index and grain yield but negatively affected ear traits. The Richards model was used to fit the dynamic changes of dry matter accumulation of maize under different treatments, and the fitting results were good. Increasing planting density increased population yield while limiting the development of individual plants, bringing the period of rapid dry matter accumulation to an early end and accelerating leaf senescence. An appropriate nitrogen rate could prolong the period of rapid accumulation of dry matter in maize, and increase the 100-kernel weight. Increasing planting density enhanced post-silking dry matter accumulation to a lesser extent, and the source-sink relationship of the maize population gradually developed from sink limitation to source limitation with increasing planting density. CONCLUSION: The decrease in yield due to the insufficient source strength to meet the sink demand at too high densities was the reason that limited further improvement of the optimal planting density. An appropriate nitrogen rate facilitated the realization of yield potential at high density. © 2023 Society of Chemical Industry.

Spin Hall Effect of Double-Index Cylindrical Vector Beams in a Tight Focus.

We investigate the spin angular momentum (SAM) of double-index cylindrical vector beams in tight focus. Such a set of beams is a generalization of the conventional cylindrical vector beams since the polarization order is different for the different transverse field components. Based on the Richards-Wolf theory, we obtain an expression for the SAM distribution and show that if the polarization orders are of different parity, then the spin Hall effect occurs in the tight focus, which is there are alternating areas with positive and negative spin angular momentum, despite linear polarization of the initial field. We also analyze the orbital angular momentum spectrum of all the components of the focused light field and determine the overwhelming angular harmonics. Neglecting the weak harmonics, we predict the SAM distribution and demonstrate the ability to generate the focal distribution where the areas with the positive and negative spin angular momentum reside on a ring and are alternating in pairs, or separated in different semicircles. Application areas of the obtained results are designing micromachines with optically driven elements.

The accuracy of simple, feasible alternatives to polysomnography for assessing sleep in intensive care: An observational study.

BACKGROUND: Sleep disturbance is common in intensive care patients. Understanding the accuracy of simple, feasible sleep measurement techniques is essential to informing their possible role in usual clinical care. OBJECTIVE: The aim of the study was to investigate whether sleep monitoring techniques such as actigraphy (ACTG), behavioural assessments, and patient surveys are comparable with polysomnography (PSG) in accurately reporting sleep quantity and quality among conscious, intensive care patients. METHODS: An observational study was conducted in 20 patients admitted to the intensive care unit (ICU) for a minimum duration of 24 h, who underwent concurrent sleep monitoring via PSG, ACTG, nursing-based observations, and self-reported assessment using the Richards-Campbell Sleep Questionnaire. RESULTS: The reported total sleep time (TST) for the 20 participants measured by PSG was 328.2 min (±106 min) compared with ACTG (362.4 min [±62.1 min]; mean difference = 34.22 min [±129 min]). Bland-Altman analysis indicated that PSG and ACTG demonstrated clinical agreement and did not perform differently across a number of sleep variables including TST, awakening, sleep-onset latency, and sleep efficiency. Nursing observations overestimated sleep duration compared to PSG TST (mean difference = 9.95 ± 136.3 min, p > 0.05), and patient-reported TST was underestimated compared to PSG TST (mean difference = -51.81 ± 144.1 7, p > 0.05). CONCLUSIONS: Amongst conscious patients treated in the ICU, sleep characteristics measured by ACTG were similar to those measured by PSG. ACTG may provide a clinically feasible and acceptable proxy approach to sleep monitoring in conscious ICU patients.

Richards's curve induced Banach space valued ordinary and fractional neural network approximation.

Here we perform the univariate quantitative approximation, ordinary and fractional, of Banach space valued continuous functions on a compact interval or all the real line by quasi-interpolation Banach space valued neural network operators. These approximations are derived by establishing Jackson type inequalities involving the modulus of continuity of the engaged function or its Banach space valued high order derivative or fractional derivatives. Our operators are defined by using a density function generated by the Richards curve, which is generalized logistic function. The approximations are pointwise and of the uniform norm. The related Banach space valued feed-forward neural networks are with one hidden layer.

Temporal trend and spatial clustering of the dengue fever prevalence in West Java, Indonesia.

Dengue fever is a notable vector-borne viral disease, currently becoming the most dreaded worldwide health problem in terms of the number of people affected. A data set of confirmed dengue incidences collected in the province of West Java has allowed us to explore dengue's temporal trends and spatial distributions to obtain more obvious insights into its spatial-temporal evolution. We utilized the Richards model to estimate the growth rate and detect the peak (or turning point) of the dengue infection wave by identifying the temporal progression at each location. Using spatial analysis of geo-referenced data from a local perspective, we investigated the changes in the spatial clusters of dengue cases and detected hot spots and cold spots in each weekly cycle. We found that the trend of confirmed dengue incidences significantly increases from January to March. More than two-third (70.4%) of the regions in West Java had their dengue infection turning point ranging from the first week of January to the second week of March. This trend clearly coincides with the peak of precipitation level during the rainy season. Further, the spatial analysis identified the hot spots distributed across central, northern, northeastern, and southeastern regions in West Java. The densely populated areas were likewise seen to be associated with the high-risk areas of dengue exposure. Recognizing the peak of epidemic and geographical distribution of dengue cases might provide important insights that may help local authorities optimize their dengue prevention and intervention programs.

Validation Study of the Richards-Campbell Sleep Questionnaire in Patients with Acute Stroke.

Sleep disorders are frequent in acute stroke. The Richards-Campbell Sleep Questionnaire (RCSQ) is a validated scale for the sleep assessment in intensive care unit. The aim of the present study is to validate RCSQ for use in patients with acute stroke. We performed a validation study by comparing the RCSQ with polysomnography (PSG), the standardized measure of sleep. Inclusion criteria were age ≥ 18 years and a radiologically confirmed diagnosis of stroke. Exclusion criteria were global aphasia, extreme severity of clinical conditions and inability to attend PSG. All patients underwent PSG in a stroke unit, the day after a subjective sleep assessment by means of the RCSQ. The RCSQ was compared with PSG parameters to assess the degree of concordance of the two measures. The cohort consisted of 36 patients. Mean RCSQ score was 61.5 ± 24.8. The total score of the RCSQ showed a good degree of concordance with the sleep efficiency index of PSG. Accuracy of the RCSQ was 70%, sensitivity 71% and specificity 68%. The RCSQ is a good tool for screening the sleep quality in the setting of a stroke unit. Therefore, it could be useful to select the patients who might beneficiate from an instrumental sleep evaluation.

Spin-Orbital Conversion with the Tight Focus of an Axial Superposition of a High-Order Cylindrical Vector Beam and a Beam with Linear Polarization.

In this paper, spin-orbital conversion in the tight focus of an axial superposition of a high-order (order m) cylindrical vector beam and a beam with linear polarization is theoretically and numerically considered. Although such a beam does not have a spin angular momentum in the initial plane and the third projection of its Stokes vector is equal to zero, subwavelength local regions with a transverse vortex energy flow and with the non-zero third Stokes projection (the longitudinal component of the spin angular momentum) are formed in the focal plane for an odd number m. This means that such a beam with an odd m has regions of elliptical or circular polarization with alternating directions of rotation (clockwise and counterclockwise) in the focus. For an even m, the field is linearly polarized at every point of the focal plane, and the transverse energy flux is absent. These beams can be used to create a micromachine in which two microparticles in the form of gears are captured in the focus of the beam into neighboring local areas in which the energy flow rotates in different directions, and therefore, these gears will also rotate in different directions.

A statistical analysis of nonlinear regression models for different treatments for layers.

As the cost of research increases, mathematical models become valuable tools to answer research questions. A major application of mathematical modeling is accurate estimation of production performance, growth, and feed consumption for poultry research and production. There are many ways that a given data set can be analyzed, and different models have been proposed to fit those curves. To explore the models available, data were investigated from a study on the effects of a series of balanced dietary protein levels on egg production and egg quality parameters in lying hens from 18 to 74 wk of age. Forty eight pullets were assigned to each of 3 different protein levels. The results clearly demonstrated that balanced dietary protein level was the limiting factor for body weight (BW), average daily feed intake (ADFI), egg weight, and egg production. To test differences of fitted curves, the sum of squared reduction test is used. Using a unique data set with data from individual hens, 6 commonly used models were fitted to hen performance technical data. The resulting statistical inferences from using individual and pooled data were compared. There are only differences in using individual or grouped data in fitting nonlinear models to laying hen response data. For the most important response variables, hen-day egg production, and feed intake, predicted responses are within 0.12 and 0.65%, respectively, throughout the production cycle.

Absolute Quantitation of Serum Antibody Reactivity Using the Richards Growth Model for Antigen Microspot Titration.

In spite of its pivotal role in the characterization of humoral immunity, there is no accepted method for the absolute quantitation of antigen-specific serum antibodies. We devised a novel method to quantify polyclonal antibody reactivity, which exploits protein microspot assays and employs a novel analytical approach. Microarrays with a density series of disease-specific antigens were treated with different serum dilutions and developed for IgG and IgA binding. By fitting the binding data of both dilution series to a product of two generalized logistic functions, we obtained estimates of antibody reactivity of two immunoglobulin classes simultaneously. These estimates are the antigen concentrations required for reaching the inflection point of thermodynamic activity coefficient of antibodies and the limiting activity coefficient of antigen. By providing universal chemical units, this approach may improve the standardization of serological testing, the quality control of antibodies and the quantitative mapping of the antibody-antigen interaction space.

The doubling time analysis for modified infectious disease Richards model with applications to COVID-19 pandemic.

In the absence of reliable information about transmission mechanisms for emerging infectious diseases, simple phenomenological models could provide a starting point to assess the potential outcomes of unfolding public health emergencies, particularly when the epidemiological characteristics of the disease are poorly understood or subject to substantial uncertainty. In this study, we employ the modified Richards model to analyze the growth of an epidemic in terms of 1) the number of times cumulative cases double until the epidemic peaks and 2) the rate at which the intervals between consecutive doubling times increase during the early ascending stage of the outbreak. Our theoretical analysis of doubling times is combined with rigorous numerical simulations and uncertainty quantification using synthetic and real data for COVID-19 pandemic. The doubling-time approach allows to employ early epidemic data to differentiate between the most dangerous threats, which double in size many times over the intervals that are nearly invariant, and the least transmissible diseases, which double in size only a few times with doubling periods rapidly growing.

A mechanistic model for nitrogen-limited plant growth.

BACKGROUND AND AIMS: Nitrogen is often regarded as a limiting factor to plant growth in various ecosystems. Understanding how nitrogen drives plant growth has numerous theoretical and practical applications in agriculture and ecology. In 2004, Göran I. Ågren proposed a mechanistic model of plant growth from a biochemical perspective. However, neglecting respiration and assuming stable and balanced growth made the model unrealistic for plants growing in natural conditions. The aim of the present paper is to extend Ågren's model to overcome these limitations. METHODS: We improved Ågren's model by incorporating the respiratory process and replacing the stable and balanced growth assumption with a three-parameter power function to describe the relationship between nitrogen concentration (Nc) and biomass. The new model was evaluated based on published data from three studies on corn (Zea mays) growth. KEY RESULTS: Remarkably, the mechanistic growth model derived in this study is mathematically equivalent to the classical Richards model, which is the most widely used empirical growth model. The model agrees well with empirical plant growth data. CONCLUSIONS: Our model provides a mechanistic interpretation of how nitrogen drives plant growth. It is very robust in predicting growth curves and the relationship between Nc and relative growth rate.