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The study presents a comprehensive investigation into the genetic determinants of 100-day milk yield (100DMY), 305-day milk yield (305DMY), total milk yield (TMY), and persistency using first lactation records of 374 Holstein heifers reared in a private farm at Çanakkale province of Türkiye, employing a genome-wide association study (GWAS) approach. The research underscores the substantial genetic component underlying these economically important traits through detailed descriptive statistics and heritability estimations. The estimated moderate to high heritabilities (0.32–0.54) for milk production traits suggest the feasibility of targeted genetic improvement strategies. By leveraging GWAS, the study identifies many significant and suggestively significant single nucleotide polymorphisms (SNP) associated with studied traits. Noteworthy genes have identified in this analysis include BCAS3, MALRD1, CTNND2, DOCK1, TMEM132C, NRP1, CNTNAP2, GPRIN2, PLEKHA5, GLRA1, SCN7A, HHEX, KTM2C, RAB40C, RAB11FIP3, and FXYD6. These findings provide valuable understandings of the genetic background of milk production and persistency in Holstein cattle, shedding light on specific genomic regions and candidate genes playing pivotal roles in these traits. This research contributes valuable knowledge to the field of dairy cattle genetics and informs future breeding efforts to improve milk production sustainability and efficiency in Holstein cattle populations. [ABSTRACT FROM AUTHOR]

Multispectral imaging by unoccupied aerial vehicles provides a nondestructive, high-throughput approach to measure biomass accumulation over successive alfalfa (Medicago sativa L. subsp. sativa) harvests. Information from estimated growth curves can be used to infer harvest biomass and to gain insights into the relationship between growth dynamics and forage biomass stability across cuttings and years. In this study, multispectral imaging and several common vegetation indices were used to estimate genetic parameters and model growth of alfalfa cultivars to determine the longitudinal relationship between vegetation indices and forage biomass. Results showed moderate heritability for vegetation indices, with median plot level heritability ranging from 0.11 to 0.64, across multiple cuttings in three trials planted in Ithaca, NY, and Las Cruces, NM. Genetic correlations between the normalized difference vegetation index and forage biomass were moderate to high across trials, cuttings, and the timing of multispectral image capture. To evaluate the relationship between growth parameters and forage biomass stability across cuttings and environmental conditions, random regression modeling approaches were used to estimate the growth parameters of cultivars for each cutting and the variance in growth was compared to the variance in genetic estimates of forage biomass yield across cuttings. These analyses revealed high correspondence between stability in growth parameters and stability of forage yield. The results of this study indicate that vegetation indices are effective at modeling genetic components of biomass accumulation, presenting opportunities for more efficient screening of cultivars and new longitudinal modeling approaches that can provide insights into temporal factors influencing cultivar stability. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Animal & Poultry Production is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract The objective of this work was to evaluate the influence of environmental factors on the lactation curve parameters and milk yield of Holstein cows. Data on lactations conducted from 2010 to 2019 in the state of Paraná, Brazil, obtained from the official dairy control service, were used. The parameters of the lactation curves were estimated using the Wood model and NLIN procedure of the SAS software. The influence of the environmental factors lactation order and calving region and season on the parameters of the lactation curves and on milk yield was evaluated using the MIXED procedure of SAS. First-lactation cows reached peak lactation later and showed a more persistent lactation. Milk yield increased with lactation order. The highest lactation peaks occurred in lactations started in winter and in fall, at 305 days. Cows raised in the center-east region of the state of Paraná had the highest milk yield at the peak and at 305 days of lactation. Lactation order and calving region and season influence the shape of the lactation curve of Holstein cows, with an increase in milk yield when lactation cycles begin in winter-spring.

The study presents a comprehensive investigation into the genetic determinants of 100-day milk yield (100DMY), 305-day milk yield (305DMY), total milk yield (TMY), and persistency using first lactation records of 374 Holstein heifers reared in a private farm at Çanakkale province of Türkiye, employing a genome-wide association study (GWAS) approach. The research underscores the substantial genetic component underlying these economically important traits through detailed descriptive statistics and heritability estimations. The estimated moderate to high heritabilities (0.32–0.54) for milk production traits suggest the feasibility of targeted genetic improvement strategies. By leveraging GWAS, the study identifies many significant and suggestively significant single nucleotide polymorphisms (SNP) associated with studied traits. Noteworthy genes have identified in this analysis include BCAS3, MALRD1, CTNND2, DOCK1, TMEM132C, NRP1, CNTNAP2, GPRIN2, PLEKHA5, GLRA1, SCN7A, HHEX, KTM2C, RAB40C, RAB11FIP3, and FXYD6. These findings provide valuable understandings of the genetic background of milk production and persistency in Holstein cattle, shedding light on specific genomic regions and candidate genes playing pivotal roles in these traits. This research contributes valuable knowledge to the field of dairy cattle genetics and informs future breeding efforts to improve milk production sustainability and efficiency in Holstein cattle populations.

Lactation curves were estimated for Montbéliarde (MO) × Holstein (HO) and Viking Red (VR) × HO 2-breed crossbred cows and for MO × VR/HO and VR × MO/HO 3-breed crossbred cows and their HO herdmates from test-day observations in 7 high-performance herds that participated in a designed study. Cows calved from 2010 to 2017. Test-day observations from milk recording were used to fit the lactation curves of cows in their first 3 lactations. Lactations of cows were required to have at least 250 DIM and to have at least 6 test days ≤265 DIM. Lactation curves from random regression (RR) were compared for 305-d production (kg), peak production (kg), peak day of production, and production from 4 to 103 DIM (kg), from 104 to 205 DIM (kg), and from 206 to 305 DIM (kg) for milk, fat, and protein. Also, the persistency of production was compared. First-lactation versus second- and third-lactation cows were analyzed separately for both the 2-breed and 3-breed crossbred cows and their respective HO herdmates. Legendre polynomial RR had the best goodness of fit for the lactation curves compared with Ali–Schaeffer and Wilmink RR from the test-day observations of milk, fat, and protein production. For fluid milk production of first-lactation cows, the MO × HO 2-breed crossbreds were not different from their HO herdmates for any of the lactation-curve characteristics, except persistency. However, the VR × HO 2-breed crossbreds had less fluid milk production compared with their HO herdmates. For first lactation, the MO × HO 2-breed crossbreds had more persistency of milk, fat, and protein production compared with their HO herdmates. The first-lactation MO × VR/HO 3-breed crossbreds had more persistency of fluid milk production compared with their HO herdmates. For second and third lactations, both the MO × HO and the VR × HO 2-breed crossbreds had higher fat production compared with their HO herdmates. Furthermore, the MO × HO 2-breed crossbreds had more protein production (kg) in all 3 periods of lactation compared with their HO herdmates. Crossbred cows may have advantages over HO cows for persistency of production in high-performance herds. [ABSTRACT FROM AUTHOR]

• Analysis of geomagnetic field's H time series during quiet geomagnetic condition. • The H time series from high latitude region shows anti-persistent behaviour. • H time series of quiet geomagnetic condition shows multifractal characteristics. • Change in multifractal characteristics with latitude is observed. • The cause of multifractality is identified as long-range correlations. The generation of geomagnetic time series frequently involves intricate spatio-temporal dynamics, wherein nonlinearity and scaling emerge as pivotal mechanisms. The present work investigates the fractal properties of geomagnetic field, and its sources during quiet geomagnetic conditions, by analyzing the horizontal component data of 1 min resolution (H time series) from different latitude regions. Analysis using Auto Correlation Function (ACF), Power spectrum analysis (PSA), Rescaled range analysis (R/S) and Detrended Fluctuation Analysis (DFA) gave indications of the presence of long-range correlations, fractal properties and scaling behaviour of quiet period H time series data. The strong q dependence of generalized Hurst exponent h(q) and scaling exponent Ʈ(q), obtained from the Multifractal Detrended Fluctuation Analysis (MFDFA) method, confirmed the multifractal behaviour of quiet period H time series. The multifractal source analysis of the quiet period H time series with its shuffled and surrogate time series data revealed that, the multifractal characteristics are caused almost entirely by the long-range correlations between small and large fluctuations. The analysis of the latitudinal variations in the multifractal characteristics is also performed as a part of the work, by considering H time series belonging to various latitudes under almost same longitude. The observed decrease in the generalized Hurst exponent values with increase in latitude indicates the change in the multifractal characteristics of the time series with latitude. Also the work revealed that, the H time series from high latitude region shows anti-persistent behaviour, even when the H time series from observatories located at the low and mid latitude regions exhibiting persistent behaviour. The change in the persistence, anti-persistence behaviour can be related to the strength of Earth's magnetic field. [ABSTRACT FROM AUTHOR]

ABSTRACT: This study aimed to assess the milk production data for New Zealand dairy goats in either a standard lactation (SL; ≤305 d in milk [DIM]) or extended lactation (EL; >305 and ≤670 DIM) using a random regression (RR) with third- and fifth-order Legendre polynomials, respectively. Persistency of EL was defined as (B/A) × 100, where A was the accumulated yield from d 1 to 305, and B was the accumulated yield from d 366 to 670. On average, goats in SL produced 1,183 kg of milk, 37 kg of fat, 37 kg of protein, and 54 kg of lactose. The average production of milk, fat, protein, and lactose in EL were 2,473 kg, 78 kg, 79 kg, and 112 kg, respectively. The average persistences for milk, fat, protein, and lactose yields during EL were 98%, 98%, 102%, and 96%, respectively. The relative prediction errors were close to 10% and the concordance correlation coefficients >0.92, indicating that the RR model with Legendre polynomials is adequate for modeling lactation curves for both SL and EL. Total yields and persistency were analyzed with a mixed model that included the fixed effects (year, month of kidding, parity, and proportion of Saanen) as covariates and the random effects of animal and residual errors. Effects of year, month of kidding, and parity were significant on the total yields of milk, fat, protein, and lactose for both SL and EL. The total milk yield of first-parity goats with SL was 946 kg and the total milk yield of second-parity goats with SL was 1,284 kg, making a total of 2,230 kg over 2 years. The total milk yield of a first-parity goat with EL was 2,140 kg. Thus, on average, a goat with SL for the first and second parity produced 90 kg more milk than a first-parity goat subjected to EL. However, a second-parity goat subjected to EL produced 43 kg more milk (2,639 kg) than a goat with SL following the second and third parity (1,284 kg + 1,312 kg). These data, along with the various other benefits of EL (e.g., fewer offspring born and reduced risk of mastitis, lameness, and metabolic problems in early lactation), indicate that EL as a management strategy holds the potential to improve dairy goat longevity and lifetime efficiency without compromising milk production.

This study aimed to assess the milk production data for New Zealand dairy goats in either a standard lactation (SL; ≤305 d in milk [DIM]) or extended lactation (EL; >305 and ≤670 DIM) using a random regression (RR) with third- and fifth-order Legendre polynomials, respectively. Persistency of EL was defined as (B/A) × 100, where A was the accumulated yield from d 1 to 305, and B was the accumulated yield from d 366 to 670. On average, goats in SL produced 1,183 kg of milk, 37 kg of fat, 37 kg of protein, and 54 kg of lactose. The average production of milk, fat, protein, and lactose in EL were 2,473 kg, 78 kg, 79 kg, and 112 kg, respectively. The average persistences for milk, fat, protein, and lactose yields during EL were 98%, 98%, 102%, and 96%, respectively. The relative prediction errors were close to 10% and the concordance correlation coefficients >0.92, indicating that the RR model with Legendre polynomials is adequate for modeling lactation curves for both SL and EL. Total yields and persistency were analyzed with a mixed model that included the fixed effects (year, month of kidding, parity, and proportion of Saanen) as covariates and the random effects of animal and residual errors. Effects of year, month of kidding, and parity were significant on the total yields of milk, fat, protein, and lactose for both SL and EL. The total milk yield of first-parity goats with SL was 946 kg and the total milk yield of second-parity goats with SL was 1,284 kg, making a total of 2,230 kg over 2 years. The total milk yield of a first-parity goat with EL was 2,140 kg. Thus, on average, a goat with SL for the first and second parity produced 90 kg more milk than a first-parity goat subjected to EL. However, a second-parity goat subjected to EL produced 43 kg more milk (2,639 kg) than a goat with SL following the second and third parity (1,284 kg + 1,312 kg). These data, along with the various other benefits of EL (e.g., fewer offspring born and reduced risk of mastitis, lameness, and metabolic problems in early lactation), indicate that EL as a management strategy holds the potential to improve dairy goat longevity and lifetime efficiency without compromising milk production. [ABSTRACT FROM AUTHOR]

This paper focuses on modeling surrender time for policyholders in the context of life insurance. In this setup, a large lapse rate at the first months of a contract is often observed, with a decrease in this rate after some months. The modeling of the time to cancelation must account for this specific behavior. Another stylized fact is that policies which are not canceled in the study period are considered censored. To account for both censoring and heterogeneous lapse rates, this work assumes a Bayesian survival model with a mixture of regressions. The inference is based on data augmentation allowing for fast computations even for datasets of over millions of clients. Moreover, frequentist point estimation based on Expectation–Maximization algorithm is also presented. An illustrative example emulates a typical behavior for life insurance contracts, and a simulated study investigates the properties of the proposed model. A case study is considered and illustrates the flexibility of our proposed model allowing different specifications of mixture components. In particular, the observed censoring in the insurance context might be up to $50\%$ of the data, which is very unusual for survival models in other fields such as epidemiology. This aspect is exploited in our simulated study. [ABSTRACT FROM AUTHOR]

Genetic and genomic analyses of longitudinal traits related to milk production efficiency are paramount for optimizing water buffaloes breeding schemes. Therefore, this study aimed to (1) compare single-trait random regression models under a single-step genomic BLUP setting based on alternative covariance functions (i.e., Wood, Wilmink, and Ali and Schaeffer) to describe milk (MY), fat (FY), protein (PY), and mozzarella (MZY) yields, fat-to-protein ratio (FPR), somatic cell score (SCS), lactation length (LL), and lactation persistency (LP) in Murrah dairy buffaloes (Bubalus bubalis); (2) combine the best functions for each trait under a multiple-trait framework; (3) estimate time-dependent SNP effects for all the studied longitudinal traits; and (4) identify the most likely candidate genes associated with the traits. A total of 323,140 test-day records from the first lactation of 4,588 Murrah buffaloes were made available for the study. The model included the average curve of the population nested within herd-year-season of calving, systematic effects of number of milkings per day, and age at first calving as linear and quadratic covariates, and additive genetic, permanent environment, and residual as random effects. The Wood model had the best goodness of fit based on the deviance information criterion and posterior model probabilities for all traits. Moderate heritabilities were estimated over time for most traits (0.30 ± 0.02 for MY; 0.26 ± 0.03 for FY; 0.45 ± 0.04 for PY; 0.28 ± 0.05 for MZY; 0.13 ± 0.02 for FPR; and 0.15 ± 0.03 for SCS). The heritability estimates for LP ranged from 0.38 ± 0.02 to 0.65 ± 0.03 depending on the trait definition used. Similarly, heritabilities estimated for LL ranged from 0.10 ± 0.01 to 0.14 ± 0.03. The genetic correlation estimates across days in milk (DIM) for all traits ranged from −0.06 (186–215 DIM for MY-SCS) to 0.78 (66–95 DIM for PY-MZY). The SNP effects calculated for the random regression model coefficients were used to estimate the SNP effects throughout the lactation curve (from 5 to 305 d). Numerous relevant genomic regions and candidate genes were identified for all traits, confirming their polygenic nature. The candidate genes identified contribute to a better understanding of the genetic background of milk-related traits in Murrah buffaloes and reinforce the value of incorporating genomic information in their breeding programs. [ABSTRACT FROM AUTHOR]

Copyright of Süleyman Demirel Law Review / Süleyman Demirel Üniversitesi Hukuk Fakültesi Dergisi is the property of Suleyman Demirel Universitesi Hukuk Fakultesi Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this research paper, we examined the influence of demographic and household factors on adecision to surrender a life insurance policy before the end of the policy term. As per thehandbook on Indian Insurance Statistics 2020-21, by the 5 th year of policy sale, only 4 out of 24 life insurers could retain half of their policies. One of the reasons for this low persistenceis the increased surrender of policies. Surrendering a policy means the policyholdercancelling the policy and agreeing to take the cash value/surrender value accrued to thepolicy over time and forgoing the death benefit or maturity benefit. Generally, a policyacquires surrender value after the policyholder has paid the premiums continuously for threeyears. A survey of randomly selected 537 policyholders was conducted using a structuredquestionnaire to examine the influence of demographic and household factors on a decisionto surrender a life insurance policy. Results of our study suggest that demographic andhousehold factors influence the decision to surrender a life insurance policy. Marital statusand occupation are statistically significant predictors of the decision to surrender a policy.

The article’s subject matter is the processing of abdominal EMG recordings and finding breathing patterns. The goal is to automatically classify respiratory patterns into two classes, or clusters, by two breathing patterns, regular and irregular, using machine learning (ML) methods. The object of the study was to obtain a dataset of 40 randomly picked abdominal EMG recordings (sampling rate equal to 200 Hz) borrowed from the complete dataset published by the Computational Clinical Neurophysiology Laboratory and the Clinical Data Animation Laboratory of Massachusetts General Hospital. The tasks to be solved are as follows: finding ETS (errors-trend-seasonality) model for the EMG series using the exponential smoothing method; obtaining denoised and detrended signals; obtaining the Hurst exponents for EMGs using the power-law decaying of correlograms for the denoised and detrended signals; describing the variabilities, SNR, the outlier fractions, and Hurst exponents by robust statistics, performing correlation analysis, and Principal Components Analysis (PCA); analyzing the structure of the distant matrix by a graph-based technique; obtaining the periodograms in the frequency domain using the known Wiener-Khinchin theorem; and finding the best models and methods of classification and clusterization and evaluating them within modern Machine Learning methods. The methods used are exponential smoothing, the Wiener-Khinchin theorem, the graph theory method, principal component analysis, programing within MAPLE 2020, and data processing by Weka. The authors obtained the following results: 1) wide data variability has been rated with the median absolute deviations, which is the most robust statistic in this case; 2) most of the signals (38 of 40) showed frequent outliers: from a few percent up to 24.6 % of emissions; 3) these four variables: outliers' percentage, variability, SNR, and persistency factors – form the attributes of input vectors of the subjects for further Machine Learning with Weka software; 4) Manhattan distances matrix among subjects' vectors in 4D attributes space allows imaging the data set as a weighted graph, the vertices of which are subjects; 5) the weights of the graph's edges reflect distances between any pair of them. "Closeness centralities" of vertices allowed us to cluster the data set on two clusters with 11 and 29 subjects, and Weka clustering algorithms confirmed this result. 6) The learning curve shows that a sufficiently small data set (from 25 subjects) might be suitable for classification purposes. Conclusions. The scientific novelty of the results obtained is as follows: 1) the Error-Trend-Seasonality model was the same for all data sets. Abdominal EMG of sleeping patients had additive errors and undamped trends without any seasonality; 2) the correlograms' decaying according to power law had been set, and Hurst exponents were in the range (of 0.776–0.887). This testifies to "long memory" (high persistence) of abdominal EMGs; 3) the modified Z-scores and robust statistics with the highest breakdown values were used for the EMG parameters because of many outliers; 4) breathing patterns were set using the periodograms in the frequency domain using the Wiener-Khinchin theorem; 5) the new graph-based method was successfully exploited to cluster the dataset. Parallel clustering with Weka algorithms confirmed the graph-based clustering results.

The objectives were to characterize the lactation curves (LC) of tropical Gyr and Sardo Negro (SN) cattle from Mexico for the design of breeding and management programs for these breeds. A total of 3561 records of 504 lactations and 3927 records of 449 lactations were used for Gyr and SN, respectively. Three lactation lengths (LL) were evaluated, namely 240 (240d), 270 (270d), and 300 (300d) days, with five non-linear models (NLM): Wood, Wiltmink, Cobby, Brody, and Sikka. Milk production was obtained at the beginning (PI; kg), daily average (PMD; kg), maximum at peak (PMX; kg), days to reach maximum production (DP), and accumulated total (PT; kg). The selection of models was made based in the Akaike and Bayesian information criteria. The NLM explained at least 88% of the variability in the data. Brody model provided the best fit for 240d and 270d, and Sikka for 300d in SN; for Gyr, Wood model showed the best fit for 240d and 270d, while Wiltmink had the best fit for 300d. The means for PMD were 5.3 kg in SN and 10.2 kg in Gyr; for PMX the averages were 6.9 kg and 12.7 kg, respectively. The average of PT, within LL (240d, 270d, and 300d), was 1297 kg, 1418 kg, and 1552 kg for SN, and 2653 kg, 2930 kg, and 3202 kg for Gyr, respectively. The first third of the LC presented the highest contribution (%), with average values of 37.4 in Gyr and 39.5 in SN; the second and third periods, contributed (%) 33.5 and 29.1 in Gyr, and 33.0 and 27.5 in SN, respectively. The 240d LL, are the proposals for the design of management, feeding, and genetic improvement programs, they presented the best statistical adjustment in both breeds.

Little data are currently available on either the dry matter (DM) production of perennial ryegrass (PRG) swards as they age beyond 5 yr (i.e. permanent pasture) or the performance of PRG varieties on commercial grassland farms. Previous work has generally assumed a connection between DM production and ground score (GS) and this link has been used as a proxy for variety persistence. The evolution of technology in the form of PastureBase Ireland has led to agronomic data of individual paddocks being made available for analysis over multiple years which has allowed the long-term assessment of varieties sown as monocultures on commercial farms. This technology allowed for the inclusion of eight PRG varieties sown in 649 paddocks across 101 farms in Ireland in the current analysis. The results show little association between GS and variety DM production as varieties age to 7 yr. Dry matter production of 1- to 4-yr-old swards appeared to provide a strong indication of variety DM production in years 5–7 post-sowing (r = 0.72, P < 0.05). The interaction of variety and sward age was not associated with DM production. Generally, varieties which produced the most DM in younger swards also produced the most DM in permanent pasture swards. Over longer-term periods these variety differences can manifest into large differences in DM produced and consumed on farm. The current analysis suggests that the long-term production benefits of utilising improved PRG varieties in pasture reseeding may be underestimated.

Copyright of Journal of Plant Protection & Pathology is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Behavioral persistency reflects internal brain states, which are the foundations of multiple brain functions. However, experimental paradigms enabling genetic analyses of behavioral persistency and its associated brain functions have been limited. Here, we report novel persistent behavioral responses caused by electric stimuli in the nematode Caenorhabditis elegans. When the animals on bacterial food are stimulated by alternating current, their movement speed suddenly increases 2- to 3-fold, persisting for more than 1 minute even after a 5-second stimulation. Genetic analyses reveal that voltage-gated channels in the neurons are required for the response, possibly as the sensors, and neuropeptide signaling regulates the duration of the persistent response. Additional behavioral analyses implicate that the animal's response to electric shock is scalable and has a negative valence. These properties, along with persistence, have been recently regarded as essential features of emotion, suggesting that C. elegans response to electric shock may reflect a form of emotion, akin to fear. [ABSTRACT FROM AUTHOR]

In this research paper, we examined the influence of demographic and household factors on adecision to surrender a life insurance policy before the end of the policy term. As per thehandbook on Indian Insurance Statistics 2020-21, by the 5 th year of policy sale, only 4 out of 24 life insurers could retain half of their policies. One of the reasons for this low persistenceis the increased surrender of policies. Surrendering a policy means the policyholdercancelling the policy and agreeing to take the cash value/surrender value accrued to thepolicy over time and forgoing the death benefit or maturity benefit. Generally, a policyacquires surrender value after the policyholder has paid the premiums continuously for threeyears. A survey of randomly selected 537 policyholders was conducted using a structuredquestionnaire to examine the influence of demographic and household factors on a decisionto surrender a life insurance policy. Results of our study suggest that demographic andhousehold factors influence the decision to surrender a life insurance policy. Marital statusand occupation are statistically significant predictors of the decision to surrender a policy. [ABSTRACT FROM AUTHOR]

When deciding on the voluntary waiting period of an individual cow, it might be useful to have insight into the persistency for the remainder of that lactation at the moment of the insemination decision, especially for farmers who consider persistency in their reproduction management. Currently, breeding values for persistency are calculated for dairy cows but, to our knowledge, prediction models to accurately predict persistency at different moments of insemination are lacking. This study aimed to predict lactation persistency for DIM 305 at different insemination moments (DIM 50, 75, 100, and 125). Available cow and herd level data from 2005 to 2022 were collected for a total of 20,508 cows from 85 herds located in the Netherlands and Belgium. Lactation curve characteristics were estimated for every daily record using the data up to and including that day. Persistency was defined as the number of days it takes for the milk production to decrease by half during the declining stage of lactation, and calculated from the estimated lactation curve characteristic ‘decay’. Four linear regression models for each of the selected insemination moment were built separately to predict decay at DIM 305 (decay-305). Independent variables included the lactation curve characteristics at the selected insemination moment, daily milk yield, age, calving season, parity group and other herd variables. The average decay-305 of primiparous cows was lower than that of multiparous cows (1.55 *10−3 vs. 2.41*10−3, equivalent to a persistency of 447 vs. 288 days, respectively). Results showed that our models had limitations in accurately predicting persistency, although predictions improved slightly at later insemination moments, with R2 values ranging between 0.27 and 0.41. It can thus be concluded that, based only on cow and herd milk production information, accurate prediction of persistency for DIM 305 is not feasible.

Introduction: Direct-acting antiviral (DAA) therapy is highly effective in curing hepatitis C virus (HCV) infection in people who inject drugs (PWID). Previous studies showed declining persistence to DAA therapy over the course of treatment. This study compares real-world medication persistence to prescription refills for 8- versus 12-week DAA in treatment-naïve PWID with chronic HCV with compensated cirrhosis or without cirrhosis. Methods: Symphony Health's claims database was used to collect data from patients with chronic HCV aged ≥ 12 years who were prescribed 8- or 12-week DAA therapy between August 2017 and November 2020 and had a diagnosis of addicted drug use within 6 months prior to index date. Eligible patients had medical/pharmacy claims in the 6 months before and 3 months after the first index medication fill date (i.e., index date). Patients completing all refills (8-week = 1 refill, 12-week = 2 refills) were deemed persistent. The percentage of persistent patients in each group, and at each refill step, was determined; outcomes were also assessed in a subgroup of Medicaid-insured patients. Results: This study assessed 7203 PWID with chronic HCV (8-week, 4002; 12-week, 3201). Patients prescribed 8-week DAA treatment were younger (42.9 ± 12.4 vs 47.5 ± 13.2, P < 0.001) and had fewer comorbidities (P < 0.001). Patients receiving 8- versus 12-week DAA had greater refill persistence (87.9% vs 64.4%, P < 0.001). Similar percentages of patients missed their first refill (8-week, 12.1% vs 12-week, 10.8%); nearly 25% of patients receiving 12-week DAA missed their second refill. After baseline characteristics were controlled, patients prescribed 8- versus 12-week DAA were more likely to be persistent (odds ratio [95% confidence interval] 4.3 [3.8, 5.0]). Findings in the Medicaid-insured subgroup were consistent. Conclusion: Patients prescribed 8- vs 12-week DAA therapy had significantly greater prescription refill persistence. Most nonpersistence was due to missed second refills, highlighting the potential benefit of shorter treatment durations in this population. [ABSTRACT FROM AUTHOR]

Recent advances in imaging technologies now allow for real-time tracking of fast-moving immune cells as they search for targets such as pathogens and tumor cells through complex three-dimensional tissues. Cytotoxic T cells are specialized immune cells that continually scan tissues for such targets to engage and kill, and have emerged as the principle mediators of breakthrough immunotherapies against cancers. Modeling the way these T cells move is of great value in furthering our understanding of their collective search efficiency. T-cell motility is characterized by heterogeneity at two levels: (a) Individual cells display different distributions of translational speeds and turning angles, and (b) each cell can during a given track, its motility, switch between local search and directional motion. Despite a likely considerable influence on a motile population's search performance, statistical models that accurately capture both such heterogeneities in a distinguishing manner are lacking. Here, we model three-dimensional T-cell trajectories through a spherical representation of their incremental steps and compare model outputs to real-world motility data from primary T cells navigating physiological environments. T cells in a population are clustered based on their directional persistence and characteristic "step lengths" therein capturing between-cell heterogeneity. The motility dynamics of cells within each cluster are individually modeled through hidden Markov model to capture within-cell transitions between local and more extensive search patterns. We explore the importance of explicitly capturing altered motility patterns when cells lie in close proximity to one another, through a non-homogenous hidden Markov model. [ABSTRACT FROM AUTHOR]

This study aimed to find the parsimonious random regression model (RRM) to evaluate the genetic potential for milk yield (MY), fat content (FC), and protein content (PC) in Tunisian Holstein cows. For this purpose, 551,139; 331,654; and 302,396 test day records for MY, FC, and PC were analysed using various RRMs with different Legendre polynomials (LP) orders on additive genetic (AG) and permanent environmental (PE) effects, and different types of residual variances (RV). The statistical analysis was performed in a Bayesian framework with Gibbs sampling, and the model performances were assessed, mainly, on the predictive ability criteria. The study found that the optimal model for evaluating these traits was an RRM with a third LP order and nine classes of heterogeneous RV. In addition, the study found that heritability estimates for MY, FC, and PC ranged from 0.11 to 0.22, 0.11 to 0.17, and 0.12 to 0.18, respectively, indicating that genetic improvement should be accompanied by improvements in the production environment. The study also suggested that new selection rules could be used to modify lactation curves by exploiting the canonical transformation of the random coefficient covariance (RC) matrix or by using the combination of slopes of individual lactation curves and expected daily breeding values. [ABSTRACT FROM AUTHOR]

The article’s subject matter is the processing of abdominal EMG recordings and finding breathing patterns. The goal is to automatically classify respiratory patterns into two classes, or clusters, by two breathing patterns, regular and irregular, using machine learning (ML) methods. The object of the study was to obtain a dataset of 40 randomly picked abdominal EMG recordings (sampling rate equal to 200 Hz) borrowed from the complete dataset published by the Computational Clinical Neurophysiology Laboratory and the Clinical Data Animation Laboratory of Massachusetts General Hospital. The tasks to be solved are as follows: finding ETS (errors-trend-seasonality) model for the EMG series using the exponential smoothing method; obtaining denoised and detrended signals; obtaining the Hurst exponents for EMGs using the power-law decaying of correlograms for the denoised and detrended signals; describing the variabilities, SNR, the outlier fractions, and Hurst exponents by robust statistics, performing correlation analysis, and Principal Components Analysis (PCA); analyzing the structure of the distant matrix by a graph-based technique; obtaining the periodograms in the frequency domain using the known Wiener-Khinchin theorem; and finding the best models and methods of classification and clusterization and evaluating them within modern Machine Learning methods. The methods used are exponential smoothing, the Wiener-Khinchin theorem, the graph theory method, principal component analysis, programing within MAPLE 2020, and data processing by Weka. The authors obtained the following results: 1) wide data variability has been rated with the median absolute deviations, which is the most robust statistic in this case; 2) most of the signals (38 of 40) showed frequent outliers: from a few percent up to 24.6 % of emissions; 3) these four variables: outliers' percentage, variability, SNR, and persistency factors – form the attributes of input vectors of the subjects for further Machine Learning with Weka software; 4) Manhattan distances matrix among subjects' vectors in 4D attributes space allows imaging the data set as a weighted graph, the vertices of which are subjects; 5) the weights of the graph's edges reflect distances between any pair of them. "Closeness centralities" of vertices allowed us to cluster the data set on two clusters with 11 and 29 subjects, and Weka clustering algorithms confirmed this result. 6) The learning curve shows that a sufficiently small data set (from 25 subjects) might be suitable for classification purposes. Conclusions. The scientific novelty of the results obtained is as follows: 1) the Error-Trend-Seasonality model was the same for all data sets. Abdominal EMG of sleeping patients had additive errors and undamped trends without any seasonality; 2) the correlograms' decaying according to power law had been set, and Hurst exponents were in the range (of 0.776–0.887). This testifies to "long memory" (high persistence) of abdominal EMGs; 3) the modified Z-scores and robust statistics with the highest breakdown values were used for the EMG parameters because of many outliers; 4) breathing patterns were set using the periodograms in the frequency domain using the Wiener-Khinchin theorem; 5) the new graph-based method was successfully exploited to cluster the dataset. Parallel clustering with Weka algorithms confirmed the graph-based clustering results. [ABSTRACT FROM AUTHOR]

The aim of current research was to investigate forage yield and crude protein content of legume-grass mixtures during four years of sward use, applying three nitrogen (N) fertilisation rates: N0, N60, and N120. Three perennial legume species - red clover Trifolium pratense (Tp), lucerne Medicago sativa (Ms) and fodder galega Galega orientalis (Go) were tested in mixtures with grasses (G). Mixtures were composed of 50% of legumes and 50% of grasses. Lucerne and fodder galega are introduced forage legume species in Latvia, and are raising an ever-growing interest in Latvia. The studies of persistency, quality and yielding ability of these legume species in Latvian agroclimatic condition in comparison with traditionally used red clover are actual. Significant differences in dry matter (DM) yields were found between successive production years, mixtures, and N fertilization rates. The highest average DM yield was found for the mixture with lucerne (Ms+G). The decline in productivity between the first and fourth production years was more expressed for red clover mixture, but a more stable productivity was demonstrated by swards with galega (Go+G). The N rate increase contributed to a significant DM yield increase for all mixtures. The positive effect of the increased N rates on DM yield increase was better expressed for red clover mixture (Tp+G). Red clover mixture (Tp+G) had the lowest average crude protein (CP) content. Mixture with galega had a higher CP content in the third and fourth production years. The CP content of red clover mixtures increased by nitrogen rate. [ABSTRACT FROM AUTHOR]

Non-payment of renewal premium within a specific time under a life insurance policy result in lapsation of the contract discontinuing life cover of the life assured. The lapsation happening just within a short period of time after issuing a life insurance policy causes the major loss to all the stakeholders in the life insurance ecosystem. Hence, persistency of insurance policies is a critical aspect of life insurance business, and every life Insurer is interested in maintaining it to higher levels. In India, the impact of a pandemic on persistency of life insurance in not yet represented well in literature. This study analyses the available secondary data to understand how policy persistency was impacted during the covid pandemic. The study also attempts to analyse primary data collected from the consumers to assess their perception towards the timely payment of premium and the need of life insurance during this pandemic. The analysis shows that there was an impact of the covid pandemic on the persistency of life insurance policies as well as the perception of people towards the enhanced need of life Insurance during the pandemic. Future long-term studies in this area may help analyse the exact nature and retention of the positive impact of a pandemic to help the life insurers to improve their policy persistency. [ABSTRACT FROM AUTHOR]

Physical fitness leads to better athletic performance, and persistent training will usually develop physical fitness. Persistency is a personality trait. It is measured in the temperament and character inventory and is considered one of the four temperament traits. In this study the researcher worked on the problem entitled "RELATIONSHIP BETWEEN PHYSICAL FITNESS AND PERSISTENCY OF 11 TO 14 YEARS KHO-KHO AND GYMNASTIC BOYS". The purpose of the study was -1. Observe the physical fitness components of difference age groups kho-kho and gymnastic players. 2. Observe the persistency of difference age groups kho-kho and gymnastic players. 3. Observe Relationship between persistency and physical fitness. The total 25 boys from different four age groups were collected as the subject of the present study. For measuring physical fitness AAHPER youth fitness test and B.K.Passi test for persistency measure. Result: 1. No significant differences were found between Gymnastics and Kho-Kho boys in Pull up, Standing Broad Jump, Shuttle run, 50 Yds and Whole Fitness. 2. Significant differences were found between Gymnastics and Kho-Kho boys in Sit up and 600 Yds. 3. No significant relationship was found between persistency and fitness components, (pull up, sit up, shuttle run, 50 yards, 600 yards, and) of kho-kho boys except standing broad jump and whole fitness. 4. No significant relationship was found between persistency and fitness components, (pull up, sit up, shuttle run, 600 yards, and whole fitness.) of gymnastic boys except 50 yards. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate the performance persistence of Turkish mutual and pension funds. 310 mutual and 259 pension funds were analyzed between the period of 2010–2019 in order to determine if there is an evidence of performance persistence. In this study, a persistence rate is developed, and the skill ratio is used to crosscheck the results of the persistence rate. Furthermore, six different risk-adjusted return measures, such as Sharpe, Treynor, Information, Jensen’s alpha, Sortino, and Omega ratios are calculated to analyze whether funds also exhibit superior risk-adjusted returns. The results indicate that only 2% of funds demonstrate persistence above 50%, and 15 out of 20 fund categories do not have any funds that show persistence in 10 years. Most of the persistent funds have positive skill ratios, and it is observed that the persistence rate is effective. However, it cannot be stated that there is performance persistence in the Turkish fund management industry, since performance persistence is not evident for various fund types, so investors do not need to invest in the best funds of the previous year. Additionally, the empirical results associated with risk-adjusted performance analysis indicate that persistent funds also do not generally yield higher risk-adjusted returns. The lack of persistence in funds’ performance is a significant result for investors in their investment decisions, for fund managers in their human resource policies and bonus schemes, and for regulators in their policy decisions.

Background: Classification criteria for antiphospholipid syndrome (APS) require that antiphospholipid antibody (aPL) positivity is confirmed after at least 12 weeks. We tested the hypothesis that aPL at high titers remain positive while low titers fluctuate over time. As both platelet-bound C4d (PC4d) and aPL are associated with thrombosis in systemic lupus erythematosus (SLE), we also evaluated whether PC4d can aid in APS diagnosis. Methods: Data from serum or plasma sent to Exagen's laboratory for routine aPL testing were analyzed. Anti-cardiolipin (aCL) and anti-beta2 glycoprotein-1 antibodies (aB2GP1) were measured by chemiluminescence or ELiA fluorescence enzyme immunoassay; anti-phosphatidylserine/prothrombin complex antibodies (aPS/PT) by ELISA; PC4d by flow cytometry. Statistical analysis included descriptive statistics, logistic regression, and Pearson correlation. Results: More than 80% of positive samples with aCL and aB2GP1 at high titers - but not low titers - were positive at a retest. Non-criteria aPL (aPS/PT) followed a similar trend. aCL and aB2GP1 measured with two different technologies were highly correlated. PC4d and IgG of the three aPL were at best moderately correlated even when only positive aPL samples were analyzed (coefficient: 0.1917 to 0.2649). Conclusions: High titers aPL are often persistently positive, allowing an earlier diagnosis and risk assessment at the time of the initial screening. Conversely, a retest may be necessary for low titers. The high correlation between two methodologies suggests that these findings are independent of assay platform. The low to moderate correlation between PC4d and aPL might suggest a possible additive value to evaluate association with thrombosis in autoimmune diseases. [ABSTRACT FROM AUTHOR]

Background: Visualizing the ultraviolet (UV) dose on skin serve as an intuitive approach to ensure appropriate sunscreen usage and reduce the risk of erythema. UV dose is determined by a number of external factors, such as properties of sunscreens, weather, and type of outdoor activity. We propose a framework for visualizing UV doses that considers various external factors. Materials and methods: First, the skin of a three‐dimensional human model was represented using triangular meshes, and various static postures and dynamic motions were simulated to express outdoor activities. Then, we evaluated the persistency and insufficiency properties of sunscreen, which are time dependent and directly affect the effectiveness of the sunscreen skin protection factor (SPF) during UV exposure. Finally, to calculate the UV dose in real time, we tracked the trajectory of the sun and motion of the skin while considering the time‐dependent properties of sunscreen. Results: An S/W system was implemented based on the proposed framework to visualize the distribution of UV doses through dynamic color changes in exposed skin areas. The color types include true colors, which represent the minimum erythema dose (MED), and pseudo colors representing states before 1 MED is reached. We devised various examples to discuss the usability of the proposed framework. Conclusion: The system conveniently displays the MED according to an individual's skin phototype. When the properties of a wide range of commercial sunscreens are added to the system database, it is expected that the rate of appropriate sunscreen usage by customers will increase. [ABSTRACT FROM AUTHOR]

BackgroundClassification criteria for antiphospholipid syndrome (APS) require that antiphospholipid antibody (aPL) positivity is confirmed after at least 12 weeks. We tested the hypothesis that aPL at high titers remain positive while low titers fluctuate over time. As both platelet-bound C4d (PC4d) and aPL are associated with thrombosis in systemic lupus erythematosus (SLE), we also evaluated whether PC4d can aid in APS diagnosis.MethodsData from serum or plasma sent to Exagen’s laboratory for routine aPL testing were analyzed. Anti-cardiolipin (aCL) and anti-beta2 glycoprotein-1 antibodies (aB2GP1) were measured by chemiluminescence or ELiA fluorescence enzyme immunoassay; anti-phosphatidylserine/prothrombin complex antibodies (aPS/PT) by ELISA; PC4d by flow cytometry. Statistical analysis included descriptive statistics, logistic regression, and Pearson correlation.ResultsMore than 80% of positive samples with aCL and aB2GP1 at high titers - but not low titers - were positive at a retest. Non-criteria aPL (aPS/PT) followed a similar trend. aCL and aB2GP1 measured with two different technologies were highly correlated. PC4d and IgG of the three aPL were at best moderately correlated even when only positive aPL samples were analyzed (coefficient: 0.1917 to 0.2649).ConclusionsHigh titers aPL are often persistently positive, allowing an earlier diagnosis and risk assessment at the time of the initial screening. Conversely, a retest may be necessary for low titers. The high correlation between two methodologies suggests that these findings are independent of assay platform. The low to moderate correlation between PC4d and aPL might suggest a possible additive value to evaluate association with thrombosis in autoimmune diseases.

The freeze–thaw cycles and joint will deteriorate the strength characteristics of jointed rock mass and may lead to geotechnical failures in cold regions. Former studies mainly focus on the effect of freeze–thaw conditions on the mechanical properties of rock. However, for rock engineering, rock joints are ubiquitous in rock mass engineering, and the water in rock joints will experience freeze–thaw process when temperature varies alternatively. The frost heaving pressure generated during this process causes the joints to propagate and hence will eventually leads to the failure of rock masses. However, few researches focus on the degradation of strength characteristics of rock joints under freeze–thaw cycles, especially for joint damage evolution mechanism of shear strength characteristics, which is actually crucial factor for rock masses stability. Therefore, in this paper, a large number of shear experiments were conducted to investigate the influence of freeze–thaw cycle-induced joint shearing degradation on cohesion as well as friction angle of joints with considering joint persistency values. Based on the damage mechanics, together with the experimental results, the damage variables of shear strength parameters under freezing–thawing cycles are analyzed. In addition, a damage evolution model for joint shearing under freeze–thaw cycles is established with considering freeze–thaw cycles as well as joint persistency, and the feasibility and capability of this proposed model are then further verified both experimentally and theoretically. [ABSTRACT FROM AUTHOR]

Festulolium are hybrids obtained by inter crossing of species from the genera Festuca and Lolium. Initially, idea was to combine Festuca tolerance to abiotic stresses and edaphic and climatic adaptability with Lolium high yield, digestibility and compatibility with intensive grasslands management. All Festulolium cultivars of the predominant contribution of Lolium genome (Lolioid type) are productive, with high quality and digestible forage, but their areal of cropping is limited according to Lolium drought susceptibility. Persistency and productivity of 15 different Lolioid Festulolium cultivars and 6 standard Festuca and Lolium species cultivars were investigated in a moderate continental climate in Kruševac, Serbia. Plots in the trial (7,5m2 ) were completely randomized, each in 3 replications. Summer persistency was analyzed by evaluation of ground cover reduction after summer periods in the second and third years. Concerning hybrid combination, best persistency (38.5% of coverage reduction in the third year) was determined for hybrid between Lolium multiflorum x Festuca arundinacea var. glaucescens even though there was only one cultivar of this type. The majority of cultivars were Lolium multiflorum x Festuca pratensis hybrids (8) and they showed residual coverage between 30 and 52%. At the end of the third year of the study, the highest dry matter yield was determined for hybrids Lolium multiflorum x Festuca gigantea and Lolium multiflorum x Festuca pratensis type. The general conclusion is that most cultivars suffered from severe stand density reduction after the first year of cutting and therefore had a lower dry matter yield compared to Festuca control cultivars, but showed significantly better persistency and higher values for dry matter yield in comparison with Lolium cultivars. [ABSTRACT FROM AUTHOR]

Lactation milk yield in dairy bovines is closely related with, and therefore a function of, peak yield, persistency and lactation length. Therefore, characteristics, curve, and persistency of lactation were studied in Jaffarabadi (Bubalus bubalis) buffaloes. A total of 1,15,339 daily morning and evening milk production performance records in 176 lactations of 1st to 6th parity of 30 Jaffarabadi buffaloes lactating at the Cattle Breeding Farm, JAU, Junagadh, Gujarat over a period of 28 years (1991-2018) were used for the study. Overall lactation length (LL), total lactation milk yield (TLMY), and standard lactation milk yield (SLMY) of the Jaffarabadi buffalo averaged 325.90 ± 5.53 days, 2009.31 ± 42.13 lit and 1872.61 ± 32.88 lit, respectively. Overall daily peak yield (DPY) was 11.27 ± 0.20 lit/day, attained at 102.00 ± 4.68 days postpartum. Overall weekly peak yield (WPY) and weeks to attain WPY averaged 64.79 ± 1.09 lit/week and 13.72 ± 0.64 weeks, respectively. Weekly milk yield could be predicted using linear function [(ŷ = 59.149 + (-0.6634) x X)] and logarithmic function [(ŷ = 1.80 x (-0.0008)^X)] with an accuracy of 66 to 73%. In contrast, monthly milk yield could be predicted using linear function [(ŷ = 261.64 + (-13.229) x X)] and logarithmic function [(ŷ = 2.45 x (-0.035)^X)] with comparatively more precision, R² value being 79.7 to 81.2 %. Overall persistency in terms of weekly and monthly milk yield was estimated to be 98.03±0.24% and 91.24±0.59%, respectively. [ABSTRACT FROM AUTHOR]

The objective of this study was to examine fluctuations in white clover (Trifolium repens L.) content in perennial ryegrass (Lolium perenne L.) swards within a high nitrogen (250 kg N/ha) input grazing dairy system. The data came from a larger, overall system experiment within which all management and growing condition variables were categorised each year for the 40 paddocks that contained perennial ryegrass-white clover swards, over four growing years. Within that study, eight perennial ryegrass cultivars were examined, each sown individually with two white clover cultivars in a 50:50 mix of 'Chieftain' and 'Crusader'. To determine management associations and meteorological patterns with white clover content and rate/direction of change, separate generalised linear models were used to analyse each individual management or meteorological variable. Paddocks with high white clover contents were associated with lower pre- and post-grazing sward heights, lower pasture cover over the winter period and shorter over-winter period. Perennial ryegrass cultivars with lower pre- and post-grazing height, lower pre-grazing pasture mass and pasture yield removed, all retained more white clover in their swards. Soil fertility remained a key factor that affected white clover persistence influencing the degree of responses in all treatments, particularly soil phosphorus (P) levels. Beyond this, higher white clover contents and lower rates of white clover decline were associated with paddocks that received lower rainfall, had higher soil moisture deficits and received more radiation into the base of the sward, particularly around the time of grazing. [ABSTRACT FROM AUTHOR]