Abstract Objectives To evaluate the linkage underpinning different clinical conditions as painful TMD and neck pain in patients affected by primary headaches. Materials and methods In this machine learning study, data from medical records of patients with headaches as migraine, tension-type headache (TTH) and other primary ones, referring to a University Hospital over a 10-year period were analysed. VAS was used to evaluate the intensity of the TMD and neck pain. Moreover, the magnetic resonance imaging was used to supplement the clinical data. Results A total of 300 patients (72 male, 228 female), mean aged 37.78 ± 5.11 years, were included. Higher TMD and neck pain VAS in migraine patients were reported. The machine learning analysis focussed on type of primary headache demonstrated that a higher TMD VAS was correlated to migraine, whereas a higher neck pain VAS was correlated to TTH or migraine. Concerning the TMD type, arthrogenous and mixed TMD were correlated to mild-moderate TMD pain (depending on neck pain intensity), whereas myogenic TMD was correlated to moderate-severe TMD pain. Conclusions Machine-learning approach highlighted the complexity of diagnosis process and demonstrated that neck pain might be an influential variable on the belonging to different group of headaches in TMD patients.

Temporomandibular disorders and neck pain in primary headache patients: a retrospective machine learning study

In this research data representing 72,946 primiparous cows from 724 herds with 638,063 total test day records calved between 2001 and 2011. These data were analysed to determine the effect of age at first and season of calving on parameters of the Wood lactation curve. Also, genetic trend of the lactation curve parameters in different calving years were evaluated. The results indicate that the highest rate of atypical lactation curve was related to cows that calved in summer (28.05 %). The maximum phenotypic relationship between initial milk yield and total 305-d milk yield was observed in cows calved in spring (0.40). The role of peak yield is more than peak time on 305-d total milk yield in primiparous Holstein. One month increase in age at first calving from 18 to 26 month raised 305-d milk yield by around 138 kg and from 27 to 32 month decreased by 61 kg. The persistency of lactation between 101 and 200 days is higher than that of 201–305 days. Our results indicate that the shape of lactation curve is largely dependent on the season of calving (higher level of milk production in cows which calved in autumn and winter). The heritabilities of parameters of lactation curve and persistency measures were low. The genetic trends for peak time, peak yield and 305-d milk yields were positive and estimated to be 0.019, 0.021 and 8.13 kg/year respectively. So the range from 24 to 26.5 month of calving is the optimum calving time in primiparous Holstein for maximizing 305-d milk yield.

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Effects of season and age at first calving on genetic and phenotypic characteristics of lactation curve parameters in Holstein cows

This study was carried out to investigate genetic, non-genetic affecting factors and estimate genetic parameters for milk production and reproductive traits of Holstein cows via animal model. The data was obtained from a commercial farm (Safi Masr for Developing the Animal Resources), located in the Nile Delta, Dakahlia, Egypt. Data included 4791 records of 1797 cows, 794 dams and 67 sires that represented the period from 2002 to 2012. The means and coefficient of variability (CV%) of milk traits as total milk yield (TMY), 305 day milk yield (305-dMY), lactation period (LP) and dry period (DP) were 5787.8 kg (31.1%), 4695 kg (22.1%),  332 day (14.9%) and 72.3 day (27.7%), respectively. Also, the means (CV%) of reproductive traits as days open (DO) and age at first calving (AFC) were 157.9 day (22.6%) and 30.5 month (16.8%), respectively. Sire, dam, parity of cow, year and season of calving had significant effects on traits studied. Heritability estimated were 0.223, 0.184, 0.112, 0.118, 0.105 and 0.285 for TMY, 305-dMY, LP, DP, DO and AFC, respectively. Estimated r G and r P among milk production traits were positive but it takes negative trend with DP and DO. Moderate heritability estimates and positive genetic correlation for most of traits studied suggested that genetic improvement of these traits would be achieved via multi-trait selection.

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Genetic and non-genetic analysis for milk production and reproductive traits in Holstein cattle in Egypt

Nowadays, when there is much concern about the demographic decline of Europe and the stringent need for public policies that support intelligent, sustainable, and inclusive growth in times of population ageing, this study aims to validate several hypotheses regarding the post-graduation migration intentions of students in economics. To analyse these intentions in the context of Romanian yearly increases of out-migration flows to Western countries, the answers to the questionnaire used for this study were obtained from three important Romanian universities. Using georeferencing, neural networks-based data mining, and two types of regression analysis, the results represent a relevant contribution to the limited body of literature. They empirically show that motivations and attitudes towards a meritocratic environment for professional advancement, and individual freedom are positive key factors for students’ migration intentions after graduation. In addition, the paper emphasises the secondary role of religiosity and intergenerational transfer of parental migration experience. It also finds that, although the income level has some influence on these intentions, its role is far less important than the one emphasised in the specific literature, which leads us to the conclusion that non-economic motivations matter more than the economic ones for the potential decision to migrate after graduation.

Exploring the Influence of Personal Motivations, Beliefs and Attitudes on Students’ Post-Graduation Migration Intentions: Evidence from Three Major Romanian Universities

In this paper, we explore the determinants of being satisfied with a job, starting from a SHARE-ERIC dataset (Wave 7), including responses collected from Romania. To explore and discover reliable predictors in this large amount of data, mostly because of the staggeringly high number of dimensions, we considered the triangulation principle in science by using many different approaches, techniques and applications to study such a complex phenomenon. For merging the data, cleaning it and doing further derivations, we comparatively used many methods based on spreadsheets and their easy-to-use functions, custom filters and auto-fill options, DAX and Open Refine expressions, traditional SQL queries and also powerful 1:1 merge statements in Stata. For data mining, we used in three consecutive rounds: Microsoft SQL Server Analysis Services and SQL DMX queries on models built involving both decision trees and naive Bayes algorithms applied on raw and memory consuming text data, three LASSO variable selection techniques in Stata on recoded variables followed by logistic and Poisson regressions with average marginal effects and generation of corresponding prediction nomograms operating directly in probabilistic terms, and finally the WEKA tool for an additional validation. We obtained three Romanian regional models with an excellent accuracy of classification (AUROC > 0.9) and found several peculiarities in them. More, we discovered that a good atmosphere in the workplace and receiving recognition as deserved for work done are the top two most reliable predictors (dual-core) of career satisfaction, confirmed in this order of importance by many robustness checks. This type of meritocratic recognition has a more powerful influence on job satisfaction for male respondents rather than female ones and for married individuals rather unmarried ones. When testing the dual-core on respondents aged 50 and over from most of the European countries (more than 75,000 observations), the positive surprise was that it undoubtedly resisted, confirming most of our hypotheses and also the working principles of support for replication of results, triangulation and the golden rule of robustness using cross-validation.

https://www.mdpi.com/2076-3417/10/7/2573/pdf

Exploring the Patterns of Job Satisfaction for Individuals Aged 50 and over from Three Historical Regions of Romania. An Inductive Approach with Respect to Triangulation, Cross-Validation and Support for Replication of Results

A total of 3460 lactation records that represented 1059 dairy Holstein-Friesian cows were used in the present study that aimed to estimate genetic parameters such as heritability, genetic correlations, phenotypic correlations and genetic trends for some productive and reproductive traits. Studied traits were total milk yield, days in milk, fat %, protein %, dry period, age at first calving, number of services per conception, days open and calving interval. Data were collected from Egyptian Copenhagen Company in Alexandria-Cairo desert road for cows calved from 1998 to 2010. Least square analysis of mixed sire model was used in analysis using Harvey (1990) program. Heritability estimates were high for all traits and very high for fat and protein % that exceeded 0.83 in two lactations. Genetic correlations were higher than phenotypic correlations and were high especially among production traits. Regression coefficients of genetic trends were positive for all studied traits except for days in milk and days open (in second lactation) and age at first calving. Generally, the current results showed genetic improvement of most of traits that reflect the efficiency of selection programs.

https://scvmj.journals.ekb.eg/article_78285_74f0a170a39b91550c5a8c4581c18137.pdf

Estimation of heritabilities, genetic correlations, phenotypic correlations and genetic trends for production and reproduction traits of Holstein-Friesian dairy cattle using sire model

This study was planned to evaluate the performance of linear discriminant analysis (LDA) and binary logistic regression (BLR) for differentiation between Friesian cows and buffaloes on the basis of days in milk (DIM), milk yield per year (kg), days open (DO), calving interval (CI), and age at first calving (AFC, month). Considering the assumptions behind each method, LDA and BLR were compared according to sample size impact and lack of multivariate normality of predictors. A random sample of 1070 cases was selected from the animals being represented by all predictors. The comparison between LDA and BLR was based on the significance of coefficients, classification rate, and area under ROC curve (AUC). Results showed that both methods selected DIM, DO and AFC as the significant (P < 0.01) contributors for data classification. The percentages of correct classification were 67.4% and 67.5%, for LDA and BLR, respectively. Besides, The AUCs were 0.660 and 0.664, for LDA and LR, respectively. Overall, sample size has the same impact on both analyses. However, BLR showed slight superiority for animals being correctly classified. In conclusion, LDA and BLR can be used effectively for classification of dairy cattle breeds, even with violation of normality assumption.

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The Robustness of Binary Logistic Regression and Linear Discriminant Analysis for the Classification and Differentiation between Dairy Cows and Buffaloes

The present study was conducted to investigate the effects of some non-genetic factors as year and season of calving on productive and reproductive traits of dairy Holstein-Friesian cows together with the effect of genetic variation in the form of sire analysis on these traits. A total of 3460 lactation records were used for 1059 dairy cows that represented the period from 1998 to 2010. Studied traits were total milk yield (TMY), days in milk (DIM), fat yield (FY), protein yield (PY), dry period (DP), age at first calving (AFC), number of services per conception (NSC), days open (DO) and calving interval (CI). Analysis was done using sire model by Harvey (1990) software for the first and second lactations. The present herd showed high milk production around 8750 kg per lactation period. Sire effects were significant (P ≤ 0.05) on all traits. Year and season of calving had significant effects on most of studied traits. Linear and quadratic regression coefficients of age at first calving, days open and total milk yield were significant for most of traits. Balanced and unbiased estimates for genetic evaluation could be obtained if the environmental factors fitted in the statistical models.

https://scvmj.journals.ekb.eg/article_78284_ec23c24cc7269fe04d11f5bb6f11f4ea.pdf

Genetic and Non-genetic Factors Affecting some Productive and Reproductive Traits in Holstein-Friesian Dairy Cows Raised in Egypt for the First Two Lactations

This research aimed to study the efficiency of freshwater fish farms among three governorates: El Sharkia, Ismailia, and Kafr El Sheikh during the period 2015 and 2016. Data of productive and economic parameters of 64 freshwater fish farms were investigated through farm records in addition to research questionnaire. One-way ANOVA procedure was fitted. All statistical analyses were carried out by SPSS for windows. The current study showed that farm locality has a notable effect on the productive and economic parameters of freshwater fish farms. Regarding total fish production, Kafr El Sheikh governorate had the highest quantity of fish production, while El Sharkia was the lowest. From the results of analysis of locality effect on economic efficiency parameters (TC, TR and NP (EGP)/kg), it was concluded that although El Sharkia governorate had the highest value of total cost (16.34 EGP) and Kafr El Sheikh governorate had the lowest one (13.12 EGP), the highest profit recorded was in El Sharkia governorate (9.01 EGP). It is strongly recommended to encourage the government to invest more in aquaculture production in studied areas as the aquaculture was reported to be a profitable business in these.

https://scvmj.journals.ekb.eg/article_60524_4a99c4f3e0e56567473d134f9a64833e.pdf

Mohamed Osman

Papers

Estimation of heritabilities, genetic correlations, phenotypic correlations and genetic trends for production and reproduction traits of Holstein-Friesian dairy cattle using sire model

The Robustness of Binary Logistic Regression and Linear Discriminant Analysis for the Classification and Differentiation between Dairy Cows and Buffaloes

Genetic and Non-genetic Factors Affecting some Productive and Reproductive Traits in Holstein-Friesian Dairy Cows Raised in Egypt for the First Two Lactations

Comparing The Productive and Economic Efficiency of Some Freshwater Fish Farms in El Sharkia, Ismailia, and Kafr El Sheikh