Canonical Analysis Research Articles

Comparative analysis of key fiber characteristics in white Pima cotton (Gossypium barbadense L.): Native accessions from the Peruvian Amazon

AbstractThe fiber quality of cotton (Gossypium barbadense L.) native to the Peruvian Amazon region is one of the most versatile and essential natural fibers in the Peruvian textile industry. There is little information about the fiber quality traits of cotton genotypes native to the Peruvian Amazon region. This study investigated the fiber quality traits of Peruvian Pima cotton accessions native to the Amazon region of the La Convención Province, Cusco, Peru, to determine the lines with the greatest potential for improving fiber quality in cotton genetic breeding programs. A total of 14 cotton accessions with white fiber color, being 12 accessions of G. barbadense L. (Pima cotton) and two accessions of Gossypium sp. (unknown cotton), were analyzed. The fiber properties determined using the high volume instrument method included seven characteristics. All fiber properties were classified into five quality classes. The data on fiber quality properties were subjected to distribution, correlation, and canonical variable analysis. The results of fiber quality properties showed that the two accessions of Gossypium sp. (unknown cotton) can be promising options to be used as high‐quality fiber progenies in crop genetic breeding programs or can be cultivated by regional farmers for the purpose of producing cotton with high fiber quality. Future investigations could utilize other methods of fiber quality analysis and compare the fiber quality of these cotton accessions native to the Peruvian Amazon region with other cotton species grown worldwide to improve the understanding of Pima cotton fiber quality and its applicability in different contexts of the textile industries.

Effects of meteorology and lunar cycle on the post-thawing quality of avian sperm.

Various climatological and lunar cycle parameters have a direct impact on animal reproduction, and in the case of the avian species, spermatozoa are extremely sensitive to heat stress. These parameters could influence sperm freezability, which will ultimately affect post-thawing semen quality, being sperm motility in roosters a relevant indicator of this quality as it is highly related to fertility. Therefore, the objective of the present study is to determine which are the climatological and lunar cycle parameters that have a greater effect on sperm freezability in roosters. Sperm was obtained from 16 Utrerana breed roosters and a total of 27 replicates were performed. A pool was made with those ejaculates that met the minimum quality criteria for each replicate, and four freezing-thawing samples per replicate were analyzed. The straws were thawed, and sperm motility was evaluated, classifying the results obtained into four seminal quality groups according to the guidelines of the Food and Agriculture Organization of the United Nations (Group 1: Good, Group 2: Satisfactory, Group 3: Acceptable but undesirable and Group 4: Unsatisfactory). The following traits were recorded for each day of semen collection: maximum temperature, minimum temperature, maximum barometric pressure, minimum barometric pressure, maximum gust, wind direction, mean wind speed, sunshine hours, rainfall, moon phase, and percentage of illuminated lunar surface over the total area. A discriminant canonical analysis was performed to determine which of these parameters offered the most information when classifying an ejaculate in each quality group, with minimum temperature, the new moon as moon phase, minimum barometric pressure, and rainfall being the most significant variables. According to the results obtained, semen quality decreases when temperature and precipitation are lower, pressure is higher, and when there is a new moon phase. Therefore, these environmental conditions should be avoided for sperm collection and processing.

Different roles of circulating and intramuscular GDF15 as markers of skeletal muscle health.

Growth Differentiation Factor 15 (GDF15) is a mitokine expressed in response to various stresses whose circulating levels increase with age and are associated with numerous pathological conditions, including muscle wasting and sarcopenia. However, the use of circulating GDF15 (c-GDF15) as a biomarker of sarcopenia is still debated. Moreover, the role of GDF15 intracellular precursor, pro-GDF15, in human skeletal muscle (SM-GDF15) is not totally understood. In order to clarify these points, the association of both forms of GDF15 with parameters of muscle strength, body composition, metabolism and inflammation was investigated. the levels of c-GDF15 and SM-GDF15 were evaluated in plasma and muscle biopsies, respectively, of healthy subjects (HS) and patients with lower limb mobility impairment (LLMI), either young (<40 years-old) or old (>70 years-old). Other parameters included in the analysis were Isometric Quadriceps Strength (IQS), BMI, lean and fat mass percentage, Vastus lateralis thickness, as well as circulating levels of Adiponectin, Leptin, Resistin, IGF-1, Insulin, IL6, IL15 and c-PLIN2. Principal Component Analysis (PCA), Canonical Discriminant Analysis (CDA) and Receiving Operating Characteristics (ROC) analysis were performed. c-GDF15 but not SM-GDF15 levels resulted associated with decreased IQS and IGF-1 levels in both HS and LLMI, while only in LLMI associated with increased levels of Resistin. Moreover, in LLMI both c-GDF15 and SM-GDF15 levels were associated with IL-6 levels, but interestingly SM-GDF15 is lower in LLMI with respect to HS. Furthermore, a discrimination of the four groups of subjects based on these parameters was possible with PCA and CDA. In particular HS, LLMI over 70 years or under 40 years of age were discriminated based on SM-GDF15, c-GDF15 and Insulin levels, respectively. our data support the idea that c-GDF15 level could be used as a biomarker of decreased muscle mass and strength. Moreover, it is suggested that c-GDF15 has a different diagnostic significance with respect to SM-GDF15, which is likely linked to a healthy and active state.

Sleep fragmentation after traumatic brain injury impairs behavior and conveys long-lasting impacts on neuroinflammation

Traumatic brain injury (TBI) causes a prolonged inflammatory response in the central nervous system (CNS) driven by microglia. Microglial reactivity is exacerbated by stress, which often provokes sleep disturbances. We have previously shown that sleep fragmentation (SF) stress after experimental TBI increases microglial reactivity and impairs hippocampal function 30 days post-injury (DPI). The neuroimmune response is highly dynamic the first few weeks after TBI, which is also when injury induced sleep-wake deficits are detected. Therefore, we hypothesized that even a few weeks of TBI SF stress would synergize with injury induced sleep-wake deficits to promote neuroinflammation and impair outcome. Here, we investigated the effects of environmental SF in a lateral fluid percussion model of mouse TBI. Half of the mice were undisturbed, and half were exposed to 5 h of SF around the onset of the light cycle, daily, for 14 days. All mice were then undisturbed 15–30 DPI, providing a period for SF stress recovery (SF-R). Mice exposed to SF stress slept more than those in control housing 7–14 DPI and engaged in more total daily sleep bouts during the dark period. However, SF stress did not exacerbate post-TBI sleep deficits. Testing in the Morris water maze revealed sex dependent differences in spatial reference memory 9–14 DPI with males performing worse than females. Post-TBI SF stress suppressed neurogenesis-related gene expression and increased inflammatory signaling in the cortex at 14 DPI. No differences in sleep behavior were detected between groups during the SF stress recovery period 15–30 DPI. Microscopy revealed cortical and hippocampal IBA1 and CD68 percent-area increased in TBI SF-R mice 30 DPI. Additionally, neuroinflammatory gene expression was increased, and synaptogenesis-related gene expression was suppressed in TBI-SF mice 30 DPI. Finally, IPA canonical pathway analysis showed post-TBI SF impaired and delayed activation of synapse-related pathways between 14 and 30 DPI. These data show that transient SF stress after TBI impairs recovery and conveys long-lasting impacts on neuroimmune function independent of continuous sleep deficits. Together, these finding support that even limited exposure to post-TBI SF stress can have lasting impacts on cognitive recovery and regulation of the immune response to trauma.

Variety is the spice: The role of morphological variation of Triatoma infestans (Hemiptera, Reduviidae) at a macro-scale

Chagas disease is caused by the protozoan parasite Trypanosoma cruzi (Chagas, 1909). One of the primary vectors of T. cruzi in South America is Triatoma infestans (Klug, 1834). This triatomine species is distributed across a huge latitudinal gradient, inhabiting domiciliary , peridomiciliary , and wild environments. Its wide geographic distribution provides an excellent opportunity to study the relationships between environmental gradients and intraspecific morphological variation. In this study, we investigated variations in wing size and shape in T. infestans across six ecoregions. We aimed to address the following questions: How do wing size and shape vary on a regional scale, does morphological variation follow specific patterns along an environmental or latitudinal gradient, and what environmental factors might contribute to wing variation? Geometric morphometric methods were applied to the wings of 162 females belonging to 21 T. infestans populations, 13 from Argentina (n = 105), 5 from Bolivia (n = 42), and 3 from Paraguay (n = 15). A comparison of wing centroid size across the 21 populations showed significant differences. Canonical Variate Analysis (CVA) revealed significant differences in wing shape between the populations from Argentina, Bolivia, and Paraguay, although there was a considerable overlap, especially among the Argentinian populations. Well-structured populations were observed for the Bolivian and Paraguayan groups. Two analyses were performed to assess the association between wing size and shape, geographic and climatic variables: multiple linear regression analysis (MRA) for size and Partial Least Squares (PLS) regression for shape. The MRA showed a significant general model fit. Six temperature-related variables, one precipitation-related variable, and the latitude showed significant associations with wing size. The PLS analysis revealed a significant correlation between wing shape with latitude, longitude, temperature-related, and rainfall-related variables. Wing size and shape in T. infestans populations varied across geographic distribution. Our findings demonstrate that geographic and climatic variables significantly influence T. infestans wing morphology.

Fault detection using machine learning based dynamic ICA-distributed CCA: Application to industrial chemical process

Unexpected accidents and events in industrial chemical processes have resulted in a considerable number of causalities and property damage. Safety process management in industrial chemical processes is critical to avoid and ensure casualties and property damage. However, due to the immense scope and high complexity of current industrial chemical processes, the traditional safety process management approaches cannot address these challenges to attain adequate fault detection accuracy. To address this issue, an innovative machine learning-based distributed canonical correlation analysis-dynamic independent component analysis (DICA-DCCA) approach is needed to improve the fault detection effectiveness of complicated systems. The (DICA-DCCA) model could potentially detect anomalies and faults in industrial chemical data by utilizing three essential statistics:Id2,Ie2and squared prediction error (SPE). The practical effectiveness of the proposed frameworks is evaluated and compared using a continuous stirred tank reactor (CSTR) framework as a standard benchmark study. The research findings present that the suggested (DICA-DCCA) approach is more resilient and effective in detecting abnormalities and faults than the ICA and DICA approaches with FDR 100 % and FAR 0 %. The implied research approach is robust, operational, and productive.

A two-group canonical variate analysis biplot for an optimal display of both means and cases

AbstractCanonical variate analysis (CVA) entails a two-sided eigenvalue decomposition. When the number of groups, J, is less than the number of variables, p, at most $$J-1$$ J - 1 eigenvalues are not exactly zero. A CVA biplot is the simultaneous display of the two entities: group means as points and variables as calibrated biplot axes. It follows that with two groups the group means can be exactly represented in a one-dimensional biplot but the individual samples are approximated. We define a criterion to measure the quality of representing the individual samples in a CVA biplot. Then, for the two-group case we propose an additional dimension for constructing an optimal two-dimensional CVA biplot. The proposed novel CVA biplot maintains the exact display of group means and biplot axes, but the individual sample points satisfy the optimality criterion in a unique simultaneous display of group means, calibrated biplot axes for the variables, and within group samples. Although our primary aim is to address two-group CVA, our proposal extends immediately to an optimal three-dimensional biplot when encountering the equally important case of comparing three groups in practice.

Fault detection and isolation for dynamic non-stationary processes with stationary subspace-based canonical variate analysis

As modern science and technology advance, industrial processes have grown more complex, characterized by dynamic and non-stationary features. Existing methods often focus on single features, necessitating the development of approaches capable of addressing multiple characteristics. This study introduces a novel approach based on stationary subspace canonical variate analysis for fault detection and isolation in dynamic non-stationary processes. The proposed model combines the strengths of stationary subspace analysis and canonical variate analysis (CVA) by introducing new detection indices and their corresponding contributions. These new indices, derived from CVA indices, are further transformed into quadratic form to facilitate easy calculation of contributions, which are based on reconstruction. A numerical example and simulation of the continuous stirred tank reactor process are carried out to demonstrate the superior sensitivity and accuracy of the proposed approach.

Deletion of Kcnj16 altered transcriptomic and metabolomic profiles of Dahl salt-sensitive rats

The essential role of inwardly rectifying K+ Channel Kir5.1 (encoded by the Kcnj16 gene) in renal salt handling and blood pressure control has been demonstrated in both human and animal models. However, the underlying mechanisms are still not fully understood. Here, we aimed to integrate transcriptomics and metabolomics to profile the comprehensive changes of genes and metabolites under the deletion of Kcnj16 in the Dahl salt-sensitive (SS) rat background to identify novel mechanisms. For the transcriptomics profiling, we performed RNA-sequencing on kidney cortex tissue of Kcnj16 knockout (KO) and wild-type (WT) SS rats (N=5 per group). For the metabolomics profiling, we performed untargeted metabolomics of kidney cortex tissue, plasma, and urine of KO (N=6) and WT (N=5) rats. Transcriptomics analysis revealed over 6,000 differentially expressed genes in KO rats compared to WT rats, with renin Ren (the gene encoding renin) being the most upregulated gene. Consistent with the phenotype observed in the KO rats, ingenuity pathway analysis (IPA) based on the transcriptomic profile predicted reduced blood pressure and kidney damage and increased ion transport. Canonical pathway analysis suggested activation of metabolic-related pathways [e.g., xenobiotic metabolism, tricarboxylic acid (TCA) cycle, phenylalanine degradation, etc.] and suppression of immune responses-related pathways [e.g., pathogen-induced cytokine storm signaling pathway, macrophage classical activation signaling pathway, nuclear factor of activated T cells (NFAT) pathway, etc.] in KO rats. Untargeted metabolomic analysis suggested distinct metabolic profiles of plasma, urine, and kidneys between WT and KO rats, with 219, 790, and 31 differentially expressed metabolites identified in plasma, urine, and kidney in KO rats compared to WT rats. Canonical pathway analysis identified spermine and spermidine degradation pathways in both plasma and urine and taurine biosynthesis pathways in both urine and kidney. Integration analysis based on transcriptomic and metabolomic profiles suggested an altered TCA cycle, amino acid, and reactive oxygen species metabolism. In conclusion, besides significantly altered ion transport, our transcriptomics and metabolomics data suggest significant suppressed immune responses-related and altered metabolic-related pathways in SS rats lacking Kir5.1, which provides new insights into the underlying mechanisms of the regulation of blood pressure and renal function by Kir5.1. This work is supported by National Institutes of Health Grants R35 HL135749 and R01 DK135644 (to A.S.), Department of Veteran Affairs grant I01 BX004024 (to A.S.), the American Physiological Society Postdoctoral Fellowship (to B.X.) and the American Society of Nephrology Dimitrios G. Oreopoulos Research Fellowship Award (to L.V.D.). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Optimized microwave-assisted azadirachtin extraction using response surface methodology

The neem tree (Azadirachta indica A. Juss) is grown mainly for shade, fuel, and numerous non-timber forest products using its leaves, fruit, and bark. It produces an essential oil that is used as a source for obtaining bioinsecticides, with a broad spectrum of action in agricultural production. Its bioinsecticidal activity is due to the presence of triterpenes, such as azadirachtin, a product in continued growth of the global biopesticide market. Optimal conditions for neem oil extraction using response surface methodology (RSM) and microwave-assisted extraction (MAE) methods have been defined. However, the extraction conditions for these methods tend to consume high volumes of organic solvent and long extraction times. The aim of the present study is to determine the optimal conditions for the extraction of azadirachtin from neem seeds in a hydroalcoholic medium using MAE and RSM with a Box-Behnken design (BBD). A BBD was applied to evaluate the effects of the factors, magnetron voltage (X1), extraction time (X2), and pH of the extraction medium (X3), on the yield of the azadirachtin extraction process. The effect of each variable on the extraction yield was studied independently, considering the pure coefficients (linear and quadratic) on the three levels that were studied in the experiments. Moreover, the study experiments were conducted in triplicate, data were presented as mean and standard deviation, homogeneity of variances was estimated using Levene's test, and a two-way ANOVA with Tukey's post hoc analysis was performed to identify the experimental conditions that allowed us to find the highest extraction yield and to analyze whether the response surface model adequately described our data. The most significant effects of the model correspond to quadratic and interaction effects (p < 0.0001); the quadratic terms voltage (X1), extraction time (X2), and pH (X3); and the interaction effects between voltage-pH (X1*X3) and time-pH (X2*X3), which had a significant influence on the model. Moreover, a canonical analysis was performed. The optimal conditions were as follows: 69.22 V, 6.89 min, and a pH value of 4.35, coinciding with the zones shown in the contour plots. Furthermore, the response obtained at the optimal conditions was 37.5 μg of azadirachtin per gram of pretreated seed.

Geographical variation in the forewing shape of the red dwarf honeybees revealed by landmark-based geometric morphometrics

Accurate intraspecific variation assessment is the prerequisite for determining subspecies, evolutionarily significant units, or management units across a species' range. However, intraspecific variation assessment is often hindered by inaccurate morphological results from traditional methods or high-cost genetic analyses. Geometric morphometrics is a promising technique for quantifying and visualising intraspecific diversity. We used landmark-based geometric morphometrics to investigate forewing shape variation and microtaxonomy of populations of Apis florea Fabricius 1787 (Apidae: Apini), which originated from some parts of Asia and Africa based on the 19 landmarks plotted at the venation intersections of forewings. We collected samples of 162 colonies from 36 different localities. On average, 13 workers per colony were analysed (1851 bees in total). Distinct spatial structures and significant differences in wing shape between the studied populations were revealed using canonical variate analysis, and no considerable overlap was detected between the colonies belonging to the western and eastern populations. The populations at higher latitudes showed significantly larger centroid sizes than those at lower latitudes, and a clinal variation in forewing size was confirmed. Significant distance-decay relationships between the studied populations were observed so that the populations located at the maximum geographical distance showed the most significant distance from each other and vice versa. Wing geometric morphometrics was an accurate tool for the reliable estimation of the population structure of the red dwarf honeybees. It is essential to increase the reliability of these variations by combining the results with further molecular data.

Geometric morphometric evaluation of mandibles of four sheep breeds: Bardoka, İvesi, Polish Mountain sheep and Turcana.

The enduring relationship between humans and domestic sheep has evolved over millennia, showcasing diverse uses such as meat, milk, wool, leather and fur, shaped by geographical, historical, cultural and social factors. The sheep breeds discussed include the Ivesi from Southeastern Anatolia, known for its varied animal products; the resilient Turcana breed of Romania; Kosovo's Bardoka, valued for its triple-purpose characteristics; and Poland's Polish Mountain Sheep, uniquely utilized for milk production in cheese making. Sheep, with their enduring relationship with humans and significant economic importance, have attracted scientific interest in morphometric studies of their mandibles, yielding valuable data applicable across various fields including basic anatomy, veterinary clinical anatomy, zooarchaeology and veterinary forensic medicine. Traditional morphometric studies rely on statistical methods to compare length, depth and angular ratios between anatomical formations, often highlighting differences between specific points but not fully revealing shape variations between distinct groups. Geometric morphometric analysis has emerged as a preferred method in recent years, enabling shape analyses using coordinate data from various imaging techniques, facilitating a comprehensive examination of mandibular morphometrics among sheep breeds across different countries. This study involved four sheep breeds from different countries, namely İvesi from Turkey, Bardoka from Kosovo, Polish Mountain Sheep from Poland and Turcana from Romania, with a total of 70 mandibles sourced from various veterinary faculties. Mandibular photographs were meticulously captured, focusing on the right side of mandible pairs and placing landmarks and semi-landmarks along the entire edge, enabling geometric morphometric analysis using tpsUtil, tpsDig2 and MorphoJ software. The analysis included principal component analysis, canonical variate analysis and discriminant function analysis for pairwise comparisons, facilitating a comprehensive examination of mandibular shape variations among the different sheep breeds. Using geometric morphometric methods, this study analysed mandibles from four distinct sheep breeds sourced from different countries, revealing notable variations in regions such as the ramus mandibula, angulus mandibula and incisive areas, attributed to genetic, geographical and dietary influences, highlighting the importance of continued research to better comprehend these shape differences.

Catalytic Cracking of Oily Sludge using Nickel Metal Catalyst Embedded in Silica Derived from Adsorbent in a Gas Process Plant

Abstract. One of the Oily Sludge (OS) recycling methods is through catalytic cracking. This process involves the reaction breaking down large molecules into smaller ones with the help of a catalyst. Nickel (Ni) metal is often used as a catalyst because it can increase fuel liquid yield while reducing the coke formation. To enhance its performance, Ni metal can be embedded in a carrier material like Silica to form the Ni-Silica catalyst. In this research, OS sourced from a Gas Process Plant is treated with catalytic cracking using Ni-Silica, where the Silica used is derived from an Adsorbent activated with NaOH. Optimization of the cracking conditions is carried out using Response Surface Methodology (RSM) with a Box-Behnken design. The optimized cracking reaction conditions include temperature (713 K, 723 K, and 733 K), time (50 min, 60 min, and 70 min), and catalyst-to-OS ratio of 1:5, 1:6, and 1:7. Statistical analysis indicates that the relationship between the reaction condition variables and the Oil Liquid Product (OLP) falls into the moderate category, as shown by the coefficient of determination (R²) of 0.5. The calculated F-value for the deviation from the mathematical model is smaller than the F-Table value (9.2) at both 5% and 1% significance levels, with a value of 0.6. This indicates that the mathematical model generated can be accepted as the mathematical model within the range of reaction conditions in this study. Calculus analysis reveals that the optimum reaction conditions are a temperature of 717.34 K, a time of 58.58 min, and a catalyst-to-OS ratio of 1:6, 15. Canonical analysis indicates that for OLP, λ1= [-12.38], λ2= [-2.27], and λ3= [4.50], where lambda values indicate that the most sensitive response surface parameter for OLP is temperature, followed by the catalyst-to-sample ratio, and the least sensitive is reaction time. Keywords: Catalytic Cracking, Ni Metal, OS, RSM, Silica

Interaction of integral parameters of physical state and biological age of students aged 17-19 years old in the process of adaptation to standard and experimental physical education programs

Background and Study Aim. The process of adaptation to physical education programs is a critical factor influencing the health and physical development of students. Understanding how these programs affect both the physical state and biological age of students can significantly improve their effectiveness. The aim of the study is to investigate the interaction between integral parameters of physical state (PS) and biological age (BA) of students aged 17-19 years old in the process of adaptation to standard and experimental physical education (PE) programs. Material and Methods. The study involved 140 first-year students of the National University of Telecommunications - 80 males and 60 females. In the course of the research, the indices of functional state, physical fitness (PF) and physical development (PD), biological age (BA) were recorded in young men and women of the control (CG) and experimental (EG) groups. To process the experimental material, methods of dispersion and canonical analysis were used and multiple correlation and determination coefficients were calculated. Results. It was revealed that the impact of PS integral parameters on students' BA is stronger than the inverse influence of BA on PS parameters. The degree of BA reduction under the influence of the studied factors is most pronounced in the EG of girls and boys. The variability of the group of PD and PF indices is accompanied by the variability of most of the BA parameters’ dispersion in all studied groups of students. The factor of gender has the greatest impact on the BA of students. Girls have lower initial values of BA and it’s a more pronounced decrease by the end of the experiment. The effectiveness of the impact of an aerobically oriented experimental program on the improvement of students’ PS and reduction of BA was confirmed. Under the influence of the experimental program, the BA of EG girls decreases to a greater extent in comparison with EG boys and students of both control groups. Changes and differences in BA of boys and girls of EG and CG are due to the combined impact of the factor of PE software and that of adaptation changes of students' PS in the annual process of PE. In the group of boys and girls more pronounced influence on BA in the course of the experiment was produced by the factor of software and adaptation changes, respectively. Conclusions. The gender factor has the strongest impact on students' BA - girls have lower initial values of BA and it’s a more pronounced decrease by the end of the experiment in comparison with boys. Adaptation changes of PS in the process of software implementation are accompanied by a decrease in BA in the experimental groups. One of the criteria and confirmations of the effectiveness of the developed PE program is the degree of mutual influence of PS integral parameters, which is most pronounced in the reduction of BA in the experimental groups of girls and boys.

Rethinking the concept of punishment: modeling the level of danger posed by criminals to society

The rapid increase in crime rates in many countries is evidence of the ineffectiveness of the current punishment system and the need to rethink the existing approach to applying punitive sanctions to criminals, taking into account the threat they pose to others. This study aims to build an analytical model for an objective assessment of the level of danger posed by suspects (convicts/prisoners) to society, based on their socio-demographic characteristics and data on previous criminal activity. To achieve this goal, discriminant canonical analysis is used as a multivariate statistical method for classifying objects. The empirical base consisted of data on 13,010 convicts serving sentences in penitentiary institutions in Ukraine. Key factors that have a significant impact on the distribution of criminals into groups (high, moderate, low) according to the level of danger they pose to society have been identified: the age at which a person was first sentenced, early dismissals, suspended convictions, education level, type of employment, the motivation for dismissal. An optimal canonical discriminant model has been constructed that allows for the accurate classification of new cases into the identified groups. The results obtained can be used in the judicial system, probation services, and law enforcement agencies to make informed decisions regarding the measure of punishment, parole, level of supervision, and ensuring public safety. The proposed applied solution can be integrated into an automated analytical system to increase the efficiency of the judicial system.

Stress and predictive psychosocial variables in Ecuadorian university teachers

ABSTRACT University professors are exposed to high levels of stress as a result of the multiple activities involved in their profession. The objective of this research is to explain how a sequence of psychosocial variables directly and indirectly influences stress. Method: A non-probabilistic and non-clinical sample of 480 professors from different Ecuadorian universities was surveyed online, and participation was anonymous. Sequential Canonical Analysis was used (SEQCA). This paper examined the following multivariate sequence: (1) resilience; (2) psychological inflexibility; (3) loneliness; (4) life engagement; and (5) stress. The model also considered the indirect influences of work-related variables including occupation, work-hours, and likelihood of losing a job. Results: The overall SEQCA was statistically significant (p < .0001) and accounted for 36% of the variance. Conclusions: Psychosocial variables predict stress more than work-related variables. The results will provide information for designing effective stress prevention programs.

Rare Earth Elements in Shells of Black Sea Molluscs: Anomalies and Biogeochemical Implications

Rare earth elements (REE) are a class of increasingly used high-tech product components and new emerging environmental pollutants, which are accumulated, in particular, in marine biota. In this study, REE contents were estimated in shells of several molluscs common in the Black Sea. The summed REE contents in mollusc shells decreased in the following order of species: Magallana gigas = Anadara kagoshimensis &gt; Flexopecten glaber ponticus ≥ Rapana venosa &gt; Mytilus galloprovincialis, ranging from 0.46 to 1.9 mg·kg−1. Canonical analysis of principal coordinates allowed for the correct identification of species based on the REE composition in no fewer than 67% of the samples. The mollusc shells were anomalously enriched in Sc, Y, La, Eu and Tb, most likely due to anthropogenic contamination. The Y/Ho ratios in all samples were represented by two fit values: 23.2 (chondritic) and 67.6 (superchondritic, mainly associated with A. kagoshimensis). A new universal relationship linking the contents of three light and heavy REE in Black Sea mollusc shells was proposed: Ce0.3 Er0.7/Yb = 2.00 ± 0.46 (mean ± standard deviation).

The potential of the mineral composition to discriminate between beef from different cattle diets and between individual muscles

The effect of the diet of cattle on the mineral composition of various beef muscles was investigated. Both dietary treatment and muscle type influenced the mineral composition (Na, Mg, P, K, Ca, Mn, Fe, Ca, Zn and Se) of beef. The possibility of discriminating beef according to its dietary background and between muscle types was also investigated. Two canonical discriminant analysis models were developed and validated using the mineral concentrations in four muscles (supraspinatus, semitendinosus, longissimus lumborum and psoas major) from cattle reared completely on grass pasture, barley-based concentrate or grass silage with added concentrate combinations. The results demonstrate that the models could correctly classify grass-, partially grass- and concentrate-fed beef (accuracy = 80.7–94.9%) and the different muscles (accuracy = 81.4%). The discriminant models extracted characteristics of Irish grass-fed beef from the mineral composition and this has the potential for distinguishing grass-fed beef from beef raised on other diets.

Morphometric study of the legs of the main Chagas vector, Triatoma infestans (Hemiptera: Reduviidae)

In triatomines, vectors of Chagas disease, active dispersal takes place by walking and flying. Flight has received more attention than walking although the last is the dispersal modality used by nymphs due to their lack of wings and also used by adults, which would facilitate the colonization and reinfestation of houses after vector control actions. The present work studied the morphometrical variation of Triatoma infestans legs, the main vector of Chagas disease the Southern Cone of South America. We described morphometric traits and the natural variation of each leg segment. Different linear, size and shape variables of each component of the three right legs of fifth instar nymphs of T. infestans were analyzed using morphometric tools. We analyzed differentiation, variation and correlation for each segment across the fore-, mid and hind legs using different statistical approaches such as general linear model, canonical variates analysis, test of equality of coefficient of variation and partial least square analysis. We also analyzed variation and correlation between segments within each leg with partial least square and morphometric disparity analyses. Our results showed that the segments differed between legs, as general trends, the dimensions (length, width and/or size) were greater in the hind legs, smaller in the forelegs and intermediate in the mid ones. The femur and tibia (length and/or width) showed differences in morphometric variation between legs and the femur and tibia showed the highest levels of correlation between legs. On the other hand, in the fore- and mid legs, the femur (length or width) showed similar variation with tibia and tarsus lengths, but in the hind legs, the femur showed similar variation with all segments and not with the tibia length, and there were strong correlations between linear measurement within each leg. Our results suggest that the femur and tibia could play a determining role in the coordination between the legs that determines the walking pattern. Considering that these segments would also be linked to the specific function that each leg has, this study suggests a preponderant role of the femur and tibia in the walking locomotion of T. infestans.

Influence of insular conditions on wing phenotypic variation in two dominant mosquito vectors, Aedes albopictus and Armigeres subalbatus (Diptera: Culicidae), in the border archipelagos of Thailand.

Insects geographically separated into island and mainland populations often exhibit phenotypic variations, a phenomenon known as insular conditions. These conditions can lead to rapid evolutionary changes that affect the morphological characteristics of mosquito vectors. Nevertheless, studies that specifically examine phenotype differences between island and mainland mosquito populations have been limited. In this study, wing variation in size and shape was investigated using the geometric morphometric (GM) technique in two dominant mosquito vectors, Aedes albopictus and Armigeres subalbatus, in the Ranong and Trat archipelagos of Thailand. Significant differences in average wing centroid size (CS) were found in 6 out of 15 population pairs for Ae. albopictus (p < 0.05) and in 5 population pairs for Ar. subalbatus (p < 0.05). After removing the allometric effect, canonical variate analyses (CVA) based on wing shape analysis revealed overlap across all populations for both Ae. albopictus and Ar. subalbatus. However, the statistical analysis indicated that Ar. subalbatus exhibited wing shape differences across all populations (p < 0.05), and most Ae. albopictus populations also displayed distinct wing shapes (p < 0.05), except for the populations from Chang Island and the mainland of Ranong, which showed no significant differences (p > 0.05). These findings enhance our understanding of mosquito adaptability in island regions and provide valuable data for the surveillance and monitoring of vector evolution.