Kurtosis Values Research Articles

Identification of exon regions in eukaryotes using fine-tuned variational mode decomposition based on kurtosis and short-time discrete Fourier transform

In genomic research, identifying the exon regions in eukaryotes is the most cumbersome task. This article introduces a new promising model-independent method based on short-time discrete Fourier transform (ST-DFT) and fine-tuned variational mode decomposition (FTVMD) for identifying exon regions. The proposed method uses the N/3 periodicity property of the eukaryotic genes to detect the exon regions using the ST-DFT. However, background noise is present in the spectrum of ST-DFT since the sliding rectangular window produces spectral leakage. To overcome this, FTVMD is proposed in this work. VMD is more resilient to noise and sampling errors than other decomposition techniques because it utilizes the generalization of the Wiener filter into several adaptive bands. The performance of VMD is affected due to the improper selection of the penalty factor (α), and the number of modes (K). Therefore, in fine-tuned VMD, the parameters of VMD (K and α) are optimized by maximum kurtosis value. The main objective of this article is to enhance the accuracy in the identification of exon regions in a DNA sequence. At last, a comparative study demonstrates that the proposed technique is superior to its counterparts.

Study of micro texture parameters, optical loss and opt-electrical calculations in CuAlZnO films

In this paper, the CuAlZnO films were deposited by rf-magnetron sputtering in room temperature on glass substrates. In this deposition process, the equilibrium amount of room temperature during deposition of the CuAlZnO films was provided by the flow of cold water at room temperature inside the copper tubes inserted behind the substrate holder. Then they were annealed by an electric furnace in the presence of argon gas for 1 h at different temperatures of 400, 500, and 600 ° C.Micro texture studies of these the CuAlZnO films using the SPIP™ 6.7.4 software, according to ISO 25178–2:2012, in room temperature and using AFM obtained data, were measured. We found that with increasing annealing temperature from 400 to 600 ° C, the uniformity and their mean height of the distribution of scattered nanoparticles on the surface of the CuAlZnO films, on films surface were increased. It can be seen that the CAZnO films annealed at 400 ° C became more irregular surface hence the maximum value of Sq belongs to these films were in about of 0.09674 mm. The core roughness height Sk calculated as a difference between two extreme levels (maximal and minimal) of surface core, for CAZnO films annealed at 500 ° C have maximum value of 0.001537 mm. It can be seen that as deposited CAZnO films have maximum number of high peaks or valleys on their surface. Due to the high polarization of space charges in the top frequency region, the value of log (dielectric loss tan(δ)) in CAZnO films annealed at 500 ° C have maximum value. It was found that CAZO films annealed at 500 ° C have minimum value of surface kurtosis in about of 8.606 mm. In high frequencies, the AC conductivity of CAZnO films annealed at 400 °C has maximum values.

An adaptive feature mode decomposition-guided phase space feature extraction method for rolling bearing fault diagnosis

Abstract The extraction of fault features from rolling bearings is a challenging and highly important task. Since they have complex operating conditions and are usually under a strong noise background. In this study, a novel approach termed phase space feature extraction guided by an adaptive feature mode decomposition (AFMDPSFE) is proposed to detect subtle faults in rolling bearings. Initially, a new method using Kullback-Leiber divergence is introduced to automatically select the optimal mode number and filter length for the decomposition of vibration signals, facilitating the automatic extraction of optimal components and ensuring efficient screening. This eliminates the need for manual configuration of feature mode decomposition parameters. Furthermore, a criterion that could determine two crucial parameters to capture system dynamics characteristics in phase space reconstruction is embedded into AFMDPSFE algorithm. Subsequently, a series of high-dimensional independent components is derived. The envelope spectrum of the principal component exhibiting the highest kurtosis value is computed to achieve fault identification, consequently enhancing the separation of signal from noise. Both simulations and experimental results confirm the effectiveness of AFMDPSFE approach. A comparison analysis shows the excellent performance of AFMDPSFE in extracting fault features from significant noise interference.

Oral Health Literacy Status, Knowledge Levels, Beliefs, and Behaviors of Pregnant Women.

Pregnancy may exacerbate the frequency and severity of some dental problems. However, most pregnant women avoid going to the dentist. To examine the oral hygiene and dental care behaviors of women during pregnancy, to measure their knowledge levels, to reveal their oral and dental health literacy status, and their beliefs about treatment. The study was conducted for a period of 1 month with pregnant women over the age of 18 who presented to the obstetrics outpatient clinic and agreed to participate in the study and who had no known anomalies or complications. A survey was completed by face-to-face interviews with 317 pregnant women of different ages and gestational weeks. Participants were asked questions regarding their sociodemographic characteristics, pregnancy characteristics, oral hygiene-related beliefs, behaviors, and knowledge levels. The data obtained in the study were analyzed with SPSS 21.0 program. Since the kurtosis and skewness values were between +3 and -3, parametric tests were used. In total, 317 pregnant women between the ages of 18 and 43 participated in the study. The most common beliefs are listed as; babies receive the necessary calcium from the teeth, antibiotics given during dental treatment harm the baby, and panoramic radiography taken during treatment harms the baby. 91.5% of the participants did not visit the dentist after planning a pregnancy, and 89% of them did not visit the dentist during pregnancy. The most common reason not to visit the dentist is not having a dental problem. The rate of knowing that dental infections during pregnancy will affect the baby is 50.5%. In the present study, it is seen that pregnant women do not have adequate oral hygiene. The reasons were listed as various false beliefs and lack of sufficient knowledge. Health professionals should provide information about oral hygiene to pregnant women and direct them to the dentist.

Descriptive analysis of wide area network flow control internet traffic on Metro-E 100 Mbps campus network

QoS in computer networking is the capability to provide better service to network traffic over various technologies such as ethernet and IP networks. This paper presents a descriptive analysis of WAN flow control and internet traffic on a Metro-E campus network. Issues on network congestion and delay in network QoS where internet traffic is gradually increasing, resulting in bursts of network capacity that affect network QoS. The method implies 12 months data collection and analysis on protocol, bytes and packets inbound and correlation between parameters on the Metro-E 100 Mbps campus network. The result presents heavy-tailed distributions on an inbound packet kurtosis value of 347 and an outbound packet kurtosis value of 780. Bytes outbound and inbound are skewed at 122 and right at 17 respectively. The average amount of data inbound and outbound is 458.5 MB and 34.8 MB. Protocol 6 TCP presents the highest amount of -traffic and a weak positive correlation at 0.104 exists between the inbound and outbound packets and bytes on the network. The correlation coefficient's 95% confidence interval ranges between 0.096 and 0.111. This research is significant in the future deployment of traffic scheduling, policing, and shaping algorithms for QoS bandwidth management on the WAN Metro-E campus network.

Do Fair Play Behaviors Reduce Aggression and Anger in Sport?

The sample group of the study, which examined the relationship between the fair play behaviors of student athletes and their levels of aggression and anger in sports, consisted of a total of 333 student athletes, 140 female and 193 male, studying at Alanya Alaaddin Keykubat University Faculty of Sports Sciences in the 2021-2022 academic year. The aim of the study, in which both screening (descriptive) and correlational models were used, was to examine the relationship between student athletes' fair play behaviors and their levels of aggression and anger in sports. The Multidimensional Scale of Sportsmanship Orientation (MSOS-25) and the Scale of Aggression and Anger in Sport (CAAS) were used to collect data. The data were collected from the participants through face-to-face forms in April 2022. In the analysis of the data obtained in the study, Cronbach Alpha reliability coefficient was calculated to examine the internal consistency of the measurement tools. According to the various demographic characteristics of the participants, t-test and ANOVA tests were applied to evaluate the levels of the Multidimensional Sportsmanship Orientation Scale and the Aggression and Anger in Sport Scale. In addition, the level of relationship between the scales was evaluated by Pearson correlation analysis. Whether the data met the prerequisites of parametric tests was decided by examining the Skewness and Kurtosis (normal distribution of data) values and Levene (equality of variance) test results. As a result of the research, it was seen that there was a significant negative relationship between the Multidimensional Sportsmanship Orientation levels of student athletes and the levels of Aggression and Anger in Sports. Accordingly, it can be said that as the fair play behaviors of student athletes increase, their levels of aggression and anger in sports decrease.

Improved Sparse Representation of Image from Inferred Angles of Steerable Wavelet

Objectives: Presenting images with sparse coefficients has a wide variety of real-time applications in compressive sensing. However, sparse representations of images present challenges due hidden similarities in the higher order moments. Literature suggests that the applications that involve natural images present a high level of similarity. Steerable basis, due to their rotational invariant property, have shown potential in sparse representation of natural images. Hence, the objective of the proposed study is to identify steerable basis that maximize the sparse representation of natural images. Method: Prior studies have used the angle of steerable basis either from the random assignment or derived from Hough transform. In this study, we propose the selection of steerable basis angle derived from maximum a prior method. Exploiting a steerable basis for better sparse representation requires the knowledge of proper steerable angles. Hence, we propose using MAP learning approach to identify this angle. Findings: The proposed method resulted in optimal steerable angle without the need for calculation of Hough Transform. In addition, the method also resulted in almost 10 percent improvement in sparse representation as indicated by higher Kurtosis. Novelty: We compare the measure of sparsity to evaluate the effectiveness of the proposed method. The results indicate the optimal sparsity from the proposed method as indicated from the maximum values of kurtosis compared to the previous related methods. In addition, the proposed method relaxes the requirement of manipulating Hough transform for optimal steerable angle. Keywords: Sparsity, Steerable Basis, Wavelet Pyramid Structure, Image Compression, Hough Transform

The value of diffusion kurtosis imaging and dynamic contrast-enhanced magnetic resonance imaging in the differential diagnosis of parotid gland tumors.

Parotid gland tumors (PGTs) are the most common benign tumors of salivary gland tumors. However, the diagnostic value of relative values of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion kurtosis imaging (DKI) parameters for PGTs has not been extensively studied. Therefore, this study aimed to evaluate the diagnostic performance of combined DKI and DCE-MRI for differentiating PGTs by introducing the concept of relative value. The DCE-MRI and DKI imaging data of 142 patients with PGTs between June 2018 and August 2022 were collected. Patients were divided into four groups by histopathology: malignant tumors (MTs), pleomorphic adenomas (PAs), Warthin tumors (WTs), and basal cell adenomas (BCAs). All MRI examinations were conducted using a 3 T MRI scanner with a 20-channel head and neck coil. Quantitative parameters of DCE-MRI and DKI and their relative values were determined. Kruskal-Wallis H test, post-hoc test with Bonferroni correction, one-way analysis of variance (ANOVA) and post-hoc test with least significant difference (LSD) method, and the receiver operating characteristic (ROC) curve were used for statistical analysis. Statistical significance was set at P<0.05. Only the combination of DKI and DCE-MRI parameters could reliably distinguish BCAs from other PGTs. PAs demonstrated the lowest transfer constant from plasma to extravascular extracellular space (Ktrans) value [0.09 (0.06, 0.20) min-1], relative Ktrans (rKtrans) [-0.24 (-0.64, 1.00)], rate constant from extravascular extracellular space to plasma (Kep) value [0.32 (0.22, 0.53) min-1], relative Kep (rKep) [0.32 (0.22, 0.53) min-1], and initial area under curve (iAUC) value [0.15 (0.09, 0.26) mmol·s/kg] compared with WTs, BCAs, and MTs (all P<0.05). The Ktrans values for MTs were substantially lower [0.17 (0.10, 0.31) min-1] than those for WTs (P=0.01). The Kep values for MTs [0.71 (0.52, 1.28) min-1] were substantially lower (all P<0.05) than those for WTs and BCAs. PAs and BCAs had higher diffusion coefficient (D) values and lower diffusion kurtosis (K) values and relative K (rK) values than MTs and WTs. However, the D and K values did not differ significantly even in their relative values of PAs and BCAs (all P>0.05). By using logistic regression, the combination of K value and rKep value further enhanced their discriminatory power between PAs and WTs [area under the ROC curve (AUC), 0.986], the combination of K and rKep value further enhanced their discriminatory power between PAs and MTs (AUC, 0.915), and the combination of D and Kep value further enhanced their discriminatory power between BCAs and MTs (AUC, 0.909). DKI and DCE-MRI can be used to differentiate PGTs quantitatively and can complement each other. The combined use of DKI and DCE-MRI parameters can improve the diagnostic accuracy of distinguishing PGTs.

Optimal filter design using mountain gazelle optimizer driven by novel sparsity index and its application to fault diagnosis

The informative frequency band (IFB) plays a vital role in detecting defects in complex machinery through visible informative features. In the present work, a denoising filter has been designed to enhance the small non-stationarities present in the signal. Initially, the system impulse is computed to estimate the filter coefficients which are further optimized by the mountain gazelle optimization (MGO) based on the maximum value fitness function. The novel sparsity index based on kurtosis and negentropy (NE) is put forward as the fitness function. Then, optimized coefficients are convolved with the system impulse to design the denoising filter. The efficacy of the designed filter is verified through vibration and acoustic signals from the defective components of the belt conveyor system. The designed filter is better able to extract the impulsiveness from the signal, give improved values of kurtosis and signal-to-noise ratio (SNR), and reduce interferences from other machinery components and the environment simultaneously.

Associations between diffusion kurtosis imaging metrics and neurodevelopmental outcomes in neonates with low-grade germinal matrix and intraventricular hemorrhage

Diffusion Kurtosis Imaging (DKI)-derived metrics are recognized as indicators of maturation in neonates with low-grade germinal matrix and intraventricular hemorrhage (GMH-IVH). However, it is not yet known if these factors are associated with neurodevelopmental outcomes. The objective of this study was to acquire DKI-derived metrics in neonates with low-grade GMH-IVH, and to demonstrate their association with later neurodevelopmental outcomes. In this prospective study, neonates with low-grade GMH-IVH and control neonates were recruited, and DKI were performed between January 2020 and March 2021. These neonates underwent the Bayley Scales of Infant Development test at 18 months of age. Mean kurtosis (MK), radial kurtosis (RK) and gray matter values were measured. Spearman correlation analyses were conducted for the measured values and neurodevelopmental outcome scores. Forty controls (18 males, average gestational age (GA) 30 weeks ± 1.3, corrected GA at MRI scan 38 weeks ± 1) and thirty neonates with low-grade GMH-IVH (13 males, average GA 30 weeks ± 1.5, corrected GA at MRI scan 38 weeks ± 1). Neonates with low-grade GMH-IVH exhibited lower MK and RK values in the PLIC and the thalamus (P < 0.05). The MK value in the thalamus was associated with Mental Development Index (MDI) (r = 0.810, 95% CI 0.695–0.13; P < 0.001) and Psychomotor Development Index (PDI) (r = 0.852, 95% CI 0.722–0.912; P < 0.001) scores. RK value in the caudate nucleus significantly and positively correlated with MDI (r = 0.496, 95% CI 0.657–0.933; P < 0.001) and PDI (r = 0.545, 95% CI 0.712–0.942; P < 0.001) scores. The area under the curve (AUC) were used to assess diagnostic performance of MK and RK in thalamus (AUC = 0.866, 0.787) and caudate nucleus (AUC = 0.833, 0.671) for predicting neurodevelopmental outcomes. As quantitative neuroimaging markers, MK in thalamus and RK in caudate nucleus may help predict neurodevelopmental outcomes in neonates with low-grade GMH-IVH.

Sediment distribution and transport pattern in the nearshore region, southeast coast of India

The present paper aimed to assess the sediment distribution pattern, mode of transport, and its interaction with hydrodynamic and topographic conditions at different depths and regions along the east coast of India. About 900 surficial sediment samples were collected and analysed on a monthly basis for the Chennai coastal region at 32 stations from 2013 to 2015. The study region is classified into four types, such as beach, inlet, 5 m, and 10 m depth. Sediment textural and grain size trend analyses were conducted to achieve the objectives. Sediment characteristics for the region were recorded as sandy, equally dominated by unimodal and bimodal at the beach, while unimodal at shallow depths (5 and 15 m). The sediments were medium sand to coarse sand at the beach, mostly fine followed by medium at 5 and 15 m depths. The sediment sorting is dominated by moderately well-sorted sediments; the skewness of beach sediments was negative, while nearshore sediments were found positive; average kurtosis values of sediments were noticed to be mesokurtic. The CM plot depicts that the sediments were mostly derived by tractive current, and the modes of transport are “bottom suspension and rolling” and “graded suspension no rolling” at beach locations and shallow water depths, respectively. The GSTA analysis reveals the annual average sediment transport pattern is northerly. The numerical hydrodynamic study confirms the GSTA and CM plot analysis. The study reveals a stable sedimentary environment south of the Chennai port and instability in the northern part. The study includes large spatiotemporal nearshore sediment data with hydrodynamic conditions, immensely helpful to coastal stakeholders and researchers.

Investigation of the Effect of Sports Participation Motivations of Students of Faculty of Sports Sciences on Their Leadership Orientations

In this study, it was aimed to determine the relationship between motivation to participate in sports and leadership orientations of students of the faculty of sports sciences. A relational survey model was used in this study. The study group consisted of students studying in the Faculty of Sports Sciences. The questionnaire part of the study consists of three parts. Firstly, includes demographic information. Secondly, the “Leadership Orientations Questionnaire”, which was developed by Bolman and Deal (1990) and adapted into Turkish by Dereli (2003), is explored. Thirdly, consists of the Participation Motivation Questionnaire, which was developed by Gill et al. (1983) and adapted into Turkish by Oyar et al. (2001). For the determine normality assumption skewness and kurtosis values was used. Skewness and kurtosis values were found to be between ±2 and it was determined that the data had a normal distribution (George and Malley, 2003). Afterward, an Independent samples t-test was used between paired groups, and a one-way analysis of variance was used for paired variables. Moreover, reliability coefficient, frequency and percentage and mean and standard deviation calculations were conducted. Simple regression analysis was used to determine the effect between the dependent and independent variables. The findings, a statistically significant difference was found in the variables of leadership orientation and age, income level, and frequency of weekly sports participation in sports participation motivation. As a result, it was determined that there was a low-level significant and negative relationship between the participants' motivation to participate in sports and their leadership orientations.Keywords: Leadership, Motivation, Sports.

Ecological groups of birds of Zhytomyr region (Ukraine) in relation to thermal regime and their future prospects in the context of global climate change

The potential impact of global climate change on the distribution of bird species can be predicted based on observed climate change and current knowledge of the factors affecting range boundaries. The concept of an ecological niche allows one to qualitatively and quantitatively characterise the impact of environmental factors on species. The study estimates the parameters of the thermal projection of the ecological niche of birds in Zhytomyr region, compares different approaches to modelling the response of species to the average annual temperature gradient, identifies ecological groups of birds based on their thermal gradient, and provides prospects for these ecological groups in the context of global climate change. The beta-function was found to reflect the reactions of different species within a single bell-shaped pattern across the entire gradient of the environmental factor. This makes it possible to estimate the optimal level for all bird species. Kurtosis can be used to distinguish between different response patterns within the beta model. Zero kurtosis indicates a symmetrical bell-shaped response. The relationship between the kurtosis of species response models and the optimum is complex. In general, species show negative kurtosis in the warm part of the range, indicating a sharp break in the species response curve in the warm part of the factor range. In the middle part of the factor range, the kurtosis value randomly fluctuates around zero, indicating a predominant tendency towards symmetrical response forms and the prevalence of the classical bell-shaped response model. The limits of variation of kurtosis are of great importance in the cold part of the range. The thermal projection of the ecological niche was used to divide bird species into ecological groups based on the position of the optimum zone and the width of the tolerance amplitude. It is shown that ecological groups differ in their prospects under global climate change. Stenotopic megatherms have the best prospects in the face of global climate change. The habitat conditions of all other bird species in the region will deteriorate over the next 70 years. The most threatening prospects should be expected for stenotopic microtherms. The stenotopic megatherms include 68 species, which is 25.9% of the total regional bird fauna. That is, global climate change poses a threat to 74.1% of the region's bird species. Stenotopic megatherms are typified by Anseriformes, Bucerotiformes, Gruiformes, and Pelecaniformes. It was predicted that Ciconia ciconia has the greatest prospects for expansion due to global climate change. The stenotopic microtherms are represented by 18 species, which is 6.9% of the regional avifauna. For these species, climatic conditions will significantly limit the number of favourable habitats. This ecological group is most strongly typified by for Galliformes, Piciformes, and Strigiformes. Climate change will lead to a shift in the range of Picus canus, which will reduce the abundance of this species in the region.

Exploring the potentials of ChatGPT for instructional assessment: Lecturers' attitude and perception

Lecturers play a crucial role in the educational process, offering unique insights and perspectives within the classroom. The issue of cred­ibility in educational assessment often rests on the shoulders of lecturers, who are responsible for eval­uating students' progress. The present study aimed to investigate lecturers' attitudes and perceptions re­garding the potential of ChatGPT for instructional assessment. A correlational research design was adopted, and purposive sampling was used to select 102 lecturers from Nigerian universities who had uti­lised ChatGPT for instructional assessment. Data was collected through an online structured question­naire. The normality and homogeneity of variance assumptions were met, as evidenced by kurtosis and skewness values falling within acceptable thresh­olds. The lecturers employed the instructional assessment questionnaire utilising ChatGPT to gather and analyse the data, employing t-tests and ANOVA. The findings revealed a statistically significant difference between perception (F (3, 98) =7.168, p=0.001 &lt;0.05) and lecturers' years of experience in using ChatGPT for instructional assessment. The study indicated that lecturers held low attitudes and had poor perception levels when it came to exploring the potential of ChatGPT. However, it is recommended that training be provided to enhance lecturers' attitudes and perception levels to fully exploit the potential of ChatGPT for instructional assessment.

Common Relationship Between Causality Orientation and the Prefrontal Region in Psychiatric Disorders as Revealed by Diffusional Kurtosis Imaging.

Background Motivation dysregulation is common in several psychiatric disorders. However, little is known about the relationships between motivation and the regional brain areas involved. We evaluated the relationships between brain microstructural features and causality orientation in patients with schizophrenia, major depressive disorder (MDD), and bipolar disorder (BD) using diffusional kurtosis imaging (DKI) techniques. Methods Forty patients with MDD, 36 with BD, and 30 with schizophrenia underwent DKI and assessment using the General Causality Orientation Scale (GCOS). We analyzed the DKI index and the GCOS subscales. Results The psychiatric patients showed significant positive correlations between the GCOS-autonomy orientation score and the mean kurtosis (MK) values in the prefrontal regions, orbitofrontal regions, and posterior cingulate cortex. When the analyses were performed separately by disease and gender, a positive correlation was found between the GCOS-autonomy orientation score and the MK values in the left prefrontal regions transdiagnostically, especially among female patients with MDD, BD, and schizophrenia. Conclusions A similar association between intrinsic motivation and MK value in the left prefrontal cortex was suggested in patients with schizophrenia, MDD, and BD. The commonality of this association among these disorders might lead to the discovery of a new biomarker for psychiatric clinical research.

Early-Stage Fault Diagnosis of Motor Bearing Based on Kurtosis Weighting and Fusion of Current-Vibration Signals.

To solve the problem of a low signal-to-noise ratio of fault signals and the difficulty in effectively and accurately identifying the fault state in the early stage of motor bearing fault occurrence, this paper proposes an early fault diagnosis method for bearings based on the Differential Local Mean Decomposition (DLMD) and fusion of current-vibration signals. This method uses DLMD to decompose the current signal and vibration signal, respectively, and weights the decomposed product function (PF) according to the kurtosis value to reconstruct the signal, and then fuses the reconstructed signals to obtain the current-vibration fusion signal after normalization, and then analyzes the fusion signal spectrally through the Hilbert envelope spectrum. Finally, the fusion signal is analyzed by the Hilbert envelope spectrum, and a clear fault characteristic frequency is obtained. The experimental results demonstrate that compared to traditional bearing fault diagnosis methods, the proposed method significantly improves the signal-to-noise ratio of fault signals, effectively enhances the sensitivity of early-stage fault detection in motor bearings, and improves the accuracy of fault identification.

Comparative study of kinship network community detection approaches

This study employs five community detection methods on a rooted tree network with 600 nodes and 599 edges based on the Galo tribe’s kin naming system in Arunachal Pradesh, India. The network was originally assumed to be made up of three communities, which the algorithms were able to further divide into smaller groupings. The Louvain approach produced the most balanced distribution of community sizes, with skewness and kurtosis values close to zero, implying that the detected communities were reasonably evenly distributed in size and without major outliers. However, the Louvain algorithm found 25 communities, which is more than the network’s previously reported three communities. Further investigation may be required to integrate some of these communities in order to obtain the original known communities. Overall, this study highlights the importance of selecting an appropriate community detection algorithm for a given network and research question.

The Quadrangular Cartilage in Rhinoplasty: A Surgically Focused CT Dimensional Analysis of Black African and Caucasian Populations.

The apparent lack of quadrangular cartilage in Black African noses is commonly observed both from a radiological and clinical point of view. To the best of our knowledge, only a few research papers have been conducted on the facial proportions and structural anatomy of black people of Southern and Eastern Africa. The aim of this retrospective comparative study is a radiological assessment of the total amount of septal quadrangular cartilage by measuring its area in sagittal CT views, in two selected Black South African and Caucasian (CA) samples and the comparison with the literature in our hands. Statistical analysis was conducted, categorical variables are shown as frequencies and percentages, while continuous variables as means and standard deviations. Normal distribution of variables was verified using the Shapiro-Wilk test or by means of skewness and kurtosis values. Differences among unpaired groups were evaluated using the independent Student's t-test for normally distributed data (complemented by the Cohen's d to show the effect size with the following cutoff: d = 0.2, "small" effect size; d = 0.5, "medium" effect size; d = 0.8, "large" effect size) and Mann-Whitney U test in case of non-normal distribution. Statistical significance was defined as p < 0.05 setting the α-error probability at 5%. This study shows that, on average, there is 30% more cartilage available in CA compared with Black African noses and confirms the apparent lack of quadrangular cartilage and in Black African noses which is commonly observed in surgery. The need for an adequate amount of autologous septal cartilage makes cartilage availability a major concern before surgery and being able to preoperative accurately measure the amount of septal cartilage that is available to be harvested for other grafts in the surgery is essential.

The Effect of High Impact Teaching Practices on Student Comprehension

Despite a large number of published studies on high-impact teaching practices (HIP), there is little consistency in design or measurable outcomes and few quantitative studies, which leads to a lack of information on how specific HIPs improve learning outcomes. Therefore, the research questions for this study are a) does the same HIP have similar results across sections and, b) does a HIP in one section result in a different learning outcome than in another section that does not have a HIP? The hypothesis for the first question is there is no difference in student comprehension between sections when all sections have the same HIP. The hypothesis for the second question is there will be a difference in student comprehension between sections, with students exhibiting greater comprehension in the section with the HIP. For several years we have been using a variety of HIPs in our classes without measuring their impact. This is a preliminary study designed to measure the impact of HIPs on two different sections of Human Anatomy and Physiology II, taught by the same professor. The design of the study is as follows: [Formula: see text] We will analyze our data for two attributes, average and variability of pre-tests and post-tests. For the first attribute, we will study mean distribution. T-test analysis of the mean will be used to measure differences between sections for the pre-test and each post-test. Similarly, T-test analysis of the means will be used within each section to analyze differences between the pre-test and each post-test. For the second attribute, we will use F-test analysis of variance. Tests of normality of grade distribution for three assignments or tests in two sections of a typical biology class were conducted. Our analyses showed that all skewness and kurtosis values were between -2 to 2, and the median and mean were very close. Thus, it is reasonable to assume that the data are from normally distributed populations. Therefore, the approach we have outlined to measure HIP impact is appropriate for our classes. The results from this preliminary study will be used to identify specific HIPs that result in higher learning outcomes and will assist us in refining our pedagogical approach. Funding was provided by Lincoln University's Offce of Title III; Award #P031E200019-HBCU Title III, Part F Program. 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.

A comparative study of diffusion kurtosis imaging and diffusion tensor imaging in detecting corticospinal tract impairment in diffuse glioma patients.

This study aimed to investigate the diagnostic performance of diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in identifying aberrations in the corticospinal tract (CST), whilst elucidating the relationship between abnormalities of CST and patients' motor function. Altogether 21 patients with WHO grade II or grade IV glioma were enrolled and divided into Group 1 and Group 2, according to the presence or absence of preoperative paralysis. DKI and DTI metrics were generated and projected onto the CST. Histograms of the CST along x, y, and z axes were developed based on DKI and DTI metrics, and compared subsequently to determine regions of aberrations on the fibers. The receiver operating characteristic curve was performed to investigate the diagnostic efficacy of DKI and DTI metrics. In Group 1, a significantly lower fractional anisotropy, radial kurtosis and mean kurtosis, and a higher mean diffusivity were found in the ipsilateral CST as compared to the contralateral CST. Significantly higher relative axial diffusivity, relative radial diffusivity, and relative mean diffusivity (rMD) were found in Group 1, as compared to Group 2. The relative volume of ipsilateral CST abnormalities higher than the maximum value of mean kurtosis combined with rMD exhibited the best diagnostic performance in distinguishing dysfunction of CST with an AUC of 0.93. DKI is sensitive in detecting subtle changes of CST distal from the tumor. The combination of DKI and DTI is feasible for evaluating the impairment of the CST.