Multivariate diversity, heritability and genetic advance in Tef Landraces in Ethiopia

Characterisation of exiting genetic variability is a prerequisite for further crop improvement activity. This study was designed to assess genetic variability among randomly selected Eragrostis tef, Zucc.Trotter (Tef) genotypes from five administrative zones in the Amhara region in Ethiopia. The experiment was conducted in 2010 main cropping season at Adet Agricultural Research Center. All traits, except first inter-node length showed highly significant differences among the 37 lines. Number of productive tillers per plant, grain yield per plant, and biomass yield per plant showed high phenotypic coefficients of variation; 18.9, 17.5 and 16.9% in that order. Harvest index (15.1%) showed the highest genotypic coefficient of variation while the lowest (3.5%) was for days to maturity. Heritability in broad sense was highest for days to heading (80.7%), followed by culm length (72.4%). Grain yield and shoot biomass yield showed heritability values of 54.6 and 57.3%, and GAM values of 18.9 and 20.6%, respectively. The first three principal components (PCs) with eigenvalues greater than one explained 75% of the observed variation. Four PCs were effective in explaining 93% of the variation among zones. Cluster analysis grouped the 37 lines into five real clusters, while zones of collection were grouped into three major clusters. These data are useful for future tef breeding/crop improvement programmes and undertakings

Multivariate diversity, heritability and genetic advance in Tef landraces in Ethiopia

Characterisation of exiting genetic variability is a prerequisite for further crop improvement activity. This study was designed to assess genetic variability among randomly selected Eragrostis tef , Zucc.Trotter (Tef) genotypes from five administrative zones in the Amhara region in Ethiopia. The experiment was conducted in 2010 main cropping season at Adet Agricultural Research Center. All traits, except first inter-node length showed highly significant differences among the 37 lines. Number of productive tillers per plant, grain yield per plant, and biomass yield per plant showed high phenotypic coefficients of variation; 18.9, 17.5 and 16.9% in that order. Harvest index (15.1%) showed the highest genotypic coefficient of variation while the lowest (3.5%) was for days to maturity. Heritability in broad sense was highest for days to heading (80.7%), followed by culm length (72.4%). Grain yield and shoot biomass yield showed heritability values of 54.6 and 57.3%, and GAM values of 18.9 and 20.6%, respectively. The first three principal components (PCs) with eigenvalues greater than one explained 75% of the observed variation. Four PCs were effective in explaining 93% of the variation among zones. Cluster analysis grouped the 37 lines into five real clusters, while zones of collection were grouped into three major clusters. These data are useful for future tef breeding/crop improvement programmes and undertakings.La caract\ue9risation de la variabilit\ue9 g\ue9n\ue9tique existante est une Characterisation of exiting genetic variability is a pr\ue9alable dans des activit\ue9s d\u2019am\ue9lioration cultural. La pr\ue9sente \ue9tude \ue9tait con\ue7ue pour \ue9valuer la variabilit\ue9 g\ue9n\ue9tique parmi les g\ue9notypes svlectionn\ue9s de tef Eragrostis, Zucc.Trotter (Tef) dans cinq zones admonistratives dans la r\ue9gion Amhara en Ethiopie. L\u2019\ue9tude \ue9tait conduit au cours de la saison culturale principale 2010 au Centre de Recherche Agricole Adet. Toutes les caract\ue9ristiques, except\ue9 la longueur inter-node ont montr\ue9 de diff\ue9rences significativement \ue9lev\ue9es parmi les 37 lign\ue9es. Le nombre de talles par plant, le rendement en grains par plant, et le rendement en biomasse par plant ont montr\ue9 des coefficients de variation ph\ue9notypique \ue9lev\ue9s de 18.9, 17.5 et 16.9% respectivement. L\u2019index de r\ue9colte (15.1%) a montr\ue9 un coefficient de variation le plus \ue9lev\ue9 pendant que le coeffiecient g\ue9notypique le moins \ue9lev\ue9 (3.5%) \ue9tait celui du nombre de jours \ue0 la maturit\ue9. L\u2019h\ue9ritabilit\ue9 au sens large \ue9tait plus \ue9lev\ue9e pour les jours relatives au heading (80.7%), suivi de la longueur du culm (72.4%). Le rendement en grains et le rendement en biomasse de tiges ont montr\ue9 des valeurs d\u2019h\ue9ritabilit\ue9 de 54.6 et 57.3%, et les valeurs de GAM de 18.9 et 20.6%, respectivement. Les trois premiers composantes principales (PCs) avec des valeurs eigen plus grandes que un, ont expliqu\ue9 75% de la variation observ\ue9e. Quatre PCs ont effectivement expliqu\ue9 93% de la variation parmi les zones. L\u2019analyse par groupements, a group\ue9 les 37 lign\ue9es en cinq groupements r\ue9els, pendant que les zones de collection \ue9taient group\ue9es en trois groupements majeurs. Ces donn\ue9es sont sont utiles pour dans le programme d\u2019am\ue9lioration du Tef

Leg Joint Angle Estimation From a Single Inertial Sensor During Variety of Walking Motions: A Deep Learning Approach

This study evaluates the capability of a single inertial sensor based joint angles estimation during four different walking patterns in an outdoor setting. The sensor was placed on the upper part of the tibia, which was chosen due to its large range of motion and minimal foot-ground impact. A Bi-LSTM (bidirectional long short-term memory) data-driven approach was used for joint angle estimation. The results showed smaller errors in intra-subject angle estimation compared to inter-subject, with an average MAE (mean absolute error) of 2.11° to 3.65°. The study suggests that deep learning approaches can effectively process data from a single IMU (inertial measurement unit) for accurate human motion monitoring, reducing the need for multiple sensors. Despite using only one sensor and four different walking patterns (zigzag, sideways, backward, and ramp walking), our method achieved similar results to previous studies that used single-motion activities. This study, conducted outdoors without instructing participants, is a step closer to real-world application, potentially providing insights into lower body biomechanics in physiotherapy, mobility improvement progress after surgery, and aiding in the development of personalized exoskeletons robots

New Sensor Data Structuring for Deeper Feature Extraction in Human Activity Recognition

For the effective application of thriving human-assistive technologies in healthcare services and human–robot collaborative tasks, computing devices must be aware of human movements. Developing a reliable real-time activity recognition method for the continuous and smooth operation of such smart devices is imperative. To achieve this, light and intelligent methods that use ubiquitous sensors are pivotal. In this study, with the correlation of time series data in mind, a new method of data structuring for deeper feature extraction is introduced herein. The activity data were collected using a smartphone with the help of an exclusively developed iOS application. Data from eight activities were shaped into single and double-channels to extract deep temporal and spatial features of the signals. In addition to the time domain, raw data were represented via the Fourier and wavelet domains. Among the several neural network models used to fit the deep-learning classification of the activities, a convolutional neural network with a double-channeled time-domain input performed well. This method was further evaluated using other public datasets, and better performance was obtained. The practicability of the trained model was finally tested on a computer and a smartphone in real-time, where it demonstrated promising results

Multivariate diversity, heritability and genetic advance in Tef landraces in Ethiopia

Characterisation of exiting genetic variability is a prerequisite for further crop improvement activity. This study was designed to assess genetic variability among randomly selected Eragrostis tef , Zucc.Trotter (Tef) genotypes from five administrative zones in the Amhara region in Ethiopia. The experiment was conducted in 2010 main cropping season at Adet Agricultural Research Center. All traits, except first inter-node length showed highly significant differences among the 37 lines. Number of productive tillers per plant, grain yield per plant, and biomass yield per plant showed high phenotypic coefficients of variation; 18.9, 17.5 and 16.9% in that order. Harvest index (15.1%) showed the highest genotypic coefficient of variation while the lowest (3.5%) was for days to maturity. Heritability in broad sense was highest for days to heading (80.7%), followed by culm length (72.4%). Grain yield and shoot biomass yield showed heritability values of 54.6 and 57.3%, and GAM values of 18.9 and 20.6%, respectively. The first three principal components (PCs) with eigenvalues greater than one explained 75% of the observed variation. Four PCs were effective in explaining 93% of the variation among zones. Cluster analysis grouped the 37 lines into five real clusters, while zones of collection were grouped into three major clusters. These data are useful for future tef breeding/crop improvement programmes and undertakings.La caractérisation de la variabilité génétique existante est une Characterisation of exiting genetic variability is a préalable dans des activités d’amélioration cultural. La présente étude était conçue pour évaluer la variabilité génétique parmi les génotypes svlectionnés de tef Eragrostis, Zucc.Trotter (Tef) dans cinq zones admonistratives dans la région Amhara en Ethiopie. L’étude était conduit au cours de la saison culturale principale 2010 au Centre de Recherche Agricole Adet. Toutes les caractéristiques, excepté la longueur inter-node ont montré de différences significativement élevées parmi les 37 lignées. Le nombre de talles par plant, le rendement en grains par plant, et le rendement en biomasse par plant ont montré des coefficients de variation phénotypique élevés de 18.9, 17.5 et 16.9% respectivement. L’index de récolte (15.1%) a montré un coefficient de variation le plus élevé pendant que le coeffiecient génotypique le moins élevé (3.5%) était celui du nombre de jours à la maturité. L’héritabilité au sens large était plus élevée pour les jours relatives au heading (80.7%), suivi de la longueur du culm (72.4%). Le rendement en grains et le rendement en biomasse de tiges ont montré des valeurs d’héritabilité de 54.6 et 57.3%, et les valeurs de GAM de 18.9 et 20.6%, respectivement. Les trois premiers composantes principales (PCs) avec des valeurs eigen plus grandes que un, ont expliqué 75% de la variation observée. Quatre PCs ont effectivement expliqué 93% de la variation parmi les zones. L’analyse par groupements, a groupé les 37 lignées en cinq groupements réels, pendant que les zones de collection étaient groupées en trois groupements majeurs. Ces données sont sont utiles pour dans le programme d’amélioration du Tef

Prevalence of Depression among Type 2 Diabetic Outpatients in Black Lion General Specialized Hospital, Addis Ababa, Ethiopia

Background. The emotional consequences of diabetes have been scrutinized by a number of investigative teams and there are varying reports about the association of depression with type 2 diabetes mellitus. However, there is limited data about this in Ethiopia. Therefore, the purpose of this study was to assess the prevalence of comorbid depression among type 2 diabetic outpatients. Methods and Materials. Institution based cross-sectional study design was conducted on a random sample of 276 type 2 diabetic outpatients from Black Lion General Specialized Hospital. Systematic random sampling technique was used to get these individual patients from 920 type 2 diabetic outpatients who have an appointment during the data collection period. Patients’ depression status was measured using Patient Health Questionnaire 9 (PHQ 9). Result. Totally 264 type 2 diabetic outpatients were interviewed with a response rate of 95.6%. The prevalence of depression among type 2 diabetic outpatients was 13%. Based on PHQ 9 score, 28.4% (75) fulfilled the criteria for mild depression, 12.1% (32) for moderate depression, 2.7% (7) for moderately severe depression, and 1.5% (4) for severe depression. But 45.8% (121) of patients had no clinically significant depression. Conclusion. This study demonstrated that depression is a common comorbid health problem in type 2 diabetic outpatients with a prevalence rate of 13%

Terrane Rotation During the East African Orogeny: Evidence from the Bulbul Shear Zone, South Ethiopia

The 100 km long, N-trending, Neoproterozoic-Early Paleozoic Bulbul Shear Zone in southern Ethiopia is marked by sheared ophiolites at the interface between the Arabian-Nubian Shield in the north and the Mozambique Belt in the south. This shear zone separates the low-grade meta-volcanic and meta-sedimentary rocks of the Bulbul Terrane in the east from the medium- to high-grade gneissic, migmatites and granulites of the Alghe Terrane in the west. Stretching lineations along the Bulbul Shear Zone vary from NE-plunging in the northern part, shallowly N- and S-plunging in the central part, to SE-plunging in the south. These lineations are developed along N-trending mylonitic foliation that is moderately to steeply E-dipping. The northern part of the Bulbul Shear Zone is dominated by SW-verging fold and thrust belt indicating top-to-the southwest tectonic transport. The central part is characterized by dextral strike-slip displacement. The southern part is dominated by E-dipping oblique normal-slip planes associated with top-to-the southeast tectonic transport. Down dip stretching lineations along E-dipping slip planes are well-developed in the eastern part of the Alghe terrane and the western part of the Bulbul terrane. We interpret the along-strike variation of stretching lineations and kinematic indicators as due to NE-SW directed oblique collision between the Bulbul Terrane and the Alghe Terrane accompanied by anti-clockwise rotation of the Bulbul Terrane. Such collision and rotation are manifested by SW-verging fold and thrust belt in the north, N-trending dextral strike-slip shear zone in the center, and SE-directed normal-slip displacement in the south. This tectonic event might have occurred between 820 and 580 Ma. This was followed by E-ward slipping of the Bulbul Terrane relative to the Alghe Terrane, probably between 580 and 500 Ma

Deep-Learning-Based Character Recognition from Handwriting Motion Data Captured Using IMU and Force Sensors

Digitizing handwriting is mostly performed using either image-based methods, such as optical character recognition, or utilizing two or more devices, such as a special stylus and a smart pad. The high-cost nature of this approach necessitates a cheaper and standalone smart pen. Therefore, in this paper, a deep-learning-based compact smart digital pen that recognizes 36 alphanumeric characters was developed. Unlike common methods, which employ only inertial data, handwriting recognition is achieved from hand motion data captured using an inertial force sensor. The developed prototype smart pen comprises an ordinary ballpoint ink chamber, three force sensors, a six-channel inertial sensor, a microcomputer, and a plastic barrel structure. Handwritten data of the characters were recorded from six volunteers. After the data was properly trimmed and restructured, it was used to train four neural networks using deep-learning methods. These included Vision transformer (ViT), DNN (deep neural network), CNN (convolutional neural network), and LSTM (long short-term memory). The ViT network outperformed the others to achieve a validation accuracy of 99.05%. The trained model was further validated in real-time where it showed promising performance. These results will be used as a foundation to extend this investigation to include more characters and subjects

Blood donation practice and associated factors among health professionals in Tigray regional state public hospitals, northern Ethiopia

Abstract Objective The demand for blood and blood products are increasing in all part of the globe, especially in the developing nations. However, there is limited information on the level of blood donation practice and their related factors. Therefore, assessing the level of blood donation practice and its determinant factors among health professionals have a paramount importance in designing an effective strategy for sustaining adequate and safe blood provision in the hospitals. Results Out of 556 health professionals, 266 (47.8%) had ever donated blood in their life time. Age above 30 years (AOR = 2.756 95% CI 1.055–7.197), married health professionals (AOR = 1.729 95% CI 1.091–2.739), health professionals’ knowledge of blood donation (AOR = 3.403 95% CI 2.296–5.044), health professionals’ attitude towards blood donation (AOR = 3.41 95% CI 2.320–5.041) and health professionals who attend degree education (AOR = 0.315 95% CI 0.104–0.950) were significantly associated with blood donation behavior of health professionals. The magnitude of blood donation practice was found low. Therefore, the Ethiopian Red Cross Society and ministry of health should continue increasing the attitude and knowledge of health professionals toward blood donation practices are the key avenues interventions

Prevalence of Methicillin-Resistant Staphylococcus aureus and Associated Risk Factors among Patients with Wound Infection at Referral Hospital, Northeast Ethiopia

Background. The spectrums of infections due to methicillin-resistant Staphylococcus aureus are manifold and are associated with worse outcomes. A study on the prevalence of these pathogens and their sensitivity patterns will give updated information which is very helpful for health personnel responsible in the management of patients and timely monitoring of the emergence of resistant bacteria. Hence, the study aimed at assessing the prevalence of methicillin-resistant Staphylococcus aureus and associated factors among patients with wound infection at Dessie Referral Hospital. Method. A cross-sectional study was conducted among 266 patients at Dessie Referral Hospital from February to May 2016. Wound swab samples were collected aseptically using Levine’s technique and transported to Dessie Regional Laboratory by using brain-heart infusion transport media. Isolation of Staphylococcus aureus was done based on cultural and biochemical profiles. Drug susceptibility test was performed using the disc diffusion technique as per the standard and interpreted based on the Clinical and Laboratory Standards Institute guidelines. The data were entered and analyzed by using SPSS version 20. Result. Staphylococcus isolates from 266 processed wound swabs were 92 (34.58%). Of these, 26 (28.3%) were identified as methicillin-resistant S. aureus and 66 (71.7%) were methicillin-sensitive S. aureus. The overall prevalence of methicillin-resistant S. aureus among the study population was 9.8%. The isolated methicillin-resistant S. aureus showed full resistance to penicillin (100%) followed by erythromycin and ciprofloxacin (16, 61.5%) and cotrimoxazole and gentamicin (14, 53.8%). From the total S. aureus isolates, 20 (21.7%) of them showed multidrug resistance. Of these methicillin-resistant S. aureus, 18 (69.8%) showed high multidrug resistance. Patients who are farmers in occupation (AOR = 6.1, 95% CI (1.086–33.724)), admitted in the hospital (AOR = 3.56, 95% CI (1.429–8.857)), and have low BMI (<18.5) (AOR = 13.89, 95% CI (4.919–39.192)) were among the risk factors significantly associated with wound infection due to methicillin-resistant S. aureus. Conclusion. All methicillin-resistant S. aureus isolates were 100% resistant to penicillin and showed high multidrug resistance. Therefore, antibiotic susceptibility test should be performed prior to treatment