Abstract: Appropriate use of agricultural technologies and diversifying the farming activities is critical to addressing food security problems in Africa, including Ethiopia. The country is experimenting with the new Agricultural Innovation System (AIS) approach alongside the well-established Transfer of Technology (ToT) approach. This paper analyzes the gaps between policy discourses (as reflected in policy documents and strategic orientation documents) and extension practices (as reflected in the daily exchanges between farmers and the frontline staff of the Ethiopian extension system). It provides insights into the challenges faced and emphasizes the need for better coordination between policy formulation and implementation to enhance extension services. Policymakers, practitioners, and researchers can benefit from the valuable perspectives the findings offer. The study contributes to understanding the relationship between policy discourses and extension practices, and its implications can inform policy design and implementation in similar contexts. A qualitative research approach was deployed to analyze policy discourse and practice. Data were collected in Fogera, a district in Northwest Ethiopia, between August 2018 and February 2019. The data for the paper were obtained from 23 Focus Group Discussions conducted with men and women. 13 Informant Interviews (KIIs) were also carried out with personnel at different levels of government agricultural services and departments. Transcripts of recordings of the Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs) were analyzed using a deductive approach. The study focuses on rice crops in the Fogera district, which are crucial for food security and reducing poverty. Although the geographic area is limited, the results can be used to improve the extension system in other areas facing similar challenges. Specifically, the study suggests switching from the traditional transfer of technology approach to the agricultural innovation system approach. Furthermore, the study's techniques, such as qualitative interviews, may have limitations and not fully capture the intricacies of policy and extension practices. The findings demonstrate that, although the policy documents strongly adhere to agricultural innovation system principles, top-down transfer of technology approaches continues to dominate in practice. Moreover, we have found potential discrepancies between the training content delivered and the specific needs of smallholder farmers. Practically, prescriptive systems are still used because agricultural innovation system approaches are not well understood by the Extension Agents. To realize a genuine agricultural innovation system, Ethiopia's extension apparatus should move forward with building committed and robust relationships between farmers, extension agents, researchers, private sectors, and non-governmental organizations. To this end, more research, enhanced training, and improved institutions are needed on what genuine agricultural innovation system could look like at the grass-roots level. This also includes understanding the roles that different actors within Ethiopia's development army should assume how a multi-actor policy dialogue can be organized.

Abstract: Vegetable farmers face a number of challenges in marketing. Having first-hand information about vegetable marketing is essential to devise appropriate strategies aimed at enhancing the value of the vegetable chain. It was in line with this view that the study was conducted to characterize vegetable markets in Northern Ethiopia. In an effort to identify the factors influencing vegetable marketing among farmers, data were collected from 283 farm households who were selected using stratified random sampling. Furthermore, the data were triangulated through focus group discussion (FGD) and key informant interviews. Descriptive statistics and the binary logistic regression model were used to identify the variables and test the probability of their influence in regard to farmers decisions in vegetable marketing. From the 13 explanatory variables included in the binary logistic regression model, six predictors were found to be statistically significant in determining the effects of participation decision on vegetable market. These variables are as follows: household family size, total land holding of the household, amount of vegetable produced and marketed, use of irrigation technologies, contact with extension agents, and access to market information. Relying on a survey result and observations, the findings of the study indicated that vegetable marketing is significantly improving the livelihood of smallholder producers.

Abstract: Delve into the diverse aspects of plant morphology, their responses to global climate change, and the spatiotemporal dynamics of forest productivity. Join us on a journey through the intricate web of plant characteristics and their impact on the environment.

Abstract: Transmission electron microscopy is an important technique in the exploration of materials’ structures. This is especially true since the development of electron optical aberration correctors greatly facilitated atomic resolution imaging. We are currently experiencing an ongoing revolution in electron microscopy with the widespread adoption of direct electron detectors. Scientists have reported a lot of key scientific findings facilitated by direct electron detectors. One particular research domain is electron ptychography, which holds promise for unraveling the intricate structures of highly beam-sensitive materials like bio samples and achieving super-resolution without the limitation of aperture in the condenser lens system. Nevertheless, challenges persist both in experimental setups and algorithmic processes. Issues such as the comparatively sluggish scanning speed of cameras and contrast reversals of the reconstructed phase for relatively thick specimens, disrupting phase or weak phase approximations, remain noteworthy limitations. This thesis addresses these challenges by the event-driven Timepix3 detector, presenting a viable solution to the speed bottleneck. Moreover, innovative approaches for applying electron ptychography to relatively thick samples, employing a middle focusing strategy, are proposed. This research aims to push the boundaries of electron microscopy, offering solutions to existing limitations and advancing the field towards more efficient and accurate imaging techniques.

Abstract: Sr2FeO3+x F1-x (x = 0.08, 0.2), an n = 1 Ruddlesden-Popperphase, was synthesized from the oxidationof Sr2FeO3F in air at high temperature followinga fluorine for oxygen substitution and Fe3+ to Fe4+ oxidation. A structural investigation of both compounds was performedusing complementary and high-resolution techniques (Synchrotron X-rayand electron diffraction, Mo''ssbauer spectroscopy, HR-STEM)coupled to DFT calculation. This study reveals that oxidation leadsto a high degree of apical anion disorder coupled to antiphase boundaries. Sr2FeO3F, an oxyfluoride compoundwith an n = 1 Ruddlesden-Popper structure,was identifiedas a potential interesting mixed ionic and electronic conductor (MIEC).The phase can be synthesized under a range of different pO(2) atmospheres, leading to various degrees of fluorinefor oxygen substitution and Fe4+ content. A structuralinvestigation and thorough comparison of both argon- and air-synthesizedcompounds were performed by combining high-resolution X-ray and electrondiffraction, high-resolution scanning transmission electron microscopy,Mo''ssbauer spectroscopy, and DFT calculations. While the argon-synthesizedphase shows a well-behaved O/F ordered structure, this study revealedthat oxidation leads to averaged large-scale anionic disorder on theapical site. In the more oxidized Sr2FeO3.2F0.8 oxyfluoride, containing 20% of Fe4+, two differentFe positions can be identified with a 32%/68% occupancy (P4/nmm space group). This originates due to the presenceof antiphase boundaries between ordered domains within the grains.Relations between site distortion and valence states as well as stabilityof apical anionic sites (O vs F) are discussed. This study paves theway for further studies on both ionic and electronic transport propertiesof Sr2FeO3.2F0.8 and its use in MIEC-baseddevices, such as solid oxide fuel cells.

Abstract: We have developed an innovative methodology to overcome the lack of techniques for real-time assessment of degradable biomedical polymers at physiological conditions. The methodology was established by combining polymer characterization techniques with electrochemical sensors. The in vitro hydrolytic degradation of a series of aliphatic polyesters was evaluated by following the molar mass decrease and the mass loss at different incubation times while tracing pH and l-lactate released into the incubation media with customized miniaturized electrochemical sensors. The combination of different analytical approaches provided new insights into the mechanistic and kinetics aspects of the degradation of these biomedical materials. Although molar mass had to reach threshold values for soluble oligomers to be formed and specimens’ resorption to occur, the pH variation and l-lactate concentration were direct evidence of the resorption of the polymers and indicative of the extent of chain scission. Linear models were found for pH and released l-lactate as a function of mass loss for the l-lactide-based copolymers. The methodology should enable the sequential screening of degradable polymers at physiological conditions and has potential to be used for preclinical material’s evaluation aiming at reducing animal tests.

Abstract: Renewed interest in the ferroelectric semi-conductor germanium telluride was recently triggered by the direct observation of a giant Rashba effect and a 30-year-old dream about a functional spin field-effect transistor. In this respect, all-electrical control of the spin texture in this material in combination with ferroelectric properties at the nanoscale would create advanced functionalities in spintronics and data information processing. Here, we investigate the atomic and electronic properties of GeTe bulk single crystals and their (111) surfaces. We succeeded in growing crystals possessing solely inversion domains of similar to 10 nm thickness parallel to each other. Using HAADF-TEM we observe two types of domain boundaries, one of them being similar in structure to the van der Waals gap in layered materials. This structure is responsible for the formation of surface domains with preferential Te-termination (similar to 68%) as we determined using photoelectron diffraction and XPS. The lateral dimensions of the surface domains are in the range of similar to 10-100 nm, and both Ge- and Te-terminations reveal no reconstruction. Using spin-ARPES we establish an intrinsic quantitative relationship between the spin polarization of pure bulk states and the relative contribution of different terminations, a result that is consistent with a reversal of the spin texture of the bulk Rashba bands for opposite configurations of the ferroelectric polarization within individual nanodomains. Our findings are important for potential applications of ferroelectric Rashba semiconductors in nonvolatile spintronic devices with advanced memory and computing capabilities at the nanoscale.

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.

Abstract: Gielis curves (GC) can represent a wide range of shapes and patterns ranging from star shapes to symmetric and asymmetric polygons, and even self intersecting curves. Such patterns appear in natural objects or phenomena, such as flowers, crystals, pollen structures, animals, or even wave propagation. Gielis curves and surfaces are an extension of Lamé curves and surfaces (superquadrics) which have benefited in the last two decades of extensive researches to retrieve their parameters from various data types, such as range images, 2D and 3D point clouds, etc. Unfortunately, the most efficient techniques for superquadrics recovery, based on deterministic methods, cannot directly be adapted to Gielis curves. Indeed, the different nature of their parameters forbids the use of a unified gradient descent approach, which requires initial pre-processings, such as the symmetry detection, and a reliable pose and scale estimation. Furthermore, even the most recent algorithms in the literature remain extremely sensitive to initialization and often fall into local minima in the presence of large missing data. We present a simple evolutionary algorithm which overcomes most of these issues and unifies all of the required operations into a single though efficient approach. The key ideas in this paper are the replacement of the potential fields used for the cost function (closed form) by the shortest Euclidean distance (SED, iterative approach), the construction of cost functions which minimize the shortest distance as well as the curve length using R-functions, and slight modifications of the evolutionary operators. We show that the proposed cost function based on SED and R-function offers the best compromise in terms of accuracy, robustness to noise, and missing data.