Abstract: Extension professionals are expected to help disseminate agricultural technologies, information, knowledge and skills to farmers. In order to develop valuable and long-lasting extension services, it is essential to understand the methods of extension that farmers find most beneficial. This understanding helps adopt improved practices, overcome barriers, provide targeted interventions and continuously improve agricultural extension programs. Thus, assessing factors affecting farmers' choice of agricultural extension methods is essential for developing extension methods that comply with farmers' needs and socio-economic conditions. Therefore, we analyzed the factors affecting farmers' preferences in extension methods, using cross-sectional data collected from 300 households in two sample districts and 16 Kebelles in Ethiopia between September 2019 and March 2020. Four extension methods, including training, demonstration, office visits and phone calls were considered as outcome variables. We fitted a multivariate probit model to estimate the factors that influence farmers' choice of extension methods. The results of the study showed that the number of dependents in the household head, formal education and membership of Idir (an informal insurance program a community or group runs to meet emergencies) were negatively associated with farmers' choices to participate in different extension methods compared to no extension. On the other hand, the sex of the household head, farm experience, participation in non-farm activities, monetary loan access, owning a mobile phone, radio access and membership of cooperatives were found to have a statistically significant positive impact on farmers' choices of extension methods. Based on these findings, the government and the concerned stakeholders should take farmers' socio-economic and institutional traits into account when selecting and commissioning agricultural extension methods. This could help to develop contextually relevant extension strategies that are more likely to be chosen and appreciated by farmers. Furthermore, such strategies can aid policymakers in designing extension programs that cater to farmers' needs and concerns. In conclusion, farmers' socio-economic and institutional affiliation should be taken into consideration when selecting agricultural extension methods.

Abstract: Electrochemical sensors have emerged as a new analytical tool for illicit drug detection to facilitate ultrafast and accurate identification of suspicious compounds on-site. Drugs of abuse can be identified using their unique voltammetric fingerprint at a given pH. Today, the right buffer solution is manually selected based on drug appearance, and in some cases, a consecutive analysis in two different pH solutions is required. In this work, we present a disposable microfluidic multichannel sensor system that automatically records fingerprints in two pH solutions (e.g., pH 5 and pH 12). This system has two advantages. It will overcome the manual selection of a buffer solution at the right pH, decrease analysis time, and minimize the risk of human errors. Second, the combination of two fingerprints, the superfingerprint, contains more detailed information about the samples, which enhances the selectivity of the analytical technique. First, real-time pH measurements proved that the sample can be brought to the desired pH within a minute. Subsequently, an electrochemical study on the microfluidic platform with 1 mM illicit drug standards of MDMA, cocaine, heroin, and methamphetamine showed that the characteristic voltammetric fingerprints and peak potentials are reproducible, also in the presence of common cutting agents. Finally, the microfluidic concept was validated with real confiscated samples, showing promising results for the user-friendly identification of drugs of abuse. In short, this paper presents a successful proof-of-concept study of a multichannel microfluidic sensor system to enrich the fingerprints of illicit drugs at pH 5 and pH 12, thus providing a low-cost, portable, and rapid identification system of illicit drugs with minimal user intervention.

Abstract: The electrochemical CO2 reduction offers a promising solution to convert waste CO2 into valuable products like CO and formate. However, CO2 capture and purification remains an energy intensive process and therefore the direct usage of industrially available waste CO2 streams containing SO2, NO and O2 impurities becomes more interesting. This work demonstrates an efficient (Faradaic efficiency > 90 %) and stable performance over 20 h with 200 ppm SO2 or NO in the feed gas stream. However, the addition of 1 % O2 to the CO2 feed causes a significant drop in Faradaic efficiency to C-products due to the competitive oxygen reduction reaction. A potential mitigation strategy is to operate at higher total current density to firstly reduce most O2 and achieve sufficient product output from CO2 reduction. These results aid in understanding the impact of flue gas impurities during CO2 electrolysis which is crucial for potentially bypassing the CO2 purification step.

Abstract: Cable bacteria are filamentous, multicellular microorganisms that display an exceptional form of biological electron transport across centimeter-scale distances. Currents are guided through a network of nickel-containing protein fibers within the cell envelope. Still, the mechanism of long-range conduction remains unresolved. Here, we characterize the conductance of the fiber network under dry and wet, physiologically relevant, conditions. Our data reveal that the fiber conductivity is high (median value: 27 S cm−1; range: 2 to 564 S cm−1), does not show any redox signature, has a low thermal activation energy (Ea = 69 ± 23 meV), and is not affected by humidity or the presence of ions. These features set the nickel-based conduction mechanism in cable bacteria apart from other known forms of biological electron transport. As such, conduction resembles that of an organic semi-metal with a high charge carrier density. Our observation that biochemistry can synthesize an organo-metal-like structure opens the way for novel bio-based electronic technologies.

Abstract: Restoration of drained peatlands through rewetting has recently emerged as a prevailing strategy to mitigate excessive greenhouse gas emissions and re-establish the vital carbon sequestration capacity of peatlands. Rewetting can help to restore vegetation communities and biodiversity, while still allowing for extensive agricultural management such as paludiculture. Belowground processes governing carbon fluxes and greenhouse gas dynamics are mediated by a complex network of microbial communities and processes. Our understanding of this complexity and its multi-factorial controls in rewetted peatlands is limited. Here, we summarize the research regarding the role of soil microbial communities and functions in driving carbon and nutrient cycling in rewetted peatlands including the use of molecular biology techniques in understanding biogeochemical processes linked to greenhouse gas fluxes. We emphasize that rapidly advancing molecular biology approaches, such as high-throughput sequencing, are powerful tools helping to elucidate the dynamics of key biogeochemical processes when combined with isotope tracing and greenhouse gas measuring techniques. Insights gained from the gathered studies can help inform efficient monitoring practices for rewetted peatlands and the development of climate-smart restoration and management strategies.

Abstract: In nature, the two-dimensional (2D) profiles of fruits from many plants often resemble ellipses. However, it remains unclear whether these profiles strictly adhere to the ellipse equation, as many natural shapes resembling ellipses are actually better described as superellipses. The superellipse equation, which includes an additional parameter n compared to the ellipse equation, can generate a broader range of shapes, with the ellipse being just a special case of the superellipse. To investigate whether the 2D profiles of fruits are better described by ellipses or superellipses, we collected a total of 751 mature and undamaged fruits from 31 naturally growing plants of Cucumis melo L. var. agrestis Naud. Our analysis revealed that most adjusted root-mean-square errors (> 92% of the 751 fruits) for fitting the superellipse equation to the fruit profiles were consistently less than 0.0165. Furthermore, there were 638 of the 751 fruits (ca. 85%) with the 95% confidence intervals of the estimated parameter n in the superellipse equation not including 2. These findings suggest that the profiles of C. melo var. agrestis fruits align more closely with the superellipse equation than with the ellipse equation. This study provides evidence for the existence of the superellipse in fruit profiles, which has significant implications for studying fruit geometries and estimating fruit volumes using the solid of revolution formula. Furthermore, this discovery may contribute to a deeper understanding of the mechanisms driving the evolution of fruit shapes.

Abstract: Coupling photosensitizers (PSs) with plasmonic nanoparticles increases the photocatalytic activity of PSs as the localized surface plasmon resonance (LSPR) of plasmonic nanoparticles leads to extreme concentration of light in their vicinity known as the near-field enhancement effect. To realize this in a colloidal phase, efficient conjugation of the PS molecules with the plasmonic nanoparticle surface is critical. In this work, we demonstrate the coupling of phthalocyanine (Pc) molecules with gold nanoparticles (AuNPs) in the colloidal phase via click chemistry. This conjugated Pc-AuNPs colloidal system is shown to enhance the photocatalytic singlet oxygen (1O2) production over non-conjugated Pcs and hence improve the photoelectrochemical detection of phenols. The plasmonic enhancement of the 1O2 generation by Pcs was clearly elucidated by complementary experimental and computational classical electromagnetic models. The dependence of plasmonic enhancement on the spectral position of the excitation laser wavelength and the absorbance of the Pc molecules with respect to the wavelength specific near-field enhancement is clearly demonstrated. A high similar to 8 times enhancement is obtained with green laser (532 nm) at the LSPR due to the maximum near-field enhancement at the resonance wavelength. Zinc phthalocyanine is covalently linked to plasmonic AuNPs via click chemistry to investigate the synergistic effect that boosts the overall activity toward the detection of HQ under visible light illumination. The 1O2 quantum yield of ZnPc improved significantly after conjugating with AuNPs, resulting in enhanced photoelectrochemical activity. image

Abstract: The efficiency of a catalytic process is assessed based on conversion, yield, and time effectiveness. However, these parameters are insufficient for evaluating environmentally sustainable research. As the world is urged to shift towards green catalysis, additional factors such as reaction media, raw material availability, sustainability, waste minimization and catalyst biosafety, need to be considered to accurately determine the efficacy and sustainability of the process. By combining the high porosity and versatility of metal organic frameworks (MOFs) and the activity of gold nanoparticles (AuNPs), efficient, cyclable and biosafe composite catalysts can be achieved. Thus, a composite based on AuNPs and the nanometric flexible porous iron(III) aminoterephthalate MIL-88B-NH2 was successfully synthesized and fully characterized. This nanocomposite was tested as catalyst in the reduction of nitroarenes, which were identified as anthropogenic water pollutants, reaching cyclable high conversion rates at short times for different nitroarenes. Both synthesis and catalytic reactions were performed using green conditions, and even further tested in a time-optimizing one-pot synthesis and catalysis experiment. The sustainability and environmental impact of the catalytic conditions were assessed by green metrics. Thus, this study provides an easily implementable synthesis, and efficient catalysis, while minimizing the environmental and health impact of the process.

Abstract: Photocathodes play a vital role in photoelectrocatalytic water splitting by acting as catalysts for reducing protons to hydrogen gas when exposed to light. Recent advancements in photocathodes have focused on addressing the limitations of noble metal-based materials. These noble metal-based photocathodes rely on expensive and scarce metals such as platinum and gold as cocatalysts or ohmic back contacts, respectively, rendering the final system less sustainable and costly when applied at scale. This mini-review summarizes the important recent progress in the development of non-noble metal-based photocathodes and their performance in the hydrogen evolution reaction during photoelectrochemical (PEC) water splitting. These advancements bring non-noble metal-based photocathodes closer to their noble metal-based counterparts in terms of performance, thereby paving the way forward toward industrial-scale photoelectrolyzers or PEC cells for green hydrogen production.

Abstract: We assessed the impact of road disturbances on the dominant mycorrhizal types in ecosystems at the global level and how this mechanism can potentially lead to lasting plant community changes. We used a database of coordinated plant community surveys following mountain roads from 894 plots in 11 mountain regions across the globe in combination with an existing database of mycorrhizal-plant associations in order to approximate the relative abundance of mycorrhizal types in natural and disturbed environments. Our findings show that roadside disturbance promotes the cover of plants associated with arbuscular mycorrhizal (AM) fungi. This effect is especially strong in colder mountain environments and in mountain regions where plant communities are dominated by ectomycorrhizal (EcM) or ericoid-mycorrhizal (ErM) associations. Furthermore, non-native plant species, which we confirmed to be mostly AM plants, are more successful in environments dominated by AM associations. These biogeographical patterns suggest that changes in mycorrhizal types could be a crucial factor in the worldwide impact of anthropogenic disturbances on mountain ecosystems. Indeed, roadsides foster AM-dominated systems, where AM-fungi might aid AM-associated plant species while potentially reducing the biotic resistance against invasive non-native species, often also associated with AM networks. Restoration efforts in mountain ecosystems will have to contend with changes in the fundamental make-up of EcM- and ErM plant communities induced by roadside disturbance.

Abstract: The structure-property relationship at interfaces is difficult to probe for thermoelectric materials with a complex interfacial microstructure. Designing thermoelectric materials with a simple, structurally-uniform interface provides a facile way to understand how these interfaces influence the transport properties. Here, we synthesized Bi2-xSbxTe3 (x = 0, 0.1, 0.2, 0.4) nanoflakes using a hydrothermal method, and prepared Bi2-xSbxTe3 thin films with predominantly (0001) interfaces by stacking the nanoflakes through spin coating. The influence of the annealing temperature and Sb content on the (0001) interface structure was systematically investigated at atomic scale using aberration-corrected scanning transmission electron microscopy. Annealing and Sb doping facilitate atom diffusion and migration between adjacent nanoflakes along the (0001) interface. As such it enhances interfacial connectivity and improves the electrical transport properties. Interfac reactions create new interfaces that increase the scattering and the Seebeck coefficient. Due to the simultaneous optimization of electrical conductivity and Seebeck coefficient, the maximum power factor of the Bi1.8Sb0.2Te3 nanoflake films reaches 1.72 mW m(-1) K-2, which is 43% higher than that of a pure Bi2Te3 thin film.

Abstract: Multi-objective optimization is an important decision-making tool for energy processes, as multiple targets need to be achieved. These objectives are usually conflicting since a single solution cannot be optimal for all objectives, resulting in a set of Pareto-optimal solutions. Multiple indicators might be available to describe a sustainability objective, such as the environmental impact which is commonly evaluated by performing a life cycle assessment. In this study, Pareto aggregation is proposed as a method which employs a novel multi-objective optimization-based approach as an alternative to the classically used aggregation in life cycle assessment. This method identifies conflicting environmental indicators and performs an aggregation among those that require a trade-off. An environmental-economic optimization of a second-generation bioethanol plant is used to illustrate and evaluate the proposed method. Process parameters from a biochemical conversion pathway flowsheet simulation model are chosen as optimization variables. To reduce the computational time, surrogate models, based on artificial neural networks, are used. Out of the eighteen ReCiPe Midpoint environmental indicators, five were identified as conflicting, resulting in an aggregated environmental objective, which was then traded off with the economic objective function, chosen as the levelized cost of ethanol. Comparison with the widely used single-score EcoIndicator99 showed that the Pareto aggregation method can reduce most of the environmental indicators by up to 6.5%. This research provides an insight on non-redundant objective functions, aiming at reducing the dimensionality of multi-objective optimization problems, while taking into consideration decision-makers’ preferences.

Abstract: Cable bacteria embed a network of conductive protein fibers in their cell envelope that efficiently guides electron transport over distances spanning up to several centimeters. This form of long-distance electron transport is unique in biology and is mediated by a metalloprotein with a sulfur-coordinated nickel (Ni) cofactor. However, the molecular structure of this cofactor remains presently unknown. Here, we applied multi-wavelength Raman microscopy to identify cell compounds linked to the unique cable bacterium physiology, combined with stable isotope labeling, and orientation-dependent and ultralow-frequency Raman microscopy to gain insight into the structure and organization of this novel Ni-cofactor. Raman spectra of native cable bacterium filaments reveal vibrational modes originating from cytochromes, polyphosphate granules, proteins, as well as the Ni-cofactor. After selective extraction of the conductive fiber network from the cell envelope, the Raman spectrum becomes simpler, and primarily retains vibrational modes associated with the Ni-cofactor. These Ni-cofactor modes exhibit intense Raman scattering as well as a strong orientation-dependent response. The signal intensity is particularly elevated when the polarization of incident laser light is parallel to the direction of the conductive fibers. This orientation dependence allows to selectively identify the modes that are associated with the Ni-cofactor. We identified 13 such modes, some of which display strong Raman signals across the entire range of applied wavelengths (405–1,064 nm). Assignment of vibrational modes, supported by stable isotope labeling, suggest that the structure of the Ni-cofactor shares a resemblance with that of nickel bis(1,2-dithiolene) complexes. Overall, our results indicate that cable bacteria have evolved a unique cofactor structure that does not resemble any of the known Ni-cofactors in biology.

Abstract: Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain. In this work, we generated a comprehensive laboratory ground truth dataset of intimately mixed mineral powders. For this, five clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide) were mixed homogeneously to prepare 325 samples of 60 binary, 150 ternary, 100 quaternary, and 15 quinary mixtures. Thirteen different hyperspectral sensors have been used to acquire the reflectance spectra of these mixtures in the visible, near, short, mid, and long-wavelength infrared regions (350-15385) nm. Overlaps in wavelength regions due to the operational ranges of each sensor and variations in acquisition conditions resulted in a large amount of spectral variability. Ground truth composition is given by construction, but to verify that the generated samples are sufficiently homogeneous, XRD and XRF elemental analysis is performed. We believe these data will be beneficial for validating advanced methods for nonlinear unmixing and material composition estimation, including studying spectral variability and training supervised unmixing approaches. The datasets can be downloaded from the following link: https://github.com/VisionlabHyperspectral/Multisensor_datasets.

Abstract: Our study compares short-range order parameters refined from the diffuse scattering in single-crystal X-ray and single-crystal electron diffraction data. Nb0.84CoSb was chosen as a reference material. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms were refined from the diffuse scattering using a Monte Carlo refinement in DISCUS. The difference between the Sb and Co displacements refined from the diffuse scattering and the Sb and Co displacements refined from the Bragg reflections in single-crystal X-ray diffraction data is 0.012 (7) angstrom for the refinement on diffuse scattering in single-crystal X-ray diffraction data and 0.03 (2) angstrom for the refinement on the diffuse scattering in single-crystal electron diffraction data. As electron diffraction requires much smaller crystals than X-ray diffraction, this opens up the possibility of refining short-range order parameters in many technologically relevant materials for which no crystals large enough for single-crystal X-ray diffraction are available.