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This study evaluates the performance of small-scale high-temperature treatment facilities for managing rural domestic waste on the Tibetan Plateau and investigates the emission characteristics of dioxin pollutants. Seven small-scale facilities (with capacities ranging from 3 to 25 t/d) selected from a total of 183 different facilities in the Tibetan Plateau region, underwent on-site sampling and laboratory multi-threaded pollutant analysis of pollutants. The results revealed that dioxin emission concentrations in the flue gas ranged from 0.085 to 53.6 ng I-TEQ/Nm3. The primary mechanism for dioxin synthesis in the flue gas of small-scale gasification incinerators and high-temperature pyrolysis furnaces consisted of the precursor formation mechanism, whereas de novo synthesis was observed in conventional incinerators. Dioxin concentrations in fly ash varied from 0.0060 to 11.59 ng I-TEQ/g, with precursor synthesis as the dominant pathway. The distribution of dioxin in activated carbon and desulfurization lye notably differed significantly from that in the flue gas and fly ash congeners. Additionally, the dioxin content in the pyrolysis products exceeded both the concentrations in purchased-coal and the relevant emission limits. The total emission factors for these facilities ranged from 0.49 to 326.92 µg I-TEQ/t, with variations of the distribution of dioxin emission factors observed across different facilities. [ABSTRACT FROM AUTHOR]

This paper describes a filleting machine designed for the popular Asian freshwater species rohu (Labeo rohita). The machine comprises three key units: conveying, filleting, and water spraying and collection. The filleting unit has two parallel disc blades for precise cutting, with adjustable spacing to accommodate a variety of fish backbone thicknesses. The conveying unit employs belt drives and spring-adjusted entry for smooth transport, while the water management unit sprays and cleans the filleting blades, ensuring efficient fish movement. The machine performed efficiently when set to its optimal settings and showed significant improvements compared to manual filleting while maintaining product quality. [ABSTRACT FROM AUTHOR]

This paper used the UK Agency for International Development sustainable livelihood framework to measure small-scale in-land fishing household’s livelihood by sustainable livelihood capital index in the vulnerable context of aquatic natural resource depletion in the wetland forest of Ca Mau province, Vietnam. Findings indicated that fishing households’ livelihood capital is unsustainable and inadequate. The result took note of the beneficial physical capital while underlining the human, natural, financial, and social capital’s limitations in achieving livelihood sustainability. The limitations were found to be a low score of composite index of sustainable livelihood capital (less than an average score of 0.5) whereas the outstanding score of physical capital was found. Providing training in the adoption of new livelihood models, learning livelihood diversification, access to formal credit, and appropriate coverage of social safety-net programs might help mitigate the unsustainable livelihood of inland fishing households.

Small-scale spatial abilities that involve the mental representation and transformation of two- and three-dimensional images and manipulation of objects at table-top have been studied extensively and are considered predictive of both interest and success in STEM disciplines. However, research investigating the relation of large-scale spatial abilities to STEM disciplines is sparse. The paper describes the design and implementation of a study for assessing individual differences (if any) in spatial abilities in both figural and environmental spaces between STEM experts (with over 10 years of experience) and non-experts (individuals without any studies in STEM fields). Participants' performance in 16 small-, 10 large-scale tasks, and one self-assessment questionnaire at environmental scale was evaluated to assess their corresponding abilities. Results indicate differences between experts and non-experts, which are mostly highlighted for small-scale abilities where experts outperform non-experts. At large scale, some significant differences are identified, which also favor experts. Correlations among the variables tested provide evidence that different abilities are prominent between experts and non-experts. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Semantic segmentation is a fundamental step in image understanding, playing a crucial role in the fields of automatic driving, medical image analysis, defect detection, etc. Despite significant progress in deep learning-based image segmentation, challenges in terms of accuracy and efficiency still exist, especially for small-scale objects. In this paper, we present a novel data augmentation method for small-scale objects in images, aiming to address the issue of class imbalance. Specifically, we extract small-scale objects from one image and then copy-scale-and-paste them to other images. Additionally, a novel multi-scale feature fusion module is proposed to effectively combine features from both deep and shallow neural network layers. Subsequently, the data augmentation method and multi-scale feature fusion module are utilized in the proposed Fast-SegNet architecture for semantic segmentation. Extensive experiments demonstrate that Fast-SegNet could improve segmentation performance, especially for small-scale objects with an acceptable computational cost. State-of-the-art performance has been achieved on CamVid, CityScapes, and MOST (Micro-optical sectioning tomography) datasets with respect to the tradeoff between accuracy and speed. Specifically, the CamVid dataset yields mean IoU (Intersection over Union) values of 45.7% and 38.6% for small-scale objects as Pedestrian and Bicyclist, respectively. The CityScapes dataset demonstrates mean IoU of 43.43% and 43.56% for small-scale objects as Traffic Light and Rider, respectively. The MOST dataset results in a segmentation mean IoU of 88.2% for vessels in the mouse brain. In conclusion, our approach achieves better results in terms of accuracy and efficiency on three datasets. Codes are available at https://github.com/apple1986/Fast-SegNet. [ABSTRACT FROM AUTHOR]

The growth of maritime shipping is leading to the creation of larger vessels. However, this expansion in size brings with it several challenges, including the development of maritime infrastructure, the potential for growth in third-world countries, and the emission of greenhouse gases. In response to these challenges, this research explores the feasibility of designing an autonomous ship capable of transporting a single standardized 40 ft. container overseas using mainly passive propulsion methods. Using advanced design tools, including CAD software and CFD simulations, as well as conducting a comprehensive analysis of relevant literature, the designs for a hull and sails were developed, and an overview of the potential active control systems required for autonomous operation was provided. The study also performed an initial analysis of strength, stability, and velocity to validate the design choices. The ship proves to adhere to the basic strength and stability requirements while reaching its maximum hull velocity at certain wind speeds. The results of the study indicate that it is possible to design and manufacture a mainly passively propelled ship capable of transporting a 40 ft. standardized container overseas and rethink the logistics at scale. [ABSTRACT FROM AUTHOR]

• A small-scale pumpless absorption refrigeration (ARC) system is established. • Switching valves method (SVM) is employed to substitute for electrical pump. • Non-toxic R134a/DMF is chosen to create high pressure differential for pumping liquid. • The pumpless ARC system is validated feasible for low-grade thermal energy recovery. • The maximum COP of the system is 0.28. To address the challenges related to corrosion, sealing, additional electrical energy consumption, and the limited adaptability imposed by the electrically-driven solution pump to small-scale absorption refrigeration cycle (ARC) system, a pumpless module based on the switching valves method (SVM) is designed and constructed for an ARC system. The pumpless operation is realized based on thermal-gravity-driven mechanism by employing a corresponding valve-assembly among three vessels, which effectively substitutes for the electrical solution pump. R134a/DMF is employed as the working pair to maintain the necessary pressure differential for efficient solution pumping process. The overall performance of the system is studied. Experimental results show that the system operating parameters fluctuate periodically, and the fluctuation induces periodic variations in heat input and cooling capacity in the range of 0.95∼1.76 kW and 0.27∼0.79 kW, respectively. For the system the maximum cooling capacity of 0.79 kW and the average cooling capacity of 0.33 kW are achieved under the conditions of valve opening of 32°, average hot oil temperature of 116.9°C, heat sink temperature of 30.9°C, cooling source temperature of 25.9°C, and cycle time of 300 s, while the average COP of 0.28 is achieved at the cycle time of 420 s under the same conditions. The pumpless module is validated feasible as a promising alternative to solution pump, especially for small-scale system. [ABSTRACT FROM AUTHOR]

Copyright of Modern Geográfia is the property of Publikon Publishers/ IDResearch Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bioprocessing has been transitioning from batch to continuous processes. As a result, a considerable amount of resource was dedicated to optimising strategies for continuous production. However, the focus has been on developing a suitable and scalable perfusion strategy with little attention given to the selection of optimal cell clones. Cell line development and lead clone selection are critical to bioprocess development. The screening and selection process is typically performed in stages. Microwell plates (MWP) are used to narrow down the number of clone candidates, which will undergo further selective screening in progressively larger small-scale bioreactors (12 mL–3 L) to identify the top clone for GMP production. Perfusion mode is typically applied at bench-scale for optimisation purposes, while process development and cell clone screening studies at mL-scale still commonly use fed-batch methods. The change of operation mode from bolus feeding to perfusion with a regular exchange of medium, leads to questions regarding the reliability and fit of initial clone selection. Is the early-stage clone ranking impacted by the discrepancy in the operation mode, and does this potentially result in the exclusion of cell clones suitable for perfusion processes? To address this question, we evaluated various CHO cell clones expressing two antibody products using MWP methodologies in fed-batch and semi-perfusion mode. We assessed growth, metabolic, and productivity performance, and ranked cell clones using two different strategies. The first strategy evaluated clones based on a single parameter: the cell-specific productivity (qP). The second considered a collection of multiple parameters using the metric of the Manufacturability index (MICL). Both ranking strategies showed an impact of operation mode and perfusion rate on the clone ranking. Notably, depending on the chosen operation mode, different sets of candidate clones might have been selected for further, more extensive screening. Additionally, we evaluated the reproducibility of our results demonstrating consistency in cell clone growth performance and ranking.

Biomass gasification has increased due to its ability to provide high-temperature heat, making it promising for the decarbonisation of industrial processes. The economic and technical challenges of large-scale operations need to be addressed by focusing on small-sized gasifiers, while the use of low-grade biomass, is essential to increase the flexibility and sustainability of the plant. However, the utilisation of low-grade biomass is hindered by challenges stemming from variations in the particle distribution and shape, which significantly impact the fluidisation process and overall. In this research, the gasification of shredded municipal waste wood in a pilot-scale bubbling fluidised bed reactor was demonstrated, and the fluid-dynamics and gas production were assessed. The gasification process was yielding a gas with a lower heating value between 3.5MJNm−3 and 3.9MJNm−3 and a cold gas efficiency (CGE) of 46.4 %–48.6 %. Notably, these CGE values are consistent with pilot-scale setups, where CGE values above 50 % are typically not achievable because of poor insulation standards. The reactor's conical shape facilitated dynamic fluid regime transitions, ensuring efficient gas-solid interactions. This design allowed optimisation of fluidisation by accommodating particles of varying sizes throughout the reactor's height, thereby promoting efficient gasification suitable for industrial applications with diverse biomass feedstocks.

Featured Application: The design and rapid manufacture of efficient scale-propellers for use on small first-person view drones, such as those used in special operations to improve their endurance. This study investigated the efficiency of scale-propellers, typically used on small drones. A scale-propeller is accepted as having a diameter of 7 to 21 inches. Recent special operations has demonstrated the utility of relatively small, low-cost first-person view (FPV) drones, which are attritable. This investigation outlines the development of a MATLAB optimisation code, based on minimum induced loss propeller theory, which calculates the optimal chord and twist distribution for a chosen propeller operating in known flight conditions. The MATLAB code includes a minimum Reynolds number functionality, which provides the option to alter the chord distribution to ensure the entire propeller is operating above a set threshold value of Reynolds (>100,000), as this has been found to be a transition point between low and high section lift-to-drag ratios. Additional functions allow plotting of torque and thrust distributions along the blade. The results have been validated on experimental data taken from an APC 'Thin Electric' 10" × 7" propeller, where it was found that both the chord and twist distributions were accurately modelled. The MATLAB code resulted in a 16% increase in the maximum propulsive efficiency. Further work will investigate a direct interface to SolidWorks to aid rapid propeller manufacturing capability. [ABSTRACT FROM AUTHOR]

Due to the increasing importance of using clean energy, Hydrodynamic screw turbine has been considered as a small-scale hydropower source. One of the characteristics that makes the mentioned turbine to be unique compared to others is its acceptable performance in low head and flow conditions. Although a lot of research has been done in the world to achieve the best configuration to achieve the maximum output efficiency using numerical and laboratory methods, but the methods of making these types of turbines have rarely been examined. In this research, for the first time in Iran, the construction of a hydrodynamic screw turbine with a traditional method based on common industrial processes has been described. Then, its testing and evaluation have been considered. The installation angle of 24 degrees was obtained as the optimal installation angle. [ABSTRACT FROM AUTHOR]

Aflatoxin B1 (AFB1) is a poisonous and carcinogenic fungal by-product produced by Aspergillus flavus and Aspergillus parasiticus species, causing acute and chronic toxicity in humans and animals. The global concern surrounding AFB1 arises from its adverse effects on public health, the economy, and social well-being. The aim of the study was to determine the prevalence of AFB1 in feeds and its awareness among small and medium scale livestock farmers. Livestock feed samples were randomly collected and analyzed in the laboratory for fungi known to produce aflatoxins using selective media. The positive samples were subjected to QSight LX50 UHPLC coupled with QSight 220 triple quadrupole Mass Spectrometer analysis to confirm presence of AFB1 and determine the quantity of the levels of AFB1. The questionnaire was employed to assess cognizance of aflatoxin among livestock farmers. On average every 27 out of 100 collected samples were found to be contaminated with aflatoxins. Poultry feeds had the highest contamination followed by feeds for other species. Further analysis revealed a significant association between storage and aflatoxins contaminations (X²= 10.65; p-value= 0.03). The contamination ranged from 6.5 to70.2ng g-1 of AFB1. The study also revealed a varied levels of awareness on AFB1 between small and medium scale farmers with medium scale farmers having a relatively higher awareness on the effect of AFB1 than small scale farmers. The presence of AFB1 shows that it is necessary to implement mitigation measures that focus on reducing the incidence of aflatoxin contamination, and improvement of AFB1 awareness in small and medium scale livestock farmers. [ABSTRACT FROM AUTHOR]

The biopharmaceutical industry is replacing fed‐batch with perfusion processes to take advantage of reduced capital and operational costs due to the operation at high cell densities (HCD) and improved productivities. HCDs are achieved by cell retention and continuous medium exchange, which is often based on the cell‐specific perfusion rate (CSPR). To obtain a cost‐productive process the perfusion rate must be determined for each process individually. However, determining optimal operating conditions remain labor‐intensive and time‐consuming experiments, as investigations are performed in lab‐scale perfusion bioreactors. Small‐scale models such as microwell plates (MWPs) provide an option for screening multiple perfusion rates in parallel in a semi‐perfusion mimic. This study investigated two perfusion rate strategies applied to the MWP platform operated in semi‐perfusion. The CSPR‐based perfusion rate strategy aimed to maintain multiple CSPR values throughout the cultivation and was compared to a cultivation with a perfusion rate of 1 RV d−1. The cellular performance was investigated with the dual aim (i) to achieve HCD, when inoculating at conventional and HCDs, and (ii) to maintain HCDs, when applying an additional manual cell bleed. With both perfusion rate strategies viable cell concentrations up to 50 × 106 cells mL−1 were achieved and comparable results for key metabolites and antibody product titers were obtained. Furthermore, the combined application of cell bleed and CSPR‐based medium exchange was successfully shown with similar results for growth, metabolites, and productivities, respectively, while reducing the medium consumption by up to 50% for HCD cultivations. [ABSTRACT FROM AUTHOR]

The promise of continuous processing to increase yields and improve product quality of biopharmaceuticals while decreasing the manufacturing footprint is transformative. Developing and optimizing perfusion operations requires screening various parameters, which is expensive and time‐consuming when using benchtop bioreactors. Scale‐down models (SDMs) are the most feasible option for high‐throughput data generation and condition screening. However, new SDMs mimicking perfusion are required, enabling experiments to be run in parallel. In this study, a method using microwell plates (MWP) operating in semi‐perfusion mode with an implemented cell bleed step is presented. A CHO cell line was cultivated in a 24‐well MWP (Vw = 1.2 mL) and grown at four high cell density (HCD) setpoints. Quasi steady‐state condition was obtained by manually performing cell bleeds followed by a total medium exchange after centrifugation. Further, two HCD setpoints were scaled up (VW = 30 mL), comparing a squared six‐well deepwell plate (DWP) to shake flasks (SF). This evaluation showed comparable results between systems (DWP vs. SF) and scales (MWP vs. DWP + SF). The results show that the well‐plate‐based methods are suitable to perform HCD and quasi steady‐state cultivations providing a robust solution to industrially relevant challenges such as cell clone and media selection. [ABSTRACT FROM AUTHOR]

The growth of maritime shipping is leading to the creation of larger vessels. However, this expansion in size brings with it several challenges, including the development of maritime infrastructure, the potential for growth in third-world countries, and the emission of greenhouse gases. In response to these challenges, this research explores the feasibility of designing an autonomous ship capable of transporting a single standardized 40 ft. container overseas using mainly passive propulsion methods. Using advanced design tools, including CAD software and CFD simulations, as well as conducting a comprehensive analysis of relevant literature, the designs for a hull and sails were developed, and an overview of the potential active control systems required for autonomous operation was provided. The study also performed an initial analysis of strength, stability, and velocity to validate the design choices. The ship proves to adhere to the basic strength and stability requirements while reaching its maximum hull velocity at certain wind speeds. The results of the study indicate that it is possible to design and manufacture a mainly passively propelled ship capable of transporting a 40 ft. standardized container overseas and rethink the logistics at scale.

With the increasing attention paid to groundwater contamination issues, the increasing demand was needed for small-scale site contamination hydrogeological work. The site contamination hydrogeological work has some particularities, which includes small scale, high resolution, and not only studying of contamination processes with the source leakage, but also studying of contaminant removal under the remediation state. Especially the transportation and reactions in the aquifer for in situ injected fluids (gases, liquids and microbes) of remediation agents need to be concerned greatly. The traditional large-scale hydrogeological work is difficult to meet the special needs above, therefore, it is necessary to propose “site contamination hydrogeology” for site-scale groundwater pollution risk management. This paper focuses on the characterization of stratigraphic media and pollution plumes in small-scale contaminated site, quantitative description of the pollutant-water-rock reactions, and the role and influence of pollutants in heterogeneous strata in multiphase systems. Finally, the main research content and key issues for site contamination hydrogeology were proposed, including: high-resolution characterization of sites at small scales, quantitative description of the physical, chemical, and biological reactions of pollutants in the underground environment during pollution and remediation processes, the migration and transformation of pollutants at the site scale in underground environmental media, transport and reaction of remediation agents (additives) in underground environments, and the pollution control and remediation in heterogeneous and low-permeability formations.

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article examines the potential overestimation of the importance of small-scale electric fields in the polar ionosphere. The author suggests that previous studies may have exaggerated the impact of these electric field variations on energy dissipation through Joule heating. The article emphasizes the need for future multispacecraft measurements to accurately determine the dimensions and lifetimes of these fluctuations. It also highlights the limitations of current satellite configurations in detecting and measuring these electric field spikes. The text concludes by stating that further research is needed to accurately assess the significance of small-scale electric field fluctuations in Joule heating. [Extracted from the article]

The COVID-19 pandemic created an unprecedented shock to capture fisheries and aquaculture sectors. This scoping review of 670 articles explored the spatial, temporal, and thematic coverage of this event. The search period was January 1, 2020 to February 7, 2022. Articles were mainly peer-reviewed journals (88%) with the remainder from the gray literature (12%). Studies were performed at the global (21%), multi-country (11%), national (45%), and sub-national (23%) levels. Most studies involved primary or secondary data collection (71%) and the remainder were either review articles (17%) or commentaries (12%). Among the studies using primary and secondary data, nearly half (49%) were performed in the first five months of the pandemic (March to July 2020), and 84% within the first year of the pandemic (March 2020–February 2021). There were many studies in South and Southeast Asia, Southern Europe, China, and the United States, and fewer studies in other regions. The pandemic created challenges and opportunities, with heterogeneity in impacts among industrial and small-scale sectors, production methods, geographies, value chains, and by gender. Cumulative impacts from climate change and conflicts contributed to pandemic-related hardships. Increased unemployment and inflation led to rising food insecurity for small-scale producers, fishworkers, and low-income households. Aquatic food intake was more severely affected than other food groups during lockdowns, and it decreased more in low- and middle-income countries than in high-income countries. Responses were diverse, reflecting the capacity and resources of a country, but in general there was unprecedented public support to sustain the private sector (i.e., income support, tax relief, subsidies). As this study focused mainly on the first year of the pandemic, future work is needed to identify which groups exited the pandemic stronger or weaker, what factors enabled some populations to bounce-back, how the crisis affected value chains, and the effectiveness of interventions. [ABSTRACT FROM AUTHOR]

Climate change significantly impacts small-scale agriculture, with limited adaptation capabilities due to lack of access to advanced science and technology. Traditional methods are ideal, but modern adaptations require significant financial investment, affecting the smallholder under-resourced agricultural sector's economic activities. The study analyzed climate change adaptation drivers among small-scale vegetable farmers, using a representative sample of 244 farmers from four villages through face-to-face interviews and semi-structured questionnaires. Using the Logistic regression model, the results showed resources (extension services), institutional (association membership) and societal influence (farm produce theft, and animal trespassing in the farming plots) to be associated with the use of modern climate change adaptation measures in the study area. The study recommends expanding extension services, strengthening community policing, creating community grazing guidelines, and training farmers on climate change causes, social cohesion, and mitigation strategies to address farm produce theft and animal trespassing. The study contributes new knowledge to the discourse of climate change adaptation by providing empirical evidence pointing out the need to consider critical non-climate factors for farmers when making climate change adaptations interventions in the smallholder farming sector.

In this paper, the diffusion characteristics and laws of hydrogen leakage in confined spaces are investigated using a combination of numerical simulations and experiments, and a small-scale cube model (dimensions: 0.47 m×0.33 m × 0.20 m) is used. The effects of leak source location, obstacles, leak hole size and shape on hydrogen diffusion and concentration evolution were investigated. The results show that the top funnel is sprayed vertically downward, the diffusion velocity decreases rapidly under the blocking effect of air and buoyancy force, and the momentum of the airflow is exchanged. During the injection phase, the leaking gas is mainly subjected to strong buoyancy forces and the hydrogen concentration shows a stratification effect. When the injection stops, the concentration difference decreases and eventually the hydrogen concentration reaches a steady state. The obstacle model in turbulence (4.3%) increases the concentration difference by a factor of about three compared to the empty room model (1.7%), which seriously affects the diffusive behavior of hydrogen. The obstacle in laminar flow model (10.4%) has almost the same concentration difference as the empty room model (10.2%). Rectangular leakage holes have a greater initial kinetic energy and diffuse more widely and faster. • Effects of obstacles, leakage hole size and shape on concentration were studied. • The rate of diffusion is reduced due to the blocking effect of air and buoyancy. • Hydrogen concentration shows a stratification effect in the presence of buoyancy. • Obstacles cause loss of gas kinetic energy and delay the averaging time. • Rectangular leakage holes have a large gas diffusion range and fast diffusion rate. [ABSTRACT FROM AUTHOR]

Due to the increasing human need for electrical energy and the reduction of non-renewable resources for its production, the use of non-fossil and renewable resources and resources that have less environmental damage have been taken into consideration. Archimedes screw turbine is used as a means of producing clean energy in waterways, and many theoretical and experimental studies have been done on it. Most of these studies, in laboratory and numerical form, are in the field of optimization of screw constituent components and their effect on its efficiency including length, inner and outer diameter, installation angle, number of blades and screw pitch. In this research, the most important studies conducted in the field of Archimedes screw turbine performance, which have been published in the last two decades, were reviewed. The results showed that the parameters of screw components have a greater effect on efficiency compared to hydraulic parameters. [ABSTRACT FROM AUTHOR]

This commentary reflects on the experiences of a cohort of human and physical geographers in enacting environmental collaborations during their doctoral studies. The authors identify three key structural barriers encountered whilst attempting a collaborative approach: (1) doctoral funding priorities, (2) doctoral resourcing and (3) assessing doctoral collaboration. The authors discuss how the negotiation of these encounters came to frame their understanding of collaborative approaches to environmental knowledge creation. Competitive application processes for doctoral studentships can encourage the overpromising of the impact of planned environmental collaboration, potentially co‐opting the voices of partners/communities to satisfy doctoral funding requirements. Given insufficient funding of collaborations, the authors argue that this overpromising of doctoral research's impact can later result in difficult trade‐offs between undertaking additional commitments at the expense of the career progression of the doctoral student, contributing to educational inequalities and scaling‐back the initial plans at the cost of collaborators encountering environmental crises. The trade‐off is further problematised by institutional assessment procedures that do not adequately recognise the more nuanced contributions of environmental collaborations and a prevailing culture promoting peer‐review publishing. Overall, the commentary argues that these barriers help to reproduce inequalities in the distribution of voice in environmental scholarship, undermining efforts to democratise environmental knowledge creation in doctoral research. The authors call for specific structural reforms of doctoral programmes to help address these challenges and support a broader resistance to the inadequate resourcing and evaluation of environmental collaborative research in UK higher education. This commentary reflects on the experiences of a cohort of human and physical geographers in enacting environmental collaborations during their doctoral programmes. We draw attention to the key structural barriers we encountered. Going forward, we call for specific structural reforms of doctoral programmes to help address these challenges and support wider environmental collaborative research. [ABSTRACT FROM AUTHOR]

This study uses a cost-benefit analysis to compare the economic effects of using three digital technologies for herbage mass estimation: Rising Plate Meter (RPM), Unmanned Aerial Vehicle with Structure from Motion (UAV SfM) and Portable Light Detection and Ranging (UAV LiDAR) systems in small-scale farms in mountainous regions of southern Germany. The results show that, at the current state of technology, digital herbage mass estimation leads to comparatively high costs, coming to a large extent from labor and depreciation costs. Despite of the relatively high annual costs, the costs associated with the use of the RPM could be compensated on all investigated farm types by improving their pasture utilization by only 5%. By contrast the costs of a UAV LiDAR could not be compensated on the current state of technology. However as soon as the technical developments and positive changes in the legal framework are implemented, the costs of the UAV-based technologies studied will decrease significantly. This will lead to their wide dissemination in pasture-based production systems. [ABSTRACT FROM AUTHOR]

In this research, whole process of small-scale and pilot-scale carrier-free 177Lu production have been developed and curie-level 177Lu was achieved. Additionally, the methodology of product key quality control inspection has been developed and verified, the control standard has been established. Key indicators of the product have met or exceeded the requirements of the European Pharmacopoeia. Up to date, about 30 Ci carrier-free 177Lu product has been obtained based on this development. The carrier-free 177Lu obtained in this research has been used in nearly 20 trial parties including units for drug R & D and clinical research. [ABSTRACT FROM AUTHOR]

Although the work of identifying animal and plant objects with highly similar patterns (e.g., texture, intensity, colour, etc.) to the background has recently attracted more research interest but rarely involves the military complex environment. Design an efficient camouflage small‐scale object detection algorithm that is capable of quickly discriminating the objects in open scenes from a long distance, to pre‐empt the enemy. In this work, we first recognize the fact that existing open‐source training datasets are scarce, and we have created a specific disguised people benchmark covering multiple scenes and weather conditions. Second, because the severe corruption of camouflage capabilities and chaotic scenes in the open battlefield on detailed features and generalization intensifies the challenge of feature extraction from a long‐range perspective, we propose a novel end‐to‐end Small‐scale open scene Camouflage Object Detection Network, called SM‐CODN. Inspired by the characteristics of biological brain partition, a multi‐domain partition module (MPM) with domain‐decoupling is proposed to enable specific knowledge learning for samples with obvious discrepancies in camouflage domain distribution. Concurrent with our work, we have designed a multi‐scale fusion module (MFM) to strengthen the semantic features related to small‐scale disguised objects. Moreover, due to the convergence direction of the detector in reasoning being inconsistent, a feature separation enhancement module (FSEM) is also proposed. Experimental results show that SM‐CODN surpasses many classic object detection methods and shows strong competitiveness compared with state‐of‐the‐art ones. [ABSTRACT FROM AUTHOR]

Brittle materials, such as oxide glasses, are usually very sensitive to flaws, giving rise to a macroscopic fracture strength that is much lower than that predicted by theory. The same applies to metallic glasses (MGs), with the important difference that these glasses can exhibit certain plastic strain prior to catastrophic failure. Here we consider the strongest metallic alloy known, a ternary Co55Ta10B35 MG. We show that this macroscopically brittle glass is flaw-insensitive at the micrometer scale. This discovery emerges when testing pre-cracked specimens with self-similar geometries, where the fracture stress does not decrease with increasing pre-crack size. The fracture toughness of this ultra-strong glassy alloy is further shown to increase with increasing sample size. Both these findings deviate from our classical understanding of fracture mechanics, and are attributed to a transition from toughness-controlled to strength-controlled fracture below a critical sample size.

This study investigated the efficiency of scale-propellers, typically used on small drones. A scale-propeller is accepted as having a diameter of 7 to 21 inches. Recent special operations has demonstrated the utility of relatively small, low-cost first-person view (FPV) drones, which are attritable. This investigation outlines the development of a MATLAB optimisation code, based on minimum induced loss propeller theory, which calculates the optimal chord and twist distribution for a chosen propeller operating in known flight conditions. The MATLAB code includes a minimum Reynolds number functionality, which provides the option to alter the chord distribution to ensure the entire propeller is operating above a set threshold value of Reynolds (>100,000), as this has been found to be a transition point between low and high section lift-to-drag ratios. Additional functions allow plotting of torque and thrust distributions along the blade. The results have been validated on experimental data taken from an APC ‘Thin Electric’ 10” × 7” propeller, where it was found that both the chord and twist distributions were accurately modelled. The MATLAB code resulted in a 16% increase in the maximum propulsive efficiency. Further work will investigate a direct interface to SolidWorks to aid rapid propeller manufacturing capability.

This article uses the concept ‘Bricoleurs’ to analyse the different categories of indigenous small- scale miners in Zimbabwe. Indigenous citizens constitute the bulk of the small and medium scale gold miners who continue to use antiquated methods of extraction and processing and they market their gold through illegal networks managed by middlemen. The study highlights the challenges Bricoleurs encounter in forcing inclusion into the mainstream mining economy, and the government’s failure to capture them into the formal gold market. The indigenous gold miners’ experiences reveal the trials posed by fragmented and incoherent legal and institutional policy frameworks that militate against the Bricoleur miners’ productivity. With gold deposits found all over the country, and in the absence of supporting organisational structures, the Bricoleurs’ self-empowerment through devious means has become accepted by mining authorities. Data for this article was collected mostly through interviews with different stakeholders in the gold mining industry in Harare, Shurugwi and Chakari in Zimbabwe.

Abstract This commentary reflects on the experiences of a cohort of human and physical geographers in enacting environmental collaborations during their doctoral studies. The authors identify three key structural barriers encountered whilst attempting a collaborative approach: (1) doctoral funding priorities, (2) doctoral resourcing and (3) assessing doctoral collaboration. The authors discuss how the negotiation of these encounters came to frame their understanding of collaborative approaches to environmental knowledge creation. Competitive application processes for doctoral studentships can encourage the overpromising of the impact of planned environmental collaboration, potentially co‐opting the voices of partners/communities to satisfy doctoral funding requirements. Given insufficient funding of collaborations, the authors argue that this overpromising of doctoral research's impact can later result in difficult trade‐offs between undertaking additional commitments at the expense of the career progression of the doctoral student, contributing to educational inequalities and scaling‐back the initial plans at the cost of collaborators encountering environmental crises. The trade‐off is further problematised by institutional assessment procedures that do not adequately recognise the more nuanced contributions of environmental collaborations and a prevailing culture promoting peer‐review publishing. Overall, the commentary argues that these barriers help to reproduce inequalities in the distribution of voice in environmental scholarship, undermining efforts to democratise environmental knowledge creation in doctoral research. The authors call for specific structural reforms of doctoral programmes to help address these challenges and support a broader resistance to the inadequate resourcing and evaluation of environmental collaborative research in UK higher education.

As protein-based therapeutics often exhibit a limited stability in liquid formulations, there is a growing interest in the development of solid protein formulations due to improved protein stability in the solid state. We used small-scale (

AbstractPoultry vaccination reduces birds’ mortality risk and its related economic impacts. The Veterinary Services Directorate of Ghana publishes a national poultry vaccination schedule for farmers to comply with. Yet disease outbreaks occur, raising the question of whether poultry farmers comply with the vaccination protocols. This paper assesses vaccination compliance and its determinants among small-scale farmers, using Birim Central Municipality as a case study. We employed descriptive statistics, Kendall’s coefficient of concordance and a Poisson count model to analyse cross-sectional data collected from 60 poultry farmers. We find that level of awareness about vaccination is higher than the level of compliance. The Poisson model reveals that access to veterinary services, poultry management training, large flock size, and having experienced poultry disease on the farm positively affect the extent of compliance with the schedule. On the other hand, male farmers are less likely to comply than female farmers. The most pressing constraints to poultry vaccination are inadequate access to finance, inadequate veterinarians and high cost of veterinary services. We recommend that poultry industry stakeholders take necessary measures to increase farmers’ contacts with veterinary officers and intensify peer education on vaccination.

Biorefinery systems that are embedded in their local setting provide an attractive framework for the valorisation of locally available food- and other bio-waste streams. They can aid in the provision of local bio-waste processing facilities as well as the targeted revalorisation of local bio-waste feedstocks by converting them in locally desired biorefinery products. Since food- and other bio-waste feedstocks are often diffuse feedstocks, small-scale biorefineries that are tailored for their local setting are the most suitable biorefining system for their processing. Whereas small-scale biorefineries cannot rely on the economy-of-scale to be an economic sustainable endeavour, they need to be meticulously optimised according to multiple sustainability objectives. These objectives can be of economic, societal, or environmental nature. A commonly used optimisation criterion in these problems is the energy requirements of the entire biorefinery system. For many commonly used biorefinery processes mass balance models are available (which are often mechanistic models), however, energy balances are difficult to obtain. Chemical process simulators, like Aspen Plus, provide an extensive toolkit to easily model the mass- and energy balances of a multitude of chemical processes. However, especially in the context of multi-objective optimisation, the obtained white-box models are too complex to simulate the considered processes efficiently consecutively. Therefore, in this contribution, a critical analysis is presented of the use of white-box versus the black-box models in the context of the multi-objective optimisation of a small-scale biorefinery. An in-house developed biorefinery network is re-modelled in Aspen Plus and used as a digital twin for the development of a surrogate model. Eventually, the modelled biorefinery network is optimised using both models and a comprehensive evaluation is drafted.

In healthcare, small‐scare data are stored with individual entities, such as hospitals, and they are not shared. However, data with one entity are not sufficient for training a machine learning model and therefore cannot be fully utilized. Given that a large amount of small‐scale data is widely distributed between hospitals/individuals, it is necessary to deploy an easy, scalable, and secure distributed computational framework. We aim to aggregate these scattered and small‐scale data to train neural networks and achieve classification and detection on coronavirus disease 2019 (COVID‐19) datasets. We propose a distributed autoencoder (AE) classifier network for this purpose. It contains a central classifier and multiple distributed AEs. The AEs are used as generators. A local generator uses an actual COVID‐19 computed tomography image as the input and outputs a synthetic image. The well‐trained generator provides an image to train the central classifier model. The central classifier network model learns information from all the generated COVID‐19 data using the distributed AE. Experiments are performed using some COVID‐19 datasets. The distributed AE classifier network outperforms all the models that use a single subset, and its performance is similar to that of a regular classifier. The proposed network solves the problem of using small‐scale and scattered COVID‐19 data to train neural networks while ensuring data privacy. The accuracy of the network is the same as that achieved using the entire data. [ABSTRACT FROM AUTHOR]

This study evaluated comparative profitability and technical efficiency of small-scale rice farmers with and without access to improved production technology in North Central Nigeria. A multistage sampling technique was adopted for this study. The data were collected through a wellstructured questionnaire of 1500 small-scale rice farmers with access to technology and 1500 smallscale rice farmers without access to technology making a total of 3000 rice farmers in the study area. The results showed that the average age of the sampled rice farmers with access to technology was 36 years, while those without - 46 years. The results showed that the rice production was profitable for both farmers with and without access to technology. The statistically significant factors influencing the rice production for small-scale farmers with access to technology were the land size (p<0.01), labour (p<0.01), fertilizer (p<0.01) and agrochemical (p<0.01), while the statistically significant factors influencing the rice production for small-scale farmers without access to technology were land size (p<0.01), labour (p<0.01) and agrochemical (p<0.10). The major challenges faced by the small-scale rice farmers with access to technology were the poor credit facilities, shortage of farm input, inadequate rainfall season, high cost of labour and instability in the planting calendar. The F-Chow test showed that there was significant impact on the technical efficiency, productivity and profitability of rice farmers with access to improved technology. Therefore, the study recommends that inputs such as improved seed varieties, fertilizers and chemical inputs should be provided to farmers. [ABSTRACT FROM AUTHOR]

Although reconfigurable intelligent surfaces (RISs) have attracted broad attention, they usually require a large scale of elements and hundreds of tunable components, particularly for beam‐steering applications. Herein, a methodology is proposed for the compact design of a transmission‐type RIS system for beam steering. The approach leverages a customized horn feed equipped with a gradient refractive index metalens to tailor the electromagnetic fields over the horn aperture, resulting in focused amplitude and uniform phase distributions. This enables us to reduce the feed‐RIS distance and significantly decrease the RIS scale using only a small number of components while still achieving acceptable beam‐steering performance. The investigations are carried out through theoretical studies, simulations, and experiments. A prototype system is fabricated as an exemplary demonstration, which occupies a volume of 3.3λ0 × 2.6λ0 × 3.5λ0, including the feed, and contains only 3 × 5 RIS elements and 60 varactors. With every single element being controlled individually by a simple network, beam‐scanning ranges of ±30° are measured on the E‐, H‐, and 45°‐planes, respectively. With the above intriguing properties, the proposal can find potential applications where miniaturization, high portability, and low cost are required for beam‐steering functions. [ABSTRACT FROM AUTHOR]