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Abstract: Once again Swedish forest industries are supposed to face a new threatening shortage of wood. Therefore, demonstration of new ideas of producing wood for pulp and fuels (heat, ethanol, hydrogen gas, dimethylether, electricity) in the most southern part of Sweden was very welcome. One example of new ideas is that some farmers planted hybrid poplars on abandoned farming land at Sångletorp (33ha), Johannesholm (15ha), Kadesjö (11ha) and Näsbyholm (2ha) in the southernmost part of Sweden in 1991. Some of these plantations were harvested in 2004, but some are still growing. The harvested wood had been used for pulp and fuel. The results of the harvest and of the plantations that are still growing are analysed here from an economic, ecologic and energy point of view. [Copyright &y& Elsevier]

Lipophilic wood extractives commonly referred to as pitch, cause significant problems for the pulp and paper industries. The reduction of these extractives is an important aspect that concerns industries around the world. In the present work the change in the amount and chemical composition of lipophilic extractives from Eucalyptus spp. stored for 20, 40, 60, 100, 140 and 180 days after harvesting was investigated. The results showed a decrease in extractives content with storage time, with the most significant decrease occurring 60 days after harvesting. In addition, fatty acids and sterols were the main classes of compounds responsible for the significant decrease in extractive content. Data were analyzed by principal component analysis. PC1 explains approximately 99% of the total variance, and β-sitosterol was the major compound responsible for the differentiation. These studies demonstrate that in terms of economical aspects, quality of the pulp and paper and minimization of pitch formation, the best period of wood storage is 60 days. [Copyright &y& Elsevier]

Highlights: [•] Evaluation of new HWP accounting method leads to significant GHG emission reduction for Canada. [•] Use of harvested wood for energy and of construction lead to largest GHG savings. [•] A cascade-use for wood and paper products is paramount for further GHG improvement. [•] The end-of-life effect of using recycled waste wood for energy is delayed due to longer carbon uptake. [•] Cradle-to-cradle utilization of wood waste has an underdeveloped reduction potential. [Copyright &y& Elsevier]

• Saffron stigmas crop generates a large amount of biomass called by-product with high added value. • Saffron floral by-products (tepals, leaves, stamens, styles, spaths, and others) are rich in flavonoids, anthocyanins, carotenoids, and volatile compounds. • Chemical compounds contained in the saffron floral by-products have excellent antioxidant and anti-microbiological activities. • Bioactive compounds of saffron floral by-products are a great coloring and aromatic agents strongly used in industrial formulations. Saffron (Crocus Sativus L.), is the most expensive spice in the world, derived from the red filaments (stigmas) of a sterile triploid geophyte plant that belongs to the Iridaceae family. Saffron stigmas have been traditionally used in food and cosmetic products due to their coloring, flavoring, and aromatic aspects, attributed to their bioactive compounds, namely crocin, picrocrocin, and safranal. After harvesting saffron stigmas, a considerable amount of saffron floral parts so-called by-products are generated: petals, leaves, stamens, and others. Recent scientific studies have focused on cosmetic, therapeutic, and nutraceutical applications of not only saffron stigmas but also their several floral by-products. The chemical compounds contained in the whole saffron flower such as polyphenols, flavonoids, and anthocyanins, are endowed with excellent potentialities like antioxidant, and antimicrobial activities which makes them strongly used in food and cosmetic products. This paper aims to provide a systematic overview of specialized (secondary) metabolites applications of saffron stigmas as well as its by-products in various fields, also, the mechanisms of action of saffron bioactive compounds activities have been explained in this paper. [ABSTRACT FROM AUTHOR]

Metastructures based on kirigami (the Japanese art of paper folding and cutting) have great potential for applications in stretchable electronics, bioprobes, and controllable optical and thermal devices. However, a theoretical framework for understanding the physics of their buckling behavior and to facilitate the search for ultrahigh stretchability has yet to be developed. Here, we present such a framework based on an energy approach. Closed-form analytical solutions and scaling laws are obtained for some key mechanical quantities, including flexibility, normalized flexibility, critical buckling strain, maximum tensile strain, elastic stretchability, normalized stretchability, and out-of-plane stiffness. Both experiments and numerical calculations are performed to validate the accuracy and scalability of the theoretical model. Systematic analyses of key mechanical quantities reveal how it is possible to bridge the gap between kirigami design by experience and by mechanically guided design, as well as how various dimensionless geometric parameters can be used to regulate buckling responses. Illustrative applications show that the ability to predict and tune the mechanical programmability of the proposed theoretical framework enables stable electromechanical conversion and programmable electromechanical kirigami with domino-like buckling. This work provides a foundation for further research and can also aid in the design of kirigami for use in programmable metastructures and metamaterials and energy harvesting. [ABSTRACT FROM AUTHOR]

• A piezoelectric energy harvesting system model based on parametric excitation and low frequency is proposed. • Geometric and damping complex nonlinear factors are considered. • An accurate theoretical model of piezoelectric energy harvesting system excited by parametric excitation is established. • Load resistance effect on the parametric excited initial threshold is explored. • Integrated parametric excitation and effect of tip mass induce significant improvement to the performance. Capitalizing on the advantages of parametric excitation and real-life low frequency vibration, the steady-state response of piezoelectric energy harvesting system composing of a cantilever beam with a tip mass and horizontal excitation at the fixed end is investigated. By applying Hamilton's principle, the nonlinear partial differential equation of a cantilever bimorph piezoelectric energy harvesting system with an additional tip mass is derived and analyzed. The cantilever is modeled as an axially non-elongated Euler Bernoulli beam with geometric and damping nonlinearities. By using the Galerkin method, the nonlinear partial differential equation is reduced to an electromechanical coupling system that governs a cantilever piezoelectric energy harvesting system with a tip mass under parametric excitation. The first-order resonance response of this harvesting system is studied by using the method of multiple scales. The analytical response expressions and first-order amplitude functions for vertical displacement, output voltage and output power are derived and analyzed. The influence of different impedance and tip mass on the piezoelectric energy harvesting system performance is summarized and concluded. For the parametric excitation system, the load resistance shows significant influence on the initial threshold of the piezoelectric energy harvesters under parametric excitation. For a short circuit, the initial threshold increases with increasing load resistance. For an open circuit, the initial threshold decreases with increasing load resistance. For an open circuit resistance or a short circuit resistance under parametric excitation, an increase in the end block mass effectively reduces the resonance frequency of the piezoelectric energy harvesters. Consequently, the energy harvesting bandwidth is increased, and the harvesting effect of the piezoelectric energy harvesters is enhanced. In this paper, a more accurate and practical theoretical model is established to predict the electromechanical coupling behavior of cantilever piezoelectric energy harvester under parametric excitation. Using this approach, it is possible to complement parametric and direct excitation such that the advantages of parametric excitation can be achieved. It is also significant to improve the energy conversion efficiency of energy harvesting system. [Display omitted] [ABSTRACT FROM AUTHOR]

Internet of Things and growing popularity of connected devices are increasing the demand for wearables applications, which is driving the development of ultra-low power secure systems. Thus, having a system running at low voltage with low power consumption introduces the use of ambient energy harvesting. Besides, batteries have several limitations reducing their compatibility with wearables, including periodical need for recharge, limited life-time, heavy and large form factor and non-eco-friendly life-cycle. Therefore ambient energy harvesting technology gives a promising alternative for self-powered wearables. The integration of these solutions on the same silicon support is a real technological challenge. This paper proposes a multi-harvesting fully-integrated system architecture combining AC and DC sources. Based on a MATLAB/Simulink model, the proposed system allows the calibration of an optimal solution. It is designed and simulated in 40 nm CMOS process, demonstrating the use of an AC source as secondary input to start a harvesting system with very low DC source as main source. • Ambient energy harvesting technology gives a promising alternative for self-powered wearables. • Multi-harvesting fully-integrated system architecture combining AC and DC sources. • Energy harvesting system level modeling using MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

As climate change and population growth intensify, the agricultural sector's need for sustainable solutions is paramount. This paper presents an overview of smart agriculture, a strategy leveraging technology and data analytics, and its potential to advance sustainability socially, economically, and environmentally. Drawing on recent research, we examine the integration of smart technologies in agriculture, their impact on sustainability, and the architectural design and key factors influencing their adoption. We critically review the literature on the effectiveness of smart agriculture, illuminating how smart farming strategies can curb environmental harm, stimulate economic growth, and promote social inclusivity. We identify existing research gaps and propose directions for future investigation, emphasising the need for rigorous studies on implementation strategies and long-term impacts of smart agriculture on rural landscapes. Our comprehensive overview aims to engage and guide diverse stakeholders, enhancing understanding of sustainable agriculture practices and encouraging more sustainable farming implementations. This paper contributes to global efforts towards harvesting a sustainable future. • Climate change and population growth drive the need for sustainable solutions in agriculture. • Smart tech in agriculture lessens environmental impact and boosts economic and social inclusivity. • Existing literature reveals the effectiveness of smart agriculture in achieving sustainability goals. • Guides stakeholders towards more sustainable farming practices and contributes to global sustainability efforts. [ABSTRACT FROM AUTHOR]

• Modelling the predator-prey ecosystem using a 'generalized' impulsive response function for the first time. • Dynamical behaviors such as sufficient conditions for the stability of prey-eradication and the permanence have been given. • The generalized solutions under asymptotically stable conditions are validated through various specific response functions. • The correctness of the derived theoretical results are further validated using numerical simulations. • Unlike previous research this paper also models the non-simultaneous occurrence of predator stocking and prey harvesting. Traditional approach for modelling the evolution of populations in the predator-prey ecosystem has commonly been undertaken using specific impulsive response function, and this kind of modelling is applicable only for a specific ecosystem under certain environmental situations only. This paper attempts to fill the gap by modelling the predator-prey ecosystem using a 'generalized' impulsive response function for the first time. Different from previous research, the present work develops the modelling for an integrated pest management (IPM) especially when the stocking of predator (natural enemy) and the harvesting of prey (pest) occur impulsively and at different instances of time. The paper firstly establishes the sufficient conditions for the local and the global stabilities of prey eradication periodic solution by applying the Floquet theorem of the Impulsive different equation and small amplitude perturbation under a 'generalized' impulsive response function. Subsequently the sufficient condition for the permanence of the system is given through the comparison techniques. The corollaries of the theorems that are established by using the 'general impulsive response function' under the locally asymptotically stable condition are found to be in excellent agreement with those reported previously. Theoretical results that are obtained in this work is then validated by using a typical impulsive response function (Holling type-II) as an example, and the outcome is shown to be consistent with the previously reported results. Finally, the implication of the developed theories for practical pest management is illustrated through numerical simulation. It is shown that the elimination of either the preys or the pest can be effectively deployed by making use of the theoretical model established in this work. The developed model is capable to predict the population evolutions of the predator-prey ecosystem to accommodate requirements such as: the combinations of the biological control, chemical control, any functional response function, the moderate impulsive period, the harvest rate for the prey and predator parameter and the incremental stocking of the predator parameter. [ABSTRACT FROM AUTHOR]

The paper deals with the harvesting model introduced by one of the authors in a joint paper with A. Bressan and W. Shen. A cost term which plays an essential role in the existence proof is removed here leading to some new phenomena. Since a solution not always exists in this case, we propose a relaxed version of the problem which is always solvable, has a geometrical interpretation in the functions space and whose unique solution, under suitable conditions, solves also the original problem. Finally, the notion of strategy limit of a sequence of smooth measures is introduced as a long-term control to fish populations. [ABSTRACT FROM AUTHOR]

Sunlight is a great substitute for indoor artificial lighting during the daytime but still isn't so viable because of the cost of fiber-based daylighting system and its efficiency. In this paper, we report the design and development of a cost-effective non-mechanical tracking-based solar concentration system using a combination of a large Fresnel lens, segmented mirrors, and segmented compound parabolic concentrator (SCPC) for indoor daylighting application. This system presents the three-stage collection of sunlight by means of extending the collection aperture vertically while keeping the horizontal area same. First one is the concentrated light from the Fresnel lens, the second one is the direct sunlight incident onto the CPC and the third one is the direct sunlight reflected from the segmented mirrors onto the CPC. Hence the light transported through this system is adequate for illumination purposes inside the room. The manufacturing of ideal CPCs through the moulding process is both expensive and complex, and it necessitates extreme precision. Therefore, a cost-effective and efficient segmented CPC is designed and developed using a highly reflecting mirror-polished aluminum sheet which works well compared to the ideal CPC. To transport concentrated sunlight inside the room a highly reflecting horizontal light pipe is designed and developed. The collimated light at the output is challenging therefore, we have coupled inverted CPC at the exit of segmented CPC in the system. Further, to guide sunlight deep into the rooms we have coupled the entire system with a rectangular light pipe. An efficient diffuser is coupled at the end of the rectangular light pipe to illuminate the room uniformly. Various optical parameters such as illuminance, color rendering index (CRI), and correlated color temperature (CCT) values are analyzed from the result obtained which shows that the system can efficiently transport sunlight deep inside the room throughout the day. Therefore, the proposed system is very much helpful for the sustainable development of a country. [ABSTRACT FROM AUTHOR]

This paper proposes a novel piezoelectric energy harvester attached with a trailing-edge flap under various installation angles, for enhancing the aeroelastic vibration and improving the harvesting performance. The mathematical models of the fluid-structure-electric coupled fields are derived, the simulation models of the multi-physical coupled fields of the harvester system with various installation angle flaps are established, and the experimental prototypes of the harvester are fabricated. The influences of the flap installation angles on the flow field and output characteristics are investigated theoretically, numerically, and experimentally. The results demonstrate that the flap stiffness and damping coefficients exert less influence on vibration characteristics and harvesting performance. The flap at a certain installation angle alters the flow field, affects the flow pattern, restricts the vortex shedding, and offsets the aerodynamic force and moment. A decrease in the flap installation angles results in increasing the vibration response and output performance. The obtained numerical results are in good agreement with the experimental and theoretical values, which verifies the effectiveness of the simulation model. The maximum plunge amplitude is 0.029 m and the output voltage is 15.51 V at 17.74 m/s and an installation angle of 0o. The enhancement ratio of the output voltage at 0o is up to 148.6% over 45o, which achieves better harvesting performance. The designed harvester system powers indirectly the pedometer for 104 s at 13.58 m/s. This research offers an essential foundation for achieving better tradeoffs in energy harvesting and vibration suppressing by appropriately selecting the flap installation angle. [Display omitted] • This paper first proposes a novel energy harvester with various installation angle flaps. • Flap alters the flow field, restricts vortex shedding, and increases output characteristics. • The maximum harvested plunge amplitude is 0.029 m and the output voltage is 15.51 V. • The enhancement ratio of the output voltage at 0o is up to 148.6% over 45o. • The harvester drives indirectly the pedometer for 104 s at 13.58 m/s. [ABSTRACT FROM AUTHOR]

• Characterization of the planting and harvesting planning problem and its modelling for medicinal plants. • Conceptual framework to characterize the crop planting and harvesting planning problem. • Model to plan planting and harvest of crops with variable molecules concentration and minimum time between harvests. • Model validation through the application to a natural food supplement supply chain case study. • Economic unfairness among farmers eliminated while respecting supply chain costs and concentration of plant molecules. The planting and harvesting of medicinal plants have characteristics that differentiate them from other crop types and complicate their planning. For example, drug processors do not require large quantities of product to be harvested but have a high concentration of active molecules. There is no evidence for any optimization tool to support the planting and harvesting of such plants. Given this sector's importance and its impact on populations' health, it is necessary to develop solutions to increase the sustainability of their supply chains. This paper aims to bridge this gap by proposing a conceptual framework to characterize a crop planting and harvesting planning problem, and a multi-objective optimization model for the planning of planting, harvesting, post-harvesting, distribution and storage of medicinal plants with variable concentrations of molecules and minimum time between harvests. The model optimizes three objectives aligned with sustainability: supply chain costs, concentration of molecules in plants, farmers' perceived economic unfairness. It is validated by its application to a case study of medicinal plants in the Basilicata region (Italy). The ε-constraint method is used to obtain 11 non dominated solutions showing the possibility of eliminating farmers' perception of economic unfairness by maintaining similar values for supply chain costs and concentrations of active molecules when planning the production of medicinal plants. Finally, the TOPSIS method is applied to select the best plan to be implemented into the supply chain. [ABSTRACT FROM AUTHOR]

In this paper, a fractional-order Hantavirus infection model incorporating harvesting is formulated and investigated. The populations are divided into susceptible mice, infected mice and alien species. Mathematical analysis and numerical simulations are performed to clarify the characteristics of the proposed fractional-order Hantavirus infection model. The existence, uniqueness, non-negativity and boundedness of the solutions are examined. The local stability of the equilibrium points of the fractional-order model is studied. The mathematical proof of the existence of transcritical bifurcation is given by using Sotomayor's theorem. The theoretical findings are illustrated by numerical simulations. The impact of fractional-order, competitive effect of alien species on mice, competitive effect of mice on alien species, carrying capacity and harvesting efforts on the stability of the Hantavirus infection model are studied. The basin of attraction regions is also illustrated. [ABSTRACT FROM AUTHOR]

Apart from electricity, high-temperature proton exchange membrane fuel cell also produces a lot of waste heat, leading to energy wasting. Harvesting the waste heat for additional cooling production may further improve the commercial competitiveness. In this paper, we propose a novel combined system model that integrates high-temperature proton exchange fuel cell with heat-driven elastocaloric cooling system. Considering different sources of irreversible effects, mathematical formulas of performance indicators for each subsystem and combined system are specified. In addition, energetic and exergetic analyses are conducted to assess the potentiality of elastocaloric cooling system as a waste heat recovery candidate. The maximum power output density of the combined system can be boosted by 9.18% in comparison with that of a single fuel cell. The basic performance features and optimum criteria of the proposed system performance are expounded. Extensive sensitivity analyses and calculation examples have been conducted to check the dependance of the proposed combined system performance on some important design variables and operation conditions. [ABSTRACT FROM AUTHOR]

• A broadband rectified metasurface is proposed for radar frequency band EM energy harvesting and wireless power transfer. • The absorber cell designed in this paper can achieve EM waves capture and high-efficiency energy harvesting in a wide band. • A rectification circuit is designed to complete the AC-to-DC conversion and the DC energy harvesting. • This design can achieve excellent RF-to-AC efficiency over a wide range of incidence angles with large HPBW. Traditional power transmission networks with complex physical wiring have struggled to meet the power needs of emerging portable and decentralized devices. Recently, rectified metasurfaces for electromagnetic (EM) energy harvesting have attracted great attention from researchers due to their customizability and application flexibility. However, many previous structures mainly focused on harvesting efficiency and ignored harvesting bandwidth. Here, we propose a broadband rectified metasurface structure for radar frequency band EM energy harvesting and wireless power transfer. The cell structure consists of a centrosymmetric hyperbolic ring (CHR) structure that can exhibit an EM wave absorptivity of greater than 80 % at wide incidence angles. The AC energy of each cell is exported through metal vias, and the energy is pooled through the feed networks. Finally, the rectification circuit is designed to complete the AC-to-DC conversion and the DC energy harvesting. Broadband EM energy harvester can be achieved when the incidence angle is 0° to 60°. The half-power bandwidth (HPBW) can be up to 55 % with a normal incidence. To verify the rectified metasurface function, a prototype with 6 × 6 metasurface array is fabricated and tested. When the rectified metasurface operates at 6.1 GHz, RF-to-DC energy harvesting efficiency of greater than 35 % can be achieved in the incidence angle range of 0° to 60° and maximum efficiency is 57 %. It makes it possible to self-power sensor network nodes working in the vicinity of communication base stations or radar base stations. [ABSTRACT FROM AUTHOR]

This abstract provides an update on development and implementation progress of the Pure community module in the 5 years since the initial launch of the service. The paper revisits the conclusions of our 2018 presentation [1] , providing updates on the 'future developments' and encourages a discussion of the complexities in supporting multi-institutional collaborations. In addition, we will provide an overview of some key challenge areas we have been working on together with community customers and community owners (technical and operational). [ABSTRACT FROM AUTHOR]

Abstract The harvesting and transportation system involves a harvest scheduling and a transportation plan. The grain, harvested by combine-harvesters, is then transported by transporters from disperse farmlands to the depot. The spot where combine-harvesters transfer wheat to transporters is dynamic because the location of these spots correspond with combine-harvesters' work. In this paper, the harvesting and transportation problem is considered as a two-echelon multi-trip vehicle routing problem with a dynamic satellite (2E-MTVRPDS) because the combine-harvester is used multiple times in the planning horizon and the transporter is used multiple times in a work day. The mixed integer linear programming model is proposed based on the features of the problem. This work presents an optimum solution with a heuristic algorithm. The dynamic satellite is transferred as the static case in the heuristic. The computational experiments are constructed to test the performances of the proposed algorithm. Five instances with different sizes are adopted to test the stability of the algorithm. The calculation deviation of testing instances is acceptable. On one hand, the optimal effectiveness can be achieved when the number of instances is less than 200. With the increase in the number of instances, the optimal efficiency declines. On the other hand, the optimal solution appears to have a time window of 0.2 h in all instances with different sizes. This study provides a decision model for agricultural production to implement optimal harvesting operations. Highlights • This paper contributes a new variant of two-echelon vehicle routing problem. • The crops harvesting and transportation problem is abstracted as 2E-MTVRPDS. • We proposed a memetic algorithm to solve 2E-MTVRPDS. • Results provide new thinking for integration of harvesting and transportation. [ABSTRACT FROM AUTHOR]

• This study proposed detection and localization methods based on deep learning and active sensing for harvesting robots in real-world environments with occlusion and varying lighting conditions. • To solve the picking problem caused by the peduncle's random tilting, this study proposed a method to calculate the peduncle's inclination angle for controlling the end-effector to make the corresponding rotation. • Experimental results indicated the error between the estimated occlusion ratio and the genuine value is 16% in average, and the active sensing method improved the confidence score in occluded situations by over 50%. And the overall successful picking rate of 300 trials is 90%. • The proposed active methods have a 33% increase in precision and a 43% increase in efficiency compared to constant methods. The predominance of branch and leaf shade in agricultural environments presents a barrier for accurate target recognition. Particularly for picking robots, precise localization of the picking object is essential. For this purpose, this paper proposes detection and localization methods based on deep learning and active sensing for harvesting robots in real-world environments with occlusion and varying lighting conditions. Using a deep learning network, the detection method firstly extracts the peduncle and fruit regions; the fruit region is then used to calculate the occlusion rate and the offset distance of the peduncle relative to the fruit. With such information, the robot arm adjusts the camera's field of view to perform multiple recognitions until the confidence is satisfied. Furthermore, to solve the picking problem caused by the peduncle's random tilting, this paper proposes a method to calculate the peduncle's tilt angle for controlling the end-effector to make the corresponding angle rotation. The robot arm and its end-effector are directed to complete the harvesting with the picking point location and tilt angle. In this study, data collection, detection and picking tests were implemented in the field, the results indicated that the method obtained an average successful picking rate of 90% after 300 trials, the error between the estimated occlusion ratio and the genuine value is 16% in average, and the active sensing method has improved the confidence score in occluded situations by over 50%. The proposed active methods have a 33% increase in precision and a 43% increase in efficiency compared to constant methods. [ABSTRACT FROM AUTHOR]

• 3-degrees of freedom (dof) linear multi-arm robotic fruit harvester models were used to harvest the fruits on high density pear and peach trees. • Pick cycle times of multi-arm robotic fruit harvesters (PCTM's) were low when the arms were arranged in height split configuration compared to length split, height split matrix, and length split matrix configurations. • Harvesting the tree sides separately resulted in lower PCTM's than harvesting both sides of the trees at once with a harvester having the same number of arms while traversing in an orchard row. • Lower pick cycle times (PCT's) that could compete with human PCT's can be achieved using linear multi-arm harvesters. In some cases, it has been shown that fruits on trees with SNAP (Simple, Narrow, Accessible, and Productive) architectures are reachable by robot arms using three linear degrees of freedom; hence, high fruit-picking efficiencies can be achieved with simpler arms. This paper uses digitized fruit position data to compute the fruit pick cycle times (PCT) of robotic fruit harvesters with multiple arms arranged in grid configurations, i.e., operating in disjoint rectangular work cells independently of each other. The effects of the robot joints' maximum linear acceleration and maximum linear velocity on PCTs were studied. As V max increased, the PCT followed a negative exponent power law (diminishing return) for any given A max. Similarly, for a constant V max , the improvement of PCT as A max increased slowed down at higher acceleration values. Also, the PCTs were computed when each arm work cell was designed based on equal fruit load or equal size criteria, using four workspace partitioning schemes (height split, length split, height split matrix, and length split matrix). Equal fruit-load configurations resulted in load balancing and exhibited lower PCTs; the height-split configuration was the best among the four different partitioning schemes, possibly because it compensated better for the fruit distribution's non-uniformity along the trees' height. Finally, the PCTs were computed while harvesting one side of an orchard row or both sides concurrently. Harvesting sides separately resulted in lower PCTs (greater speed) due to non-uniform fruit distributions on the different sides of trees. The insights gained in this paper can inform the design of harvesting robots utilizing arrays of 3-dof linear arms. [ABSTRACT FROM AUTHOR]

Robot harvesting has emerged as an urgent need for apple industry due to a sharp decline in agricultural labor. In the field of harvesting robots, the use of multiple robotic arms to improve operational efficiency and promote industrial applications has gained significant attention. Despite the significant progress made in multi-arm harvesting robots in recent years, their widespread application in orchard production is hindered by insufficient efficiency of operation and the accuracy of fruit positioning. This paper focuses on the precise perception and multi-arm collaborative control issues of harvesting robots, and proposes a multi-arm apple harvesting robot system. Firstly, the paper introduces the hardware and software integration method and kinematic configuration of the robot, and presents its workspace division and asynchronous sequential operation mode. Secondly, the paper proposes a stereo vision fruit recognition and localization algorithm based on multi-task deep learning to enhance the accuracy of apple fruit positioning and a method of combining multiple perspectives to acquire a global fruit map is introduced. Finally, the paper presents a multi-arm task planning method based on the Markov game framework to optimize the target harvesting order of each arm and improve the collaboration efficiency. The effectiveness of the robot and its perception and control methods are verified through multiple field experiments in orchards. The field trials showed that the proposed vision system reduces the median locating error of the robot system by up to 44.43%; the proposed task planning algorithm can reduce the average cycle time by 33.3% compared to the heuristic-based algorithm, and time taken for optimizing task planning ranged from 1.14 s to 1.21 s; and the robot's harvest success rate varied from 71.28% to 80.45%, and the average cycle time ranged from 5.8 s to 6.7 s. • A visual recognition and localization algorithm by multiple stereo cameras. • A point-cloud-processing pipeline by a frustum-based method. • A task planning scheme based on multi-agent reinforcement learning framework. • A highly integrated four-arm apple harvesting robotic system. [ABSTRACT FROM AUTHOR]

Chitosan lactate (CSS) has been widely used for academic and industrial applications due to its biocompatibility, biodegradability, and high biological activity. Unlike chitosan, which is generally soluble only in acid solution, CSS can be directly used by dissolving in water. In this study, CSS was prepared from moulted shrimp chitosan at room temperature by a solid-state method. Chitosan was first swollen in a mixture of ethanol and water, making it more susceptible to reacting with lactic acid in the next step. As a result, the prepared CSS had a high solubility (over 99 %) and zeta potential (+ 99.3 mV) and was comparable to the commercial product. The preparation method of CSS is facile and efficient for a large-scale process. In addition, the prepared product exhibited a potential flocculant for harvesting Nannochloropsis sp., a marine microalga widely used as a popular food for larvae. In the best condition, the CSS solution (250 ppm) at pH 10 showed the highest recovery capacity (∼ 90 % after 120 min) for harvesting Nannochloropsis sp. Besides, the harvested microalgal biomass showed excellent regeneration after 6 culture days. This paper's findings suggest a circular economy in aquaculture by producing value-added products from solid wastes, which can minimize the environmental impact and move towards sustainable zero-waste. [Display omitted] • Chitosan lactate was prepared from moulted shrimp chitosan in a solid state. • The chitosan salt had a high purity and high solubility. • The product is exhibited as a potential flocculant for harvesting microalgae. • This paper's findings suggest a circular economy in aquaculture. [ABSTRACT FROM AUTHOR]

• A novel piezoelectric energy harvester with double hinged beam is presented. • The output characteristics are investigated by simulation and experiments. • The first-order resonant frequency of the harvester is as low as 12.65 Hz. • Multimodal energy harvesting is achieved at the first and third order resonance. • The excellent harvesting performance in the low-frequency environment is verified. This paper proposes a novel piezoelectric energy harvester with rotating-DOF to efficiently achieve multimodal vibration energy harvesting in low-frequency environments. The designing of the harvester based on the beam whose ends were connected to rotating shafts was accomplished firstly, and then the dynamic properties of the structure were numerically calculated by finite element analysis. Finally, experimental prototypes and test systems were designed to verify the correctness of the theory. This paper analyzed how that different key structural parameters and acceleration affect its output characteristics. Especially, the effect of double-rotating shafts on the energy harvesting performance was analyzed innovatively. The results acquired by experiments were in accord with those of simulation. Its first-order resonant frequency is down to 12.65 Hz, at which excellent output characteristics were obtained. The harvesting performance at the third-order resonant frequency was also remarkable, indicating the application prospect in the multimodal vibration circumstances. Moreover, the harvesting performance can be enhanced by the adjustable counterweight and proof mass, which improve environmental adaptability. Its maximum output is 35.73 V (12.65 Hz) and 24.69 V (43.64 Hz), and the output power is 2.13 mW and 1.02 mW under an acceleration of 1.96 m/s2. This paper provides a novel idea for low-frequency multimodal energy harvesting techniques. [ABSTRACT FROM AUTHOR]

In this paper, a Holling–Tanner predator–prey model with constant-yield prey harvesting and anti-predator behavior is investigated. It is shown that the codimension of a nilpotent cusp is 3 and a degenerate Bogdanov–Takens bifurcation of codimension 3 acts as an organizing center for rich dynamical behaviors including saddle–node bifurcation, Hopf bifurcation, saddle–node bifurcation of limit cycles, and homoclinic bifurcation. Moreover, a Hopf bifurcation of codimension 2 is found, a codimension-2 cusp of limit cycles is firstly observed, and the corresponding normal form coefficients are also obtained, which indicate that there exists an acute angle region of three coexistent limit cycles. In particular, a reversed S-shaped saddle–node bifurcation curve of limit cycles is found. In addition, we observe that the anti-predator behavior may cause nearly extinction of the predator population while the prey population reaches its maximum which is less than the carrying capacity due to the effect of harvesting; however, the constant-yield prey harvesting may drive both species to extinction suddenly. Finally, numerical simulations including bifurcation diagrams and phase portraits are given to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

• Dynamic modeling of hybrid robots has been presented for agricultural purposes. • An innovative method has been used to divide the system into several open chains. • Dynamic couplings between all sub-structures have been considered. • All the steps for systematic derivation are presented in computational algorithms. • A relatively complicated hybrid robotic system with 15 D.O.F has been simulated. Harvesting of agricultural crops, especially when the ripe products have to be picked one by one, has always been a major concern of farmers and growers. Consequently, the use of robots and the mechanization of harvesting operations have been considered as the effective means of tackling such challenges. In the present research, the use of hybrid robots (which combine open-loop and closed-loop manipulators) has been proposed for this purpose; because these robots help reduce the size of the workforce and thus slash the harvesting costs, and they also boost the speed and accuracy of harvesting operations. However, using this type of robots without paying attention to some important factors (e.g., using motors of optimal power at the actuated joints of a robot and choosing appropriate lengths for robot links) can have a substantial adverse effect on the manufacturing cost, working space and the effective functioning of such robots. So the main focus of this paper is on the kinematic and dynamic analysis of hybrid robotic systems. The main advantage of this research over similar works is the generality by which it describes the mechanical behavior of these robots; so that by using the recursive algorithms presented in this paper, all kinds of robots in the hybrid class can be analyzed. However, due to the complexity in the analysis of such systems, a hybrid robot consisting of three closed loops and one open loop was considered in this paper as a sample case study, so that we could explain, visually and graphically, all the steps involved in deriving its motion equations. The simulation results for this robotic system demonstrate the efficacy of the proposed method in the kinematic and dynamic analysis of hybrid robots, as efficient and functional crop harvesting equipment. [ABSTRACT FROM AUTHOR]

In order to improve the separation and conveying effect of the potato excavator, this paper combines the intelligent simulation method to improve the design of the separation and conveying machinery and equipment of the potato excavator in the heavy soil, and selects the grid-type excavation shovel. The digging shovel can ensure the least amount of soil entering into the subsequent separation device without digging potatoes to the greatest extent, and reduce the load of the subsequent separation device. Moreover, the structural parameters of the shaking separation conveying system are designed in this paper, and the hydraulic transmission method is adopted, so that there is a flexible connection between the implement and the walking tractor, so that there is relative movement between the two. Through the inspection of the potato excavator separation and conveying mechanical equipment designed in this paper, it can be seen that the potato excavator separation and conveying mechanical equipment designed in this paper can play a certain role in the potato harvesting in heavy soil. • Equipment of the potato excavator in the heavy soil. • The structural parameters of the shaking separation. • Flexible connection between the implement and the walking tractor. • The potato excavator separation and conveying mechanical. [ABSTRACT FROM AUTHOR]

As well known that the sudden environmental shocks and toxicant can affect the population dynamics of fish species, a mechanistic understanding of how sudden environmental change and toxicant influence the optimal harvesting policy requires development. This paper presents the optimal harvesting of a stochastic two-species competitive model with Lévy noise in a polluted environment, where the Lévy noise is used to describe the sudden climate change. Due to the discontinuity of the Lévy noise, the classical optimal harvesting methods based on the explicit solution of the corresponding Fokker–Planck equation are invalid. The object of this paper is to fill up this gap and establish the optimal harvesting policy. By using of aggregation and ergodic methods, the approximation of the optimal harvesting effort and maximum expectation of sustainable yields are obtained. Numerical simulations are carried out to support these theoretical results. Our analysis shows that the Lévy noise and the mean stress measure of toxicant in organism may affect the optimal harvesting policy significantly. [ABSTRACT FROM AUTHOR]

This paper deals with a vegetable production-planning problem in which a farmer has to simultaneously determine the crop rotations and harvest schedules for a number of vegetables in his farmlands. The crop rotation decisions include the determination of crop sequence, cropping times, and cropping size in each farmland. The harvest decisions include the collection times and harvesting size for each planted crop. By taking into account the growing season and technical-ecological constraints, this paper formulates a mixed integer linear programming model to develop vegetable production decisions for organic farmers. Due to the complexity of the model, we proposed a two-phase heuristic approach to solve the model. We applied the proposed model to analyze an organic farm in Taiwan. Computational results show that the proposed heuristic is superior to CPLEX in terms of solution quality and computational times for large scale problems. In addition, some sensitivity analyses were also conducted to evaluate the impact of parameters in the model. [ABSTRACT FROM AUTHOR]

Caragana korshinskii Kom. (CKK) is one of the main trees for wind and sand control in northwest China. According to its biological characteristics, flat stubble is the main measure and the critical stage of nurturing management. However, the quality of the CKK sawing surface not only affects the sprouting rate of the following year but also reflects the mechanical properties of flat stubble. To reduce the sawing power consumption of the CKK stubble device and improve the quality of sawing cross-section, this paper conducted branch sawing tests on a self-designed sawing experiment rig. Using the central composite design test method, the operating parameters of the sawing experiment rig were studied experimentally, with sawing speed (v a), moving speed (v ' f), and inclination angle of the circular blade (α) as the influencing factors, sawing power consumption (Y 1) and cross-section integrity rate (Y 2) as the objective functions, to establish a multiple mathematical regression model between them. The test results show that the influence of each factor on the sawing power consumption in the order of significance is the v a , v ' f , and α, and the influence of each factor on the cross-section integrity rate in the order of significance is the v ' f , v a , and α. The optimal combination of working parameters is v a of 42 m/s, v' f of 0.3 m/s, and α of 10°, which corresponds to Y 1 and Y 2 of 279.73 W and 82.6% respectively. Based on the optimal combination of working parameters, the prototype was processed and field tests were conducted. The field test results showed that the stubble breaking rate and missed cutting rate of the CKK harvester are 5.5% and 4.7% respectively, and the CKK branches sprouted well in the following year after flattening the stubble, which all met the requirements of the CKK harvesting operation. • For the unique growth mode of CKK, the sawing method was chosen through actual investigation in the field. • For CCK harvesters, cross-section integrity directly determines the sprouting rate of the following year. • The central combination test method was used to explore the effects of the test factors on the target values. • It was verified through field trials that the circular saw operated well with an optimized combination of cutting parameters. [ABSTRACT FROM AUTHOR]

• Machine learning is a successful dynamic device for foreseeing crop yields, just as for choosing which harvests to plant and what to do about them during the developing season. • Since it operates with a large amount of data produced by several variables, the farming system is highly complicated. • Methods of machine learning can aid intelligent system decision-making. • The following paper investigates a variety of methods for predicting crop yields using a variety of soil and environmental variables. • The main purpose of this project is to make a machine learning model make predictions. Machine Learning is a successful dynamic device for foreseeing crop yields, just as for choosing which harvests to plant and what to do about them during the developing season. Since it operates with a large amount of data produced by several variables, the farming system is highly complicated. Methods of machine learning can aid intelligent system decision-making. The following paper investigates a variety of methods for predicting crop yields using a variety of soil and environmental variables. The main purpose of this project is to make a machine learning model make predictions. By taking into account several variables, machine learning algorithms can help farmers decide which crop to grow in addition to increasing yield. Farmers can benefit from yield estimation because it allows them to minimize crop loss and obtain the best prices for their crops. A machine learning model may be descriptive or predictive, depending on the research question and study objectives. [ABSTRACT FROM AUTHOR]

Monoculture farming pollutes the environment by increasing the use of inputs, accelerating soil erosion, polluting water resources, raising carbon level in the atmosphere, and decreasing biodiversity. Therefore, farmers are advised to implement diversified farming systems such as crop rotation. However, crop rotation, i.e., planting more than one crop in the same field over a given year, may also harm the environment. To combat the environmental problems of monoculture, Turkey announced to implement a new crop rotation policy in 2020. The government said it would not provide support payments if farmers planted the same crop in the same plot for three consecutive years. This paper estimates the impact of this crop rotation policy on monoculture and shows how agricultural fires changed with this policy. We find that Turkey's crop rotation policy significantly decreased monoculture practices. Farmers decreased their cotton acreages and replaced cotton with wheat as the primary and corn as the secondary crop. However, since farmers burn their fields after the primary crop is harvested, the number of fires tripled after the policy. This environmentally friendly policy unexpectedly polluted the environment. Our paper shows how policies may create unintended environmental problems if they do not consider farmers' behavioral constraints. • This paper estimates the impact of a crop rotation policy on monoculture and the number of fires in Turkey. • We find that the crop rotation policy significantly decreased monoculture farming. • Farmers decreased their cotton acreages and replaced cotton with wheat as the primary and corn as the secondary crop. • Since farmers burn their fields after the primary crop is harvested to plant the secondary crop, the number of fires tripled with the policy change. • Consequently, an environmentally friendly policy unexpectedly polluted the environment. [ABSTRACT FROM AUTHOR]

This study aimed to identify markers in pear capable of predicting the development of internal browning disorder (IBD) at harvest or during early storage. ´ Conference ´ pears were harvested from different orchards at commercial maturity and stored under high CO 2 atmosphere conditions to induce disorders. The predictive markers studied were associated with 1-aminocyclopropane-1-carboxylic acid (ACC) metabolism, antioxidants and the tricarboxylic acid cycle (TCA cycle). The partial least square (PLS) model built for prediction at harvest identified ACC, malonyl ACC (MACC), and dehydroascorbic acid (DHA): the oxidized form of ascorbate, as the best markers for defining initial fruit sensitivity to IBD. A clear relationship was also found between increases in succinate levels during the first two weeks of storage and the incidence and severity of IBD after storage. Collectively, the results presented in this work reinforce the idea that IBD is determined by initial fruit maturity. They also question the current dogma concerning ascorbate, suggesting that rather than ascorbate, the most reliable marker for sensibility at harvest is DHA. Our results also highlighted that increased succinate levels should be considered one of the earliest responses to damaging storage conditions and offer an interesting short-term marker for IBD. The paper discusses how succinate is regulated during storage in relation to IBD development and an explanatory model is presented. • Different markers able to predict IBD disorder are defined in pear. • ACC, MACC and DHA are the best marker at harvest. • IBD severity may be predicted by succinate increase during short-term storage. • A new explicative model relating succinate changes and IBD is presented. [ABSTRACT FROM AUTHOR]

The capability of robotic fruit-harvesting systems to accurately assess the ripeness of fruits is crucial for fulfilling the diverse standards of the market and the preferences of consumers. Existing studies involving fruit ripeness estimation mainly focus on detecting of ripe strawberries as one class or classifying of ripeness into several stages, such as overripe, ripe, and unripe. Current harvesting robots also lack the ability to determine the ripeness of the back of fruit with respect to the robots. This paper proposes a lightweight convolutional neural network (CNN) regression model for ripeness quantification based on the internal image sensing system of the gripper with full-view coverage of the fruit for strawberry-harvesting robots. A gripper internal sensing system was developed using two RGB cameras that could provide full-view fruit coverage for a more accurate estimation of fruit ripeness. Four base CNN networks capable of feature learning were used for feature extraction, followed by the utilization of newly added dense layers that produced a regressed value to represent the strawberry ripeness. However, the base networks were cumbersome and relatively slow due to their complex structures. To simplify this, a new MiniNet with fewer convolutional layers was proposed to reduce the model size and inference time. All models were trained via two loss functions, mean square error and Huber loss. The results showed that the models trained via Huber loss performed better. An Xception model trained on Huber loss showed the best performance with a mean absolute error of 4.0% and an average inference time of 42.5 ms. Of all the models, the new MiniNet was the most lightweight and fastest model while maintaining high performances (an mean absolute error of 4.8% and an inference time of 6.5 ms for Huber loss trained model). The proposed method may be also applicable to other fruit-harvesting systems. • Gripper internal sensing system allows multi-view comprehensive ripeness assessment. • Regression models can estimate ripeness levels effectively, with a minimal MAE of 4.0%. • The newly developed MiniNet performed well with a 4.8% MAE, and is faster and lighter. [ABSTRACT FROM AUTHOR]

The last quarter of a century saw the international political community make concerted efforts to regulate global caviar trade and prevent illegal harvesting of critically endangered sturgeon. Ironically, the regulations have enabled the emergence of novel forms of illicit trade which intertwine legal and illegal streams of caviar on the international marketplace. This paper foregrounds these licit-illicit interfaces and argues that the international caviar trade constitutes a 'grey market' characterized by a host of laundering practices that entangle legal and illegal caviar flows. Drawing on geographical scholarship on political animals and fleshy geopolitics, the paper theorises how the fleshy material properties of caviar, namely its chemical-isotope profile and composite form, directly shape the European caviar grey market. By highlighting how the materiality of caviar creates grey interfaces between legal and illegal caviar economies, the paper unsettles dominant dichotomized representations of illegal caviar trade which tend to foster overwhelmingly securitized policy-enforcement approaches in Europe. In pointing to the hidden 'fleshy geopolitics' surrounding EU enforcement strategies, the paper calls for a reshaping of policy and enforcement which better attends to the grey dimensions of the caviar market and provides increased protection for wild sturgeon populations and marginalised communities located at the Eastern borders of Europe. • The European caviar economy is a grey market which intertwines legal and illegal caviar streams. • The 'fleshy' material properties of caviar shape the character of the grey caviar market. • The grey caviar market must be conceptualised from a more-than-human perspective. • Attention to caviar's materiality provokes new considerations of the role of nonhumans in 'fleshy geopolitics'. • Current EU policy-enforcement approaches ineffectively tackle illicit caviar trade. [ABSTRACT FROM AUTHOR]

• A heterogeneous energy coupling model is established for optimal operation and configuration. • Annual 8760 data of wind, solar and load are achieved and utilized. • Waste heat originated from CCHP is harvested by ORC system. • Carbon Singular Point shows the directionality of multi-objective optimization. Integrated energy system characterizes with improving cascade utilization rate of energy and efficient energy conservation and substantial carbon reduction. Aiming at the total annual cost and annual carbon emission of integrated energy system, the capacity optimal configuration model of integrated energy system based on the principles of cooling determining heat and heat determining electricity is established in this paper, considering energy complementary coupling characteristic and distribution ratio. Moreover, Non-dominated Sorting Genetic Algorithm-II combined with Technique Order Preference by Similarity to an Ideal Solution comprehensive solution model is adopted to achieve the optimal solution under Pareto solution set. The configuration result reflected that renewable energy is preferred, and there are more electricity storage devices with less electricity equipment. Furthermore, the optimal operation schemes of three typical season days are analyzed and compared, specifically presenting the effectiveness of the operation strategy proposed in this paper. In addition, waste heat originated from integrated energy system and harvested by ORC is analyzed herein, which highlights generating electricity with 2.19 × 104 kWh totally participating in operation of power subsystem and reducing CO 2 emissions by 15.056 tons. Furthermore, the sensitivity of carbon emission factors is analyzed, achieving that there is a Carbon Singular Point with 0.18 kg/kWh of natural gas emission and 0.98 kg/kWh of power grid emission respectively in the optimization process, which is significant for multi-objective optimization and construction of Integrated energy system. [ABSTRACT FROM AUTHOR]

The aim of the present paper is to evaluate the most intensive demonstration of harvesting of olive tree prunings (OTP) ever occurred in Greece. In Agios Konstantinos, an integrated shredder was used to harvest the local olive groves. The harvesting campaign was performed for two consecutive years. In total, for both years, the harvesting campaign lasted for 20 days where around 81 ha of olive groves were harvested, that amounted to 252 dry Mg of harvested prunings. The aim of the paper is to evaluate an agricultural residue mobilization value chain in terms of performance, economics and fuel analyses of the harvested OTP. Via detailed monitoring, the present paper compares the harvesting demonstration results for both years. In brief, the average material capacity increased from 2.2 dry Mg/h (first year) to 2.4 dry Mg/h (second year), whereas the corresponding harvesting and haulage costs of these harvesting campaigns were calculated at 62.3 €/Mg (dry basis) and 63.7 €/Mg (dry basis), with an estimated commercial operation cost at 46.0 €/Mg (dry basis). Finally, from 49 samples of OTP collected, the average moisture content was at 27.5% (as received), ash content at 4.5% (dry basis) and the average LHV at 12.2 MJ/kg (as received). [Display omitted] • Detailed monitoring of a two-year mechanized harvesting and haulage of olive prunings. • Material Capacities at 2.2 dry Mg/h and 2.4 dry Mg/h in two consecutive years. • Estimated commercial cost of harvesting and haulage at 46.0 €/dry Mg olive pruning. • Harvested prunings averaged 12.2 MJ/kg LHV, 27.5% moisture and 4.5% ash content. • Mechanized harvesting of olive prunings (<3 Mg/ha) proved to be economical feasible. [ABSTRACT FROM AUTHOR]

• We presented the Deep-ToMaToS, capable of recognizing harvesting information. • We constructed a custom photo-realistic simulator for building a large-scale dataset. • We presented a harvest motion based on the Peck-and-Pull manipulation method. This paper presents the development of an autonomous harvesting robot system for tomato, a representative crop cultivated in the facility horticulture smart farm. The automated harvesting work using a robotic system is very challenging because of the appearance, environmental features, such as the atypical directions of the peduncles or their growing form in a bunch. Also, the robot system should enable the harvesting of the target fruit only without damaging other fruits, stems, and branches. Hence, this paper presents a deep learning network pipeline, Deep-ToMaToS, capable of three-level maturity classification and 6D pose (3D translation + 3D rotation) estimation of the target fruit simultaneously. Due to the difficulties encountered in building a large-scale dataset to train and test the deep learning model for the 6D pose estimation in the real world, we presented an automatic data collection scheme based on a photo-realistic 3D simulator environment. The robotic harvesting system includes a harvesting motion control algorithm based on the result of the 6D pose estimation. The overall process of the motion control phase is described along with the decision way of the appropriate final posture of the harvesting module mounted at the end-effector of the robot manipulator via removal of invalid motions getting out of the valid workspace or redundant motions. We conducted experiments on the 6D pose estimation based on the Deep-ToMaToS and the harvesting motion control in virtual and real smart farm environments. The experimental results showed a 6D pose estimation accuracy of 96 % based on the ADD_S metric, and the proposed harvesting motion control algorithm achieves the harvesting success rate of 84.5 % on average. The experimental results reveal that the harvesting robot system has significant potential to extend to harvesting works for other fruits and crops. [ABSTRACT FROM AUTHOR]

Last few decades have witnessed a rapid development in robotic technology. Different types of intelligent machines which facilitate various tasks in industry environment are becoming popular. This paper focuses on designing a low cost coconut tree climbing and harvesting robot. The kinematics and the motion of the robot are designed by referring to the motion of coconut harvester. The robot consists of two segments joined by a pair of threaded rods coupled to motors. The mechanical frame is designed in draft sight software and is implemented using aluminum segments and threaded rods. It has two arms driven by motors for holding. Locomotion of the robot is achieved using six motors out of which four motors are used in two hands and other two are used for upward and downward motion. The other part is a robotic arm for cutting down the coconuts. The robotic arm is attached on top of the climbing part. The operation of the cutting arm is done manually from the ground using a remote. The robot is automated using Arduino-Uno, motor H-bridge drivers, current and level sensors and other supporting circuits. The forward and the reverse motion of the motors are controlled by the Arduino through driver modules. Robot has automatic and manual functions fully controlled by the end-user. This paper has taken into account of the safety, reliability and the ease of use. A locomotion algorithm is developed to provide the robot with an autonomous capability for climbing. The prototype of the robot is implemented and tested successfully. [ABSTRACT FROM AUTHOR]

The UK has had a Temporary Migrant Worker Programme (TMWP) for agricultural ‘guestworkers’ since 1943. Most recently referred to as the Seasonal Agricultural Workers Scheme (SAWS), SAWS accommodated 25,000 workers per annum by its 2004 peak. However, the UK government then announced the scheme's closure (initially for 2011, but then delayed until 2014). This paper examines employers' response to this closure and, specifically, juxtaposes the academic critiques of TMWPs with the very strong employer preference for them. This preference, the paper concludes, is about the way in which TMWPs allow labour to be more readily and more extensively controlled, and, also allow employers access to ‘better quality’ workers. Considering these benefits of quality and control, alongside the academic critiques, the paper concludes that SAWS should be retained, but with major changes and safeguards. [ABSTRACT FROM AUTHOR]

After decades focused on promoting economically valuable species, management of northern temperate forests has increasingly become focused on promoting tree species diversity. Unfortunately, many formerly common species that could contribute to diversity including yellow birch ( Betula alleghaniensis Britton.), paper birch ( Betula papyrifera Marsh), eastern hemlock ( Tsuga canadensis L.), and eastern white pine ( Pinus strobus L.) are now uncommon in the seedling layer, raising concerns about our ability to use these species to increase diversity. In this study, two related seed addition experiments conducted in 45 variably-sized harvest gaps (unharvested to 6500 m 2 ) in adjacent mesic northern hardwood stands, Emmet County, Michigan, USA were used to investigate mechanisms potentially limiting seedling recruitment. The first experiment examined the influence of light (i.e. harvest gap size), competing vegetation, and deer browsing on seedling survival for three years in a 2 × 2 factorial, where subplots were unfenced or fenced to exclude deer, unclipped or clipped to control competing vegetation, and located across the gradient of gap sizes. The second experiment explored the influence of scarification, light, and competing vegetation on germination and subsequent survival for 2 years in a 2 × 2 factorial, in subplots that were unscarified or scarified to remove litter, unclipped or clipped to control competing vegetation, and located across the gradient of gap sizes. Eastern hemlock, paper birch, and yellow birch, all smaller-seeded species, were 12, 17, and 95 times more abundant in scarified plots compared to unscarified plots. In contrast, white pine, the largest-seeded species, was unaffected by scarification and had low overall germination. Shade tolerant hemlock and shade intolerant paper birch germinated at higher densities in lower light, smaller harvest gap environments, while both mid-tolerant species, white pine and yellow birch, were unaffected by light. Each species’ initial survival significantly increased with increasing light availability, and with the exception of yellow birch, each species also survived at a significantly higher rate with increasing light availability. Paper birch and hemlock third year survival also increased with increasing light. By the end of the third growing season, only paper birch survival was negatively impacted by competition from vegetation and no species were affected by exposure to deer browse pressure. At the conclusion of the study, large group selection gaps (24–50 m diameter) contained the highest density of each species except white pine, suggesting that large group selection gaps may provide the best opportunity for reestablishing this particular group of species in the seedling layer. [ABSTRACT FROM AUTHOR]

The contribution of the European food sector to the total amount of greenhouse gases emissions is equal to 15%. The main environmental impact is due to the cultivation phase while the transformation has limited consequences. The sustainability of the food sector can be traced using an important indicator: Product Carbon Footprint. In this framework this paper presents the case of a traditional product: truffle sauce, which is a mixture of extra virgin olive oil and truffle. Its carbon footprint has been calculated based on ISO 14067, through the use of specific Product Category Rules, able to describe theoretical pre-requisites and practical rules to be followed during the analysis in order to make results comparable with other studies. Different allocation techniques have been analyzed: system expansion has been compared with allocation based on mass and economical value. It was shown that 3% variation in the mass yield of olive oil implies 2% variation in the final carbon footprint. Different harvesting techniques were considered and their energy consumption was measured on site. Final carbon footprint for truffle sauce, assuming allocation based on system expansion, is equal to 1.93 kg CO 2 eq/kg. Truffle sauce has a lower impact compared to other similar commodities (extra virgin olive oil for example). The final result of the Product Carbon Footprint is not the only scientific value added by this paper, because Product Category Rules can be used by other researchers to calculate emissions released during truffle sauce or olive oil life cycle in other particular environments. Knowing the value of these emissions, reduction measures can be designed. The limits of this study are represented by the fact that these values are deeply influenced by seasonal variability, so this aspect should be evaluated by further studies. [ABSTRACT FROM AUTHOR]

This paper provides a feasibility study on a low cost system called Hydrokinetic Wells turbine for surface wave energy conversion without using plenum chambers. The elimination of the plenum chamber and its complicated valve systems can reduce the expenses of wave energy conversion up to 23%.The feasibility process were done for high and low frequency conditions. For the low frequency waves, we offer the 300 rpm angular velocity as an optimum selection for further studies. For the high frequency condition a reliable analytical approach based on validated methods was developed. The analytical results indicate that a wells turbine with 60 cm diameter could produce up to 1600 Watts power in high frequency waves. The efficiency and power coefficient values in high frequency condition are less in compared with low frequency situation, nevertheless the vast usage of the small scale and elimination of the plenum chambers can reduce the total cost of the conversion. The abundant availability of high frequency surface waves is a motivation for developing Hydrokinetic Wells turbine farms to harvest a great source of clean energy with lower cost levels. • HKWT is a feasible low cost device for conversion of both low and high frequency surface wave's energy. • Angular velocity of 300 RPM is an optimum selection for future low frequency condition designs. • The use of HKWT at farm scales is possible and the elimination of plenum chambers can lower the LCOE up to 23%. • HKWT with 60 cm diameter can produce up to 1600 [w] power in a high frequency situation. [ABSTRACT FROM AUTHOR]

• Developed BioRTC as the first model for real time control (RTC) of biofilters. • High parameter transferability allows BioRTC capable of evaluating RTC strategies. • Explored RTC with scenario testing on a field-scale biofilter system using BioRTC. • The presence of Pareto fronts reveals the necessity of muti-objective optimisation. • RTC allows for the adaptation to climate change and changing demands for harvesting. Biofilters with real time control (RTC) have great potential to remove microbes from stormwater to protect human health for uses such as swimming and harvesting. However, RTC strategies need to be further explored and optimised for each specific location or end-use. This paper demonstrates that the newly developed BioRTC model can fulfil this requirement and allow effective and efficient exploration of the potential of RTC applications. We describe the development of BioRTC as the first RTC model for stormwater biofilters, including: selection of a 'base' model for microbial removal prediction, its modification to include RTC capabilities, as well as calibration and validation. BioRTC adequately predicted the performance of two previously developed RTC strategies, with Nash Sutcliffe Efficiency (E c) ranging from 0.65 to 0.80. In addition, high parameter transferability was demonstrated during model validation, where we employed the parameter sets calibrated for another biofilter study without RTC to predict the performance of RTC biofilters. We then employed the BioRTC model to explore RTC applications on a hypothetical biofilter system located at the outlet of an existing catchment. With different scenarios, we tested the impact of input parameters such as RTC set-points and design characteristics, and evaluated the influence of operational conditions on the microbial removal performance of the hypothetical biofilter with RTC. The results showed that strategy rules, set-point values, and biofilter design all govern the performance of RTC biofilters, and that operational conditions could impact the suitability of different RTC strategies. Particularly, the presence of Pareto fronts established that muti-objective optimisation is necessary to balance competing needs. These results underscore the importance of RTC, which allows for local experimentation, climate change adaptation, and adjustment to changing demands for the harvested water. Furthermore, they illustrate the practical use of the newly developed BioRTC model, enabling researchers and practitioners to explore and assess potential RTC strategies and scenarios quickly and cost-effectively. [Display omitted] [ABSTRACT FROM AUTHOR]

• Novel tendon-driven continuum manipulator (TDCM) is presented, that manipulate distal tip in 3D using planar geometry. • The proposed design uses decoupled tendon routing and avoids tendon interference. • The proposed manipulator offers an expanded workspace (∼ 22 % more) than traditional TDCMs. • Kinematic and Kineto-static models are presented considering external uncertain forces. • Calibration and experimental results validated the proposed design. Continuum Manipulators (CMs) have gained popularity as a promising solution for exploring unstructured environments due to their dexterity, compliance, and redundancy. Studies on CMs have focused individually on planar and spatial configurations, ranging from single to multi-section constructions. Planar CMs are easier to design, have simpler kinematics equations and possesses less number of tendons with reduced dexterity, redundancy, and reach. Whereas spatial CMs, offer a larger workspace with improved dexterity and redundancy while computationally expensive. This paper introduces a novel two-section tendon-driven continuum manipulator (TDCM) design that uses two planar sections to manipulate the distal end of the manipulator in three-dimensional space to handle external interaction from the environment. The proposed solution offers improved performance in terms of handling payloads and tip deflection under external interactions. This design is intended for agricultural applications such as vegetable harvesting and requires larger workspace and fewer actuators. We demonstrate the effectiveness of our design through kinematic and static analysis. The kineto-static model estimates the profile of the proposed TDCM under external interaction acting at the manipulator's distal end. Finally, the proposed design is experimentally validated by an in-housed prototype of an two-section TDCM, actuated by two tendons/section. [ABSTRACT FROM AUTHOR]