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This paper shares results from a pedagogical experiment that assigns undergraduates to "cheat" on a final class essay by requiring their use of text-generating AI software. For this assignment, students harvested content from an installation of GPT-2, then wove that content into their final essay. At the end, students offered a "revealed" version of the essay as well as their own reflections on the experiment. In this assignment, students were specifically asked to confront the oncoming availability of AI as a writing tool. What are the ethics of using AI this way? What counts as plagiarism? What are the conditions, if any, we should place on AI assistance for student writing? And how might working with AI change the way we think about writing, authenticity, and creativity? While students (and sometimes GPT-2) offered thoughtful reflections on these initial questions, actually composing with GPT-2 opened their perspectives more broadly on the ethics and practice of writing with AI. In this paper, I share how students experienced those issues, connect their insights to broader conversations in the humanities about writing and communication, and explain their relevance for the ethical use and evaluation of language models. [ABSTRACT FROM AUTHOR]

Flexible thermoelectrics (TEs) involving simplified processeability are attractive, with limited choice of materials and low endurance, remaining as major challenges. Herein, an economic emery paper‐based thermoelectric generator (PTEG) from graphite as p‐type leg and bismuth as n‐type leg is introduced, prepared by simple bulk tracing. Tracing provides a feasible approach to modulate the TE properties, as supported by finite‐element analysis. From individual bismuth trace a power factor of 5.85 μW m−1 K−2 ≈100 °C (2.09 μWm−1 K−2 at room temperature (RT)) and for graphite a power factor 7.7 μW m−1 K−2 at ≈100 °C (≈5.1 μW m−1 K−2 at RT) is obtained. A six‐pair p–n module‐integrated PTEG drives an open‐circuit voltage of 35.8 mV producing an output power of 14.6 nW whereas from a 60‐pair PTEG, voltage ≈348 mV with ≈137.5 nW output power is produced for ΔT ≈ 70 K. The scalability of the fabricated PTEGs is understood from Seebeck voltage being directly proportional to the number of p–n modules and is further tested for harvesting waste heat from electronics. This facile approach may be extended to other organic and inorganic TE materials, contributing to the research in self‐powered heat sensors, wearables, and as thermal harvesters in IoT equipment. [ABSTRACT FROM AUTHOR]

Now days there has been an increase in the consumers demand for great food, produced in environmentally cost-effective and friendly processes, being increasingly necessary new cultivation techniques able to ensure the required standards for banana growers and consumers. Therefore, the research aimed to evaluate the effects of bunch cover materials on development and quality of 'BRS Platina' banana fruits. The experimental design was in randomized blocks, with six treatments, four replications and four plants per plot, being the treatments: WB - without bagging; BBTK - black polypropylene bag (TNT) + kraft paper; BBPK - black polyethilene bag + kraft paper; KP - kraft paper; WBT - non-woven polypropylene white bag (TNT) and WBP - white polyethylene plastic bag. The 'BRS Platina' banana bunches cover improved fruits quality and the treatment polyethylene white bag (WBP) can be an advantageous option for the banana growers because of its effectiveness on the reduction of damages caused by flowers thrips (Frankliniella spp), providing a good agronomic performance and also does not delay the harvesting. [ABSTRACT FROM AUTHOR]

Fruit bagging protects fruits from pest infestation and multiple biotic and abiotic stresses during development without reducing yield. It also can potentially improve the quality and market value of fruits. Hence, the present study aimed to determine the effect of pre-harvest fruit bagging on the yield and quality of tomato (Solanum lycopersicum) cv. BARI Tomato-2. The experiment was laid out in a Randomized Complete Block Design (RCBD) with three replications that constituted the various treatments-T0: Control (no bagging), T1: White paper bag (single layer), T2: Brown paper bag (double layer), T3: Non-woven fabric bag, and T4: Jute bag from October 2021 to March 2022. The results showed that the non-woven fabric bag had the highest fruit length (57.79 mm), diameter (57.81 mm), number of fruits plant-1 (55.9), yield (4.06 kg plant-1), vitamin C (24.63mg/ 100g-1), and lycopene content (0.12 mg g-1). The maximum insect incidence (18.41%) was recorded in control and the minimum was counted in T3 (2.17%). The highest total soluble solid (6.73%0Brix) and dry matter (8.63%) were observed in a white paper bag. The highest mean color score (6.08), firmness (26.81%), and shelf life (13 days) found in fabric bags outperformed non-bagged fruits. The fabric bag showed maximum net income (21.12 TK) and the highest benefit: cost ratio (2.36). Thus, the fabric bag was the best for improving the physical and chemical qualities of tomatoes (Solanum lycopersicum) among the various fruitcovering materials. [ABSTRACT FROM AUTHOR]

In this paper, we introduce multilateral strategies to improve the efficiency and brightness of quantum dot light‐emitting diodes. First, electrically and thermally endurable device architecture is adopted for highly bright light‐emission. Second, an exciton harvesting layer consisting of blue‐emitting thermally‐activated delayed fluorescent materials is introduced to improve device efficiency. Our approaches realize remarkable improvements in the device performance. [ABSTRACT FROM AUTHOR]

The hornification processes undergone by the fibers in the paper industry recycling processes lead to the loss of properties of the final products, which exhibit poor mechanical properties. Among the most promising solutions is the reinforcement of secondary fibers with cellulose nanofibers. The present work addresses two important issues: the efficient production of cellulose nanofibers from scarcely exploited agricultural wastes such as horticultural residues and vine shoots, and their application as a reinforcement agent in recycled linerboard recycling processes. The effect of the chemical composition and the pretreatment used on the nanofibrillation efficiency of the fibers was analyzed. Chemical pretreatment allowed a significantly higher nanofibrillated fraction (45–63%) than that produced by mechanical (18–38%), as well as higher specific surface areas (>430 m2/g). The application of the nanofibers as a reinforcing agent in the recycled linerboard considerably improved the mechanical properties (improvements of 15% for breaking length, 220–240% for Young's modulus and 27% for tear index), counteracting the loss of mechanical properties suffered during recycling when using chemically pretreated cellulose nanofibers from horticultural residues and vine shoots. It was concluded that this technology surpasses the mechanical reinforcement produced by conventional mechanical refining used in the industry and extends the number of recycling cycles of the products due to the non-physical modification of the fibers. [ABSTRACT FROM AUTHOR]

The entomopathogenic fungus Beauveria bassiana (Balsamo) Vuillemin (Hypocreales: Cordycipitaceae) has been widely studied against a wide range of arthropod pests, including many of medical and veterinary importance. New investigators must sort through a wide array of published methods for the production, harvest, storage, and bioassay methods for this pathogen. Simplified methods for production of conidia using Sabouraud dextrose agar with yeast (SDYA) plates and two conidial harvesting methods are described. Dry harvesting yields conidia that are ready to incorporate into dusts and food baits, but the fungal product includes mycelial debris that can hamper quantification and introduces variable amounts of unwanted bulk. Wet harvesting with filtration produces a cleaner product that is immediately ready for testing in liquid formulations. Examples of bioassays with house flies are presented that include conidia applied topically to the dorsal thorax for dose–mortality assays and conidial suspensions applied to filter paper disks for concentration mortality assays. [ABSTRACT FROM AUTHOR]

Background: The use of human amniotic membrane transplantation is rapidly increasing for the management of various ocular surface disorders. Despite its numerous advantages, amniotic membrane is not widely available due to the lack of awareness among ophthalmologists regarding its preparation and preservation techniques. Purpose: To provide an instructional video demonstrating the technique of harvesting, preparation, preservation of human amniotic membrane, and its uses in the management of ocular surface diseases. Synopsis: The amniotic membrane is the innermost layer of the human placenta. Properties of the amniotic membrane, like the presence of various growth factors, anti-inflammatory and anti-angiogenic factors, and its low immunogenicity, contribute to its ability to promote epithelial growth and differentiation with the reduction in fibrosis during healing. To harvest amniotic membrane, informed consent is obtained from a patient undergoing an elective caesarian section, and the donor is screened to exclude the risk of infections. Under sterile precautions, the amniotic membrane is separated from the chorion and washed free of blood clots. With the epithelial surface up, the amniotic membrane is spread uniformly without folds or tears on individually sterilized 0.22 µm nitrocellulose filter papers of the required sizes. The prepared filter paper with the adherent amniotic membrane is placed in freshly prepared Dulbecco's Modified Eagle's Medium and stored at -80°C. The amniotic membrane can be used for surgical procedures like symblepharon release, pterygium or dermoid excision, perforated ulcers, nonhealing epithelial defects, etc. Highlights: Instructional videos demonstrating the preparation and preservation of amniotic membrane are very sparse. This video clearly explains how any ophthalmologist can learn to prepare and preserve the human amniotic membrane and gives a glimpse of its properties, advantages, and scope of use. Video Link: https://youtu.be/8HfSjXUKoiY. [ABSTRACT FROM AUTHOR]

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]

Blueberries have high nutritional and economic value and are easy to cultivate, so they are common fruit crops in China. There is a high demand for blueberry in domestic and foreign markets, and various technologies have been used to extend the supply cycle of blueberry to about 7 months. However, blueberry grows in clusters, and a cluster of fruits generally contains fruits of different degrees of maturity, which leads to low efficiency in manually picking mature fruits, and at the same time wastes a lot of manpower and material resources. Therefore, in order to improve picking efficiency, it is necessary to adopt an automated harvesting mode. However, an accurate maturity detection model can provide a prerequisite for automated harvesting technology. Therefore, this paper proposes a blueberry ripeness detection model based on enhanced detail feature and content-aware reassembly. First of all, this paper designs an EDFM (Enhanced Detail Feature Module) that improves the ability of detail feature extraction so that the model focuses on important features such as blueberry color and texture, which improves the model's ability to extract blueberry features. Second, by adding the RFB (Receptive Field Block) module to the model, the lack of the model in terms of receptive field can be improved, and the calculation amount of the model can be reduced at the same time. Then, by using the Space-to-depth operation to redesign the MP (MaxPool) module, a new MP-S (MaxPool–Space to depth) module is obtained, which can effectively learn more feature information. Finally, an efficient upsampling method, the CARAFE (Content-Aware Reassembly of Features) module, is used, which can aggregate contextual information within a larger receptive field to improve the detection performance of the model. In order to verify the effectiveness of the method proposed in this paper, experiments were carried out on the self-made dataset "Blueberry—Five Datasets" which consists of data on five different maturity levels of blueberry with a total of 10,000 images. Experimental results show that the mAP (mean average precision) of the proposed network reaches 80.7%, which is 3.2% higher than that of the original network, and has better performance than other existing target detection network models. The proposed model can meet the needs of automatic blueberry picking. [ABSTRACT FROM AUTHOR]

The article "Harvesting Knowledge: Illuminating Advances in Brassica Crops Genomics and Breeding" discusses the importance of Brassica crops, which include vegetables, oil crops, ornamentals, and condiments, in global agriculture. The article highlights the unique morphological types and polyploidization events within Brassica species, making them ideal models for studying genetic complexities. The article also explores the progress in genomic sequencing technologies, functional genomics, and molecular marker-assisted breeding in Brassica crops. The research papers featured in the article provide valuable insights into genetic mechanisms, stress responses, biochemical characteristics, and genetic improvement of Brassica crops. The findings contribute to advancements in breeding research and hold promise for enhanced productivity, adaptability, and nutritional value of Brassica crops. [Extracted from the article]

This paper deals with the trade-off between conversion time and power in nW-power capacitance-to-digital converters (CDCs). The CDC used in this work operates at nW power and low voltage down to 0.3 V without the need for any additional circuitry, references, or voltage regulation. It is built on swappable oscillators and takes advantage of the delay-power flexibility of dual-mode logic. Its self-calibration corrects PVT changes and mismatches at any point in the chip lifecycle, doing away with the necessity for cutting during testing. A CDC's test chip in 180 nm demonstrates that its power consumption can be dynamically modified from 1.37 nW down to 418 pW at a conversion time down to hundreds of ms, making it suited for harvesting systems with a very tight power budget and changing power sources. [ABSTRACT FROM AUTHOR]

Surface charge density is a key factor that greatly enhances the performance of a natural-based triboelectric nanogenerator (TENG), which is essential for future sustainable sensing and harvesting devices. This work introduced a conductive interlayer between a main frictional layer and electrode. This approach can suppress the charge recombination rate and improve the amount of charges produced during the triboelectrification process. Bacterial cellulose (BC) film was selected as a main frictional layer for the TENG. A conductive nanomaterial, i.e. silver flake, was incorporated into the BC film as an intermediate layer for enhancing TENG performance. As firstly reported, the maximum electrical outputs for the multi-layer BC structure could be found when using silver flake/BC composite (ratio 1:5) as an intermediate layer, which has 122 V and 8.2 µA of output voltage and current, respectively. This is higher than the output voltage and current of a single layer BC TENG by approximately 3 and 8 times, respectively. The maximum output power of ∼440 µW is achieved by connecting with a load resistor of ∼10 MΩ. This demonstrates an efficient strategy for designing a high performance energy harvester by adding an intermediate layer for the target of practical purposes in sustainable systems. [ABSTRACT FROM AUTHOR]

Pedoclimatic elements and smart technology act simultaneously on the biological processes of agricultural crops and on the level of harvest, which requires the study of their correlation to determine the continuous influence of these factors in obtaining the planned levels of production. In Romania, annually, over 2.1 million hectares of wheat are cultivated, with annual productions of over 10 million tons, placing wheat crops in the first place as economic importance. Knowing the management of natural resources in quantitative terms is especially valuable when we talk about their sustainable use. Our evaluation includes in this paper the relationship between the pedoclimatic resources of South-Eastern Romania and the zoning of wheat varieties in order to obtain superior quantitative and qualitative productions. The last 11 agricultural years are analyzed, both in terms of the influence of global warming and in terms of wheat zoning to obtain sustainable production to highlight the genetic potential of the varieties under the conditions of the Brailei Plain. A stability of the varieties Glosa, Miranda, Litera (varieties over 15 years old) was observed, but not least of the new ones created by the National Research and Development Institute from Fundulea such as: Pitar, Ursita, Adelina, Izvor. [ABSTRACT FROM AUTHOR]

The automated harvesting of clustered fruits relies on fast and accurate visual perception. However, the obscured stem diameters via leaf occlusion lack any discernible texture patterns. Nevertheless, our human visual system can often judge the position of harvesting points. Inspired by this, the aim of this paper is to address this issue by leveraging the morphology and the distribution of fruit contour gradient directions. Firstly, this paper proposes the calculation of fruit normal vectors using edge computation and gradient direction distribution. The research results demonstrate a significant mathematical relationship between the contour edge gradient and its inclination angle, but the experiments show that the standard error projected onto the Y-axis is smaller, which is evidently more conducive to distinguishing the gradient distribution. Secondly, for the front view of occluded lychee clusters, a fully convolutional, feature prototype-based one-stage instance segmentation network is proposed, named the lychee picking point prediction network (LP3Net). This network can achieve high accuracy and real-time instance segmentation, as well as for occluded and overlapping fruits. Finally, the experimental results show that the LP3Net based on this study, along with lychee phenotypic features, achieves an average location accuracy reaching 82%, significantly improving the precision of harvesting point localization for lychee clusters. [ABSTRACT FROM AUTHOR]

Rice lodging not only brings trouble to harvesting but also reduces yield. Therefore, the effective identification of rice lodging is of great significance. In this paper, we have designed a bilinear interpolation upsampling feature fusion module (BIFF) to decompose the quadruple upsampling of the connected part of encoder and decoder into two double upsampling processes and insert the intermediate feature layer in the backbone network for feature fusion in this process. The global attention mechanism(GAM) attention module is added to the feature extraction network, allowing the network to effectively focus on the lodging regions, thus effectively improving the segmentation effect. The average accuracy of the improved network is 93.55%, mrecall is 93.65%, and mIoU is 88.10%, and the feasibility of the improvement is demonstrated by ablation experiments and comparison with other algorithms. In addition, the angle calculation method is designed by combining the detection algorithm, adding a detection head branch to the output results for reading the distance information from the depth camera, and combining the distance information with mechanical analysis to determine the relationship between the angle of the stalk and the vertical direction when the rice is upright, tilted and fallen. A comparison of the calculated angle with the actual measured angle gives a final average error of approximately 5.364%, indicating that the harvest boundary extraction algorithm in this paper is highly accurate and has value for application in real-time harvesting scenarios. [ABSTRACT FROM AUTHOR]