Miracle-dz/UniFAR-FTUs huggingface dataset:
The Results of Studies on the Assessment of the Destruction of Soil Clods during Combine Harvesting of Potatoes

Existing potato harvesters cause damage to marketable products as a result of the interaction of potato tubers with each other, with working bodies and soil clods, given the wide variety of soil and climatic conditions in which the harvesting process takes place. In addition, under homogeneous soil and climatic conditions within the same accounting area, there is a large deviation from the average values of the main physical soil constants—moisture and hardness. Field studies were carried out to determine the fractional composition of soil clods, size-mass parameters, as well as their physical and mechanical properties with the identification of the greatest force for their destruction. The article presents a methodology for conducting research to assess the influence of working bodies on the magnitude of the force impact on potato tubers and soil clods during harvesting, a methodology for assessing the dynamic destruction of soil clods. The results of comparative studies of the force impact of the working bodies of modern potato harvesters, which affect the destruction of soil clods, causing damage to potato tubers as a result of their interaction with soil clods are presented.
Color Names Affect the Precision of Memorized Hues. The effect of increased color name distinctiveness

Color names influence the memory of a specific hue by shifting it closer to the prototypical color associated with the name. Typically, in studies regarding color naming and memory maximally seven traditional color names are used. We tested whether the distinctiveness of the color name can modify the shift of the memorized hue by introducing unique color names for all hues presented in the experiment. Specifically, we gave unique names to boundary colors, defined, based on previous experiments, as hues that are equally likely named using two traditional names. Central colors are consistently named with one of the seven traditional color names. We observed that more distinctive names were associated with a poorer color recall performance than the traditional names. We propose it can be the result of long-term memory overload caused by having to memorize new color names. At the same time, when distinctive names were provided for boundary colors, the difference in the ability to accurately recall a hue between the boundary and central colors was smaller than when only traditional names were used. Moreover, when using only the traditional color names for boundary colors, we observed a consistent shift in the recalled hue towards the direction of the color name that accompanied it. This study should be considered a preliminary one. Follow-up experiments should be conducted to assess the exact cause of the observed differences. As the next step, we propose to test whether alternate labels to Pantone would lead to similar results.
Grid-Based Essential Urban Land Use Classification: A Data and Model Driven Mapping Framework in Xiamen City

Accurate and timely mapping of essential urban land use categories (EULUC) is vital to understanding urban land use distribution, pattern, and composition. Recent advances in leveraging big open data and machine learning algorithms have demonstrated the possibility of large-scale mapping of EULUC in a new cost-effective way. However, they are still limited by the transferability of samples, models, and classification results across space, particularly across different cities. Given the heterogeneities of environmental and socioeconomic conditions among cities, in-depth studies of data and model adaptation towards city-specific EULUC mappings are highly required to support policy making, and urban renewal planning and management practices. In addition, the trending need for timely and detailed small land unit data processing with finer data granularity becomes increasingly important. We proposed a City Meta Unit (CMU) data model and classification framework driven by multisource data and artificial intelligence (AI) algorithms to address these challenges. The CMU Framework was innovatively applied to systematically set up a grid-based data model and classify urban land use with an improved AI algorithm by applying Moore neighborhood correlations. Specifically, we selected Xiamen, Fujian, in China, a coastal city, as the typical testbed to implement this proposed framework and apply an AI transfer learning technique for grid and parcel land-use study. Experimental results with our proposed CMU framework showed that the grid-based land use classification performance achieves overall accuracies of 81.17% and 76.55% for level I (major classes) and level II (minor classes), which is much higher than the parcel-based land use classification (overall accuracies of 72.37% for level I, and 68.99% for level II). We further investigated the relationship between training sample size and classification performance and quantified the contribution of different data sources to urban land use classifications. The CMU framework makes data collections and processing intelligent and efficient, with finer granularity, saving time and cost by using existing open social data. Incorporating the CMU framework with the proposed grid-based model is an effective and new approach for urban land use classification, which can be flexibly extended and applied to various cities.
Studies on the Efficiency of Iron Release from Fe(III)-EDTA and Fe(III)-Cit and the Suitability of These Compounds for Tetracycline Degradation

Iron ions can be used to degrade tetracycline dispersed in nature. Studies of absorption and fluorescence spectra and quantum chemistry calculations showed that iron is more readily released from Fe(III)-citrate than from Fe(III)-EDTA, so Fe(III)-citrate (Fe(III)-Cit) is more suitable for tetracycline (TC) degradation. At 30 °C, a severe degradation of TC by Fe(III)-Cit occurred as early as after 3 days of incubation in the light, and after 5 days in the dark. In contrast, the degradation of TC by Fe(III)-EDTA proceeded very slowly in the dark. By the fifth day of incubation of TC with Fe(III)-Cit in darkness, the concentrations of the former compound dropped by 55% and 75%, at 20 °C and 30 °C, respectively. The decrease in tetracycline concentrations caused by Fe(III)-EDTA in darkness at the same temperatures was only 2% and 6%, respectively. Light increased the degradation rates of TC by Fe(III)-EDTA to 20% and 56% at 20 °C and 30 °C, respectively. The key role of the light in the degradation of tetracycline by Fe(III)-EDTA was thus demonstrated. The TC degradation reaction showed a second-order kinetics. The rate constants of Fe(III)-Cit-induced TC degradation at 20 °C and 30 °C in darkness were k = 4238 M−1day−1 and k = 11,330 M−1day−1, respectively, while for Fe(III)-EDTA were 55 M−1day−1 and 226 M−1day−1. In light, these constants were k = 15,440 M−1day−1 and k = 40,270 M−1day−1 for Fe(III)-Cit and k = 1012 M−1day−1 and 2050 M−1day−1 at 20 °C and 30 °C; respectively. A possible reason for the higher TC degradation rate caused by Fe(III)-Cit can be the result of its lower thermodynamical stability compared with Fe(III)-EDTA, which we confirmed with our quantum chemistry calculations. Two quantum chemistry calculations showed that the iron complex with EDTA is more stable (the free energy of the ensemble is 15.8 kcal/mol lower) than the iron complex with Cit; hence, Fe release from Fe(III)-EDTA is less effective.
Accelerating the Discovery of Rare Materials with Bounded Optimization Techniques

Discovering a rare material within a vast search space exhibits a Needle-in-a-1 Haystack challenge. This challenge of finding a rare material, i.e. , the "needle", 2 inside a vast search space, i.e. , the "haystack", arises when there is an extreme 3 imbalance of optimum conditions relative to the size of the search space. For ex-4 ample, only 0 . 82% out of 146 k total materials in the open-access Materials Project 5 database have a negative Poisson’s ratio, a rare material property. However, current 6 state-of-the-art optimization algorithms are not designed with the capabilities to 7 find solutions to these challenging multidimensional Needle-in-a-Haystack prob-8 lems, resulting in slow convergence to a global optimum or pigeonholing into a 9 local minimum. In this paper, we present a Zooming Memory-Based Initialization 10 algorithm, entitled ZoMBI, that builds on conventional Bayesian optimization 11 principles to quickly and efficiently optimize Needle-in-a-Haystack problems in 12 both less time and fewer experiments by addressing the common convergence 13 and pigeonholing issues. ZoMBI actively extracts knowledge from the previously 14 best performing evaluated experiments to iteratively zoom in the sampling search 15 bounds towards the global optimum "needle" and then prunes the memory of 16 low-performing historical experiments to accelerate compute times by reducing 17 the algorithm time complexity from O ( n 3 ) to O (1) , as the number of experiments 18 sampled increases. Additionally, ZoMBI implements two custom acquisition func-19 tions that use active learning to further guide the sampling of new experiments 20 towards the global optimum. We validate the algorithm’s performance on two 21 real-world 5-dimensional Needle-in-a-Haystack material property optimization 22 datasets: discovery of auxetic Poisson’s ratio materials and discovery of high ther-23 moelectric figure of merit materials. The ZoMBI algorithm demonstrates compute 24 time speed-ups of 400x compared to traditional Bayesian optimization as well as 25 efficiently discovering materials in under 100
A NEW SYNTHETIC METHOD FOR STREAM TEARING IN PROCESS SYSTEMS ANALYSIS

A straightforward heuristic-oriented method for stream tearing is proposed in this work. It does not use the traditional methods of evolutionary process-cycle analysis. First, an edge (stream) weighted spanning-tree is constructed from the process graph using weights based on the ‘in’ and ‘out’ degrees of the process digraph vertices. Second, a directed acyclic graph (DAG) is constructed such that it is the maximum edge (stream) acyclic sub-set of the process digraph. The DAG is constructed by adding (‘put-back’), where possible, directed edges (streams) not already in the spanning-tree. A hierachial ordering based on the same preferential weighting system as the spanning-tree determines the sequence of the ‘put-back’ trials. The remaining edges which cannot be ‘put-back’ into the DAG form a tear set. The weighting system used formed a minimal cardinality tear set in all of the examples tested. Pre-partitioning of the network into strongly connected components is not required and a node computational orde.
The asymptopia of quasi-local mass and momentum. I. General formalism and stationary spacetimes

The quasi-local measures of mass and momentum introduced by Hawking, Ludvigsen and Vickers and Penrose are calculated for spheres near null infinity. Asymptotic expansion for the connection of an Einstein-Maxwell spacetime are obtained and an expansion of the 2-surface twistor equations is developed. Exact solutions are obtained for stationary spacetimes. For such spacetimes, unphysical contributions to the quasi-local mass found in the Hawking and Ludvigsen-Vickers definitions are eliminated in the twistor construction at the orders considered. In the twistor approach the total angular momentum contributes to the effective vacuum energy density and the absolutely conserved quantities associated with the Maxwell field contribute to the field momentum densities. The angular momentum twistor is found to have the required hermiticity properties with a particular choice of the twistor norm.
Scatter correction for cone-beam computed tomography using simulated object models

Scattered radiation is a major source of artifacts in flat detector based cone-beam computed tomography. In this paper, a novel software-based method for retrospective scatter correction is described and evaluated. The method is based on approximation of the imaged object by a simple geometric model (e.g., a homogeneous water-like ellipsoid) that is estimated from the set of acquired projections. This is achieved by utilizing a numerical optimization procedure to determine the model parameters for which there is maximum correspondence between the measured projections and the projections of the model. Monte-Carlo simulations of this model are used for calculation of scatter estimates for the acquired projections. Finally, using the scatter-corrected projections, tomographic reconstruction is conducted by means of cone-beam filtered back-projection. The correction method is evaluated using simulated and experimentally acquired projection data sets of geometric and physical head phantoms. It is found that the method is able to accurately estimate mean scatter levels in X-ray projections, allowing to significantly reduce scatter-caused artifacts in 3D reconstructed images.
Transcriptome Analysis and Identification of Chemosensory Genes in Baryscapus dioryctriae (Hymenoptera: Eulophidae)

Simple Summary The parasitic wasp Baryscapus dioryctriae (Hymenoptera: Eulophidae) was originally discovered in the pupae of Dioryctria insects. It can also parasitize many Pyralidae pests, such as Ostrinia furnacalis, Chilo suppressalis and Galleria mellonella, suggesting that this parasitic wasp has a great potential to serve as a natural enemy against agricultural and forest insect pests. The olfactory system plays an important role in this wasps’ reception of chemical signals emitted from their surrounding environment, and various chemosensory genes are involved in this system. In this study, seven chemosensory gene families, namely, the odorant-binding proteins (OBPs), chemosensory proteins (CSPs), Niemann–Pick type C2 proteins (NPC2s), odorant receptors (ORs), ionotropic receptors (IRs), gustatory receptors (GRs) and sensory neuron membrane proteins (SNMPs) of B. dioryctriae were identified and analyzed using transcriptome sequencing and bioinformatic analyses. Moreover, the quantitative expression of the candidate chemosensory genes, which are female antennae- and ovipositor-biased expression was validated by RT-qPCR. These results lay a molecular foundation for further investigation of the mechanism of chemoreception by the olfactory system during host recognition, location, and oviposition site selection in B. dioryctriae. Abstract Baryscapus dioryctriae is a pupal endoparasitoid of many Pyralidae pests and has been used as a biocontrol agent against insect pests that heavily damage the cone and seed of the Korean pine. The olfactory system of wasps plays an essential role in sensing the chemical signals during their foraging, mating, host location, etc., and the chemosensory genes are involved in detecting and transducing these signals. Many chemosensory genes have been identified from the antennae of Hymenoptera; however, there are few reports on the chemosensory genes of Eulophidae wasps. In this study, the transcriptome databases based on ten different tissues of B. dioryctriae were first constructed, and 274 putative chemosensory genes, consisting of 27 OBPs, 9 CSPs, 3 NPC2s, 155 ORs, 49 GRs, 23 IRs and 8 SNMPs genes, were identified based on the transcriptomes and manual annotation. Phylogenetic trees of the chemosensory genes were constructed to investigate the orthologs between B. dioryctriae and other insect species. Additionally, twenty-eight chemosensory genes showed female antennae- and ovipositor-biased expression, which was validated by RT-qPCR. These findings not only built a molecular basis for further research on the processes of chemosensory perception in B. dioryctriae, but also enriched the identification of chemosensory genes from various tissues of Eulophidae wasps.
RECIPE FOR THE GLOBAL PLATE: POLICY RECOMMENDATION TO GLOBALISE INDONESIAN CULINARY ARTS

Low Indonesian culinary exports indicate that Indonesian cuisine is not well-known internationally. Culinary promotes national identity, multiethnic cultures, and tourism. On the other hand, tourism exposes local culinary practices and can become a country's international brand. Furthermore, culinary relevance to public diplomacy is recognized. Through these connections, Indonesia can utilize gastro diplomacy to capture the global culinary arts market. Indonesia can learn from Thailand and South Korea how to implement the program more effectively by using the policy transfer framework. Thailand programs addressed various elements that must be developed when opening an overseas culinary arts business. They involved governmental and non-governmental agencies because the programs are board. The South Korean program was more formalized than the Thai programs by enacting a specific law and establishing a distinct organization to oversee the program’s execution. In addition to the healthy image of South Korean cuisine and the global trend toward healthier lifestyles, South Korea's program rode the Korean pop culture wave, which set the stage for the success of the program. Based on the analysis, the recommended model for Indonesia’s program implementation consists of six components in terms of menu and target diners, regulation, responsible organizations and coordination, goals, financing sources, and personnel.
Utilizing Human Feedback for Primitive Optimization in Wheelchair Tennis

Agile robotics presents a difficult challenge with robots moving at high speeds requiring precise and low-latency sensing and control. Creating agile motion that accomplishes the task at hand while being safe to execute is a key requirement for agile robots to gain human trust. This requires designing new approaches that are flexible and maintain knowledge over world constraints. In this paper, we consider the problem of building a flexible and adaptive controller for a challenging agile mobile manipulation task of hitting ground strokes on a wheelchair tennis robot. We propose and evaluate an extension to work done on learning striking behaviors using a probabilistic movement primitive (ProMP) framework by (1) demonstrating the safe execution of learned primitives on an agile mobile manipulator setup, and (2) proposing an online primitive refinement procedure that utilizes evaluative feedback from humans on the executed trajectories.
CLOSED SUBMODULES OF NORMALIZING BIMODULES OVER SEMIPRIME RINGS

In this paper we study closed sub-bimodules of normalizing bimodules over semiprime rings. We extend the main results which are known for centred bimodules and several other results which are new even for centred bimodules are also obtained. In particular, we prove that the theorem on one-to-one correspondence between closed submodules obtained in former papers for centred bimodules is also true for normalizing bimodules. Finally, we give some applications of the main results. *Partially supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brazil).
Progress on Thin Film Freezing Technology for Dry Powder Inhalation Formulations

The surface drying process is an important technology in the pharmaceutical, biomedical, and food industries. The final stage of formulation development (i.e., the drying process) faces several challenges, and overall mastering depends on the end step. The advent of new emerging technologies paved the way for commercialization. Thin film freezing (TFF) is a new emerging freeze-drying technique available for various treatment modalities in drug delivery. TFF has now been used for the commercialization of pharmaceuticals, food, and biopharmaceutical products. The present review highlights the fundamentals of TFF along with modulated techniques used for drying pharmaceuticals and biopharmaceuticals. Furthermore, we have covered various therapeutic applications of TFF technology in the development of nanoformulations, dry powder for inhalations and vaccines. TFF holds promise in delivering therapeutics for lung diseases such as fungal infection, bacterial infection, lung dysfunction, and pneumonia.
Tensions Between the Proxies of Human Values in AI

Motivated by mitigating potentially harmful impacts of technologies, the AI community has formulated and accepted mathematical definitions for certain pillars of accountability: e.g. privacy, fairness, and model transparency. Yet, we argue this is fundamentally misguided because these definitions are imperfect, siloed constructions of the human values they hope to proxy, while giving the guise that those values are sufficiently embedded in our technologies. Under popularized methods, tensions arise when practitioners attempt to achieve each pillar of fairness, privacy, and transparency in isolation or simultaneously. In this position paper, we push for redirection. We argue that the AI community needs to consider all the consequences of choosing certain formulations of these pillars-not just the technical incompatibilities, but also the effects within the context of deployment. We point towards sociotechnical research for frameworks for the latter, but push for broader efforts into implementing these in practice.
The strength of submicron-sized materials

Recent rapid advancements in nano- and micro-machinery technologies call for an urgent need to understand the mechanical behaviour of materials of dimensions in the sub-micron regime. The initial yield strength of submicron crystals exhibits remarkable statistical scatter as well as dependence upon size and time under load. Submicron-sized materials are also found to creep many orders of magnitude faster than bulk counterparts. In this paper, the recent experimental evidence for these phenomena is reviewed. Theoretical explanation of these phenomena is also discussed. The statistical scatter and time dependence of the yield strength are interpreted by a scaling model derived from atomistic simulations. The results indicate that, within a certain load range, the strength of a sub-micron sized material is not deterministic and can only be described by a survival probability. The much faster creep in the submicron regime is interpreted in terms of the much shorter diffusion length compared to bulk creep.
A perturbation model of radiometric manifestations of oceanic currents

Extracting quantitative oceanographic information from microwave images of the ocean surface requires a physical understanding and an efficient mathematical model of surface wave interaction with currents. In this paper, we consider “weak” currents (with velocities up to a few tens of centimeters per second) and discuss a perturbation approach that leads to numerically efficient models of surface roughness modulation by the current fields with arbitrary dependence on horizontal coordinates and time. With the wave‐atmosphere interaction being described within the relaxation approximation, closed‐form analytic expressions are obtained for surface roughness modulation. The hydrodynamic theory is combined with an electromagnetic model based on the small‐slope approximation to simulate microwave emission from the ocean surface. Analysis of the theoretical results demonstrates that the physics of surface wave interaction with time‐dependent currents, which are inhomogeneous in two spatial dimensions, is more rich and complex than is suggested by the one‐dimensional models considered theoretically in the past. Of particular interest for remote sensing is the finding that realistic two‐dimensionally inhomogeneous currents, unlike their one‐dimensional models, can produce perturbations in microwave brightness temperature that extend well beyond the current field itself. Our model suggests that microwave brightness temperature measurements should be a sensitive tool of observing and quantitatively evaluating surface currents in the ocean.