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Monitoring cattle feed intake is crucial for evaluating animal health, productivity, and farm profitability. In particular, an abnormal intake is related to the cattle activity. Therefore, outlier detection forms the basis for intake monitoring. This study employed multiple algorithms ranging from statistics to deep learning to detect outliers in time-series data of cattle intake. We used five models implementing mean + standard deviation, moving average, box plot, time series decomposition, and autoencoder, and attempted to enhance the detection performance by a voting system to combine more than one model. Both box plot and time-series decomposition demonstrated high accuracy (over 95 %) and F1-score (harmonic mean of precision and recall). Thus, it reliably distinguished normal values from outliers. Moving average exhibited a high true-skill statistic (TSS), thereby rendering it suitable for outlier detection. The voting system gave F1 and TSS scores of 0.49 and 0.65, respectively. Thus, it enhanced the detection performance compared with the individual model. These results demonstrate that the performance metrics vary depending on the type of algorithm. This, in turn, highlights the need to select algorithms adapted to the monitoring objectives. The algorithmic selection can be complemented by a voting system. This demonstrates its potential for generating a reliable database with accurate outlier detection and aiding decision-making by livestock producers.

Abstract The western conifer seed bug (WCSB) Leptoglossus occidentalis (Heidemann) (Heteroptera: Coreidae) is a pest insect that causes significant losses of coniferous trees worldwide. In this study, we sought to project the potential distribution of the WCSB based on dual CLIMEX modeling and random forest (RF) analysis to obtain basic data for WCSB monitoring strategies. The CLIMEX model, a semimechanistic niche model that responds to climate‐based environmental parameters, is a species distribution model that focuses on regional climatic suitability. Given that this model can be used to select areas that are likely to reflect the climatically favorable spread of species, which we initially used CLIMEX to evaluate the potential distribution of the WCSB. The RF algorithm was used to predict the potential occurrence of WCSB and to evaluate the relative importance of environmental variables for WCSB occurrence. Using the RF model, land cover was found to be the most important variable for classifying the presence/pseudo‐absence of the WCSB, with an accuracy of 77.1%. Climatic suitability for the WCSB was predicted to be 2.4‐fold higher in Southern Europe than in Western Europe, and the WCSB was predicted to occur primarily near coniferous forests. Given that CLIMEX and RF analyses yielded different prediction results, using the findings of both models may compensate for the shortcomings of these models when used independently. Consequently, to ensure greater prediction reliability, we believe that it would be beneficial to base predictions on the combined potential distribution data obtained using both modeling approaches.

The tropical fire ant (TFA, Solenopsis geminata) is an aggressive fire ant species that can cause health problems in humans and damages ecosystems. The TFA can be found across the world, from North and South America to Africa, Asia, and Oceania; furthermore, it has been introduced into new areas by human transport or natural flights. In this study, species distribution modeling was applied to the TFA for the first time, and its potential distribution as a response to climate change was evaluated. This study used CLIMEX as the climate-specific species distribution modeling tool with the distribution data for TFA, current global meteorological data, and two types of climate change scenarios. Thus, although the climatic suitability of the TFA was assumed to decrease with climate change, its distribution limit was expected to increase. In addition, the difference between potential distributions predicted using Special Report on Emissions Scenarios A1B and Special Report on Emissions Scenarios A2 increased over time. In conclusion, even with an overall decrease in climatic suitability, in the future, the TFA will still be able to invade a new area that it cannot inhabit under the current climatic scenario. As the first study that predicts TFA distribution using a species distribution model, we expect that this study will provide the basic information for further TFA modeling and for setting up quarantine and control measures.

Climate has been used as a main variable in species distribution model, suggesting that the type of meteorological data can affect the predictive range of a target species. This study was to investigate the effect of meteorological data on the prediction of the potential distribution of a species in the CLIMEX model. We constructed three different types of meteorological data to be inserted into the CLIMEX model to predict the climatic suitability of the spotted lanternfly [Lycorma delicatula (Hemiptera: Fulgoridae)] in South Korea: (1) minimum–maximum data (Y-data), (2) annual average data (AY-data), and (3) 30-year long-term average data (A-data). As a result, the climatic suitability represented by the Ecoclimatic Index (EI) was significantly different in the Y-data compared with the other data sets because of the extreme winter condition in which they were recorded. In contrast, the AY- and A-data sets showed similar climatic suitability, but the AY-data showed slightly higher Ecoclimatic Index values than the A-data. It is conclusive that the AY- and A-data sets were suitable for evaluating annual variations by the years of data collection and current potential distribution, respectively, whereas the Y-data could be used for simulation under extreme climate conditions for a conservative assessment. Keywords: Climatic suitability, CLIMEX, Meteorological data, Potential distribution

We herein report manufacturing of dental crowns made of 5-mol% yttria partially stabilized zirconia (5Y-PSZ) with desired mechanical properties, optical translucency and dimensional accuracy using digital light processing (DLP). To this end, all processing parameters were carefully controlled and optimized. First, 5Y-PSZ particles with a bimodal distribution were prepared via calcination of as-received granules and subsequent ball-milling and then used to formulate 5Y-PSZ suspensions with a high solid loading of 50 vol% required for high densification after sintering. Dispersant content was also optimized. To provide high dimensional accuracy, initial dimensions of dental crowns for 3D printing were precisely determined by considering increase and decrease in dimensions during photopolymerization and sintering, respectively. Photopolymerization time was also optimized for a given layer thickness of 50 μm to ensure good bonding between layers. A multi-step debinding schedule with a slow heating rate was employed to avoid formation of any defects. After sintering at 1500 °C for 2 h, 5Y-PSZ could be almost fully densified without noticeable defects within layers and at interfaces between layers. They had high relative densities (99.03 ± 0.39%) with a high cubic phase content (59.1%). These characteristics allowed for achievement of reasonably high mechanical properties (flexural strength = 625.4 ± 75.5 MPa and Weibull modulus = 7.9) and % transmittance (31.4 ± 0.7%). In addition, 5Y-PSZ dental crowns showed excellent dimensional accuracy (root mean square (RMS) for marginal discrepancy = 44.4 ± 10.8 μm and RMS for internal gap = 22.8 ± 1.6 μm) evaluated by the 3D scanning technique.

Recent advances in species distribution models (SDMs) associated with artificial intelligence (AI) and increased volumes of available data for model variables have allowed reliable evaluation of the potential distribution of any species. A reliable SDM requires suitable occurrence records and variables with optimal model structures. In this study, we developed three different machine learning-based SDMs [MaxEnt, random forest (RF), and multi-layer perceptron (MLP)] to predict the global potential distribution of two invasive ants under current and future climates. These SDMs showed that the potential distribution of Solenopsis invicta would be expanded by climatic change, whereas it would not significantly change for Anoplolepis gracilipes. The models were compared using model performance metrics, and the optimal model structure and spatial projection were selected. The MaxEnt exhibited high performance, while the MLP model exhibited low performance, with the largest variation by climate change. Random forest showed the smallest potential distribution area, but it was robust considering the number of occurrence records and changes in model variables. All the models showed reliable performance, but the difference in performance and projection size suggested that optimal model selection based on data availability, model variables, study objectives, or an ensemble approach was necessary to develop a comprehensive SDM to minimize modeling uncertainty. We expect that this study will help with the use of AI-based SDMs for the evaluation and risk assessment of invasive ant species.

The spongy moth (Lymantria dispar) is a forest pest that damages a variety of trees in North America and Eurasia. A spongy moth outbreak occurred in part of South Korea in 2020 and caused severe damage to domestic forests and human society. Since the occurrence of spongy moths is influenced by climatic factors, this study examines the causes of spongy moth outbreaks by analyzing the temporal and spatial differences in climatic factors, influencing spongy moth occurrence using specimens collected during field surveys. Climatic factors were identified using global occurrence coordinates to compare the weather characteristics of spongy moth occurrence in domestic regions, using the kernel density function. Spatial and temporal comparisons were performed for monthly weather factors obtained from field surveys in 2020 and 2021 in areas with high and low spongy moth larvae densities. Spongy moth outbreaks may result from particular combinations of variable seasonality in temperature and precipitation, including high temperatures during cold periods and low precipitation during developmental periods.

Ganglioside GM3 is known as an inhibition factor of cell differentiation and proliferation via inhibition of epidermal growth factor receptor (EGFR) phosphorylation. Our previous study showed that the exogenous ganglioside GM3 reduced the meiotic maturation of porcine oocytes and induced apoptosis at 44 h of in vitro maturation (IVM). However, the role of ganglioside GM3 in the relationship between EGFR signaling and apoptosis during porcine oocyte maturation has not yet been studied. First, porcine cumulus-oocyte complexes (COCs) were cultured in the NCSU-23 medium with exogenous ganglioside GM3 according to maturation periods (non-treated, only IVM I: 0 - 22 h, only IVM II: 22 - 44 h and IVM I & II: 0 - 44 h). We confirmed that the proportion of germinal vesicle breakdown (GVBD) increased significantly in the IVM I treated group than in the control group. We also confirmed that the meiotic maturation until M II stage and polar body formation decreased significantly in the only IVM I treated group. Cumulus cell expansion and mRNA levels of the expansion-related factors (HAS2, TNFAIP6 and PTX3) decreased significantly in the IVM I treated group than in the control group. Protein levels of EGFR, p-EGFR, ERK1/2, and p-ERK1/2 decreased significantly in the GM3-treated groups, during the IVM I period. In addition, cellular apoptosis, determined using TUNEL assay, and protein levels of Cleaved caspase 3, were increased significantly in the GM3-treated COCs during the IVM I period. Based on these results, ganglioside GM3 exposure of porcine COCs during the IVM I period reduced meiotic maturation and cumulus cell expansion via inhibition of EGFR activity in pigs.

Background: Changes in dietary patterns have led to a decrease in rice consumption, raising demands for the cultivation of alternative crops that meet the current requirements. Potatoes are highly productive and can be stored for a relatively long period, thereby ensuring adequate income for farmers; however, optimal cultivation is necessary to maximize yield. Objective: This study proposes optimal cultivation regions for potato considering climate and soil conditions. Materials and methods: The CLIMEX model was developed to evaluate climatic suitability, while the soil suitability was scored based on five soil characteristics. The final areal suitability for potato cultivation was classified into 4 levels: very suitable, suitable, marginal, and unsuitable. Results: Overall, 36.5% of South Korea had very suitable climate, but areas with the best values for soil conditions were approximately 10% of the climatically suitable areas. When considering the climate and soil conditions simultaneously, climatic suitability and soil condition were inversely related, resulting in only 1.2% of optimal areas with Jeju Island as the most suitable area. Conclusions: Because both climate and soil conditions need to be suitable for growing crops, this study can provide potential paddy-cultivation areas for potato cultivation and a method for evaluating suitable areas for crop cultivation.

The yellow crazy ant (Anoplolepis gracilipes) has destroyed local ecosystems in numerous countries, and their population sizes and distribution are likely to increase under global warming. To evaluate the risk of invasion by yellow crazy ant in South Korea, this study identified their potential habitats and predicted their future global distribution by modeling various climate change scenarios using CLIMEX software. Our modeling predicted that future climate conditions in South Korea will be favorable for the yellow crazy ant, and they could invade by the mid-21st century. We highlight the use of predictive algorithms to establish geographical areas with a high risk of yellow crazy ant invasion under Representative Concentration Pathways (RCP) 8.5 climate scenarios. Keywords: Anoplolepis gracilipes, climate change scenario, CLIMEX, invasive species, yellow crazy ant

Lycorma delicatula is one of the major invasive pests of Korea. Careful monitoring is required to protect domestic agriculture as this pest causes severe damage to agricultural crops, such as wilting and sooty mold. This study was designed to confirm the potential distribution of L. delicatula using the modeling software CLIMEX and to suggest fundamental data for preventing agricultural damage by L. delicatula. Our results show that Korean weather seems to be adequate for L. delicatula habitation, indicating that approximately 60% of areas examined have a very high possibility of potential distribution. Particularly, we showed that Gyeongsang-do and Jeonla-do, which have not yet been invaded by L. delicatula, were very suitable locations for its growth. Therefore, although it is necessary to set up feasible strategies for preventing further L. delicatula invasions, subsequent studies are needed for assessing other invasive species considering the impact of future climate change. Keywords: CLIMEX software, invasive pest, Lycorma delicatula, potential distribution

In this study, functional particles such as piezoelectric (PZT) ceramic and shape memory alloy (SMA) particles have been incorporated in composite laminates to accelerate the loss of vibration energy. PZT ceramic particles and SMA particles are mixed with epoxy resin and rolled into a film shape before they are interleaved between prepreg plies for better distribution of the particles. Loss factor (tan δ) was measured with various particle loadings to verify the effectiveness of interleaving in the vibration damping of laminate specimens. It was observed that there existed an optimal content for maximizing the damping ability avoiding an aggregation of the particles. In addition, when PZT and SMA particles are applied simultaneously, PZT could enhance the vibration damping capability of SMA because PZT particles could generate thermal energy, and it would accelerate the phase change of the SMA particles. In this research, the effective way for enhancing the particle dispersion was suggested, and the particle loading could be controlled by finding an optimal content. Flexural moduli of the specimens were also measured, and they exhibited no change as the content of the particles increases. Therefore, dispersed particles used in this study increased the vibration damping capacity without reducing the mechanical properties.

Climate change has caused various environmental and ecological problems worldwide, as well as triggered invasions by alien insects that cause damage to the local ecology and agriculture. Metcalfa pruinosa has caused significant damage to agriculture and human life and South Korea is no exception. This species is spreading rapidly in South Korea and causing persistent damage with the change in climate; thus, there is an urgent need for effective monitoring of the potential distribution of this species. This study aimed to predict the potential distribution of M. pruinosa in response to climate change. CLIMEX software, specialized software for predicting species distribution, was used to evaluate the future distribution pattern of M. pruinosa by combining biological information and climatic conditions. According to our simulation, the distribution of M. pruinosa has expanded on a national scale; however, its invasion will decrease with the current trend in climate change.

Ganglioside GD1a is specifically formed by the addition of sialic acid to ganglioside GM1a by ST3 β- galactoside α -2,3-sialyltransferase 2 (ST3GAL2). Above all, GD1a are known to be related with the functional regulation of several growth factor receptors, including activation and dimerization of epidermal growth factor receptor (EGFR) in tumor cells. The activity of EGF and EGFR is known to be a very important factor for meiotic and cytoplasmic maturation during in vitro maturation (IVM) of mammalian oocytes. However, the role of gangliosides GD1a for EGFR-related signaling pathways in porcine oocyte is not yet clearly understood. Here, we investigated that the effect of ST3GAL2 as synthesizing enzyme GD1a for EGFR activation and phosphorylation during meiotic maturation. To investigate the expression of ST3GAL2 according to the EGF treatment (0, 10 and 50 ng/ml), we observed the patterns of ST3GAL2 genes expression by immunofluorescence staining in denuded oocyte (DO) and cumulus cell-oocyte-complex (COC) during IVM process (22 and 44 h), respectively. Expression levels of ST3GAL2 significantly decreased (p

Abstract Osteoporosis is one of the most common skeletal disorders caused by the imbalance between bone formation and resorption, resulting in quantitative loss of bone tissue. Since stem cell‐derived extracellular vesicles (EVs) are growing attention as novel cell‐free therapeutics that have advantages over parental stem cells, the therapeutic effects of EVs from adipose tissue‐derived stem cells (ASC‐EVs) on osteoporosis pathogenesis were investigated. ASC‐EVs were isolated by a multi‐filtration system based on the tangential flow filtration (TFF) system and characterized using transmission electron microscopy, dynamic light scattering, zeta potential, flow cytometry, cytokine arrays, and enzyme‐linked immunosorbent assay. EVs are rich in growth factors and cytokines related to bone metabolism and mesenchymal stem cell (MSC) migration. In particular, osteoprotegerin (OPG), a natural inhibitor of receptor activator of nuclear factor‐κB ligand (RANKL), was highly enriched in ASC‐EVs. We found that the intravenous administration of ASC‐EVs attenuated bone loss in osteoporosis mice. Also, ASC‐EVs significantly inhibited osteoclast differentiation of macrophages and promoted the migration of bone marrow‐derived MSCs (BM‐MSCs). However, OPG‐depleted ASC‐EVs did not show anti‐osteoclastogenesis effects, demonstrating that OPG is critical for the therapeutic effects of ASC‐EVs. Additionally, small RNA sequencing data were analysed to identify miRNA candidates related to anti‐osteoporosis effects. miR‐21‐5p in ASC‐EVs inhibited osteoclast differentiation through Acvr2a down‐regulation. Also, let‐7b‐5p in ASC‐EVs significantly reduced the expression of genes related to osteoclastogenesis. Finally, ASC‐EVs reached the bone tissue after they were injected intravenously, and they remained longer. OPG, miR‐21‐5p, and let‐7b‐5p in ASC‐EVs inhibit osteoclast differentiation and reduce gene expression related to bone resorption, suggesting that ASC‐EVs are highly promising as cell‐free therapeutic agents for osteoporosis treatment.

Background To date, many methods have been proposed to resolve the sunken eyelid. We treated our clinical cases of sunken upper eyelid based on whether there is a concurrent presence of the dermatochalasis or blepharoptosis and then performed the autologous fat grafting using either closed or open technique. Methods According to the classification of the patients, we used the following injection techniques: First, we solely performed the autologous fat grafting using the closed technique in the sunken upper eyelid only group, for which we did the injection using a micro-injector cannula on the suborbicularis plane. Second, we performed such procedures as skin excision, orbicularis oculi muscle strip excision and levator aponeurosis advancement to manage each symptom in the sunken upper eyelid with dermatochalasis or blepharoptosis group. Simultaneously, we also made a small window in the lateral portion of the orbital septum using the open technique with metzenbaum scissors. Thus, we performed the intraseptal injection of the autologous fat. Results During a period ranging from January of 2012 to April of 2014, we treated a total of 53 patients. The patients were followed up during a mean period of four months. Thus, we obtained satisfactory treatment outcomes without notable complications. Conclusions In conclusion, our results indicate not only that surgeons should consider the fat grafting as one of eyelid-surgery procedures but also that they should perform it concurrently with blepharoplasty or blepharoptosis correction for the purposes of obtaining good treatment outcomes.