The exploration of dominant spoilage bacteria in blue mussels (Mytilus edulis) stored under different modified atmospheres by MALDI-TOF MS in combination with 16S rRNA sequencing

Few studies have addressed species-level identification of spoilage bacteria in blue mussels packed under modified atmospheres (MAs). We investigated the effect of MAs and seasons on the tentative species-level of dominant spoilage bacteria in blue mussels. Summer (s) and winter (w) blue mussels were stored at 4 °C in the atmospheres (CO2/O2/N2): A40s (30/40/30), B60s (40/60/0), C60s (0/60/40), A40w (30/40/30), and D75w (25/75/0). In total, 122 culturable isolates were obtained at the final stage of shelf life, when mortality was high (56–100) and total psychrotrophic bacteria counted >7 log CFU g−1. Biochemical properties were analyzed using gram reactions, catalase and oxidase activities, and salt tolerance tests. Culturable isolates were identified through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and 16 S rRNA gene sequence analysis. Spoilage potential tests were investigated by evaluating protease, lipase, and fermentation activities as well as gas and H2S production. The culturable isolates showed tolerance to varied salt concentrations. Psychromonas arctica, Pseudoalteromonas elyakovii, and Shewanella frigidimarina were dominating in specific MAs. Winter blue mussels resulted in a higher variation of spoilage bacteria, including S. frigidimarina, S. vesiculosa, S. polaris, Micrococcus luteus, Paeniglutamicibacter terrestris sp. nov., and Alteromonas sp. © 2023 Elsevier Lt

Local Community Readiness to Implement Smart Tourism Destination in Yogyakarta, Indonesia

Local economic development for relatively long period of time. Tourism also allows rapid recovery of local economy after COVID-19 outbreak. Amongst different kinds of approaches for tourism development, smart tourism destination (STD) has been widely believed as an excellent approach to rapidly recover tourism sector during post-pandemic. STD concept also allows improvement of adaptive capacity that is critical to anticipate any future disturbances including the unpredicted ones. However, a question remains regarding the readiness of local communities for implementing STD. Therefore, this research aims to address this gap by examining the readiness of managers of community-based tourism in the Special Region of Yogyakarta province, Indonesia. An online survey was conducted to collect data from various community-based tourism destinations located in this region. Data were analyzed using descriptive statistics to measure the overall readiness of community-based tourism to implement STD. For triangulation purpose, interviews were conducted to complement the online survey. © The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024

Evaluating academic performance and scholarly impact of rectors of indonesia’s public universities: a dual bibliometric and scholastic analysis

This research conducted a combined bibliometric and scholastic analysis for characterizing and assessing rectors’ academic performance and scholarly impact at public universities in Indonesia. This bibliometric study evaluated the academic performance of 82 rectors of public universities in Indonesia from 93 initial candidates, focusing on 2706 data obtained through triangulation of open and verified data sources. The analysis showed male dominance, disparities in scientific productivity, and a tendency toward academic inbreeding. In citation analysis, the supremacy of natural science fields, especially Fisheries, Biology, Physics, and Engineering, becomes clear, showing a wider global impact than Accounting, Sociology, and Medicine. The richness and diversity of scientific areas are reflected in a higher range of citations, highlighting multidisciplinary integration and adaptation in responding to global challenges. These results trigger the need for intervention strategies to increase leadership diversity, scientific productivity, and gender equality in Indonesian public universities

Estimating finger joint angles by surface EMG signal using feature extraction and transformer-based deep learning model

Human-machine interfaces frequently use electromyography (EMG) signals. Based on previous work, feature extraction has a great deal of influence on the performance of EMG pattern recognition. Furthermore, the Deep Learning method is supposed to increase performance and not depend on feature engineering. However, directly processing raw signals will require a higher computation rate. This study proposed a new method that combines feature extraction and Deep Learning to address those issues while improving performance, reducing architecture size, and producing a more representative output. The proposed architecture employs the Transformer model as the backbone to get the correlation between elements and focus on the important information for estimating the flexion-extension of finger joint angles. This study uses experiment three of the NinaPro (Non-Invasive Adaptive Hand Prosthetics) DB5 dataset. Each experiment produces 16 Surface EMG data streams from two Myo Armbands devices representing 22 finger joint angles as output. This study compares the windowing process, feature extraction, execution time, and results with previous studies. The results show that the proposed model outperforms the previous study, from 0.957 in the previous study to become 0.970 in this study for the R-Square score. This result is obtained using 100 data points for the windowing process and Median Frequency for the best feature extraction method. © 202

Long-term conversion of upland to paddy increased SOC content and N availability in a sand dune of Japan

Land use change driven by anthropogenic activities has greatly affected terrestrial C and N cycling; however, it remains unclear how dynamics of soil organic carbon (SOC) and nitrogen (N) availability respond to long-term land use change in sand dunes. Here, we investigated the changes in SOC, total nitrogen (TN), and their aerobic and anaerobic decomposition or mineralization in a vinyl film paddy, compared with dry land use and management changes (LUMCs) (original upland, greenhouse, and agricultural forest (tree area)) in Shonai sand dunes, northeast Japan. The vinyl film paddy had been singly cultivated for 54 years. Soil samples were collected from five soil depths (0�10, 10�20, 20�30, 30�40, 40�50 cm) to compare the effects of depth and LUMC among the four treatments. The C decomposition (Dec-C) was assessed as the aerobic CO2 production and anaerobic methane and CO2 productions. Meanwhile, N mineralization (Min-N) was determined as aerobic NH4+ and NO3� production and anaerobic NH4+ production. The results showed that the vinyl film paddy increased SOC and TN contents, Dec-C and Min-N than upland and greenhouses at 0�30 cm depth but lower levels than the tree area at all depths. The arithmetic mean for all depths showed the aerobic Dec-C in the paddy (216.0 mg kg�1) was higher than the corresponding anaerobic Dec-C (192.8 mg kg�1). Conversely, the aerobic Min-N (35.9 mg kg�1) was lower than the anaerobic Min-N (75.7 mg kg�1). There were significantly positive correlations among SOC, TN, aerobic and anaerobic Dec-C and Min-N, whereas the paddy had steeper slope than other three LUMCs. Conclusively, our results indicated that long-term conversion of upland to vinyl film paddy increased SOC and TN accumulation and N availability (Min-N) in Shonai sand dunes, which can be applied as an effective agricultural practice to improve fertility of coastal sandy soils. © 2023 Elsevier B.V

Related party lending and rural bank risk: Evidence during the Covid-19 period

This study aims to investigate bank lending behaviors during the Covid-19 period and further to examine the effect of related party lending (RPL) on the rural bank risk. We posit there is significant change on the lending growth and related party lending proportion during this period. We utilize 730 rural banks in Indonesia using panel data approach from 2019 to 2022. Utilizing panel data estimations to test the impact of RPL on risk and to further investigate its interaction with the COVID-19 using system GMM, we document that RPL is negatively associated with rural bank risk proxied by loan loss provision as ex-ante credit risk and positively associated with Z-Score as bank default risk. Moreover, the COVID-19 weaken the relationship between related party lending and rural bank risk. These results provide new insight into understanding risk management implementation for minimizing these risks. We also adopt several proxies and a split sample analysis to check for the robustness. Finally, we seek for lesson learned from the crisis and propose some implication for bank and relevant authorities. © 2023 Elsevier B.V

Identification of early flowering mutant gene in Phalaenopsis amabilis (L.) Blume for sgRNA construction in CRISPR/Cas9 genome editing system

Phalaenopsis amabilis (L.) Blume commonly called Moth Orchid (Orchidaceae) is a natural orchid species designated as the National Flower of Indonesia for its beautiful flower shape and long-lasting flowering period. Basically, P. amabilis has a long vegetative phase that cause late flowering, about 2 to 3 years for flowering, hence a method to shorten vegetative period is desired. The latest technological approach that can be used to accelerate flowering of P. amabilis is the CRISPR/Cas9 genome editing method to inactivate the GAI (Gibberellic Acid Insensitive) gene as a mutant gene that can accelerate the regulation of FLOWERING TIME (FT) genes flowering biosynthesis pathway. The approach that needs to be taken is to silence the GAI gene with a knockout system which begins with identifying and characterizing the GAI target gene in the P. amabilis which will be used as a single guide RNA. CRISPR/Cas9 mediated knockout efficiency is highly dependent on the properties of the sgRNA used. SgRNA consists of a target sequence, determining its specificity performance. We executed phylogenetic clustering for the PaGAI protein with closely related orchid species such as Dendrobium capra, Dendrobium cultivars and Cymbidium sinensis. SWISS-Model as tool webserver for protein structure homology modeling. Results show that P. amabilis has a specific domain with the occurrence of point mutations in the two conservative domains. Therefore, a single guide RNA reconstruction needs to be implemented. © 2024, Instituto Internacional de Ecologia. All rights reserved

Model Deteksi COVID-19 dari Citra CT Scan Dada Menggunakan DenseNet-121

The primary diagnosis of COVID-19 is the RT-PCR test, but it was found that RT-PCR has the disadvantage of low sensitivity in the early phase of infection. Chest CT has the advantage of higher sensitivity in the early phase of infection compared to RT-PCR, so it can be used as a complement to the RT-PCR test to help reduce the spread of COVID-19 due to false negative results. To help medical personnel, Deep Learning can be used to automate the COVID-19 detection process via chest CT images. In this research, a COVID-19 detection model was built by transfer learning of DenseNet-121. Several variations were done, that is without & with fine tuning, also variations on Learning Rate (LR) which was default LR (0.001) & LR obtained from Learning Rate Finder (0.0001). The model was trained using ReduceLROnPlateau & EarlyStopping callbacks. The dataset used was a dataset made of 3 classes (Normal, Pneumonia, & COVID-19) from COVIDx CT-2A which has gone through an undersampling process & various types of image augmentation. The model performance was then evaluated using various evaluation metrics namely accuracy, sensitivity, precision, & specificity. The best results obtained were from the model with fine tuning & LR obtained from Learning Rate Finder. This model worked well, with an accuracy of 97.64%; precision of 96.49%; sensitivity of 96.43%; & specificity of 98.25%