bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of persimmon (Diospyros kaki L.) as biodiversity originated from Indonesia
Authors: Yuniastuti E , Saputro M A A , Nandariyah  , Delfianti M N I 
Published: July 2021

Abstract
Persimmon (Diospyros kaki L.) belongs to the family Ebenaceae is widely grown in the climate zones range in the world. Persimmon grows well in media rich in organic matter with sufficient water content and generally at an altitude above 1000 masl. It is one type of subtropical fruit plant that is classified as rare in Indonesia. It has the potential to be developed for cultivation. The diversity characteristics of persimmon in each region are represented by the qualitative and quantitative. It may be caused by environmental factors or gene changes. Thus, the lack of environmental factors, plant growth will be disorder and will stop. Temperature is one of the factor affecting photosynthesis and plant metabolism at the cellular level. The difference in the temperatur range can be attributed to variations in latitude, topography, proximity to large bodies of water represented. The research aimed to identify morphological characters of persimmon at Selo District and to determine the level of persimmon diversity based on their morphological characters. The research was conducted in February – May 2020 in Selo Village, Boyolali, Central Java Province. This research used 15 samples of persimmon plant. The observation variable include geographical conditions and plant morphological characteristics (trees, stems, leaves, fruits). The data obtained were presented descriptively. The grouping of elements between samples was carried out by cluster analysis with the UPGMA method using the NTSYS. The results of the cluster analysis were presented in the form of dendogram. The results showed that Selo, persommon had various characters but several observation variables showed uniformity. The persimmon similarity coefficient is 0.66.
The role of dolomite and vermicompost in nutrient uptake and production of sweet potato (Ipomoea batatas L) on acid soil
Authors: Nufus N H , Sabrina T. , Hasanah Y 
Published: July 2021

Abstract
Sweet potato production is limited where it is caused by the lack of nutrients needed by the plant, where most of the sweet potato is planted on acid dry land where liming on the soil is an important activity that is sometimes neglected by farmers. so that the need for the nutrients needed is not fulfilled, so that the production of sweet potatoes is lo, by giving Dolomite and Bio-Vermi can help to increase nutrient uptake and plant production. The purpose of this study was to determine the effectiveness of dolomite and Bio-Vemi in optimizing nutrient absorption in the growth and production of sweet potato (Ipomoea batatas L.). The research was conducted in Aras Kabu Village, Beringi District, Deli Serdang Regency, North Sumatra using a randomized block design (RAK) with two factors and three replications. The first factor is the provision of Dolomite with 3 levels, namely D0 (without dolomite), D1 (1.5 ton/ha) and D2 (3 ton/ha). The second factor is the application of Bio-vermi with 4 levels, namely P0 (without Bio-vermi), P1 (100g/plant), P2 (150g/plant), P3 (200g/plant). The results showed that the application of dolomite and bio-vermi could increase soil pH, plant length growth and the number of yams planted. The highest increase in pH was found in D1 (1.5 ton/ha) of 5.57 and P2 (150g/plant) of 5.53, the longest plant length in P3 treatment (200g/plant) along 64.31 and D2 (3 ton/ha) along 64.27, the highest number of planted yams in treatment P1 (100g/plant) was 5.62. There is a significant interaction with dolomite and biovermi in increasing plant growth and nutrient uptake, with the provision of D1 (1.5 ton/ha) can increase soil pH and organic matter by 1% in acid soils, so that the longest plant length in treatment D1P3 is 69, 33 this proves that by giving Dolomite and Bio-vermi can help nutrient uptake and growth and production of sweet potato in acid soils.
Governance of mangrove restoration and conservation to climate change resilience in Bintan Island
Authors: Akbar D , Mariani  , Yudiatmaja W E , Edison  
Published: July 2021

Abstract
Policy of climate change mitigation and adaptation play an important role to socio-economic aspect. Controlling pollution and degradation of environment in coastal area adapted by capacity initiatives to protect marine environment from pollution and climate change. Climate change distributes micro-plastic to the ocean, including the activity of marine debris, fisheries and marine products industry, and shipping line (oil spill). Industry, agriculture in daily life contributes 80% of marine pollution, in addition, hundreds hectares of mangrove deforestation in Kepulauan Riau caused by development. According to Governmental Law No 19 year 1999 of pollution and damage control of the sea and implementation of The Bali Declaration as an adaptation of the 4th Intergovernmental Review Meeting (IGK4) to the Regional Capacity Canter for Clean Seas (RC3S) in Bali by mainstreaming protection of ocean and coastal ecosystem from the threat of chemical, waste, and micro plastic pollution. Mangrove as one of the best alternative of climate change mitigation divided into several zones, namely zone of core, zone utility and zone sustainability. The goals of this research are mapping the destruction factors and rehabilitation efforts, and also to know the interconnected key stakeholders on conserve mangrove and community based ecological mangrove restoration. Restoration and conservation of Mangrove in Kepulauan Riau, especially in Bintan and Batam, to the management of sustainable coastal through the method of Mangrove Restoration Opportunity Evaluation in collaboration between regional government, private sector, civil society, and expert. In recommendation, according to the program of Agency of Peat and Mangrove Restoration (BRGM) of Presidential Decree No 120/2020 by planting, survey, utility and other researches, mangrove sustainability needs consideration of the legality area and common analysis of Ministry and Provincial Government to avoid misunderstanding of taking action between conserve and build, and also taking further action of RZWP3K in Kepulauan Riau.
Snail mucus suppresses anti dsDNA antibodies in lupus mice
Authors: Nurudhin A , Prabowo N A , Ramadhani A 
Published: July 2021

Abstract
Lupus is closely related to weather changes. Changes in extreme weather due to climate changes can trigger lupus flares and cause death. Therefore, many studies are trying to find a drug that can cure lupus. Snail mucus has the properties of suppressing the immune system. The aim of this study is to see how snail mucus affects the levels of anti-dsDNA antibodies in lupus model mice. Experimental study uses a posttest-only group design. The control group was mice with 0.5 cc intraperitoneal (IP) saline. The lupus nephritis group was mice with pristane 0.5 cc IP, and the therapy group was mice with 0.5 cc IP pristane and 0.5 cc snail mucus per day at the 4th month of treatment for 14 days and after that the mice blood serum was taken and examined in the laboratory. The dsDNA antibody examination used the ELISA method. Statistical test with Anova followed by post hoc test. P is significant if it is less than 0.05. There was an increase in the levels of antibody dsDNA (p = 0.016) in the lupus group (75.13 + 22.5mg/dL) compare with the control group (56.96 ± 11.77 mg/dL), but there was a decrease in anti-dsDNA antibodies in the mice with snail mucus (56.01 ± 8.29 mg/dL; p = 0.02), and the methyl prednisolone group (53.47 ± 13.53 mg/dL; p = 0.009) when compared to the lupus group. Snail mucus suppresses anti dsDNA antibody levels in lupus mice.
Morphological characteristics of Temanggung’s robusta coffee (Coffea canephora Pierre ex A. Froehner) at different altitudes
Authors: Pangestika I W , Susilowati A , Purwanto E 
Published: July 2021

Abstract
Temanggung is the center of a coffee plantation in Central Java Province Indonesia since its altitude and cold climate are suitable for the growth and development of the plant. However, due to the climate changes in recent years, the air temperature at a specific altitude is not as cold as before. Vegetation responds to climate change by changing its phenological pattern, i.e., changing morphology. This study aimed to analyze the morphological characters of Temanggung robusta coffee at different altitudes by current climates condition. An exploratory study was conducted on two clusters of altitudes; there are 600 and 900 m asl approximately. Each group repeated in three locations, with each consisting of 5 trees. Fifteen quantitative morphological characters were evaluated using analysis of variance and further test performed using a 5%-LSD-test. Among those, the canopy diameter, plant height, leaf width, fruit length, fruit thickness, bean length, and bean thickness exhibited significant differences. Ten qualitative morphological characters were also evaluated. The characters varied between altitudes, i.e. leaf shape, young leaf color, fruit shape, and ripe fruit color. Meanwhile, there are no significant differences in leaf length and leaf petiole length characters.
The yield of three promising lines cempo ireng black rice M7 generation from gamma-ray irradiation
Authors: Nandariyah  , Sukaya  , Pujiasmanto B , Chasanah U 
Published: July 2021

Abstract
Black rice as a functional food crop contains high anthocyanins to prevent free radicals triggered by global climate change. However, black rice is often uncultivated because of weaknesses such as low yields and long harvest times. Breeding using gamma-ray irradiation is one solution to obtain new high-yielding varieties. This study aims to examine the yield and anthocyanin content of promising lines of cempo ireng black rice M7 generation from gamma-ray irradiation, the yield test is required in plant breeding. The research was conducted from December 2019 to August 2020 at Karanganyar, using different treatment of plant lines: three irradiated lines of black rice and a line without irradiation (control). Observations were made on 30 random sample plants each line. Data were analyzed descriptively and the comparison between mutant and control plant performance using the T-test. Observational variables included plant height, flowering and plant age, number of productive and non-productive tillers, panicle length, number of pithy and empty grains, the weight of 1,000 seeds, productivity, and anthocyanin content. The yield and anthocyanin content of irradiated lines were better than the control line. The highest production value of 8.29 tons/ha and the highest anthocyanin content of 75.04 ppm in line 52.
Laboratory examination to measure antibodies formed after vaccination of COVID-19
Authors: Hasugian A R , Khariri  
Published: July 2021

Abstract
Coronavirus Disease (COVID-19) as the reemerging disease which first discovered on December 2019 in Wuhan, China. World Health Organization (WHO) has designated COVID-19 as a global pandemic on March 11th, 2020. Covid-19 is related with the climate change which influences the environment of life cycle of SARS-CoV2 vector. With there are no drug of choice for Covid-19 until this time, giving vaccination is one of the strategy of prevention to break the transmission and reduce the number of cases. Vaccination can trigger immunity by forming antibodies and protect the individual from antigen which came in to host and can be a marker for future vaccine for disease relates unpredicted climate change. This paper reviews several laboratory methods that can be used to detect antibodies such as Lateral Flow Immunoassay (LFIA), Enzyme-linked Immunosorbent Assay (ELISA) and Electro-Chemiluminescence Immunoassay (ECLIA) and see their ability to protect individuals from COVID-19 after vaccination using neutralization test such as Plaque Reduction Neutralization Test (PNRT) or Surrogate Reduction Neutralization Test (sRNT). The benefit of this reviews is to understand the optimal methods to measure and detect antibody and to improve vaccine development strategy for the disease relate with unpredicted climate change in the future based on antibodies seroconversion and seroprotection.
Farmers’ adaptation in dealing with limited water (A case study on Wonogiri Regency)
Authors: Wardani R I K , Widiyanto  , Rusdiyana E , Rinanto Y , Sudibya  
Published: July 2021

Abstract
The vulnerability of farmers to drought is determined by the interaction of the potential impacts of climate change. The impact of climate change is felt by residents of Paranggupito District, one of which is in Ketos Village in the agricultural sector, especially rainfed land which is very vulnerable to long drought conditions. Farmers ‘losses to drought are determined by the interaction of climate change impacts and farmers’ adaptation. This research aims to find out the adapting strategy the farmers take in dealing with water limitation. The subject of research consisted of farmers in Ketos Village, Paranggupito Sub District, Wonogiri Regency. The research design used was descriptive qualitative one with purposive and snowball sampling techniques. Data collection was carried out using observation, in-depth interview, focus group discussion, and documentation. Data was analyzed using triangulation technique. The result of research shows that to adapt to their condition, the farmers adopt short-and medium-term adapting behaviour, including: determining crop calendar, selecting plant variety, applying intercropping system, determining appropriate planting pattern, controlling pest and disease, determining planting technique, and monitoring continuously.
Effect of supplementary irrigation on rice yield in dry land during rainy season
Authors: Anshori A , Suswatiningsih T E , l Viandari N A , Rajiman  , Mujiyo  
Published: July 2021

Abstract
Climate change causes change in rainfall patterns, which will affect water availability. Water is a limiting factor for rice production on dry land. Increasing rice yields on dry land requires precise water management. This study aimed to investigate the effect of supplementary irrigation when it does not rain on rice yields in dry land during rainy season. The research was conducted on dry land in Playen, Gunung Kidul, Daerah Istimewa Yogyakarta, Indonesia during rainy season of November 2020 to February 2021. The treatments were supplementary irrigation if 1 day without rain (A1), if 2 days without rain (A2) and if 3 days without rain (A3), and they were compared to control without supplementary irrigation (A0). This research used a randomized completely block design, each treatments replicated 4 times. The results showed A1 gave the highest grain yield, namely 7.786 ton ha−1, significant different with other treatments of A2, A3 and A0. Dry straw of A1 was 7.324 ton ha−1, significant different with A2, A3 and A0. Carbon absorption of A1 was 6.860 ton ha−1, consisting of carbon in grain 3.575 ton ha−1 and straw 3.285 ton ha−1, it was significant different with other treatments of A2, A3 and A0 (p<0.05; n=16). B/C A2 1.73 was highest from the others and its farmers have profit Rp. 19,276,360 ha−1.
Identifying the sustainability level of urban slums in the Greater Jakarta, Indonesia using a composite index
Authors: Yuniar A Z , Kristanto G A , Dahlan A V , Kemala D 
Published: July 2021

Abstract
The Republic of Indonesia’s government aims to alleviate slums to mark the start of smart city development. The goals of KotaKu, a national program established to handle slum issues, are 100% access to sanitation and clean water and the reduction of slum areas to zero, which aligns with the nation’s commitment to Sustainable Development Goals to tackle climate change and its impacts. Slum identification and intervention are undertaken through the government’s emphasis on the settlement’s environment, resulting in the wrongful judgment of an area as a slum or vice versa. This study is conducted in four urban slums or kampungs located in the Greater Jakarta area (i.e. Kampung Cikini, Kampung Gedong Pompa, Kampung Cimone-Cincau, and Kampung Markisa). Each area’s sustainability level was calculated using a composite index that used indicators to represent the three pillars of sustainability, i.e., social, economy, and environment. Kampung Cimone-Cincau had the best sustainability (0.75), while Kampung Gedong Pompa had the worst (0.52). Across all the study areas, access to sanitation reached 97% and, access to clean water reached 98%. More thorough indicators to identify slum sustainability can help resolve an area’s wrongful judgment, and a more suitable approach for slum intervention can be made.
Technical efficiency of organic rice farming in Ngawi Regency (The case of the Komunitas Ngawi Organic Center)
Authors: Krisdiyanto R , Harisudin M , Irianto H 
Published: July 2021

Abstract
Soil degradation fertility is a form of environmental damage due to climate change, ironically caused by the agricultural sector as the largest contributor to global warming. One of the efforts to overcome the problem of climate change issues in the agricultural sector is through organic rice farming practices. This study aims to analyze organic rice farming which includes farming profiles, influencing factors, and technical efficiency level of organic rice farming in Ngawi Regency which focuses on the Komunitas Ngawi Organic Center (KNOC). This study used a quantitative descriptive basic method with a census of all active member organic rice farmers of KNOC. The production factors of organic rice were analyzed using the Cobb-Douglass stochastic frontier production function. The results showed that in general the average organic rice farming profile on certified land was superior than non-certified land, with 1.96 R/C ratio on certified land, while 1.41 R/C ratio on non-certified land. The time it takes for land to become certified organic is three consecutive growing seasons applying supervised organic farming. Production factors that positively significantly influence organic rice farming are land area, labor, and organic pesticides. Excessive use of organic fertilizer input can increase the number of wild weeds on organic rice fields which can inhibit the growth of organic rice and reduce grain production. The level of technical efficiency achieved by respondent farmers varies widely between 0.57 - 0.93 with an average of 0.80 which is considered efficient.
Farmers’ conservation behavior in Solo Hulu Watershed
Authors: Anantanyu S , Suwarto  , Winarno J , Wibowo A , Permatasari P 
Published: July 2021

Abstract
Watershed management is an important aspect to support the preservation of surrounding area. The function of upstream area as water catchment area should be protected by keeping the utilization of area from support capability surpassing the environment. Community participation is very necessary to maintain the environment in the ecosystem. This research will provide information about anything related to the profile of farmers, farming, and farming system in Beruk Village. Research is means of providing sustainable livelihood farming programs very useful to the farmer community. The research method used was case study, in which data was collected through in-depth interview, focus group discussion and participatory observation. Participative approach was conducted through in-depth interview, observation and involving farmers in Forum Group Discussion (FGD). The result of research showed that to minimize landslide in the farming area, farmer communities in Beruk Village always consider soil cultivating technique and irrigation system. Irrigation system organization is the farmers’ way of maintaining their land preservation. Farmers do not plant their land with big trees because they are afraid that the trees will shade their vegetables and lead to the death of vegetables. Local leadership in Beruk Village can be seen from presence of community leader.
An approach to gene-based testing accounting for dependence of tests among nearby genes
Authors: Yurko Ronald , Roeder Kathryn , Devlin Bernie , G’Sell Max 
Published: July 2021

Abstract
In genome-wide association studies (GWAS), it has become commonplace to test millions of single-nucleotide polymorphisms (SNPs) for phenotypic association. Gene-based testing can improve power to detect weak signal by reducing multiple testing and pooling signal strength. While such tests account for linkage disequilibrium (LD) structure of SNP alleles within each gene, current approaches do not capture LD of SNPs falling in different nearby genes, which can induce correlation of gene-based test statistics. We introduce an algorithm to account for this correlation. When a gene’s test statistic is independent of others, it is assessed separately; when test statistics for nearby genes are strongly correlated, their SNPs are agglomerated and tested as a locus. To provide insight into SNPs and genes driving association within loci, we develop an interactive visualization tool to explore localized signal. We demonstrate our approach in the context of weakly powered GWAS for autism spectrum disorder, which is contrasted to more highly powered GWAS for schizophrenia and educational attainment. To increase power for these analyses, especially those for autism, we use adaptive $P$-value thresholding, guided by high-dimensional metadata modeled with gradient boosted trees, highlighting when and how it can be most useful. Notably our workflow is based on summary statistics.
DLpTCR: an ensemble deep learning framework for predicting immunogenic peptide recognized by T cell receptor
Authors: Xu Zhaochun , Luo Meng , Lin Weizhong , Xue Guangfu , Wang Pingping , Jin Xiyun , Xu Chang , Zhou Wenyang , Cai Yideng , Yang Wenyi , Nie Huan , Jiang Qinghua 
Published: July 2021

AbstractAccurate prediction of immunogenic peptide recognized by T cell receptor (TCR) can greatly benefit vaccine development and cancer immunotherapy. However, identifying immunogenic peptides accurately is still a huge challenge. Most of the antigen peptides predicted in silico fail to elicit immune responses in vivo without considering TCR as a key factor. This inevitably causes costly and time-consuming experimental validation test for predicted antigens. Therefore, it is necessary to develop novel computational methods for precisely and effectively predicting immunogenic peptide recognized by TCR. Here, we described DLpTCR, a multimodal ensemble deep learning framework for predicting the likelihood of interaction between single/paired chain(s) of TCR and peptide presented by major histocompatibility complex molecules. To investigate the generality and robustness of the proposed model, COVID-19 data and IEDB data were constructed for independent evaluation. The DLpTCR model exhibited high predictive power with area under the curve up to 0.91 on COVID-19 data while predicting the interaction between peptide and single TCR chain. Additionally, the DLpTCR model achieved the overall accuracy of 81.03% on IEDB data while predicting the interaction between peptide and paired TCR chains. The results demonstrate that DLpTCR has the ability to learn general interaction rules and generalize to antigen peptide recognition by TCR. A user-friendly webserver is available at http://jianglab.org.cn/DLpTCR/. Additionally, a stand-alone software package that can be downloaded from https://github.com/jiangBiolab/DLpTCR.