bluuebunny/crossref_metadata_2025 huggingface dataset:
Meloidogyne enterolobii (Pacara earpod tree root-knot nematode).
Authors: Castillo Pablo , Castagnone-Sereno Philippe
Published: April 2021

The risk of introducing nonindigenous plant pathogens or pests into new areas is increasing rapidly due to globalization and the extensive trade and transport network now established within and among continents (Hulme, 2009). Meloidogyne spp. are universally associated with vegetable production across the globe. Meloidogyne enterolobii is a highly pathogenic and aggressive invasive species emerging as an economically important species worldwide. As a root-knot nematode species, M. enterolobii can easily be transmitted with soil and plant material. Infested soil and growing media, plants for planting, bulbs and tubers from countries where M. enterolobii occurs are the most probable pathways of introduction into different regions. Soil attached to machinery, tools, footwear or plant products is also another possible pathway. The recent interception of this pest in several countries in Europe and the Mediterranean region (Germany, The Netherlands, UK) illustrates that it has the potential to enter different regions. In addition, M. enterolobii could survive under glasshouse conditions across regions with a sub-Mediterranean or a continental climate. Once root-knot nematodes have been introduced, it is generally difficult to control or eradicate them. Only in the EPPO region has this nematode been listed as a quarantine pest (EPPO A2 list No.361).
Lobesia botrana (European grapevine moth).
Authors: Lucchi Andrea , Scaramozzino Pier Luigi
Published: April 2021

Lobesia botrana should be regarded as a potentially serious pest on a worldwide scale for all the vine-growing areas that are presently unaffected. L. botrana could be introduced as larvae or pupae on infested propagation material from the Old World and Latin America (Chile and Argentina) and especially on imported table grapes for consumption. It could also be introduced through the movement of unsanitized machinery. Thus L. botrana must have a strict quarantine status in all countries still unaffected.
Conservation and reintroduction of the rare and endangered orchid
Paphiopedilum armeniacum
Authors: Wang Meina , Li Suzhen , Chen Lijun , Li Jian , Li Liqiang , Rao Wenhui , Liu Hong , Chen Jianbin , Ren Hai
Published: April 2021

Paphiopedilum armeniacum
is a rare and endangered lady’s slipper orchid in China. It is distributed around the mid-elevations of the Nu Mountains in southwest China. Due to over-harvest, habitat loss, and degradation, wild populations of
P. armeniacum
has declined drastically. A combination of approaches involving biotechnology, habitat restoration, and interspecific relationship reconstruction was used to carry out the reintroduction of the species. Integrated conservation program for this species included
in-situ
protection,
ex-situ
conservation, and reintroduction, which helped to rebuild a harmonious relationship between local farmers and
P. armeniacum
. The sustainable utilization of native plant resources in poor areas can promote regional sustainable development which is compatible with species protection.
Hear hear!—the question
Authors: Featonby David
Published: April 2021

The human ears are wonderful detectors, and sound gets to them in many different ways. This ‘what happens next?’ briefly examines two experiments which are informative in the ways in which sound travels and is heard.
Directionality preservation of nuclear recoils in an emulsion detector for directional dark matter search
Authors: Alexandrov A. , De Lellis G. , Di Crescenzo A. , Golovatiuk A. , Tioukov V.
Published: April 2021

Nuclear emulsion is a well-known detector type proposed also for the directional detection of dark matter. In this paper, we study one of the most important properties of direction-sensitive detectors: the preservation by nuclear recoils of the direction of impinging dark matter particles. For nuclear emulsion detectors, it is the first detailed study where a realistic nuclear recoil energy distribution with all possible recoil atom types is exploited. Moreover, for the first time we study the granularity effect on the emulsion detector directional performance. As well as we compare nuclear emulsion with other directional detectors: in terms of direction preservation nuclear emulsion outperforms the other detectors for WIMP masses above 100 GeV/c2.
Tunable synchronized dual-wavelength pulsed operation in an Er/Yb double-clad fiber laser
Authors: Durán-Sánchez M , Álvarez-Tamayo R I , García-Flores Y A , Pottiez O , Posada-Ramírez B , Bello-Jiménez M , Alaniz-Balón J , Armas-Rivera I , Montiel-Piña E , Ibarra-Escamilla B
Published: April 2021

We present a simple and efficient experimental approach to synchronized dual-wavelength pulsed operation in an all-fiber laser. Four different dual-wavelength emissions of synchronized picosecond pulses are generated through simple adjustments of a wave retarder. Autocorrelation traces exhibit modulation profiles corresponding to dual-wavelength emissions with wavelength separations ranging over one order of magnitude, from 0.96 to 9 nm. In all cases, it is observed stable dual-wavelength operation and perfect synchronization between both pulsed components, without requiring of intra-cavity dispersion management. For the first time, to the best of our knowledge, synchronous tunable dual-wavelength pulse emission in a single-cavity Er/Yb double clad ring fiber laser is experimentally demonstrated.
Thermal expansion and thermal conductivity of RT
2 (R: Gd, Dy, Er; T: Al, Ni) intermetallic compounds for magnetic refrigerator
Authors: Watanabe S , Komatsu S , Futatsuka K , Kumazawa N , Matsumoto K , Kamiya K , Takeya H , Numazawa T
Published: April 2021

Highly efficient hydrogen liquefaction is required for upcoming hydrogen energy society. Magnetic refrigeration is expected as a method to realize efficient hydrogen liquefaction, and the performance depends on properties of magnetic materials. RT
2 (R: rare-earth; T: Al, Ni) Laves phase intermetallic compounds with a second-order magnetic phase transition are one of the promising magnetocaloric materials. Thermal expansion, magnetostriction, and thermal conductivity of ErAl2, DyNi2, DyAl2 and GdNi2 were measured in magnetic fields using polycrystalline samples because of the important properties for practical use in a magnetic refrigerator. Thermal expansions showed anomalies at the magnetic transition temperature. However, those in 0 T were nearly the same as copper. Magnetostriction were not as large as magnetocaloric materials with a first-order magnetic phase transition such as TbMn2. Thermal conductivities in 0 T were almost in agreement with the literature data, and magnetic field dependence was small. These results indicate that RT
2 compounds are suitable as magnetic refrigerants for hydrogen liquefaction in practical use.
Effect of hyperbranched polymer modified on the impact strength of epoxy resin at cryogenic temperature
Authors: Zhao YL , Huang RJ , Zhang H , Zhou ZR , Wu ZX , Zhang HC , Zhang C , Wang YG , Li LF
Published: April 2021

In order to investigate the effect of hyperbranched polymer modified on impact strength of epoxy resin at 77K. One modifier called H204 was employed to methyl nadic anhydride (MNA) cured diglycidyl ether of bisphenol A (DGEBA) epoxy resin system. The impact strength at 77 K was studied and the results indicated that introduction of modifier used in this study can enhance the impact strength at cryogenic temperature. The 58.57% increase was obtained by addition of 10 wt% H204 into the epoxy matrix. Furthermore, scanning electron microscopy (SEM) was used to investigate the fracture mechanism and strengthening effect.
Robust Normality Test in the Presence of Outliers
Authors: Rana Sohel , Eshita Nishat Naila , Al Mamun Abu Sayed Md.
Published: April 2021

In classical statistics, detecting the normality of the data is one of the essential assumptions. However, if the selected random samples have some outliers, this assumption is violated. It is now evident that the Jarque-Bera (JB) test is one of the most powerful tests of normality. The study shows that in the presence of outliers, the JB test does not perform well in many situations. Thus, they proposed a robust Jarque-Bera (RJB) test as an alternative. In this article, we incorporate the idea of Gel and Gastwirth and proposed also a modified Jarque-Bera (MJB) test which has more power than the RJB. The results of the real-life example and simulation study shows that the power of MJB is higher in detecting normality of data compared to the JB and RJB test.
Handling Missing Values and Unusual Observations in Statistical Downscaling Using Kalman Filter
Authors: Saputra M D , Hadi A F , Riski A , Anggraeni D
Published: April 2021

Rainfall forecasting model using data Global Circular Model (GCM) with Statistical Downscaling technique has a fairly high accuracy. However, missing local climate information poses a constraint in data analysis and forecasting. Missing value imputation is one solution that can be used. Kalman Filter Imputation and State Space Model Arima are imputation methods that operate recursively where there is an update of prediction values when data updates occur. This study aimed to find the best model to use for missing value imputation with small imputation errors. The results of the missing value imputation were used to obtain the best statistical downscaling model on a 3 × 3 to 12 × 12 grid. The research was conducted on the daily rainfall data of Kupang City with 17% missing values and 8% unusual data at the Eltari Meteorological observation station, Kupang city. The average daily rainfall data in East Nusa Tenggara Province were utilized as a reference for the characteristics of rainfall data at the Kupang City observation station. The best missing value imputation was obtained by using the Arima State-Space Model (2,1,1) with a Root Mean Square Error (RMSE) of 0.930 and the model was statistical downscaling best obtained on a grid 6 × 6 with a Mean Absolute Percentage Error (MAPE) of 1.3 % and the number of PCs 11.
A Bayesian Logit-Normal Model in Small Area Estimation
Authors: Sunandi E , Kurnia A , Sadik K , Notodiputro K A
Published: April 2021

The Logit-Normal model is one of the GLM Bayes models with random covariates used in binary data. This study aimed to examine and evaluate the characteristics of the Logit-Normal model. The second objective was to apply the Logit-Normal model to estimate the proportion of poverty in the small area of Mukomuko District in Bengkulu Province. We used the Hierarchical Bayes (HB) method to estimate parameters model. The simulation results obtained from the optimum number of iterations and gibbs samples, namely 500 iterations and 100 gibbs samples, respectively. In addition, when seen the value of

p

ˆ

i

H
B

has the same tendency with the parameter pi and

p

ˆ

i

D
E

. The value of

p

ˆ

i

H
B

tends to overestimate at

p

ˆ

i

H
B

⩽ 60%. Conversely,

p

ˆ

i

H
B

tends to underestimate

p

ˆ

i

H
B

> 60%. Furthermore, in the simulation results the estimated value of variance and MSE

p

ˆ

i

H
B

tends to be smaller than the variance of proportion. The application of the HB method for Logit-Normal model in the Mukomuko District poverty data produces

p

ˆ

i

H
B

which has the same tendency as the result of direct estimator (

p

ˆ

i

D
E

). The majority (21 villages) value of var(

p

ˆ

i

H
B

) are smaller or equal to the var(

p

ˆ

i

D
E

). This indicates that the estimation using the HB method can improve the estimation of the proportion parameters obtained by using the direct estimation method on poverty data.
An Alternative Procedure to Produce a P-Spline Small Area Estimation Model Based on Partial Residual Plot and Significance Test of Spline Term
Authors: Purwa Taly
Published: April 2021

This study provides an alternative procedure to produce the penalized spline small area estimation (P-Spline SAE) model by plotting each of auxiliary variable and variable interest as a simple nonlinearity identification and performing the iterative procedure: by estimating the model, producing partial residual plots to check model adequacy and also identify the nonlinearity, and testing the significance of spline term using Restricted Likelihood Ratio Test (RLRT). These procedures are applied to estimate the monthly average per-capita expenditure of district level in the Province of Bali, 2014 using direct survey estimates from the National Socio-Economic Survey (Susenas 2014) and auxiliary variables from the administrative record of village data (PODES 2014). The Fay-Herriot (FH) model (M1) as a benchmark and four P-Spline SAE model, i.e. the P-Spline SAE with spline term: x2 and x3 (M2), x3 and x4 (M3), x2, x3 and x4 (M4), and x1, x2, x3 and x4 (M5), are obtained. From RLRT, the spline term of M3, M4, and M5 are statistically significant. According to the parametric bootstrap of mean squared prediction error (MSPE) and coefficient of variation (CV), the M4 and M5 show a significant improvement with the CV values range from about 1%-6% compared to M1 with a range from about 4%-17%, shows that these two models more efficient. The M3 model shows the opposite performance even though has the smallest AIC value. More detail, the MSPE and CV produced by M4 are slightly better than M5 makes the M4 is the best model in this study.
Hybrid Modeling of Singular Spectrum Analysis and Support Vector Regression for Rainfall Prediction
Authors: Athoillah Ibnu , Wigena Aji Hamim , Wijayanto Hari
Published: April 2021

Rainfall can provide many benefits such as for agriculture, water resource management, and electricity. However, it can also cause hydrometeorological disasters such as floods and droughts, so that an accurate rainfall prediction is needed to anticipate the risks and minimize the losses. Rainfall characteristics are diverse, complex, and uncertain. Thus rainfall data are usually nonlinear time series and difficult to predict using traditional methods such as ARIMA. In recent years, machine learning models such as support vector regression (SVR) hybrid model has been developed to improve prediction accuracy. The SVR hybrid model can be carried out with Singular Spectrum Analysis (SSA) for data pre-processing. The SSA method is used to decompose original time series data into trend, oscillatory, and noise components. The SVR model is then used to predict rainfall based on reconstruction series from SSA without noise components. The grid search algorithm using an optimization method is used to estimate the parameters of the SVR model. This research aims to apply an SSA-SVR hybrid model and compares it to the SVR model using monthly rainfall data at Kemayoran Station from 1980 to 2019. Based on the result showed that the hybrid model yielded more accurate than the single model.
Hybrid ARIMAX-ANFIS based on LM Test for Prediction of Time Series with Holiday Effect
Authors: Hendikawati P , Subanar  , Abdurakhman  , Tarno
Published: April 2021

This paper aims to introduce the ARIMAX-ANFIS hybrid model based on LM test for forecasting time series that is influenced by holidays due to the calendar effect. The optimal ANFIS model architecture selection is made by selecting the input variable and determining the number of membership functions (MFs) based on the LM test. Simulation data and real data are used as case studies. The results showed that ARIMAX-ANFIS based on LM test could be used as an alternative procedure for selecting ANFIS architecture. In the simulation data, the best model is obtained with five input variables and four numbers of MFs. Meanwhile, the foodstuff price index data as real data gives optimal results with five input variables and two numbers of MFs. In general, the use of calendar effect dummy variables in the ARIMAX-ANFIS hybrid model shows more accurate results than the ARIMA-ANFIS model. The effect of holidays as a variation calendar also affects predictions’ accuracy, as seen from the RMSE, MAPE, and R2 values in the ANFIS training and testing process.
Forecasting Inflow and Outflow of Currency in Central Java using ARIMAX, RBFN and Hybrid ARIMAX-RBFN
Authors: Maghfiroh Z F , Suhartono  , Prabowo H , Salehah N A , Prastyo D D , Setiawan
Published: April 2021

This research aims to forecast the inflow and outflow currency in Central Java. Inflow and outflow data contained both non-linear and linear patterns with calendar variation effects. Calendar variation model based on ARIMAX as a linear model, Radial Basis Function Network (RBFN) as a non-linear model, and hybrid ARIMAX-RBFN as a combination linear and non-linear model are used to forecast inflow and outflow of currency in Central Java. The data used in this research consists of inflow and outflow of currency in Central Java from January 2010 until June 2019. The denomination used is 32 denominations of inflow and 32 denominations of outflow currency. RMSE and sMAPE values from the out-of-sample data are used to select the best model. The results show that hybrid ARIMAX-RBFN is the best model of 19 denominations of inflow currency and 22 denominations of outflow. In general, the hybrid model tends to provide a more accurate forecast than the individual forecasting model used in this research.
Comparison of Average Linkage and K-Means Methods in Clustering Indonesia’s Provinces Based on Welfare Indicators
Authors: Yusniyanti A L , Virgantari F , Faridhan Y E
Published: April 2021

This study compares two clustering methods, i.e. average linkage and K-means, in grouping Indonesia’s provinces based on welfare indicators in education, health, and income. Data from Statistics Indonesia (BPS) covering Indonesia’s 34 provinces are used. Welfare variables exercised in this study are population, rate of population with government-assisted health covers, morbidity rate, human development index, expense rate per capita, and rate of the population aged 15 or over who graduated from junior high school (completed Year 9). Results show that the average linkage method generates three clusters; the first cluster of which consists of 32 provinces, while the second and third clusters each consist of only one province. On the other hand, the K-means method is set to generate equally three clusters. Unlike the first method, K-means’s first cluster, in this case, consists of 14 provinces, while its second and thirds clusters consist of 13 and 7 provinces, respectively. Performances of both methods are measured using the variance ratio. The average linkage and k-means cluster methods yield variance ratios of 0.08275 and 0.28881, respectively. Based on these criteria, the average linkage method is shown to exercise a better performance due to its smaller variance ratio.
Modification of Multivariate Adaptive Regression Spline (MARS)
Authors: Prihastuti Yasmirullah Septia Devi , Otok Bambang Widjanarko , Trijoyo Purnomo Jerry Dwi , Prastyo Dedy Dwi
Published: April 2021

Multivariate Adaptive Regression Spline (MARS) is a nonparametric regression method that can accommodate additive effects and interaction effects between predictor variables. Generally, MARS has been used for modeling pairs of data with continuous or categorical responses. One type of categorical data that needs special attention in modeling is count data. The count data is often encountered, especially in the health sector. The existence of count data motivates the development of the theory and application of the MARS method, which is the Multivariate Adaptive Poisson Regression Spline (MAPRS). The MAPRS is a combination of MARS and Poisson regression. It can accommodate and analyze the data according to its type and distribution. The application of MAPRS to model the count of Tuberculosis (TB) shows that it outperforms the Poisson regression.
A Novel Treatment of Antibiotic Effluent pollution From Abattoirs In Mosul City
Authors: Aldweag Abdullah F. S. , Albanna Ayman
Published: April 2021

Beta-lactam substances released into the environment by continuous using via human, animal and plant protection from bacterial infection. These of antibiotic presence has considered very dangerous problem of the public health in general throughout many side effects. Also, the prevalence of antibiotics into the wastewater abattoirs leads to environmental hazard as results of remains into the surrounding and difficulty disposal. In this study, the research have focused on how to elimination of antibiotic from wastewater abattoirs (animal slaughtered sources), in particular, subunits of wastewater stations have not ability to trapping these kinds of substances. Chemical pathways have used to interact directly with Beta-lactam group and convey to the chemical complex and easy to completely removal from wastewater discharged by using Copper sulfate salts. Our results found that using four molecules of CuSo4 for one molecule of Beta-lactam, in order to complete removal process and possibility reusing it at the same time almost 300% percentage. Also, for increase the reaction process, it is recommended to use optimal a temperature between 40-60 ° C. Overall, we need strict laws to limit the spread of antibiotic contamination in the nature as a results of harmful and side effects on all creatures.
The application of electronic management in the agricultural extension organization in Iraq
Authors: Salih Al-Hamdany Majeed Hadi , Abd Al-Rekibe Hakeem Sultan
Published: April 2021

The application of electronic management in the agricultural extension organization in Iraq has been studied through four fields in the application, as the form included four item, namely: scientific recommendation, extension activities, agricultural employees, and administrative affairs, to enhancing the ability to implement electronic management in the agricultural extension organization. This research was executed in the province of Iraq. The provinces It was divided into four regions, which is next: Northern, Central, Middle Euphrates, and Southern governorates, 4,4,4,3, respectively, the study was carried out of 400 agricultural employees, the a proportional sample of 50% from the total respondents, which included 16 extension centers, 57 extension farms, the Agricultural Extension and Training Department Center, The descriptive approach was used to achieve the objects of the research about the electronic management of the extension organization in Iraq, the data was collected using the questionnaire, for analyzed the data use the (Frequency, and percentage). the results showed that the application of electronic management in the agricultural extension organization is Weak, and a few departments, divisions, extension centers and extension farms of the agricultural extension organization use electronic management in performing agricultural extension activities to communicate scientific recommendations to farmers and deal with agricultural employees in modern management. the recommended to use electronic management in the agricultural extension organization to save time and effort in communicating agricultural scientific guidelines quickly and communicating what is modern to farmers in developing agricultural production.
Effect of rootstock and bio-fertilizers on some mineral concentrations in the leaves of Local Lemon (Citrus
limon L.) transplants and available nutrients in the Media
Authors: Al-Zuhairi Faris F. A. , Al-Aareji Jassim M. A. , Al-Taae Ali K.
Published: April 2021

The study was conducted in the Lath-house/Department of Horticulture and landscape design/College of Agriculture and Forestry/University of Mosul on budded local lemon (Citrus
limon L.) at one year old, by using Randomized Complete Block Design (RCBD) with two factors, three replications and four transplants for each experimental unit, First factor was rootstock(soure orange and Citrumelo swingle), second factor was inoculation with Bacillus
subtilis bacteria and Trichoderma
harzianum fungi, in addition to control treatment (without inoculation), as the inoculation with the bacterial and fungus suspension was carried out twice a season according to the treatments, by adding 10 ml.transplant−1 in each addition, first was in the mid-March and the second was after three months of first treatment. Results indicated that the transplants budded on C. swingle gave the highest values of leaves concentration and soil availability of N, P and available Fe in the media, while the transplants budded on soure orange gave the highest values of leaves K and Fe concentrations. As for biological fertilizers the inoculation with T.
harzianum gave the highest values of leaves N and K concentrations and availability of N and Fe in the media, while the inoculation with B.
subtilis gave the highest values of other parameters(leaves concentrations of P and Fe and P availability in the media). The interaction between rootstock and bio-fertilizers significantly effected on all studied characteristics, the interaction between C. swingle and T.
harzianum gave the highest values of leaves N and available N in the media, while the interaction between C. swingle and B.
subtilis gave the highest values of leaves P and its availability in the media, as for leaves K, the interaction between soure orange and T.
harzianum gave the highest values of it, while the interaction between soure orange and B.
subtilis gave the highest values of leaves Fe concentration.
Application GIS Software to Determine the Distribution of T.D.S. Concentrations Along the Tigris River
Authors: Chabuk Ali , Abed Salwan Ali , Al-Zubaidi Hussein A. M. , Al-Ansari Nadhir , Maliki Ali A. A. , Ewaid Salam Hussein , Laue Jan
Published: April 2021

Tigris River is a major source to supply water for a big part of Iraq. Lately, Iraq has experienced water shortage problems such as variability in climate and the building of huge dams in the upstream countries (Turkey and Iran). In this work, the total dissolved salts (T.D.S.) were measured at fourteen sites on the Tigris River in two periods of the year 2014. The first period consisted of six rainy-months (April–September) and the second period covered non-rainy-months (October-March). Interpolation technique of inverse-distance-weighting (I.D.W.) in ArcGIS was applied to create the prediction maps of the river for (T.D.S.) concentration in both periods. The findings revealed that the (T.D.S.) levels continued to the last site in Al-Qurnah-city (Basrah) from the first site in Fish-Khabur-city (S-1). In the first period, the (T.D.S.) levels at fourteen selected sites were over the levels in the second period. According to World-Health-Organization (2003), the (T.D.S.) concentration on the Tigris River in both periods in 2014 was graded into five classes, then, the prediction maps of the (T.D.S.) classifications were created.
Application weight mathematical model (WQI) to assess water quality for irrigation: A case study of Tigris river in Nineveh governorate
Authors: Al-Saffawi Abdulaziz Y. T. , Al-Shanoona Reem A.A. , Alobidy Omar M. S.
Published: April 2021

The current study included a qualitative assessment of the water of the Tigris river in Nineveh governorate for irrigation purposes using the sub-index model (IWQI) that was applied to eleven parameters of irrigation water to identify the quality of the river’s water for irrigation. Water samples were collected monthly from nine sites on the river starting from November. Until august to conduct physiochemical analyzes, as well as calculating the irrigation parameters. The results indicated that the water quality index values ranged between (29.08-41.46). Despite the high values of the index with the course of the river, especially the city of Mosul, due to the drainage of sewage through many estuaries spread on both sides of the river, the water quality in the studied sites was of the excellent water category for irrigation.
Effect of organic manure and tillage depths on sunflower (Helianthus annuus L.) production
Authors: Muhsin Sadiq J , Ramadhan Marwan N , Nassir Aqeel J
Published: April 2021

One of the factors affecting the productivity of sunflower is poor management of soil service operations such as tillage depth. As choosing the depth of tillage helps in increasing the growth of the root system, which is reflected in the plant vegetative growth. Although the addition of animal manure can increase the activities of microorganisms in the soil and the soil contents of available nutrients, the effects on sunflowers were not tested under dry land conditions of Basrah province. Field experiment was carried out during the 2020 growing season, at two locations, to determine the effect of three tillage depths (10, 20 and 30 cm) and four organic manure levels (M0 = without manure, M1 = 6 t ha−1, M2 = 8 t ha−1, M3 = 10 t ha−1) on sunflower performance, seed yield and selected soil properties. Results showed that, the maximum vegetative parameters, yield component and yield were recorded at 30 and 20 cm tillage depth treatments at the both growing locations without significant differences between them compared to 10 cm tillage depth. Number of seeds head−1 was not influenced by tillage depth treatments over the two locations. Tillage depth of 30 cm significantly improved seed yield as compared to 10 cm tillage depth. The maximum seed yield recorded by 30 cm tillage depth. The application of organic manure had a significant effect on sunflower seed yield, biomass yield, head diameter, 500 seed weight, seeds head−1, leaf area, leaves plant−1, plant height and stem girth at the both growing locations.
The implications of urban expansion to commuter travel behavior in the Jakarta Metropolitan Area
Authors: Suharto B B , Kusuma M E , Wijaya K A P
Published: April 2021

For decades, urban development is characterized by a rapid growth population and built-up expansion into the outskirts. Residential development shifted from the city center to the suburbs or the peripheral area, known as suburbanization. Jakarta Metropolitan Area (JMA) is a primate urban area in Indonesia, marked with only 0.33% of the national land area. Still, this region contributes about one-fourth of Indonesia’s Gross Domestic Products (GDP) and accommodates about 12,4 % of Indonesia’s total population in 2017. JMA is still rapidly growing and encouraging the expansion of residents into its suburbs, and this will affect the travel behavior of daily commuting to and from home to destination. This article aims to analyze the implications of JMA expansion to its commuter’s travel behavior from the perspective of the commuter’s social-economic and physical psychological burden. The result of this study shows that the more expansion urban areas in metropolitan areas, the more increasingly causing problems in commuting from the suburbs to activities centers, in term of longer travel distances, longer travel times, more travel cost, and all these cause commuter stress, and more robust for the lower-income groups.
Mapping the green open spaces system in the sub-district of Tangerang, Tangerang City of Banten
Authors: Budiyanti R B , Ardila S
Published: April 2021

Law of the Republic of Indonesia Number 26 of 2007 concerning Spatial Planning states that the proportion of green open space in a city area is at least 30 (thirty) percent of the area of an urban area. Tangerang city as one of the cities in the Greater Jakarta area with an area of 17,729,746 hectares, has 13 districts. One of them is Tangerang District which has the most extensive and diverse green open space compared to other districts, but it has not reached 30 percent. In addition, the existing green open space is not connected to one another, so it has not formed a system that can increase the green open space. This study is to find out whether green open space in Tangerang sub-district has the opportunity to form a green space system, in an effort to increase its area. Examination of the green space system can be done by looking at the landscape structure and land use. The overlay method is used to determine the opportunities and green space system that is suitable for Tangerang sub-districts. The results showed that the green open space in Tangerang sub-district had the opportunity to be developed as a green open space system with a linear pattern.
Assessment of local communities capacities on developing ethnographic tourism of Kampung Naga, West Java, Indonesia
Authors: Djatmiko A , Syarifuddin D , Raharja A B , Fitriani S A
Published: April 2021

This study aims to examine the capacity of local communities in the administration of tourism. Ethnographic tourism is one of the popular products built in Tasikmalaya Regency. It is known as the capital of Kabarataan of Galunggung which has a Sundanese culture style that is rich with local customs. This is an opportunity to promote Sundanese arts and culture as well as concerns of disruption caused by open access to outside communities. Kampung Naga offers physical and non-physical potential which gives a unique experience for tourists. The improvement of local community and their capability in managing tourism have a significant role on developing ethnographic tourism. The research method used is in the form of descriptive qualitative through several stages; an interview to a stakeholder of tourism organizers in Kampung Naga, an act of compiling community capacity data using radar diagrams, and an interpretation of community capacity in zoning the village area. Based on the analysis, the development of tourism activities in Kampung Naga actually provides economic benefits for local people and education of human and natural harmony for visitors. Local people also have a good capacity in maintaining the socio-cultural identity and the use of the environment in developing sustainable tourism.
Research in the effectiveness of acid treatments productive formations on oil fields in Western Siberia
Authors: Akopov A S , Yanukyan A P , Kushch I I , Kaverzin S A , Beketov S B
Published: April 2021

The Article studies the efficiency of acid bottom-hole formations treatment dependence in productive zones of the Sangopai formation from various technological parameters. The correlation dependencies of the average production rate of oil before and after acid treatment in addition to the analysis of acid treatment influence on the injection wells infectivity are presented. The purpose of this research is to determine the most optimal technological parameters of bottom-hole formation zone acid treatment.
Open-source deep-learning software for bioimage segmentation
Authors: Lucas Alice M. , Ryder Pearl V. , Li Bin , Cimini Beth A. , Eliceiri Kevin W. , Carpenter Anne E.
Published: April 2021

Microscopy images are rich in information about the dynamic relationships among biological structures. However, extracting this complex information can be challenging, especially when biological structures are closely packed, distinguished by texture rather than intensity, and/or low intensity relative to the background. By learning from large amounts of annotated data, deep learning can accomplish several previously intractable bioimage analysis tasks. Until the past few years, however, most deep-learning workflows required significant computational expertise to be applied. Here, we survey several new open-source software tools that aim to make deep-learning–based image segmentation accessible to biologists with limited computational experience. These tools take many different forms, such as web apps, plug-ins for existing imaging analysis software, and preconfigured interactive notebooks and pipelines. In addition to surveying these tools, we overview several challenges that remain in the field. We hope to expand awareness of the powerful deep-learning tools available to biologists for image analysis.
Optimal management of older people with frailty non-weight bearing after lower limb fracture: a scoping review
Authors: Aloraibi Saleh , Booth Vicky , Robinson Katie , Lunt Eleanor Katharine , Godfrey Deborah , Caswell Alan , Kerr Margaret , Ollivere Benjamin , Gordon Adam Lee , Gladman J R F
Published: April 2021

Background

Patients with lower limb fractures who are non-weight bearing are at risk of the complications of the associated immobility and disability, particularly people with frailty, but there is lack of clarity about what constitutes optimal care for such patients. A scoping literature review was conducted to explore what evidence is available for the management of this patient group.

Methods

MEDLINE (PubMed) CINAHL, EMBASE and the Cochrane databases of published literature and the HMIC and SIGLE sites for grey literature were searched for primary research studies and expert reports, using an iterative approach initially including the key term ‘non-weight bearing’. All study types were included. Analysis was by narrative synthesis.

Results

No papers were identified from a search using the key phrase ‘non-weight bearing’. With this term removed, 11 indirectly relevant articles on lower limb fractures were retrieved from the searches of the electronic databases comprising three observational studies, five non-systematic review articles, a systematic review, an opinion piece and a survey of expert opinion that had relevance to restricted weight bearing patients. The observational studies indicated depression, cognition and nutrition affect outcome and hence have indirect relevance to management. The non-systematic reviews articles emphasised the importance of maintaining strength and range of movement during immobilisation and advised an orthogeriatric model of care. Fourteen UK and 97 non-UK guidelines relevant to fragility fractures, falls and osteoporosis management were found in the grey literature, but none made specific recommendations regarding the management of any period of non-weight bearing.

Discussion

These findings provide a summary of the evidence base that can be used in the development of a clinical guideline for these patients but is not sufficient. We propose that, a guideline should be developed for these patients using an expert consensus process.
Using Machine Learning to Identify and Investigate Moderators of Alcohol Use Intervention Effects in Meta-Analyses
Authors: Parr Nicholas J , Loan Christopher M , Tanner-Smith Emily E
Published: April 2021

Aims

To illustrate a machine learning-based approach for identifying and investigating moderators of alcohol use intervention effects in aggregate-data meta-analysis.

Methods

We illustrated the machine learning technique of random forest modeling using data from an ongoing meta-analysis of brief substance use interventions implemented in general healthcare settings. A subset of 40 trials testing brief alcohol interventions (BAIs) was used; these trials provided 344 estimates of post-intervention effects on participants’ alcohol use as well as data on 20 potential moderators of intervention effects. These candidate moderators included characteristics of trial methodology and implementation, intervention design and participant samples.

Results

The best-fitting random forest model identified 10 important moderators from the pool of 20 candidate moderators. Meta-regression utilizing the selected moderators found that inclusion of prescriptive advice in a BAI session significantly moderated BAI effects on alcohol use. Observed effects were also significantly moderated by several methodological characteristics of trials, including the type of comparison group used, the overall level of attrition and the strategy used to address missing data. In a meta-regression model that included all candidate moderators, fewer coefficients were found to be significant, indicating that the use of a preliminary data reduction technique to identify only important moderators for inclusion in final analyses may have yielded improved statistical power to detect moderation.

Conclusions

Machine learning methods can be valuable tools for clarifying the influence of trial, intervention and sample characteristics on alcohol use intervention effects, in particular when numerous candidate moderators are available.
Protlego: a Python package for the analysis and design of chimeric proteins
Authors: Ferruz Noelia , Noske Jakob , Höcker Birte
Published: April 2021

Motivation

Duplication and recombination of protein fragments have led to the highly diverse protein space that we observe today. By mimicking this natural process, the design of protein chimeras via fragment recombination has proven experimentally successful and has opened a new era for the design of customizable proteins. The in silico building of structural models for these chimeric proteins, however, remains a manual task that requires a considerable degree of expertise and is not amenable for high-throughput studies. Energetic and structural analysis of the designed proteins often require the use of several tools, each with their unique technical difficulties and available in different programming languages or web servers.

Results

We implemented a Python package that enables automated, high-throughput design of chimeras and their structural analysis. First, it fetches evolutionarily conserved fragments from a built-in database (also available at fuzzle.uni-bayreuth.de). These relationships can then be represented via networks or further selected for chimera construction via recombination. Designed chimeras or natural proteins are then scored and minimized with the Charmm and Amber forcefields and their diverse structural features can be analyzed at ease. Here, we showcase Protlego’s pipeline by exploring the relationships between the P-loop and Rossmann superfolds, building and characterizing their offspring chimeras. We believe that Protlego provides a powerful new tool for the protein design community.

Availability and implementation

Protlego runs on the Linux platform and is freely available at (https://hoecker-lab.github.io/protlego/) with tutorials and documentation.

Supplementary information

Supplementary data are available at Bioinformatics online.
Wood anatomy of the crown lineages in Proteoideae (Proteaceae): implications for evolution and adaptive value of bordered pits in imperforate tracheary elements
Authors: Stepanova A V , Akinlabi F M , Sebiloane K , Van Wyk B-E , Oskolski A A
Published: April 2021

As Proteaceae subfamily Proteoideae are richly represented in the Cape Floristic Region of southern Africa and in south-western Australia, it is a convenient group for comparative studies of evolution and adaptation of plants in widely separated areas with a Mediterranean-type climate. Although species of Proteoideae attract considerable attention of researchers, the structural diversity of wood in this group remains under-explored. The wood structure of 51 species of 14 African and Australian genera of Proteoideae (Proteaceae) has been studied. These taxa are uniform in their wood structure; the diversity patterns are more related to plant stature, climatic factors and fire-survival strategies than to the taxonomy or phylogeny of the subfamily. Increases in length and diameter of fibres and diameter of pits in fibre walls are associated with a shift from a semi-arid winter-dry climate to a milder climate with winter rainfall. These trends may imply the transition from non-conducting imperforate tracheary elements to conducting elements in Mediterranean-type climatic regions. This presumable gain of hydraulic function of imperforate tracheary elements could be explained by adaptation to freeze–thaw stress during the late Quaternary, at least in the Cape Region. Vessel grouping shows no correlations with climatic factors. The seeders have a higher vessel frequency and narrower and lower rays than sprouters. We hypothesize that the larger rays in overground stems of sprouters serve as the sites of epicormic buds that provide for resprouting after fire or other damage. The occurrence of sclerified cells and/or irregularly arranged (occasionally circular) tracheary elements in broad rays of some species are thought to be responses to excessive sucrose transport in secondary phloem.
Olfaction inAnophelesmosquitoes
Authors: Konopka Joanna K , Task Darya , Afify Ali , Raji Joshua , Deibel Katelynn , Maguire Sarah , Lawrence Randy , Potter Christopher J
Published: April 2021

As vectors of disease, mosquitoes are a global threat to human health. The Anopheles mosquito is the deadliest mosquito species as the insect vector of the malaria-causing parasite, which kills hundreds of thousands every year. These mosquitoes are reliant on their sense of smell (olfaction) to guide most of their behaviors, and a better understanding of Anopheles olfaction identifies opportunities for reducing the spread of malaria. This review takes a detailed look at Anopheles olfaction. We explore a range of topics from chemosensory receptors, olfactory neurons, and sensory appendages to behaviors guided by olfaction (including host-seeking, foraging, oviposition, and mating), to vector management strategies that target mosquito olfaction. We identify many research areas that remain to be addressed.
Medium-Term Outcomes in Severely to Critically Ill Patients With Severe Acute Respiratory Syndrome Coronavirus 2 Infection
Authors: Gautam Nandan , Madathil Shyam , Tahani Natascia , Bolton Shaun , Parekh Dhruv , Stockley James , Goyal Shraddha , Qureshi Hannah , Yasmin Sadhika , Cooper Brendan G , Short Jennifer , Geberhiwot Tarekegn
Published: April 2021

Background

The medium- and long-term effects of severe acute respiratory syndrome coronavirus 2 infection on survivors are unknown. In the current study, we assessed the medium-term effects of coronavirus disease 2019 (COVID-19) on survivors of severe disease.

Methods

This is a retrospective, case series of 200 patients hospitalized across 3 large Birmingham hospitals with severe-to-critical COVID-19 infection 4–7 months from disease onset. Patients underwent comprehensive clinical, laboratory, imaging, lung function tests (LFTs), and quality of life and cognitive assessments.

Results

At 4–7 months after disease onset, 63.2% of patients reported persistent breathlessness; 53.5%, significant fatigue; 37.5%, reduced mobility; and 36.8% pain. Serum markers of inflammation and organ injuries that persisted at hospital discharge had normalized on follow-up, indicating no sustained immune response causing chronic maladaptive inflammation. Chest radiographs showed complete resolution in 82.8%, and significant improvement or no change in 17.2%. LFTs revealed gas transfer abnormalities in 80.0% and abnormal spirometric values in 37.6% of patients. Compared with patients who did not experience breathlessness, those who did had significantly higher incidences of comorbid conditions and residual chest radiographic and LFT abnormalities (P < .01 to all). For all parameters assessed and persisting symptoms there were no significant differences between patients in hospital wards and those in intensive treatment units. All patients reported a significantly reduced quality of life in all domains of the EQ-5D-5L quality-of-life measures.

Conclusions

A significant proportion of severely ill patients with COVID-19 still experience symptoms of breathlessness, fatigue, pain, reduced mobility, depression and reduced quality of life 4–7 months after disease onset. Symptomatic patients tend to have more residual chest radiographic and LFT abnormalities.