scholarly journals Water Availability Forecasting Using Univariate and Multivariate Prophet Time Series Model for ACEA (European Automobile Manufacturers Association)

2021 ◽  
Vol 1 (2) ◽  
pp. 43-54
Author(s):  
Prismahardi Aji Riyantoko ◽  
Tresna Maulana Fahrudin ◽  
Kartika Maulida Hindrayani ◽  
Amri Muhaimin ◽  
Trimono
Keyword(s):  
Time Series ◽  
Water Availability ◽  
The Other ◽  
Multivariate Approach ◽  
Augmented Dickey Fuller ◽  
Decomposition Time ◽  
Groundwater Drainage ◽  
Data Transforming ◽  
Temperature Depth ◽  
Better Than

Time series is one of method to forecasting the data. The ACEA company has competition with opened the data in the Water Availability and uses the data to forecast. The dataset namely, Aquifers-Petrignano in Italy in water resources field has five parameters e.g. rainfall, temperature, depth to groundwater, drainage volume, and river hydrometry. In our research will be forecast the depth to groundwater data using univariate and multivariate approach of time series using Prophet Method. Prophet method is one of library which develop by Facebook team. We also use the other approach to making the data clean, or the data ready to forecast. We use handle missing data, transforming, differencing, decomposition time series, determine lag, stationary approach, and Augmented Dickey-Fuller (ADF). The all approach will be uses to make sure that the data not appearing the problem while we tried to forecast. In the other describe, we already get the results using univariate and multivariate Prophet method. The multivariate approach has presented the value of MAE 0.82 and RMSE 0.99, it’s better than while we forecast using univariate Prophet.

scholarly journals Forecasting COVID-19 in Pakistan

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242762
Author(s):  
Muhammad Ali ◽  
Dost Muhammad Khan ◽  
Muhammad Aamir ◽  
Umair Khalil ◽  
Zardad Khan
Keyword(s):  
Time Series ◽  
Prediction Interval ◽  
Arima Model ◽  
The Other ◽  
Time Series Models ◽  
Cumulative Number ◽  
Arima Models ◽  
Forecasting Accuracy ◽  
Statistical Measures ◽  
Better Than

Objectives Forecasting epidemics like COVID-19 is of crucial importance, it will not only help the governments but also, the medical practitioners to know the future trajectory of the spread, which might help them with the best possible treatments, precautionary measures and protections. In this study, the popular autoregressive integrated moving average (ARIMA) will be used to forecast the cumulative number of confirmed, recovered cases, and the number of deaths in Pakistan from COVID-19 spanning June 25, 2020 to July 04, 2020 (10 days ahead forecast). Methods To meet the desire objectives, data for this study have been taken from the Ministry of National Health Service of Pakistan’s website from February 27, 2020 to June 24, 2020. Two different ARIMA models will be used to obtain the next 10 days ahead point and 95% interval forecast of the cumulative confirmed cases, recovered cases, and deaths. Statistical software, RStudio, with “forecast”, “ggplot2”, “tseries”, and “seasonal” packages have been used for data analysis. Results The forecasted cumulative confirmed cases, recovered, and the number of deaths up to July 04, 2020 are 231239 with a 95% prediction interval of (219648, 242832), 111616 with a prediction interval of (101063, 122168), and 5043 with a 95% prediction interval of (4791, 5295) respectively. Statistical measures i.e. root mean square error (RMSE) and mean absolute error (MAE) are used for model accuracy. It is evident from the analysis results that the ARIMA and seasonal ARIMA model is better than the other time series models in terms of forecasting accuracy and hence recommended to be used for forecasting epidemics like COVID-19. Conclusion It is concluded from this study that the forecasting accuracy of ARIMA models in terms of RMSE, and MAE are better than the other time series models, and therefore could be considered a good forecasting tool in forecasting the spread, recoveries, and deaths from the current outbreak of COVID-19. Besides, this study can also help the decision-makers in developing short-term strategies with regards to the current number of disease occurrences until an appropriate medication is developed.

Closing the GAP—A 5Å Scanning Microscope

1969 ◽  
Vol 27 ◽  
pp. 6-7
Author(s):  
A. V. Crewe
Keyword(s):  
Normal Form ◽  
The Other ◽  
Resolving Power ◽  
Scanning Microscope ◽  
Conventional Microscope ◽  
Other Hand ◽  
Closing The Gap ◽  
Thermal Sources ◽  
Better Than ◽  
Transmission Microscope

We have become accustomed to differentiating between the scanning microscope and the conventional transmission microscope according to the resolving power which the two instruments offer. The conventional microscope is capable of a point resolution of a few angstroms and line resolutions of periodic objects of about 1Å. On the other hand, the scanning microscope, in its normal form, is not ordinarily capable of a point resolution better than 100Å. Upon examining reasons for the 100Å limitation, it becomes clear that this is based more on tradition than reason, and in particular, it is a condition imposed upon the microscope by adherence to thermal sources of electrons.

MUNDANE MIRACLES IN AWADH. ENCOUNTERS WITH THE REVEALED AND THE HIDDEN

2020 ◽  
pp. 130-140
Author(s):  
Maxim B. Demchenko ◽  
Keyword(s):  
The Other ◽  
Local People ◽  
Natural Phenomena ◽  
Mughal Empire ◽  
The Public ◽  
British Raj ◽  
The Subject ◽  
Other World ◽  
Better Than

The sphere of the unknown, supernatural and miraculous is one of the most popular subjects for everyday discussions in Ayodhya – the last of the provinces of the Mughal Empire, which entered the British Raj in 1859, and in the distant past – the space of many legendary and mythological events. Mostly they concern encounters with inhabitants of the “other world” – spirits, ghosts, jinns as well as miraculous healings following magic rituals or meetings with the so-called saints of different religions (Hindu sadhus, Sufi dervishes),with incomprehensible and frightening natural phenomena. According to the author’s observations ideas of the unknown in Avadh are codified and structured in Avadh better than in other parts of India. Local people can clearly define if they witness a bhut or a jinn and whether the disease is caused by some witchcraft or other reasons. Perhaps that is due to the presence in the holy town of a persistent tradition of katha, the public presentation of plots from the Ramayana epic in both the narrative and poetic as well as performative forms. But are the events and phenomena in question a miracle for the Avadhvasis, residents of Ayodhya and its environs, or are they so commonplace that they do not surprise or fascinate? That exactly is the subject of the essay, written on the basis of materials collected by the author in Ayodhya during the period of 2010 – 2019. The author would like to express his appreciation to Mr. Alok Sharma (Faizabad) for his advice and cooperation.

Producers' Response to Changes in Prices and Marketing Policies: A Case Study of Sugarcane and Paddy in Eastern U.P. by S. C. Gupta and A. Majid. New York: Asia Publishing House, 1965.

1968 ◽  
Vol 8 (2) ◽  
pp. 308-309
Author(s):  
Mohammad Irshad Khan
Keyword(s):  
New York ◽  
Time Series ◽  
Time Series Data ◽  
Publishing House ◽  
Economic Incentives ◽  
The Other ◽  
Series Data ◽  
Poor Countries ◽  
Northern India

It is alleged that the agricultural output in poor countries responds very little to movements in prices and costs because of subsistence-oriented produc¬tion and self-produced inputs. The work of Gupta and Majid is concerned with the empirical verification of the responsiveness of farmers to prices and marketing policies in a backward region. The authors' analysis of the respon¬siveness of farmers to economic incentives is based on two sets of data (concern¬ing sugarcane, cash crop, and paddy, subsistence crop) collected from the district of Deoria in Eastern U.P. (Utter Pradesh) a chronically foodgrain deficit region in northern India. In one set, they have aggregate time-series data at district level and, in the other, they have obtained data from a survey of five villages selected from 170 villages around Padrauna town in Deoria.

Temperature Effects during Endodormancy Induction on Subsequent Anthesis and Growth of Peach Trees

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 452c-452 ◽  
Author(s):  
Schuyler D. Seeley ◽  
Raymundo Rojas-Martinez ◽  
James Frisby
Keyword(s):  
Temperature Effects ◽  
Shoot Length ◽  
The Other ◽  
Nighttime Temperatures ◽  
Peach Trees ◽  
Better Than

Mature peach trees in pots were treated with nighttime temperatures of –3, 6, 12, and 18 °C for 16 h and a daytime temperature of 20 °C for 8 h until the leaves abscised in the colder treatments. The trees were then chilled at 6 °C for 40 to 70 days. Trees were removed from chilling at 40, 50, 60, and 70 days and placed in a 20 °C greenhouse under increasing daylength, spring conditions. Anthesis was faster and shoot length increased with longer chilling treatments. Trees exposed to –3 °C pretreatment flowered and grew best with 40 days of chilling. However, they did not flower faster or grow better than the other treatments with longer chilling times. There was no difference in flowering or growth between the 6 and 12 °C pretreatments. The 18 °C pretreatment resulted in slower flowering and very little growth after 40 and 50 days of chilling, but growth was comparable to other treatments after 70 days of chilling.

Forecasting based on spectral time series analysis: prediction of the Aurubis stock price

2020 ◽  
Vol 17 (4) ◽  
pp. 215-227
Author(s):  
Julia Babirath ◽  
Karel Malec ◽  
Rainer Schmitl ◽  
Kamil Maitah ◽  
Mansoor Maitah
Keyword(s):  
Time Series ◽  
Risk Management ◽  
Time Series Analysis ◽  
Wiener Process ◽  
Stock Price ◽  
Percentage Error ◽  
Portfolio Performance ◽  
Stock Price Prediction ◽  
Series Analysis ◽  
Augmented Dickey Fuller

The attempt to predict stock price movements has occupied investors ever since. Reliable forecasts are a basis for investment management, and improved forecasting results lead to enhanced portfolio performance and sound risk management. While forecasting using the Wiener process has received great attention in the literature, spectral time series analysis has been disregarded in this respect. The paper’s main objective is to evaluate whether spectral time series analysis can produce reliable forecasts of the Aurubis stock price. Aurubis poses a suitable candidate for an investor’s portfolio due to its sound economic and financial situation and the steady dividend policy. Additionally, reliable management contributes to making Aurubis an investment opportunity. To judge if the achieved forecast results can be considered satisfactory, they are compared against the simulation results of a Wiener process. After de-trending the time series using an Augmented Dickey-Fuller test, the residuals were compartmentalized into sine and cosine functions. The frequencies, amplitude, and phase were obtained using the Fast Fourier transform. The mean absolute percentage error measured the accuracy of the stock price prediction, and the results showed that the spectral analysis was able to deliver superior results when comparing the simulation using a Wiener process. Hence, spectral time series can enhance stock price forecasts and consequently improve risk management.

Nglyc: A Random Forest Method for Prediction of N-Glycosylation Sites in Eukaryotic Protein Sequence

2020 ◽  
Vol 27 (3) ◽  
pp. 178-186 ◽  
Author(s):  
Ganesan Pugalenthi ◽  
Varadharaju Nithya ◽  
Kuo-Chen Chou ◽  
Govindaraju Archunan
Keyword(s):  
Random Forest ◽  
Protein Sequence ◽  
Glycosylation Site ◽  
Computational Method ◽  
The Other ◽  
Eukaryotic Protein ◽  
Random Forest Method ◽  
Glycosylation Sites ◽  
Human And Mouse ◽  
Better Than

Background: N-Glycosylation is one of the most important post-translational mechanisms in eukaryotes. N-glycosylation predominantly occurs in N-X-[S/T] sequon where X is any amino acid other than proline. However, not all N-X-[S/T] sequons in proteins are glycosylated. Therefore, accurate prediction of N-glycosylation sites is essential to understand Nglycosylation mechanism. Objective: In this article, our motivation is to develop a computational method to predict Nglycosylation sites in eukaryotic protein sequences. Methods: In this article, we report a random forest method, Nglyc, to predict N-glycosylation site from protein sequence, using 315 sequence features. The method was trained using a dataset of 600 N-glycosylation sites and 600 non-glycosylation sites and tested on the dataset containing 295 Nglycosylation sites and 253 non-glycosylation sites. Nglyc prediction was compared with NetNGlyc, EnsembleGly and GPP methods. Further, the performance of Nglyc was evaluated using human and mouse N-glycosylation sites. Results: Nglyc method achieved an overall training accuracy of 0.8033 with all 315 features. Performance comparison with NetNGlyc, EnsembleGly and GPP methods shows that Nglyc performs better than the other methods with high sensitivity and specificity rate. Conclusion: Our method achieved an overall accuracy of 0.8248 with 0.8305 sensitivity and 0.8182 specificity. Comparison study shows that our method performs better than the other methods. Applicability and success of our method was further evaluated using human and mouse N-glycosylation sites. Nglyc method is freely available at https://github.com/bioinformaticsML/ Ngly.

pLoc_bal-mEuk: Predict Subcellular Localization of Eukaryotic Proteins by General PseAAC and Quasi-balancing Training Dataset

2019 ◽  
Vol 15 (5) ◽  
pp. 472-485 ◽  
Author(s):  
Kuo-Chen Chou ◽  
Xiang Cheng ◽  
Xuan Xiao
Keyword(s):  
Drug Development ◽  
Subcellular Localization ◽  
Basic Research ◽  
The Other ◽  
Training Dataset ◽  
Sequence Information ◽  
Eukaryotic Proteins ◽  
Validation Tests ◽  
User Friendly ◽  
Better Than

<P>Background/Objective: Information of protein subcellular localization is crucially important for both basic research and drug development. With the explosive growth of protein sequences discovered in the post-genomic age, it is highly demanded to develop powerful bioinformatics tools for timely and effectively identifying their subcellular localization purely based on the sequence information alone. Recently, a predictor called “pLoc-mEuk” was developed for identifying the subcellular localization of eukaryotic proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems where many proteins, called “multiplex proteins”, may simultaneously occur in two or more subcellular locations. Although it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mEuk was trained by an extremely skewed dataset where some subset was about 200 times the size of the other subsets. Accordingly, it cannot avoid the biased consequence caused by such an uneven training dataset. </P><P> Methods: To alleviate such bias, we have developed a new predictor called pLoc_bal-mEuk by quasi-balancing the training dataset. Cross-validation tests on exactly the same experimentconfirmed dataset have indicated that the proposed new predictor is remarkably superior to pLocmEuk, the existing state-of-the-art predictor in identifying the subcellular localization of eukaryotic proteins. It has not escaped our notice that the quasi-balancing treatment can also be used to deal with many other biological systems. </P><P> Results: To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mEuk/. </P><P> Conclusion: It is anticipated that the pLoc_bal-Euk predictor holds very high potential to become a useful high throughput tool in identifying the subcellular localization of eukaryotic proteins, particularly for finding multi-target drugs that is currently a very hot trend trend in drug development.</P>

scholarly journals Chance or Necessity—The Fungi Co−Occurring with Formica polyctena Ants

Insects ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 204
Author(s):  
Igor Siedlecki ◽  
Michał Gorczak ◽  
Alicja Okrasińska ◽  
Marta Wrzosek
Keyword(s):  
Molecular Identification ◽  
High Frequency ◽  
Its Rdna ◽  
The Other ◽  
Formica Polyctena ◽  
Ant Nests ◽  
Mutualistic Fungi ◽  
The Tropics ◽  
High Diversity ◽  
Better Than

Studies on carton nesting ants and domatia−dwelling ants have shown that ant–fungi interactions may be much more common and widespread than previously thought. Until now, studies focused predominantly on parasitic and mutualistic fungi–ant interactions occurring mostly in the tropics, neglecting less−obvious interactions involving the fungi common in ants’ surroundings in temperate climates. In our study, we characterized the mycobiota of the surroundings of Formica polyctena ants by identifying nearly 600 fungal colonies that were isolated externally from the bodies of F. polyctena workers. The ants were collected from mounds found in northern and central Poland. Isolated fungi were assigned to 20 genera via molecular identification (ITS rDNA barcoding). Among these, Penicillium strains were the most frequent, belonging to eight different taxonomic sections. Other common and widespread members of Eurotiales, such as Aspergillus spp., were isolated very rarely. In our study, we managed to characterize the genera of fungi commonly present on F. polyctena workers. Our results suggest that Penicillium, Trichoderma, Mucor, Schwanniomyces and Entomortierella are commonly present in F. polyctena surroundings. Additionally, the high diversity and high frequency of Penicillium colonies isolated from ants in this study suggest that representatives of this genus may be adapted to survive in ant nests environment better than the other fungal groups, or that they are preferentially sustained by the insects in nests.

scholarly journals Women in Violent Extremism in Sweden

Proceedings ◽  
2021 ◽  
Vol 77 (1) ◽  
pp. 15
Author(s):  
Hernan Mondani ◽  
Amir Rostami ◽  
Tina Askanius ◽  
Jerzy Sarnecki ◽  
Christofer Edling
Keyword(s):  
Mental Disorders ◽  
The Other ◽  
Average Score ◽  
Far Right ◽  
Employment Share ◽  
Study Population ◽  
Role Of Women ◽  
Islamic Extremism ◽  
Better Than

This presentation summarizes a register-based study on women who have been identified as belonging to three violent extremist milieus in Sweden: violent Islamic, violent far-right, and violent far-left extremism. We studied the women in these milieus along a number of analytical dimensions, ranging from demographic and educational to criminal background and network relationships, and compared them to three reference groups: (i) non-extremist biological sisters to female extremists in the study population; (ii) men in the respective extremist milieus; and (iii) female members of other antagonistic milieus such as organized crime. Our results showed that there are both similarities and differences between groups. In some cases, like age and region of birth, there are commonalities between violent far-right and violent far-left women. Regarding region of birth and migration background, women affiliated to violent far-right and violent far-left extremism are predominantly born in Sweden. Women affiliated to violent Islamic extremism tend to be born in Sweden to a greater extent than men in the same milieu, but to a much lesser degree than women in the violent far-right and violent far-left. When it comes to education, women in the violent Islamic milieu are closer to women in violent far-right extremism. Women in violent far-left extremism perform best at school, with consistently higher grades. The average score of women in violent far-left extremism is identical to that of their sisters, and women in violent far-left extremism perform on average substantially better than men in the same milieu. Women in violent Islamic extremism, in contrast, perform on average similarly to men in violent far-left extremism, and they perform better than their biological sisters. Regarding labor market attachment, violent Islamic extremists have the weakest attachment and the highest dependency upon financial assistance as well as a low employment share (36 percent in 2016), but also a relatively high share of individuals with a high number of unemployment days, suggesting that women in violent Islamic extremism experience higher social exclusion. We find the highest employment share among women in violent far-left extremism, where 89 percent are gainfully employed in 2016 (80 percent for at least three of the last five years) and about a 20 percent unemployment share. Men in violent far-left extremism have an employment share around 10 percent below that of the women in far-left extremism for 2016. The highest fractions of individuals that have not been in contact with the health system due to mental disorders are among violent Islamic extremism, with the women’s fraction at 84 percent, compared to their non-extremist sisters and men in the same milieu that are just above 79 percent. Women in violent far-left extremism have the highest share of in-patient major mental disorders among the extremist milieus (3 percent), higher than men in the same milieu (less than 1 percent) as well as than women and their sisters in the other categories. During the period 2007–2016, 68 percent of individuals in the extremist milieus are covered by the register of suspected individuals. The coverage is substantially higher for men, 72 percent than for women, 43 percent. Compared to their sisters, women in all three milieus are criminally active to a much higher extent. However, women in all three milieus are less criminally active than women in other antagonistic milieus, among whom 67 percent have been suspected at least once. In all three milieus, the share of men with a criminal record is about twice as large as that of women. As far as the gender aspect is concerned, we know that extremist milieus generally have a conservative view of the role of women in society. In our results, this is reflected in the low rates of crime in women compared to men, and relatively marginal positions in the co-offending networks. The fact that women in violent far-left extremism have stronger positions in their networks than the other women in the study population is expected, given that the ideology of this milieu allows for greater equality. This means that women in violent far-left extremism participate more often than, e.g., women in violent far-right extremism, in political actions where violence is common. This pattern of gender roles and criminal involvement also holds concerning women in violent Islamic extremism. This milieu has a more traditional view of the role of women than views among even violent far-right extremists. Women in violent Islamic extremism are less involved in crime and, in particular, violent crime.

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