Evaluation of crop growing periods at some stations in northest Brazil

Results of a study of crop .growing periods at some stations in northeast Brazil are presented in this paper. Daily soil moisture values for a minimum period of 25 years are evaluated by means of a simple soil moisture model using temperature and precipitation data. A first order Markov chain model is applied to the soil moisture data and initial and conditional probabilities of wet and dry soil days are obtained. Soil moisture averages and probabilities are used to evaluate crop growing periods at the stations. The effect of uncertainties in the model parameters on the estimated growing periods is investigated.

A climatological study of soil moisture under corn crop at Campina Grande (NE Brazil)

ABSTRACT. Results of a climatological study of soil moisture under corn crop at Campina Grande (NE Brazil) are presented in this paper. Daily values of available moisture content during the crop growing period are evaluated for a period of 25 years. A six zone versatile soil moisture budget model is used for this purpose and approximately 5. 7.5, 12.5, 25, 25 and 25% of the available water capacity (AWC) are attributed to zones one to six respectively. Different root activity coefficients are assumed for the six zones in different growth stages and the dependence of these coefficients on moisture content is taken into consideration. The same moisture releasing characteristics are assumed for all soil zones. On rainy days moisture loss due to evapotranspiration is assumed to take place before precipitation. Four AWC values and three corn growing periods between March and September are considered in this study. A first order Markov chain model is applied to the daily soil moisture data. Soil moisture averages and probabilities are used to identify the optimum growing period for corn at this station. The irrigation requirements of the crop are briefly discussed.

SARS-CoV-2 and MERS-CoV Share the Furin Site CGG-CGG Genetic Footprint

At present, the polybasic furin cleavage site on the spike glycoprotein of the SARS-CoV-2 is still a missing link. Remarkably, the two arginine residues this of site are encoded by the CGG arginine codon, which is rare in Betacoronavirus proteins. Arginine dimers are common at viral furin sites, but are not CGG-CGG encoded. The question is: Is that genetic footprint, encoding arginine pairs, unique to the SARS-CoV-2? To address the issue, using Perl scripts, here I dissect in detail the NCBI Virus database in order to report the arginine dimers that exist in Betacoronavirus proteins. As main result, a set of Middle East respiratory syndrome-related coronavirus (MERS-CoV) (isolates: camel/Nigeria/NVx/2016, host: Camelus dromedarius) have the CGG-CGG encoded arginine pair in the spike protein polybasic furin cleavage site. In addition, CGG-CGG encoded arginine pairs were also found in the orf1ab polyprotein from HKU9 and HKU14 Betacoronavirus, as well as, in the nucleocapsid phosphoprotein from few SARS-CoV-2 isolates. To quantify the presence probability of CGG-CGG arginine-arginine in Betacoronavirus, a First-Order Markov Chain was defined. It is highly unlikely to find it in betacoronaviruses wildlife, but it is there. Collectively, results shed light on recombination as origin of the virus CGG-CGG arginine dimer in the S1/S2 cleavage site.

Dynamics of rice production among the food crops of Tanzania

Rice is an important crop in Tanzania which contributes significantly to the farmers, consumers, and the government. Recognising this importance, the government has made initiatives to attain rice self-sufficiency. These initiatives are crucial in contributing to regional self-sufficiency, enabling rice market leadership, and injecting productivity through significant improvements in the quality, quantity, and value of rice produced in Tanzania. We investigated the dynamics of rice area, production, and productivity and identified shifts in the land-use patterns in Tanzania. To analyse secondary data collected over a 33-year period from 1986/1987 to 2018/2019, we used compound annual growth rates, Cuddy-Della Valle Index and a first-order Markov chain approach. We found that the growth in the areas under rice cultivation, production and productivity were inconsistent as evidenced by the presence of instabilities. Rice remains the third most stable crop in the country in terms of area under production retention; however, this might decline in the next 2 years. Policies in future must enable strategies to increase productivity as well as promote high-yielding varieties, efficient input usage, and irrigation infrastructure development.

Online to offline social interaction on gaming motivations

PurposeThis research examined the social interactions of online game players based on the proposed motivation model in order to understand the transitions of motivation of online game. The authors also separated samples into four categories to compare the difference of different type of online game players.Design/methodology/approachThis study proposed a motivation model for online game player based on existence–relatedness–growth theory. The authors also analyze the transitions of motivations via first-order and second-order Markov chain switching model to obtain the journey of online to offline socialization.FindingsTeamwork–socialization players preferred to make friends in their online gaming network to socialize. Competition–socialization players were mostly students who played games to compete and socialize and may share experience in online or offline activities. Teamwork–mechanics players purely derived pleasure from gaming and were not motivated by other factors in their gaming activities. Competition–mechanics players may already have friends with other gamers in real life.Research limitations/implicationsMore samples can be added to generate more generalizable findings and the proposed motivation model can be extended by other motivations related to online gaming behavior. The authors proposed a motivation model for online to offline socialization and separated online game players into four categories: teamwork–socialization, competition–socialization, teamwork–mechanics and competition–mechanics. The category of teamwork–socialization may contribute to online to offline socialization area. The category of competition–mechanics may add value to the area of traditional offline socialization. The categories of competition–socialization and teamwork–mechanics may help extant literature understand critical stimulus for online gaming behavior.Practical implicationsThe authors’ findings can help online gaming industry understand the motivation journey of players through transition. Different types of online games may have various online game player's journey that can assist companies in improving the quality of online games. Online game companies can also offer official community to players for further interaction and experience exchange or the platform for offline activities in the physical environment.Originality/valueThis research proposed a novel motivation model to examine online to offline socializing behavior for online game research. The motivations in model were interconnected via the support of literature. The authors also integrated motivations by Markov chain switching model to obtain the transitions of motivational status. It is also the first attempt to analyze first-order and second-order Markov chain switching model for analysis. The authors’ research examined the interconnected relationships among motivations in addition to the influential factors to online gaming behavior from previous research. The results may contribute to extend the understanding of online to offline socialization in online gaming literature.

Design Embedding: Representation Learning of Design Thinking to Cluster Design Behaviors

Design thinking is essential to the success of a design process as it helps achieve the design goal by guiding design decision-making. Therefore, fundamentally understanding design thinking is vital for improving design methods, tools and theories. However, interpreting design thinking is challenging because it is a cognitive process that is hidden and intangible. In this paper, we represent design thinking as an intermediate layer between human designers’ thought processes and their design behaviors. To do so, this paper first identifies five design behaviors based on the current design theories. These behaviors include design action preference, one-step sequential behavior, contextual behavior, long-term sequential behavior, and reflective thinking behavior. Next, we develop computational methods to characterize each of the design behaviors. Particularly, we use design action distribution, first-order Markov chain, Doc2Vec, bi-directional LSTM autoencoder, and time gap distribution to characterize the five design behaviors. The characterization of the design behaviors through embedding techniques is essentially a latent representation of the design thinking, and we refer to it as design embeddings. After obtaining the embedding, an X-mean clustering algorithm is adopted to each of the embeddings to cluster designers. The approach is applied to data collected from a high school solar system design challenge. The clustering results show that designers follow several design patterns according to the corresponding behavior, which corroborates the effectiveness of using design embedding for design behavior clustering. The extraction of design embedding based on the proposed approach can be useful in other design research, such as inferring design decisions, predicting design performance, and identifying design actions identification.

The dynamics of social deprivation in Mexico

This paper aims to model the dynamics of social deprivation in Mexico using a Markovian approach. First, we establish a scenario where a list of items characterizing social deprivation evolves as a first-order Markov chain under the sample period (2002-2012). Then, we estimate latent states and ergodic vectors of a hidden-Markov model to verify the strength of the conclusions drawn from such a scenario. After collecting results from both kinds of analyses, we find a similar pattern of impoverishment. The paper's conclusions state that the evolution of Mexico's deprivation profile may slightly worsen soon.

Analysis of a Batch Arrival, Batch Service Queuing-Inventory System with Processing of Inventory While on Vacation

A single-server queuing-inventory system in which arrivals are governed by a batch Markovian arrival process and successive arrival batch sizes form a finite first-order Markov chain is considered in this paper. Service is provided in batches according to a batch Markovian service process, with consecutive service batch sizes forming a finite first-order Markov chain. A service starts for the next batch on completion of the current service, provided that inventory is available at that epoch; otherwise, there will be a delay in starting the next service. When the service of a batch is completed, the inventory decreases by 1 unit, irrespective of batch size. A control policy in which the server goes on vacation when a service process is frozen until a quorum can initiate the next batch service is proposed to ensure idle-time utilization. During the vacation, the server produces inventory (items) for future services until it hits a specified level L or until the number of customers in the system reaches a maximum service batch size N, with whichever occurring first. In the former case, a server stays idle once the processed inventory level reaches L until the number of customers reaches (or even exceeds because of batch arrival) a maximum service batch size N. The time required for processing one unit of inventory follows a phase-type distribution. In this paper, the steady-state probability vector of this infinite system is computed. The distributions of inventory processing time in a vacation cycle, idle time in a vacation cycle, and vacation cycle length are found. The effect of correlation in successive inter-arrival times and service times on performance measures for such a queuing system is illustrated with a numerical example. An optimization problem is considered. The proposed system is then compared with a queuing-inventory system without the Markov-dependent assumption on successive arrivals as well as service batch sizes using numerical examples.