Spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level

In recent history, Coronavirus Disease 2019 (COVID-19) is one of the worst infectious disease outbreaks affecting humanity. The World Health Organization has defined the outbreak of COVID-19 as a pandemic, and the massive growth of the number of infected cases in a short time has caused enormous pressure on medical systems. Mexico surpassed 3.7 million confirmed infections and 285,000 deaths on October 23, 2021. We analysed the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We computed weekly Moran’s I index to assess spatial autocorrelation over time and identify clusters of the disease using the “flexibly shaped spatial scan” approach. Finally, we compared Euclidean, cost, resistance distances and gravitational model to select the best-suited approach to predict inter-municipality contagion. We found that COVID-19 pandemic in Mexico is characterised by clusters evolving in space and time as parallel epidemics. The gravitational distance was the best model to predict newly infected municipalities though the predictive power was relatively low and varied over time. This study helps us understand the spread of the epidemic over the Mexican territory and gives insights to model and predict the epidemic behaviour.

Reflection of India-China Relations in Indian Media: Problems and Perspectives

China and India interactions are dominated by strategic and business concerns. Despite the massive growth of bilateral trade between China and India, tensions over territorial and political issues have also grown, particularly in the last years. These effects are mediated and often inflamed by media depictions and perceptions of these tensions. India and China are both aware that peace and cooperation are essential. But it seems some media are more intent on fanning the flames than focusing on the ties that bind the two ancient civilizations. The media can play a constructive role in promoting mutual understanding. This paper deals with different areas of bilateral competition and convergence covered by the media as well as discusses the key differences between the Indian medias coverage of China and the Chinese medias reporting on India of the last years and especially in 2020. The article proposes to discover the problems and perspectives of the Indian media in India-China relations today.

Do Financial Literacy and Technology Affect Intention to Invest in the Capital Market in the Early Pandemic Period?

Research aims: This paper discusses the effect of financial literacy and automatic investment technology on intention to invest in the capital market during the early pandemic.Design/Methodology/Approach: The research population was students studying economics and finance in institutions located in Yogyakarta Special Region Province. The sample of 384 respondents was obtained through questionnaires distributed online. To test the impact of financial literacy and automatic investment technology on intention to participate in the capital market, multiple linear regression was used.Research findings: The researchers found that financial literacy and automatic investment technology affected students’ intention to invest in the capital market. The number of students with a moderate level of financial literacy score dominated, followed by the students with low and high literacy scores. Besides, students’ background in economic and finance appeared inadequate to solely determine the financial literacy score.Theoretical contribution/Originality: This paper contributes to the investment area, especially related to the automatic investment technology “Robo advisor,” that is still rarely studied yet, which will be a significant issue in the future. It also provides empirical results, which explain the investment intention through financial literacy. Moreover, this study was conducted during the massive growth of investors in Indonesia during the pandemic.Practitioner/Policy implication: This study provides a useful reference to the financial sector, especially the capital market. Inclusive programs regarding financial literacy should be expanded for wider society to enhance their knowledge and dismiss lack of confidence in capital market participation. Private sectors providing automatic investment technology are suggested to continue developing a more convenient application to be accessible by a broader range of society.Research limitation/Implication: The research included only students as the sample; hence, further research may use a larger area of the sample with various backgrounds and ages. Other determinants, such as norms, environment, risk, and more advanced financial literacy measurement, can also be added to enrich future studies and literature.

Reconfigurable Neighborhood—Mechatronisation of the Urban Design

Today more than half of the world’s population lives in cities not yet ready for the massive growth and adaptation required to meet global urbanization predicted for the next decades. The planning, design, and urban governance must urgently evolve. Future cities should become more efficient, inclusive, and sustainable. The intelligent town we anticipate combines the concepts of new information flow as well as research proposals for the design, upgrade of buildings and municipal infrastructure using robots and mechatronic systems at the scale of dwelling, building, neighborhood, district or town. This article presents the conceptual framework for the role of kinetic and responsive design at the scale of small urban areas, taking into account dynamic adaptation to users’ needs and changing environmental conditions across a day, week, month and year.

Special Issue on Emerging Trends and Challenges in Supervised Learning Tasks

With the massive growth of data-intensive applications, the machine learning field has gained widespread popularity [...]

Development of a Low-Cost Optical Sensor to Detect Eutrophication in Irrigation Reservoirs

In irrigation ponds, the excess of nutrients can cause eutrophication, a massive growth of microscopic algae. It might cause different problems in the irrigation infrastructure and should be monitored. In this paper, we present a low-cost sensor based on optical absorption in order to determine the concentration of algae in irrigation ponds. The sensor is composed of 5 LEDs with different wavelengths and light-dependent resistances as photoreceptors. Data are gathered for the calibration of the prototype, including two turbidity sources, sediment and algae, including pure samples and mixed samples. Samples were measured at a different concentration from 15 mg/L to 4000 mg/L. Multiple regression models and artificial neural networks, with a training and validation phase, are compared as two alternative methods to classify the tested samples. Our results indicate that using multiple regression models, it is possible to estimate the concentration of alga with an average absolute error of 32.0 mg/L and an average relative error of 11.0%. On the other hand, it is possible to classify up to 100% of the samples in the validation phase with the artificial neural network. Thus, a novel prototype capable of distinguishing turbidity sources and two classification methodologies, which can be adapted to different node features, are proposed for the operation of the developed prototype.

Loyalty of Paratransit Users in the Era of Competition with Ride Sourcing

As a mode serving urban mobility in developing countries, paratransit is experiencing competition with the fast and massive growth of ride sourcing. This study aims to investigate the loyalty of paratransit users in Bandung, Indonesia, in the era of competition with ride sourcing. Data collected by questionnaires and distributed to 400 paratransit users in Bandung were analysed using hierarchical structural equation modelling. The analysis shows that satisfaction is positively influenced by service quality variables. Though there is less satisfaction compared to the previous decade, satisfaction with the service still has a positive influence on total satisfaction with the mode. It can also be concluded that loyalty is positively influenced by satisfaction. Satisfaction with the image and the unique characteristics of paratransit retains passengers' intentions toward loyalty in the future, including current personal characteristics (i.e., age, income, occupation) and travel characteristics (i.e., fare, vehicle ownership) of passengers. This study warns of the high probability of mode-changing behaviour from paratransit to another mode.

Assessing long-read sequencing with Nanopore R9, R10, and PacBio CCS to obtain high-quality metagenome assembled genomes from complex microbial communities

Short-read DNA sequencing has led to a massive growth of genome databases but mainly with highly fragmented metagenome assembled genomes from environmental systems. The fragmentation is a result of closely related species, strains, and genome repeats that cannot be resolved with short reads. To confidently explore the functional potential of a microbial community, high-quality reference genomes are needed. In this study, we evaluated the use of different combinations of short (Illumina) and long-read technologies (Nanopore R9.4, R10.3, and PacBio CCS) for recovering high-quality metagenome assembled genomes (HQ MAGs) from a complex microbial community (anaerobic digester). Depending on the sequencing approach, 33 to 86 HQ MAGs (encompassing up to 34 % of the assembly and 49 % of the reads) were recovered using long reads, with Nanopore R9 featuring the lowest sequencing costs per HQ MAG recovered. PacBio CCS was also found to be an effective platform for genome-centric metagenomics (74 HQ MAGs) and produced HQ MAGs with the lowest fragmentation (median of 9 contigs) as a stand-alone technology. Using PacBio CCS MAGs as reference, we show that, although a high number of high-quality MAGs can be generated using Nanopore R9, systematic indel errors are still present, which can lead to truncated gene calling. However, polishing the Nanopore MAGs with short-read Illumina data, enabled recovery of MAGs with similar quality as MAGs from PacBio CCS.

Effect of the Rise in Online Motorcycle Taxi Services on the Number of Motorcycles using the Interrupted Time Series Method

The substantial growth of motorcycle users in Indonesia is hypothesized to be influenced by a government policy on motorcycle purchase waivers and the massive growth of online motorcycle taxis. This study aims to analyse the relationship between the emergence of online motorcycle taxis and government policy changes towards the number of motorcycles and compare the estimation model seen from the consumer and sales sides. The data were collected from the Indonesian Bureau of Statistics, Motorcycle Industry Association, and World Bank. Several estimation models were built using the interrupted time series method. The results showed that changes in government policy and income per capita significantly increased the number of motorcycles. However, the emergence of online motorcycle taxis negatively affected the increasing number of motorcycles. The results also showed that models with data representing motorcycle usage behavior provided better results than the model with motorcycle sales.