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Agriculture is vital to Sumbawa Regency's economy, with key activities such as rice cultivation, corn production, onion farming, and cattle rearing. This study applies artificial neural networks (ANN) to predict land cover changes, focusing on agricultural land expansion. Using land cover datasets from ESRI, digital elevation model, and topographical maps, we analyzed land cover changes from 2017 to 2023 and generated future projections for 2050 with the MOLUSCE plugin in qGIS. The predictive model achieved an 85% accuracy rate when comparing 2023 actual data with predictions. Results indicate a significant increase in agricultural land cover by 2050. The key finding is that over a long-term period, the simulation of land use and land cover (LULC) change in Sumbawa reveals an increase of crop areas in the Lunyuk and Labangka Districts. This study highlights the effectiveness of ANN in land cover prediction and emphasizes the need for sustainable practices to balance agricultural expansion. AI-driven insights can aid policymakers in opti-mizing resource allocation and ensuring long-term environmental and economic stability in Sumbawa Regency. Future research should refine models and incorporate additional factors for improved accuracy.

Rainfall-triggered shallow landslides are destructive hazards and play an important role in landscape processes. A theory explaining the size distributions of such features remains elusive. Prior work connects size distributions to topography, but field-mapped inventories reveal pronounced similarities in the form, mode, and spread of distributions from diverse landscapes. We analyze nearly identical distributions occurring in the Oregon Coast Range and the English Lake District, two regions of strikingly different topography, lithology, and vegetation. Similarity in minimum sizes at these sites is partly explained by theory that accounts for the interplay of mechanical soil strength controls resisting failure. Maximum sizes, however, are not explained by current theory. We develop a generalized framework to account for the entire size distribution by unifying a mechanistic slope stability model with a flexible spatial-statistical description for the variability of hillslope strength. Using hillslope-scale numerical experiments, we find that landslides can occur not only in individual low strength areas but also across multiple smaller patches that coalesce. We show that reproducing observed size distributions requires spatial strength variations to be strongly localized, of large amplitude, and a consequence of multiple interacting factors. Such constraints can act together with the mechanical determinants of landslide initiation to produce size distributions of broadly similar character in widely different landscapes, as found in our examples. We propose that size distributions reflect the systematic scale dependence of the spatially averaged strength. Our results highlight the critical need to constrain the form, amplitude, and wavelength of spatial variability in material strength properties of hillslopes.

Biological systems exhibit strong dynamic variations; for example, a system may have a tendency towards either a steady state, periodic behaviour or chaotic oscillations. These findings, explained by dynamic systems theory, have allowed researchers to formally relate a wide variety of systems, such as the theory of rumour propagation, glucose metabolism or the activity of a neuronal circuit. Interestingly, among all of the dynamic characteristics mentioned, qualitative aspects frequently observed in highly complex systems can be obtained through the recursive application of a very simple parabolic function known as the logistic equation. Currently, the importance of these dynamic phenomena for biomedicine is recognized, but simple models such as the logistic equation have not been sufficiently exploited in the training of biologists and health professionals. We briefly review some properties of the dynamics governed by the logistic equation, with a direct application to the theory of cancer based on the dynamics of aneuploidy. We believe that this already known mathematical application is an opportunity for integrated teaching of mathematics and biology. For this purpose we finally provide an appendix with some activities, all of them related to this article, which can be practiced in a simple spreadsheet that we have shared.

Change is something that is bound to happen. Employees in service industries such as hospitality business must have innovative work behavior to help companies grow and thrive in a constantly changing environment. One way to get employee work integrity in the face of change is to set work goals. The involvement of employees in setting work goals is inseparable from the role of superiors to provide feedback. This study aims to describe the relationship between goal-setting participation and employees' innovative work behavior and their relationship with feedback as a moderating variable. The research methodology uses a quantitative descriptive approach, whereas 101 of four-star hotel employees in Belitung Regency and employed convenience sampling. The results revealed that goal-setting variable has a positive and meaningful relationship with the feedback variable. Moreover, the feedback variable has a role both as an independent and a moderator variable in the relationship between goal-setting variable and innovative work behavior. The implications of the research results provide input to hotel business actors the importance of encouraging goal-setting participation and employing the goals as the positive feedback for the employees.

An educational activity is proposed that uses software for proteomic analysis and databases available for free on the Internet to estimate the structure and function of a hypothetical protein from its coding nucleotide sequence. This bioinformatics activity is recommended for integrated introductory courses that address the structure function relationship in proteins.

Background An epidemiological model (susceptible, un-quarantined infected, quarantined infected, confirmed infected (SUQC)) was previously developed and applied to incorporate quarantine measures and calculate COVID-19 contagion dynamics and pandemic control in some Chinese regions. Here, we generalized this model to incorporate the disease recovery rate and applied our model to records of the total number of confirmed cases of people infected with the SARS-CoV-2 virus in some Chilean communes. Methods In each commune, two consecutive stages were considered: a stage without quarantine and an immediately subsequent quarantine stage imposed by the Ministry of Health. To adjust the model, typical epidemiological parameters were determined, such as the confirmation rate and the quarantine rate. The latter allowed us to calculate the reproduction number. Results The mathematical model adequately reproduced the data, indicating a higher quarantine rate when quarantine was imposed by the health authority, with a corresponding decrease in the reproduction number of the virus down to values that prevent or decrease its exponential spread. In general, during this second stage, the communes with the lowest social priority indices had the highest quarantine rates, and therefore, the lowest effective viral reproduction numbers. This study provides useful evidence to address the health inequity of pandemics. The mathematical model applied here can be used in other regions or easily modified for other cases of infectious disease control by quarantine.

The authors describe an activity they have created in which students can visualize a theoretical neural network whose states evolve according to a well-known simple law. This activity provided an uncomplicated approach to a paradigm commonly represented through complex mathematical formulation. From their observations, students learned many basic principles and concepts of the dynamic systems, all necessary to understand the structure-dynamic relationship. This last relation is one of the main paradigms in the integrated curriculum of many health sciences professionals. In the activity, the authors proposed to students a theoretical "human" neural network, with each student representing a neuron. In this article, they describe some essential aspects used to obtain the dynamics of the neural network. (Contains 1 table and 2 figures.)

Qualitative questions are proposed to assess the understanding of solubility and some of its applications. To improve those results, a simple quantitative problem on the precipitation of proteins is proposed.