Mapping the Future: Revealing Habitat Preferences and Patterns of the Endangered Chilean Dolphin in Seno Skyring, Patagonia.

Species distribution modeling helps understand how environmental factors influence species distribution, creating profiles to predict presence in unexplored areas and assess ecological impacts. This study examined the habitat use and population ecology of the Chilean dolphin in Seno Skyring, Chilean Patagonia. We used three models-random forest (RF), generalized linear model (GLM), and artificial neural network (ANN)-to predict dolphin distribution based on environmental and biotic data like water temperature, salinity, and fish farm density. Our research has determined that the RF model is the most precise tool for predicting the habitat preferences of Chilean dolphins. The results indicate that these dolphins are primarily located within six kilometers of the coast, strongly correlating with areas featuring numerous fish farms, sheltered waters close to the shore with river inputs, and shallow productive zones. This suggests a potential association between dolphin presence and fish-farming activities. These findings can guide targeted conservation measures, such as regulating fish-farming practices and protecting vital coastal areas to improve the survival prospects of the Chilean dolphin. Given the extensive fish-farming industry in Chile, this research highlights the need for greater knowledge and comprehensive conservation efforts to ensure the species' long-term survival. By understanding and mitigating the impacts of fish farming and other human activities, we can better protect the habitat and well-being of Chilean dolphins.

IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water.

The in-line determination of chemical parameters in water is of capital importance for environmental reasons. It must be carried out frequently and at a multitude of points; thus, the ideal method is to utilize automated monitoring systems, which use sensors based on many transducers, such as Ion Selective Electrodes (ISE). These devices have multiple advantages, but their management via traditional methods (i.e., manual sampling and measurements) is rather complex. Wireless Sensor Networks have been used in these environments, but there is no standard way to take advantage of the benefits of new Internet of Things (IoT) environments. To deal with this, an IoT-based generic architecture for chemical parameter monitoring systems is proposed and applied to the development of an intelligent potassium sensing system, and this is described in detail in this paper. This sensing system provides fast and simple deployment, interference rejection, increased reliability, and easy application development. Therefore, in this paper, we propose a method that takes advantage of Cloud services by applying them to the development of a potassium smart sensing system, which is integrated into an IoT environment for use in water monitoring applications. The results obtained are in good agreement (correlation coefficient = 0.9942) with those of reference methods.

Composition and structure of the skin microbiota of rorquals off the Eastern South Pacific.

Recent advances in high-throughput sequencing have enabled the large-scale interrogation of microbiota in the most diverse environments, including host-associated microbiota. This has led to the recognition that the skin microbiota of rorquals is specific and structurally different from that of the ocean. This study reveals the skin microbiome of 85 wild individuals along the Chilean coast belonging to Megaptera novaeangliae, Balaenoptera musculus and Balaenoptera physalus. Alpha diversity analysis revealed significant differences in richness and phylogenetic diversity, particularly among humpback whales from different locations and between blue and humpback whales. Beta diversity was partially explained by host and location but only accounting for up to 17% of microbiota variability (adjusted VPA). Overall, we found that microbiota composition was dominated by bacterial genera such as Cardiobacter, Moraxella, Tenacibaculum, Stenotrophomonas, Flavobacteria and Pseudomonas. We also found that no ASVs were associated with the three rorqual species. Up to four ASVs were specific of a location, indicating a great variability in the microbiota. To the best of our knowledge, this is the first report on the composition and structure of the skin microbiota of whales off the coast of Chile, providing a foundational dataset to understand the microbiota's role in rorquals.

New Contact Sensorization Smart System for IoT e-Health Applications Based on IBC IEEE 802.15.6 Communications.

This paper proposes and demonstrates the capabilities of a new sensorization system that monitors skin contact between two persons. Based on the intrabody communication standard (802.15.6), the new system allows for interbody communication, through the transmission of messages between different persons through the skin when they are touching. The system not only detects if there has been contact between two persons but, as a novelty, is also able to identify the elements that have been in contact. This sensor will be applied to analyze and monitor good follow-up of hand hygiene practice in health care, following the "World Health Organization Guidelines on Hand Hygiene in Health Care". This guide proposes specific recommendations to improve hygiene practices and reduce the transmission of pathogenic microorganisms between patients and health-care workers (HCW). The transmission of nosocomial infections due to improper hand hygiene could be reduced with the aid of a monitoring system that would prevent HCWs from violating the protocol. The cutting-edge sensor proposed in this paper is a crucial innovation for the development of this automated hand hygiene monitoring system (AHHMS).

A New Ammonium Smart Sensor with Interference Rejection.

In many water samples, it is important to determine the ammonium concentration in order to obtain an overall picture of the environmental impact of pollutants and human actions, as well as to detect the stage of eutrophization. Ion selective electrodes (ISEs) have been commonly utilized for this purpose, although the presence of interfering ions (potassium and sodium in the case of NH4+-ISE) represents a handicap in terms of the measurement quality. Furthermore, random malfunctions may give rise to incorrect measurements. Bearing all of that in mind, a smart ammonium sensor with enhanced features has been developed and tested in water samples, as demonstrated and commented on in detail following the presentation of the complete set of experimental measurements that have been successfully carried out. This has been achieved through the implementation of an expert system that supervises a set of ISEs in order to (a) avoid random failures and (b) reject interferences. Our approach may also be suitable for in-line monitoring of the water quality through the implementation of wireless sensor networks.

Author Correction: 50 Years of Cetacean Strandings Reveal a Concerning Rise in Chilean Patagonia.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

50 Years of Cetacean Strandings Reveal a Concerning Rise in Chilean Patagonia.

Cetacean strandings (CS) have been reported in increasing numbers in coastal areas worldwide. Although the causes of these strandings are unknown, a number of anthropogenic and environmental factors have been suggested. This paper aims to characterize CS patterns and describe their fine-scale spatiotemporal dynamics. We analysed spatial and spatiotemporal CS patterns in Chile from January 1968 to January 2020. We identified a total of 389 CS events affecting eight cetacean families, 21 genera, and 35 species, which represent more than 85% of the reported species richness for the country. Most CS events (94.1%) were single (i.e., ≤two individuals). There were also 18 mass stranding (three to 24 individuals, 4.1%) and nine unusually large mass stranding events (>25 individuals, 2%). Purely spatial tests showed CS events appearing in random occurrence along the Chilean coast. Local tests for spatio-temporal clusters, however, identified a greater number of hotspots reported in the southernmost part of the country, namely, Chilean Patagonia. Specifically, significant spatio-temporal clusters were identified and defined as containing three or more individuals within a two-month period as a focal coastal event (<1 km radius). It is a cause of concern that CS events in Chile have been increasing consistently over the last decades, and although we were not able to identify their causes, we are able to highlight the importance of changes in climate conditions and of an increase in monitoring activities as primary drivers for such patterns, particularly important in Chilean Patagonia.

Physicochemical characteristics of citrus jelly with non cariogenic and functional sweeteners.

In this study the effect of sweeteners with low glycemic index and non-cariogenic characteristics (isomaltulose, oligofructose and tagatose) in jelly prepared with citrus juice has been evaluated considering a citrus jelly formulated with sucrose as reference. The soluble solids, moisture content, pH, water activity, antioxidant capacity, optical and mechanical properties of jelly made using different sweeteners was determined during storage. Besides, mesophilic aerobics and moulds and yeasts was also counted to determine their stability over time. Sensory evaluation of the citrus jelly has also been done. The results showed the antioxidant activity decreased during storage in all formulations. Tagatose increased lightness whereas coordinates a*, b* and chrome of all the jellies prepared using new sweeteners were lower than jellies with sucrose. However, citrus jelly with only oligofructose or tagatose or with the mixture of isomaltulose and tagatose were most closely resembled to the control jelly with respect to mechanical properties. Jelly prepared with the combination of isomaltulose and tagatose in equal proportions obtained the best score in the sensorial analysis.

Ultra-Low Power Optical Sensor for Xylophagous Insect Detection in Wood.

The early detection of pests is key for the maintenance of high-value masterpieces and historical buildings made of wood. In this work, we the present detailed design of an ultra-low power sensor device that permits the continuous monitoring of the presence of termites and other xylophagous insects. The operating principle of the sensor is based on the variations of reflected light induced by the presence of termites, and specific processing algorithms that deal with the behavior of the electronics and the natural ageing of components. With a typical CR2032 lithium battery, the device lasts more than nine years, and is ideal for incorporation in more complex monitoring systems where maintenance tasks should be minimized.

A Reference Model for Monitoring IoT WSN-Based Applications.

The Internet of Things (IoT) is, at this moment, one of the most promising technologies that has arisen for decades. Wireless Sensor Networks (WSNs) are one of the main pillars for many IoT applications, insofar as they require to obtain context-awareness information. The bibliography shows many difficulties in their real implementation that have prevented its massive deployment. Additionally, in IoT environments where data producers and data consumers are not directly related, compatibility and certification issues become fundamental. Both problems would profit from accurate knowledge of the internal behavior of WSNs that must be obtained by the utilization of appropriate tools. There are many ad-hoc proposals with no common structure or methodology, and intended to monitor a particular WSN. To overcome this problem, this paper proposes a structured three-layer reference model for WSN Monitoring Platforms (WSN-MP), which offers a standard environment for the design of new monitoring platforms to debug, verify and certify a WSN's behavior and performance, and applicable to every WSN. This model also allows the comparative analysis of the current proposals for monitoring the operation of WSNs. Following this methodology, it is possible to achieve a standardization of WSN-MP, promoting new research areas in order to solve the problems of each layer.

Active Low Intrusion Hybrid Monitor for Wireless Sensor Networks.

Several systems have been proposed to monitor wireless sensor networks (WSN). These systems may be active (causing a high degree of intrusion) or passive (low observability inside the nodes). This paper presents the implementation of an active hybrid (hardware and software) monitor with low intrusion. It is based on the addition to the sensor node of a monitor node (hardware part) which, through a standard interface, is able to receive the monitoring information sent by a piece of software executed in the sensor node. The intrusion on time, code, and energy caused in the sensor nodes by the monitor is evaluated as a function of data size and the interface used. Then different interfaces, commonly available in sensor nodes, are evaluated: serial transmission (USART), serial peripheral interface (SPI), and parallel. The proposed hybrid monitor provides highly detailed information, barely disturbed by the measurement tool (interference), about the behavior of the WSN that may be used to evaluate many properties such as performance, dependability, security, etc. Monitor nodes are self-powered and may be removed after the monitoring campaign to be reused in other campaigns and/or WSNs. No other hardware-independent monitoring platforms with such low interference have been found in the literature.

Underwater acoustic wireless sensor networks: advances and future trends in physical, MAC and routing layers.

This survey aims to provide a comprehensive overview of the current research on underwater wireless sensor networks, focusing on the lower layers of the communication stack, and envisions future trends and challenges. It analyzes the current state-of-the-art on the physical, medium access control and routing layers. It summarizes their security threads and surveys the currently proposed studies. Current envisioned niches for further advances in underwater networks research range from efficient, low-power algorithms and modulations to intelligent, energy-aware routing and medium access control protocols.

A proposal for modeling real hardware, weather and marine conditions for underwater sensor networks.

Network simulators are useful for researching protocol performance, appraising new hardware capabilities and evaluating real application scenarios. However, these tasks can only be achieved when using accurate models and real parameters that enable the extraction of trustworthy results and conclusions. This paper presents an underwater wireless sensor network ecosystem for the ns-3 simulator. This ecosystem is composed of a new energy-harvesting model and a low-cost, low-power underwater wake-up modem model that, alongside existing models, enables the performance of accurate simulations by providing real weather and marine conditions from the location where the real application is to be deployed.

Underwater sensor networks: a new energy efficient and robust architecture.

The specific characteristics of underwater environments introduce new challenges for networking protocols. In this paper, a specialized architecture for underwater sensor networks (UWSNs) is proposed and evaluated. Experiments are conducted in order to analyze the suitability of this protocol for the subaquatic transmission medium. Moreover, different scheduling techniques are applied to the architecture in order to study their performance. In addition, given the harsh conditions of the underwater medium, different retransmission methods are combined with the scheduling techniques. Finally, simulation results illustrate the performance achievements of the proposed protocol in end-to-end delay, packet delivery ratio and energy consumption, showing that this protocol can be very suitable for the underwater medium.

Historical building monitoring using an energy-efficient scalable wireless sensor network architecture.

We present a set of novel low power wireless sensor nodes designed for monitoring wooden masterpieces and historical buildings, in order to perform an early detection of pests. Although our previous star-based system configuration has been in operation for more than 13 years, it does not scale well for sensorization of large buildings or when deploying hundreds of nodes. In this paper we demonstrate the feasibility of a cluster-based dynamic-tree hierarchical Wireless Sensor Network (WSN) architecture where realistic assumptions of radio frequency data transmission are applied to cluster construction, and a mix of heterogeneous nodes are used to minimize economic cost of the whole system and maximize power saving of the leaf nodes. Simulation results show that the specialization of a fraction of the nodes by providing better antennas and some energy harvesting techniques can dramatically extend the life of the entire WSN and reduce the cost of the whole system. A demonstration of the proposed architecture with a new routing protocol and applied to termite pest detection has been implemented on a set of new nodes and should last for about 10 years, but it provides better scalability, reliability and deployment properties.