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The Cyber-Physical Production System (CPPS) is a concept derived from software (cyber) and hardware (physical) applications and is based on global information exchange between such systems. The CPPS is known as a trend of Industry 4.0 (I4.0) focusing on flexibility regarding new products and adaptability to new requirements. This paper focuses on two I4.0 scenarios described by the Platform Industrie 4.0 that describe challenges for the industry towards its digital future. First, it looks at the Order Controlled Production (OCP) scenario that deals with flexible and self-configuring production networks. It describes the dynamic organization of production resources required to execute a production order. Second, the Adaptable Factory (AF) application scenario is discussed, which focuses on the configuration of production resources and describes the adaptability of an individual facility through (physical) modification. This paper first provides a detailed analysis of the requirements from these scenarios. Furthermore, it analyses the current Multi-Agent System (MAS) architectures and agent-based planning and decision support systems requirements. MAS can be used to create application-independent I4.0 systems with arbitrary hardware automation platforms. To create a scalable communication network that also supports application independence and enables the semantically machine-readable description of the exchanged data, the OPC UA standard was adopted. As a result of the study, the concept shows how different and independent automation platforms can be seamlessly connected via OPC UA. The proposed MAS concept has been evaluated in different use cases, namely OCP and AF.

The growing complexity of production systems requires appropriate control architectures that allow flexible adaptation during their runtime. Although cyber-physical production systems (CPPS) provide the means to cope with complexity and flexibility, the migration with existing control systems is still a challenge. The term CPPS denotes a mechatronic system (physical world) coupled with software entities and digital information (cyber part), both enabling the smart factory concept for the Industry 4.0 (I4.0) paradigm. In this regard, design patterns could help developers to build their software with common solutions for manufacturing control derived from experiences. We provide a description and comparison of the already existing multi-agent systems (MAS) design patterns, which were collected and classified by introducing two classification criteria to support MAS developers. The applicability of these criteria is shown in the case of specific example architectures from the lower and higher control levels. The authors, together with experts from the German Agent Systems committee FA 5.15, gathered more than twenty MAS patterns, evaluated, and compared four selected patterns with the presented criteria and terminology. The main contribution is a CPPS architecture that fulfills requirements related to the era of smart factories, as well as the Reference Architectural Model I4.0 (RAMI 4.0). The conclusions indicate that agent-based patterns greatly benefit the CPPS design. In addition, it is shown that manufacturing based on MAS is a good way to address complex requests of the CPPS development.

Industry 4.0 (I4.0) brings together new disruptive technologies, increasing future factories’ productivity. Indeed, the control of production processes is fast becoming a key driver for manufacturing operations. Manufacturing control systems have recently been developed for distributed or semi-heterarchical architectures, e.g., holonic systems improving global efficiency and manufacturing operations’ reactiveness. So far, previous studies and applications have not dealt with continuous production processes, such as applications for Water Supply System (WSS), oil refining, or electric power plants. The complexity of continuous production is that a single fault can degrade extensively and even cause service disruption. Therefore, this paper proposes the Holonic Production Unit (HPU) architecture as a solution to control continuous production processes. An HPU is created as a holon unit depicting resources in a continuous process. This unit can detect events within the environment, evaluate several courses of action, and change the parameters aligned to a mission. The proposed approach was tested using a simulated model of WSS. The experiments described in this paper were conducted using a traditional WSS, where the communication and decision-making features allow the application of HPU. The results suggest that constructing a holarchy with different holons can fulfill I4.0 requirements for continuous production processes.

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The Internet of Things (IoT) plays an important role in the development of applications for the Electrical Industry. The data has become essential for the technological advances in this industry, changing abruptly due to the distributed energy resources and the smart grid concept. The data integration also represents a relevant matter to address when performing IoT projects for electrical industry applications. The electrical industry requires incorporating different IoT protocols to comply with the distinct scenarios and the interoperability. This work proposes integrating the HTTP REST, MQTT, LoRaWAN, and OPC UA open communications protocols into an IoT platform and interoperable architecture for smart grid applications. This approach intends to contribute to smart grid solutions and automation systems in the electrical industry, promotes further integration of communication protocols for this field, and enables additional data-based applications for their automation systems. A Multi-Agent System architecture based on the IoT integration is proposed as an application to show how implementable is this approach in current and technological electrical systems.

One of the main issues in the medical field and clinical practice is the development of novel and effective treatments against infections caused by antibiotic-resistant bacteria. One avenue that has been approached to develop effective antimicrobials is the use of silver nanoparticles (Ag-NPs), since they have been found to exhibit an efficient and wide spectrum of antimicrobial properties. Among the main drawbacks of using Ag-NPs are their potential cytotoxicity against eukaryotic cells and the latent environmental toxicity of their synthesis methods. Therefore, diverse green synthesis methods, which involve the use of environmentally friendly plant extracts as reductive and capping agents, have become attractive to synthesize Ag-NPs that exhibit antimicrobial effects against resistant bacteria at concentrations below toxicity thresholds for eukaryotic cells. In this study, we report a green one-pot synthesis method that uses extract as a reducing and capping agent, to produce Ag-NPs with applications as therapeutic agents to treat infections in vivo. The Ag-NPs were characterized using transmission electron microscopy (TEM), high-resolution TEM, selected area electron diffraction, energy-dispersive spectroscopy, ultraviolet-visible, and Fourier transform infrared. We show that Ag-NPs are spherical with a narrow size distribution. The Ag-NPs show antimicrobial activities in vitro against Gram-negative ( , , and a clinical multidrug-resistant strain of ) and Gram-positive ( ) bacteria. Moreover, antimicrobial effects of the Ag-NPs, against a resistant clinical strain, were tested in a murine skin infection model. The results demonstrate that the Ag-NPs reported in this work are capable of eradicating pathogenic resistant bacteria in an infection in vivo. In addition, skin, liver, and kidney damage profiles were monitored in the murine infection model, and the results demonstrate that Ag-NPs can be used safely as therapeutic agents in animal models. Together, these results suggest the potential use of Ag-NPs, synthesized by green chemistry methods, as therapeutic agents against infections caused by resistant and nonresistant strains.

The loss of function melanocortin 4-receptor (MC4R) Ile269Asn mutation has been proposed as one of the most important genetic contributors to obesity in the Mexican population. However, whether patients bearing this mutation respond differently to weight loss treatments is unknown. We tested the association of this mutation with obesity in 1683 Mexican adults, and compared the response of mutation carriers and non-carriers to three different weight loss interventions: dietary restriction intervention, phentermine 30 mg/day treatment, and Roux-en-Y gastric bypass (RYGB) surgery. The Ile269Asn mutation was associated with obesity [OR = 3.8, 95% CI (1.5–9.7), p = 0.005]. Regarding interventions, in the dietary restriction group only two patients were MC4R Ile269Asn mutation carriers. After 1 month of treatment, both mutation carriers lost weight: −4.0 kg (−2.9%) in patient 1, and −1.8 kg (−1.5%) in patient 2; similar to the mean weight loss observed in six non-carrier subjects (−2.9 kg; −2.8%). Phentermine treatment produced similar weight loss in six carriers (−12.7 kg; 15.5%) and 18 non-carriers (−11.3 kg; 13.6%) after 6 months of pharmacological treatment. RYGB also caused similar weight loss in seven carriers (29.9%) and 24 non-carriers (27.8%), 6 months after surgery. Our findings suggest that while the presence of a single MC4R loss of function Ile269Asn allele significantly increases obesity risk, the presence of at least one functional MC4R allele seems sufficient to allow short-term weight loss in response to dietary restriction, phentermine and RYGB. Thus, these three different interventions may be useful for the short-term treatment of obesity in MC4R Ile269Asn mutation carriers.

Phosphorus (P) is an important nutritional element needed by plants. Roots obtain P as inorganic phosphate (Pi), mostly in H2PO−4 form. It is vital for plants to have a sufficient supply of Pi since it participates in important processes like photosynthesis, energy transfer, and protein activation, among others. The physicochemical properties and the organic material usually make Pi bioavailability in soil low, causing crops and undomesticated plants to experience variations in accessibility or even a persistent phosphate limitation. In this study, transcriptome data from pepper roots under low-Pi stress was analyzed in order to identify Pi starvation-responsive genes and their relationship with metabolic pathways and functions. Transcriptome data were obtained from pepper roots with Pi deficiency by RNASeq and analyzed with bioinformatic tools. A total of 97 differentially expressed genes (DEGs) were identified; Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment revealed that metabolic pathways, such as porphyrin and chlorophyll metabolism, were down-regulated, and galactose and fatty acid metabolism were up-regulated. The results indicate that bell pepper follows diverse processes related to low Pi tolerance regulation, such as the remobilization of internal Pi, alternative metabolic pathways to generate energy, and regulators of root development.

Aedes aegypti is widely distributed worldwide and is the main vector mosquito for dengue, one of the most important infectious diseases in middle- and low-income countries. The landscape composition and vegetation cover determine appropriate environments for this mosquito to breed, and it is fundamental to define the most affordable methodology to understand these landscape variables in urban environments. The proposed methodology integrated drone technologies and traditional entomological surveillance to strengthen our knowledge about areas suitable for Ae. aegypti infestation. We included an analysis using the vegetation indexes, NDVI and NDVIRe, and their association with Ae. aegypti larvae and adults in houses from the El Vergel neighborhood Tapachula, Chiapas, Mexico. We used drone technology to obtain high-resolution photos and performed multispectral orthomosaic constructions for the data of vegetation indexes with a kernel density analysis. A negative binomial regression was performed to determine the association between the numbers of Ae. aegypti larvae and adults with the kernel density based on NDVI and NDVIRe. Medium and high values of kernel density of NDVIRe (both p-value < 0.05) and NDVI (both p-value < 0.05) were associated with a higher amount of mosquito adults per houses. The density of Ae. aegypti larvae per house did not show an association with medium and high values of NDVIRe (both p-value > 0.05) and NDVI (both p-value > 0.05). The vegetation indexes, NDVI and NDVIRe, have potential as precise predictors of Ae. aegypti adult mosquito circulation in urban environments. Drone technology can be used to map and obtain landscape characteristics associated with mosquito abundance in urban environments.

Purpose Astrocytomas are a type of malignant brain tumor with an unfavorable clinical course. The impact of AGT and MGMT somatic variants in the prognosis of astrocytoma is unknown, and it is controversial for TP53 . Moreover, there is a lack of knowledge regarding the molecular characteristics of astrocytomas in Mexican patients. Methods We studied 48 Mexican patients, men and women, with astrocytoma (discovery cohort). We performed DNA deep sequencing in tumor samples, targeting AGT , MGMT and TP53 , and we studied MGMT gene promoter methylation status. Then we compared our findings to a cohort which included data from patients with astrocytoma from The Cancer Genome Atlas (validation cohort). Results In the discovery cohort, we found a higher number of somatic variants in AGT and MGMT than in the validation cohort (10.4% vs < 1%, p < 0.001), and, in both cohorts, we observed only women carried variants AGT variants. We also found that the presence of either MGMT variant or promoter methylation was associated to better survival and response to chemotherapy, and, in conjunction with TP53 variants, to progression-free survival. Conclusions The occurrence of AGT variants only in women expands our knowledge about the molecular differences in astrocytoma between men and women. The increased prevalence of AGT and MGMT variants in the discovery cohort also points towards possible distinctions in the molecular landscape of astrocytoma among populations. Our findings warrant further study.