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Mucogingival surgery encompasses any procedure designed to correct defects in the morphology, position, or enhance the dental gingival junction. The lack of keratinized gingiva and the presence of gingival recession can be an esthetic and functional problem for the patient. This paper will review the gingival dimensions of the periodontium in health and address the prevalence, etiology, and predisposing factors related to defects in the quality and quantity of gingiva.Gingival augmentation techniques and indications will be reviewed, including root coverage and non-root coverage procedures. Autogenous soft tissue grafts will be described, as well as several non-autogenous graft materials.Ultimately, careful diagnosis, realistic expectations, clear goals, and correct technique selection are essential for the most successful clinical results.

This paper presents an evaluation of different convolutional neural network (CNN) architectures using false-colour images obtained by multispectral sensors on drones for the detection of Black Sigatoka in banana crops. The objective is to use drones to improve the accuracy and efficiency of Black Sigatoka detection to reduce its impact on banana production and improve the sustainable management of banana crops, one of the most produced, traded, and important fruits for food security consumed worldwide. This study aims to improve the precision and accuracy in analysing the images and detecting the presence of the disease using deep learning algorithms. Moreover, we are using drones, multispectral images, and different CNNs, supported by transfer learning, to enhance and scale up the current approach using RGB images obtained by conventional cameras and even smartphone cameras, available in open datasets. The innovation of this study, compared to existing technologies for disease detection in crops, lies in the advantages offered by using drones for image acquisition of crops, in this case, constructing and testing our own datasets, which allows us to save time and resources in the identification of crop diseases in a highly scalable manner. The CNNs used are a type of artificial neural network widely utilised for machine training; they contain several specialised layers interconnected with each other in which the initial layers can detect lines and curves, and gradually become specialised until reaching deeper layers that recognise complex shapes. We use multispectral sensors to create false-colour images around the red colour spectra to distinguish infected leaves. Relevant results of this study include the construction of a dataset with 505 original drone images. By subdividing and converting them into false-colour images using the UAV’s multispectral sensors, we obtained 2706 objects of diseased leaves, 3102 objects of healthy leaves, and an additional 1192 objects of non-leaves to train classification algorithms. Additionally, 3640 labels of Black Sigatoka were generated by phytopathology experts, ideal for training algorithms to detect this disease in banana crops. In classification, we achieved a performance of 86.5% using false-colour images with red, red edge, and near-infrared composition through MobileNetV2 for three classes (healthy leaves, diseased leaves, and non-leaf extras). We obtained better results in identifying Black Sigatoka disease in banana crops using the classification approach with MobileNetV2 as well as our own datasets.

Placental trophoblastic site tumor (PSTT) is a rare type of gestational trophoblastic neoplasia (GTN). PSTT has a higher mortality than other types of gestational trophoblastic disease (GTD), with a rate of 16.1%, due to its relatively unpredictable behavior and reduced response to chemotherapy. Its diagnostic and management are very challenging in Low resources settings particularity in Haiti where MRI, PET Scan and IHC are not available. Further, the follow-up is very difficult because of social, political, and economic issues limiting the capacity of our patients to be present at all scheduled visits. No case of PSTT has been publicly described yet the Haitian experience in the literature in the management of such case compared to the developed world. We present a case of PSTT successfully diagnosed and managed at Mirebalais University Hospital (MUH) in Haiti with the support of telepathology and intentional partners while highlighting the difference that we observed compare to the developed world.

Abstract Glaucoma is an age-related neurodegenerative disease of the visual system, affecting both the eye and the brain. Yet its underlying metabolic mechanisms and neurobehavioral relevance remain largely unclear. Here, using proton magnetic resonance spectroscopy and functional magnetic resonance imaging, we investigated the GABAergic and glutamatergic systems in the visual cortex of glaucoma patients, as well as neural specificity, which is shaped by GABA and glutamate signals and underlies efficient sensory and cognitive functions. Our study shows that among the older adults, both GABA and glutamate levels decrease with increasing glaucoma severity regardless of age. Further, our study shows that the reduction of GABA but not glutamate predicts the neural specificity. This association is independent of the impairments on the retina structure, age, and the gray matter volume of the visual cortex. Our results suggest that glaucoma-specific decline of GABA undermines neural specificity in the visual cortex and that targeting GABA could improve the neural specificity in glaucoma.

Background:: Human user authentication can be implemented by token-, keyword-, or identity-based mechanisms for digital environment session entry (i.e., smartphones, platforms with log-in). Physiological signals, such as ECG, have shown discriminative properties for user identity recognition. Due to ECG hidden nature, it is resilient to public trait exposition, light/noise saturation, or eavesdropping in contrast to fingerprint, facial, voice, or password approaches. ECG might fill those gaps toward a cooperative authentication environment. Methods:: This paper proposes a Deep Learning identification scenario in which the inclusion of sex recognition directs the input sample toward a sex-specialized identity classification model, simplifying the discrimination space for each model. The architecture proposed could be suitable for large populations. Our scheme worked with an ECG three-axis pseudo-orthogonal configuration in which each axis is transformed into a time-frequency space. Additionally, we combine each lead matrix in an RGB image, joining the contribution of each wavelet waveform. Results:: Our results suggest that it is possible to identify people by using RGB wavelet representations, achieving a classification average of 99.97%. In addition, the inclusion of the sex category for our identification purpose does not significantly affect the classification performance, making it a feasible solution for systems with a larger population. Conclusions:: With the features of our database, we have evidence that it is possible to recognize a person’s identity using an ECG sex recognition module through our proposed architecture.

Cultivation of the Horvin plum is one of the main economic activities in the region of Márquez, in the department of Boyacá, in Colombia. However, its selection process, which needs to be optimized and improved, is still done manually and leads to delays, high labor costs and errors in its classification due to long working days. In this paper, an electromechanical system for plum classification into three classes –morphologically defined by the experience of farmers in the region— is proposed, in nutshell: The first category is the largest and most desirable, the second is smaller in size compared to the first, and the third exhibits visual impairments, rendering it undesirable. For this, 1928 samples, distributed in three categories, were entered into a convolutional neural network using the low-cost architecture available for the research. Initially, a classification accuracy of 80% was obtained for the validation data. Ultimately, following a regularization process that included DropOut and data augmentation, the algorithm achieved a 90% accuracy rate on samples not encountered during the training phase. In addition, through the Grad-CAM algorithm, the operation of the CNN was ratified, evidencing the patterns learned in each of the convolutional layers. Considering the above, it was possible to implement a machine vision system capable of classifying plums into three categories using low-cost devices.

The European Federation for Medical Informatics Association (EFMI) is the leading organisation in medical informatics in Europe and represents 29 countries, RSMI being an active and valuable member. EFMI is organized as a nonprofit organisation concerned with the theory and practice of Information Science and Technology within Health and Health Science in a European context. The objectives when founded in 1976 were: to advance international cooperation and dissemination of information in Medical Informatics on a European basis; to promote high standards in the application of medical informatics; to promote research and development in medical informatics; to encourage high standards in education in medical informatics; to function as the autonomous European Regional Council of IMIA. Since 2018 EFMI participates actively in European financed projects contributing with its members’ expertise in dissemination, education, data processing, user experience, and several other domains. HosmartAI (2020-2024) is a H2020 project with 24 partners, 12 EU countries, 10 mil Euros funding. In the HosmartAI project – AI for the Smart Hospital of the future - EFMI is leading in WP6 the T6.3 task - Standardization and Legislation, T6.4 task - Certification, Staff training & education and alignment with existing practice and had a consistent contribution in WP2 with EFMI MIMO tool. The EFMI team will present the solutions developed during the project and invite audience to give feedback.

La configuración de la red social de transferencia de conocimiento en transformación digital (TD) del sector olivarero de Andalucía es analizada mediante el uso de técnicas de Análisis de Redes Sociales. Los resultados indican que las universidades y las empresas tecnológicas son los principales agentes emisores de conocimiento, mientras los olivareros y las cooperativas son los principales agentes receptores. La red tiene un alto potencial para la creación de capital social, aunque la mayoría de las interacciones son de intensidad muy débil, lo que podría conllevar a que algunos actores queden aislados del conocimiento en TD.

Our planet is currently facing unprecedented interconnected environmental, societal, and economic dilemmas due to climate change, the outbreak of pandemics and wars, among others. These global challenges pose direct threats to food security and safety and clearly show the urgent need for innovative scientific solutions and technological approaches. Backed by the current alarming situation, many food-related trends have emerged in recent years in response to these global issues. This review looks at two megatrends in agriculture and the food industry; the shift to vegetable diets and the digital transformation in food production and consumption patterns. On one side, several innovative technologies and protein sources have been associated with more sustainable food systems and enhanced nutritional quality and safety. On the other side, many digital advanced technologies (e.g., artificial intelligence, big data, the Internet of Things, blockchain, and 3D printing) have been increasingly applied in smart farms and smart food factories to improve food system outcomes. Increasing adoption of vegetal innovations and harnessing Industry 4.0 technologies along the food supply chain have the potential to enable efficient digital and ecological transitions.

Embracing innovation and emerging technologies is becoming increasingly important to address the current global challenges facing many food industry sectors, including the dairy industry. Growing literature shows that the adoption of technologies of the fourth industrial revolution (named Industry 4.0) has promising potential to bring about breakthroughs and new insights and unlock advancement opportunities in many areas of the food manufacturing sector. This article discusses the current knowledge and recent trends and progress on the application of Industry 4.0 innovations in the dairy industry. First, the “Dairy 4.0” concept, inspired by Industry 4.0, is introduced and its enabling technologies are determined. Second, relevant examples of the use of Dairy 4.0 technologies in milk and its derived products are presented. Finally, conclusions and future perspectives are given. The results revealed that robotics, 3D printing, Artificial Intelligence, the Internet of Things, Big Data, and blockchain are the main enabling technologies of Dairy 4.0. These advanced technologies are being progressively adopted in the dairy sector, from farm to table, making significant and profound changes in the production of milk, cheese, and other dairy products. It is expected that, in the near future, new digital innovations will emerge, and greater implementations of Dairy 4.0 technologies is likely to be achieved, leading to more automation and optimization of this dynamic food sector.

Fish and other seafood products represent a valuable source of many nutrients and micronutrients for the human diet and contribute significantly to global food security. However, considerable amounts of seafood waste and by-products are generated along the seafood value and supply chain, from the sea to the consumer table, causing severe environmental damage and significant economic loss. Therefore, innovative solutions and alternative approaches are urgently needed to ensure a better management of seafood discards and mitigate their economic and environmental burdens. The use of emerging technologies, including the fourth industrial revolution (Industry 4.0) innovations (such as Artificial Intelligence, Big Data, smart sensors, and the Internet of Things, and other advanced technologies) to reduce and valorize seafood waste and by-products could be a promising strategy to enhance blue economy and food sustainability around the globe. This narrative review focuses on the issues and risks associated with the underutilization of waste and by-products resulting from fisheries and other seafood industries. Particularly, recent technological advances and digital tools being harnessed for the prevention and valorization of these natural invaluable resources are highlighted.

The current war in Ukraine has severely disrupted global food supply chains due to the significant decline in the production of grain commodities, of which Ukraine and Russia are major global suppliers. This creates problems in today’s globalised food systems. In particular, a number of countries are heavily dependent on food imports from Ukraine and/or Russia, particularly some developing nations in regions like the Middle East and North Africa. As a result, alternative suppliers need to increase production and food supply chains need to adapt distribution processes. In these situations, building resilience in food supply chains is critical to react to disruptions. Resilience has become a widely researched topic in the context of food supply chains, leading to the exploration of different strategies. One potential strategy to improve resilience is to integrate digital technologies to optimise food operations. One of the digital technologies at the core of Industry 4.0, and one that is increasingly being used, is the Internet of Things (IoT). The IoT refers to systems that connect devices via the Internet, allowing them to collect and share data in real time within a network. The successful use of IoT in industrial systems has already been demonstrated and the food industry has begun to embrace the opportunities this technology offers. This research focuses on the potential of the IoT to support food supply chains by making them more resilient, particularly in the context of the disruptions caused by the war in Ukraine. Using a literature review and data from statistical sources, we explore the challenges posed to food supply chains by the Russo–Ukrainian war, and identify specific vulnerabilities that the IoT can address. We discuss the challenges of implementing this technology, particularly in wartime situations, and its potential to strengthen food supply chain operations through its ability to collect and share accurate data in real time.

Personalized cancer vaccines based on neoantigens are a new and promising treatment for cancer; however, there are still multiple unresolved challenges to using this type of immunotherapy. Among these, the effective identification of immunogenic neoantigens stands out, since the in silico tools used generate a significant portion of false positives. Inclusion of molecular simulation techniques can refine the results these tools produce. In this work, we explored docking and molecular dynamics to study the association between the stability of peptide–HLA complexes and their immunogenicity, using as a proof of concept two HLA-A2-restricted neoantigens that were already evaluated in vitro. The results obtained were in accordance with the in vitro immunogenicity, since the immunogenic neoantigen ASTN1 remained bound at both ends to the HLA-A2 molecule. Additionally, molecular dynamic simulation suggests that position 1 of the peptide has a more relevant role in stabilizing the N-terminus than previously proposed. Likewise, the mutations may have a “delocalized” effect on the peptide–HLA interaction, which means that the mutated amino acid influences the intensity of the interactions of distant amino acids of the peptide with the HLA. These findings allow us to propose the inclusion of molecular simulation techniques to improve the identification of neoantigens for cancer vaccines.

Human sex recognition with electrocardiogram signals is an emerging area in machine learning, mostly oriented toward neural network approaches. It might be the beginning of a field of heart behavior analysis focused on sex. However, a person’s heartbeat changes during daily activities, which could compromise the classification. In this paper, with the intention of capturing heartbeat dynamics, we divided the heart rate into different intervals, creating a specialized identification model for each interval. The sexual differentiation for each model was performed with a deep convolutional neural network from images that represented the RGB wavelet transformation of ECG pseudo-orthogonal X, Y, and Z signals, using sufficient samples to train the network. Our database included 202 people, with a female-to-male population ratio of 49.5–50.5% and an observation period of 24 h per person. As our main goal, we looked for periods of time during which the classification rate of sex recognition was higher and the process was faster; in fact, we identified intervals in which only one heartbeat was required. We found that for each heart rate interval, the best accuracy score varied depending on the number of heartbeats collected. Furthermore, our findings indicated that as the heart rate increased, fewer heartbeats were needed for analysis. On average, our proposed model reached an accuracy of 94.82% ± 1.96%. The findings of this investigation provide a heartbeat acquisition procedure for ECG sex recognition systems. In addition, our results encourage future research to include sex as a soft biometric characteristic in person identification scenarios and for cardiology studies, in which the detection of specific male or female anomalies could help autonomous learning machines move toward specialized health applications.

In reference to cultural patterns in collectivistic societies, teaching and learning are greatly influenced by the teachers’ collectivistic or individualistic cultural orientation (Kaur & Noman, 2015). However, in dealing with both audiences and their teaching platforms, a chasm appears between methodologies and their applications since collectivistic societies are reluctant to accept methodologies perceived as mere Western innovations. In other words, a seemingly pedagogical incongruence arises where direct individualistic Western influence is perceived as unsuitable to a collectivistic mindset. One must keep in mind that family members in collectivist societies, who view themselves as part of a group rather than independent individuals, seem to feel more interdependent and mutually responsible for each other. In addition to Vygotski’s assertion that children’s cognitive development is enriched through social interaction with more skilled individuals (1978), Bandura (1982) emphasizes that the degree to which learners believe in their own self-efficacy influences their functioning cognitively, motivationally, emotionally, and their decision making process. Also, self-efficacy is perceived to accelerate the process of adapting to a new environment while learners adopt new cultural practices and consent to norms and expectations. In our exploration, second-language learners (SLLs) from collectivistic societies advance academically—English as a second language included—within the frame of sociocultural theory, since they seem to be motivated by their culturally-induced sense of obligation to honor their parents and other group members. These SLLs are positively influenced by their prior experiences with the group’s perceptions and expectations of their capability to learn an additional language (Bandura & Schunk, 1981; Schunk, 1991). Our research seems to indicate that this outcome is significantly affected by the self-efficacy and self-reliance produced by prior successes in challenging tasks that may have been mandated by the SLL’s elders. In addition, SLLs also seem to succeed in accomplishing more challenging goals as they observe their families’ values and traditions even when they are in a society that enforces individualistic values.

Making decisions under uncertainty is very challenging but necessary as most real-world scenarios are plagued by disturbances that can be generated internally, by the hardware itself, or externally, by the environment. Hence, we propose a general decision-making framework which can be adapted to optimally address the most heterogeneous real-world domains without being significantly affected by undesired disturbances. Our paper presents a multi-agent based structure in which agents are capable of individual decision-making but also interact to perform subsequent, and more robust, collaborative decision-making processes. The complexity of each software agent can be kept quite low without a deterioration of the performance since an intelligent and robust-to-uncertainty decision-making behaviour arises when their locally produced measure of support are shared and exploited collaboratively. We show that by equipping agents with classic computational intelligence techniques, to extract features and generate measure of supports, complex hybrid multi-agent software structures capable of handling uncertainty can be easily designed. The resulting multi-agent systems generated with this approach are based on a two-phases decision-making methodology which first runs parallel local decision making processes to then aggregate the corresponding outputs to improve upon the accuracy of the system. To highlight the potential of this approach, we provided multiple implementations of the general framework and compared them over four different application scenarios. Results are promising and show that having a second collaborative decision-making process is always beneficial.

Two new records of Myrtaceae (Myrcia ishoaquinicca and Psidium acidum) for the Amazonian forests of Caquetá, Cauca, and Putumayo departments, Colombia, are reported. Comments about the habitats in which these species are growing, as well as observations on their expanded distribution ranges, are included.

We report the synthesis of CaMn0.9Mo0.1O3 manganite by glow discharge (GD) plasma treatment under Argon-Air atmosphere. The morphological, structural and magnetic properties were evaluated by scanning electron microscopy (SEM), X-ray diffraction (XRD) and magnetization measures. The results from these measures reveal that the properties of GD synthesized manganite are similar to that exhibited by CaMn0.9Mo0.1O3 produced by conventional resistive furnace. The Rietveld analysis of XRD patterns performed at room temperature show that the samples crystallize in orthorhombic structure of Pnma (62) space group. The magnetization curves as a function of temperature show two inflection points related to paramagnetic-antiferromagnetic and structural transition. The GD treatment produces a compound with similar properties, reducing the time and energy consumption in comparison with conventional synthesis route by using resistive furnace.

Food is one of the most traded goods, and the conflict in Ukraine, one of the European breadbaskets, has triggered a significant additional disruption in the global food supply chains after the COVID-19 impact. The disruption to food output, supply chains, availability, and affordability could have a long-standing impact. As a result, the availability and supply of a wide range of food raw materials and finished food products are under threat, and global markets have seen recent increases in food prices. Furthermore, the Russian-Ukrainian conflict has adversely affected food supply chains, with significant effects on production, sourcing, manufacturing, processing, logistics, and significant shifts in demand between nations reliant on imports from Ukraine. This paper aims to analyze the impacts of the conflict between Russia and Ukraine on the effectiveness and responsiveness of the global food supply chains. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, including grey literature, was deployed to investigate six key areas of the food supply chains that would be impacted most due to the ongoing war. Findings include solutions and strategies to mitigate supply chain impacts such as alternative food raw materials, suppliers and supply chain partners supported by technological innovations to ensure food safety and quality in warlike situations.

Physiological signals are strongly related to a person’s state of health and carry information about the human body. For example, by ECG, it is possible to obtain information about cardiac disease, emotions, personal identification, and the sex of a person, among others. This paper proposes the study of the heartbeat from a soft-biometric perspective to be applied to smartphone unlocking services. We employ the user heartbeat to classify the individual by sex (male, female) with the use of Deep Learning, reaching an accuracy of 94.4% ± 2.0%. This result was obtained with the RGB representation of the union of the time-frequency transformation from the pseudo-orthogonal X, Y, and Z bipolar signals. Evaluating each bipolar contribution, we found that the XYZ combination provides the best category distinction using GoogLeNet. The 24-h Holter database of the study contains 202 subjects with a female size of 49.5%. We propose an architecture for managing this signal that allows the use of a few samples to train the network. Due to the hidden nature of ECG, it does not present vulnerabilities like public trait exposition, light/noise sensibility, or learnability compared to fingerprint, facial, voice, or password verification methods. ECG may complement those gaps en route to a cooperative authentication ecosystem.

Aim of study: This study evaluates, through the input-output (I-O) methodology, the economic and social impacts (Gross Value Added –GVA– and job creation) of the national biodiesel industry on the Spanish economy in the recent past (between 2005 and 2018). These impacts are also simulated for different scenarios, for an average year following a trend from the past, based on different hypotheses on biodiesel production, trade balance and national production of raw materials. The aim is to guide decision-makers in the planning and design of regulations with implications in the domains of energy, economy and employment. Area of study: Spain. Material and methods: I-O methodology. Main results: The contribution of the biodiesel sector to GVA and job creation in Spain was very high during the construction phase of the biodiesel industry. However, this has been very limited during the operational phase, mainly due to imports of biodiesel and raw material, from Indonesia and Argentina. The economic and social impacts of this industry would be greater if higher amounts of domestic raw materials were used. Research highlights: The results justify public support for the operation of existing biodiesel plants in Spain in order to increase gross domestic product and employment, including the further implementation of specific measures to encourage domestic production. Policy measures to increase the use of national raw materials could include promoting rapeseed as an ideal cereal rotation in Spain and establishing contracting systems that guarantee farmers' profitability.

This paper reports the synthesis and characterization of Bi1-xLuxFeO3 (x = 0.00, 0.02 and 0.04) produced by solid-state reaction, in order to evaluate the influence of lutetium on the structural and magnetic properties of bismuth ferrite (BiFeO3). The samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX) and magnetic analysis by vibrating sample magnetometer (VSM) in temperature range from 50 to 320 K. The obtained results allowed to confirm the formation of crystalline materials of rhombohedral structure, space-group R3c (161), with defined morphology and particle sizes between 2.25 and 4.5 μm. The Lu3+ insertion in structure generated an increasing in magnetization, purity of BiFeO3 and a decrease in the synthesis temperature compared with the reported in the literature.

Glaucoma is a group of ophthalmologic conditions characterized by progressive retinal ganglion cell death, optic nerve degeneration, and irreversible vision loss. While intraocular pressure is the only clinically modifiable risk factor, glaucoma may continue to progress at controlled intraocular pressure, indicating other major factors in contributing to the disease mechanisms. Recent studies demonstrated the feasibility of advanced diffusion magnetic resonance imaging (dMRI) in visualizing the microstructural integrity of the visual system, opening new possibilities for non-invasive characterization of glaucomatous brain changes for guiding earlier and targeted intervention besides intraocular pressure lowering. In this review, we discuss dMRI methods currently used in visual system investigations, focusing on the eye, optic nerve, optic tract, subcortical visual brain nuclei, optic radiations, and visual cortex. We evaluate how conventional diffusion tensor imaging, higher-order diffusion kurtosis imaging, and other extended dMRI techniques can assess the neuronal and glial integrity of the visual system in both humans and experimental animal models of glaucoma, among other optic neuropathies or neurodegenerative diseases. We also compare the pros and cons of these methods against other imaging modalities. A growing body of dMRI research indicates that this modality holds promise in characterizing early glaucomatous changes in the visual system, determining the disease severity, and identifying potential neurotherapeutic targets, offering more options to slow glaucoma progression and to reduce the prevalence of this world’s leading cause of irreversible but preventable blindness.

Here we present the first two complete plastid genomes for Brunelliaceae, a Neotropical family with a single genus, Brunellia. We surveyed the entire plastid genome in order to find variable cpDNA regions for further phylogenetic analyses across the family. We sampled morphologically different species, B. antioquensis and B. trianae, and found that the plastid genomes are 157,685 and 157,775 bp in length and display the typical quadripartite structure found in angiosperms. Despite the clear morphological distinction between both species, the molecular data show a very low level of divergence. The amount of nucleotide substitutions per site is one of the lowest reported to date among published congeneric studies (π = 0.00025). The plastid genomes have gene order and content coincident with other COM (Celastrales, Oxalidales, Malpighiales) relatives. Phylogenetic analyses of selected superrosid representatives show high bootstrap support for the ((C,M)O) topology. The N-fixing clade appears as the sister group of the COM clade and Zygophyllales as the sister to the rest of the fabids group.

The global economy, and agriculture, in particular, faces significant challenges and transformation pressures. A major challenge, and opportunity, is the transformation towards digital agriculture or agriculture 4.0, where knowledge transfer (KT) has an important role to play not only in ensuring that digital innovations reach end-users, but also that these innovations contribute to development in rural landscapes. This paper analyses the role of KT in the framework of digital transformation (DT) in the Andalusian olive landscape. Thus, from the perspective of knowledge-generating agents, the main knowledge emitting and receiving actors in the DT are identified by using Social Network Analysis techniques (SNA). Subsequently, the performance of the Technological Innovation System (TIS) in KT is evaluated by using the multi-criteria Analytic Hierarchy Process (AHP) method. The results suggest that the knowledge-generating agents, the knowledge transfer actors, and the scientific and dissemination media actors are the main knowledge emitters and highlight their role as cohesive actors of the social network. The main knowledge receivers are olive growers, cooperatives and non-cooperative groups. The results also indicate that the global performance of the TIS in the KT function is medium/low. Furthermore, in the KT sub-functions where the TIS in DT performs best is the quality of the transfer processes of DT, and where it performs worst is the sufficiency of spaces for KT.

Introduction. Tuberculosis is one of the most widely distributed infectious diseases worldwide. It is the most common cause of mortality among AIDS patients. In Colombia, 12,918 tuberculosis cases were notified, and 926 deaths were reported in 2015. Objective. To determine the prevalence and risk factors associated to mycobacterial infections in HIVpositive patients in two public hospitals from Bogotá. Materials and methods. A prospective and descriptive study was carried out by an active search for tuberculosis cases and non-tuberculous mycobacterial infections in HIV-positive patients. We considered demographic, social, clinical, and personal habits as variables. Statistical analyses were done using Stata 13™ software. Results. Three hundred and fifty six patients were included, 81.2% were men and 18.8% were women; the mean age was 36.5 years. Tuberculosis infection had a frequency of 19.9% (95% CI: 15.9-24.5%) and non-tuberculous mycobacterial infection had a 3.9% frequency (95% CI: 2.16-6.5%). Bivariate analysis showed a statistically significant association between tuberculosis infection and CD4+ T cell counts (p=0.003), viral load (p=0.008), antiretroviral therapy (p=0.014), and body mass index (BMI)

A new species of Myrcia (Myrtaceae) from the subandean forests of the Nariño department, Colombia, is described and illustrated. Additionally, a new record of Eugenia (Myrtaceae) for the flora of the same region is identified. Taxonomic affinities of the new taxon are discussed, as well as unusual morphological characteristics of the fruit’s.

En Colombia, el derecho a la pensión, en cualquiera de sus modalidades, constituye uno de los mecanismos para garantizar el derecho a la seguridad social. Con el propósito de determinar cuáles regímenes pensionales se adecúan más a la realidad social y laboral de la población con discapacidad en el país, se revisaron la legislación y la jurisprudencia colombianas mediante un método de estudio exploratorio–descriptivo. Se encontró que ese derecho confiere un tratamiento especial para las personas con discapacidad. En la legislación colombiana se regulan con protección constitucional especial, cuanto menos, diez clases de pensiones para este grupo de personas.

This article makes a review of the legislation in force in Colombia on peace processes that we have had, recommending to the Colombian State, take into account the main settings for the current negotiation, from the perspective of the right to peace embodied in our Constitution and the legal framework for the peace established in the Legislative Act 1 of 2012.

Objective: The post-reconstitution chemical stability and microbial challenge hold time of nonpreserved telavancin for injection was determined using common reconstitution diluents and intravenous (IV) infusion solutions stored at room temperature with light (ambient) or at 2°C to 8°C without light (refrigeration). Methods: Telavancin was reconstituted with 5% dextrose, 0.9% normal saline, or sterile water (15 mg/mL). Infusion solutions at 0.6 and 8.0 mg/mL were prepared in ViaFlex (polyvinyl chloride) IV bags (Baxter International Inc, Deerfield, Illinois) using 5% dextrose, 0.9% normal saline, or lactated Ringer’s solution. Chemical stability was evaluated for up to 14 days under refrigeration and for up to 3 days under ambient conditions. Telavancin concentration and degradant levels were determined using a stability-indicating HPLC method. Solutions were subjected to microbial-challenge testing for up to 48 hours (ambient) or for up to 6 days (refrigeration). Results: All reconstituted or infused telavancin solutions met the prespecified stability acceptance criteria after 2 days under ambient and minimum 7 days under refrigeration. Following inoculation with gram-positive and gram-negative microorganisms, telavancin infusion solutions stored under ambient conditions reduced or inhibited populations of all organisms up to 48 hours, except for Serratia marcescens, which exhibited growth of >0.5 log10 after 12 hours. All refrigerated samples inhibited or reduced bacterial populations up to 6 days. Conclusions: These results are supportive of a total hold time for reconstituted telavancin in vials plus the time in IV infusion solutions in polyvinyl chloride bags to not exceed 12 hours under ambient conditions and 7 days under refrigeration.

Olive groves are representative of the landscape and culture of Spain. They occupy 2.5 M ha (1.5 M ha in Andalusia) and are characterised by their multifunctionality. In recent years, socio-economic and environmental factors (i.e., erosion) have compromised their sustainability, leading farmers to abandon their farms or intensify their management. The main objective/purpose of this research was to study the drivers and concerns that condition farmers’ choice of a given olive grove management model. Taking the Estepa region as a case study (Andalusia, Spain), surveys were conducted among farmers with integrated and organic managed olive groves. The socio-economic aspects were the main objectives and concerns of the farmers with integrated olive groves. In the case of farmers with organic management, conservation objectives prevailed, and their concerns were oriented to environmental threats. The education level was a key factor in the adoption of given farm management, as it increased the level of environmental awareness. In the context of multifunctional agriculture, it would be desirable to increase this awareness of the environmental threats against olive groves, in order to provide incentives for the implementation of agri-environmental practices that would enhance the sustainability of these systems.

The persistence of innovation is a topic that has been used in recent years. Companies must be in continuous production of innovations to achieve a competitive advantage in the market and for this, it is necessary to have elements that positively influence the persistence of innovating. The objective of the article is to describe the elements that positively influence the persistence of innovation through a systematic literature review in the range of the last 10 years (2010–2019). As a result, 34 articles were obtained and it was identified that investment in R & D, human resources and knowledge management positively influences the persistence of innovation.

This work aims to assess, in a comparative way, the sustainability of organic and conventional olive growing systems in the Sfax region (Tunisia). This assessment will be undertaken based on I) a multidimensional perspective considering the three classical dimensions of sustainability – environmental, economic and socio-territorial – and II) on an experts’ knowledge approach selecting the adequate criteria of sustainability to compare both systems. The Analytic Hierarchy Process methodology (AHP) was applied as the adequate framework to fulfil the study objectives based on a survey directed with a panel of 20 Experts. Results suggest the need to reinforce the economic performance of organic olive growing production system through political strategies focusing on I) the improvement of the productivity by the implementation of good practices II) the increase of the demand of organic products in the local market, essentially by the improvement of the consumer’s purchase capacity and III) the adoption of a strategic plan to explore new markets.

This article shows an analysis and landscape of human resources development from the strategic point of view. It will consider a conceptual framework of the importance of training in management practices; the training as “human resource development” and importance of HRD studies today. An analysis of existing theoretical frameworks and review papers in databases was performed. In the end it shows the importance of strategic HRD in the literature and studies and seminal authors from the academy.

Rapeseed oil is expected to be increasingly used in Spain as raw material to produce biodiesel to the detriment of extra-EU imports of biodiesel mainly based on soybean oil from Argentina. Therefore, the environmental impacts produced throughout the life cycle of energy crops used to produce biodiesel which is consumed in Spain could be radically affected. In this context, the environmental impacts of rapeseed cultivation in Spain and soybean cultivation in Argentina, were compared under certain growing conditions using Life Cycle Assessment (LCA). Two methods of calculation for Life Cycle Impact Assessment (LCIA) and two functional units (FUs) were used to test potential biases. The results showed that the cultivation of soybean in Argentina had, in general, fewer environmental impacts than rapeseed cultivation in Spain when the FU was the area of cultivation, but these findings are inverted when the analysis is conducted according to the energy content of the biodiesel obtained from these crops. Soybean in fact has very low oil content, meaning that larger areas of land are required to obtain the same amount of biodiesel and that consequently it has a higher environmental impact by energy content. Fertilization was, in general, the process that generated the greatest environmental burdens, and is an area in which improvement is necessary in order to increase sustainability, particularly with regard to Spanish rapeseed.

Se describe e ilustra una especie nueva de Myrcia (Myrtaceae) para los Andes de Colombia. Se discuten las afinidades taxonómicas del nuevo taxón dentro de las Myrtaceae colombianas. Adicionalmente, se presentan cinco nuevos registros de Myrtaceae para la flora nativa colombiana.

This article suggests the need to modify the Institutional structure of disability in Colombia, adjusting it to the new conceptual models posed by the UN Convention on the Rights of Persons with Disabilities This new institutional design, proposes the creation of the Presidential Council on Disability, the National Institute on Disability, a National Disability Rights Watch, the National Disability Fund and the Deputy Attorney´s office on disability.

En América Latina solo el 2% de libros son accesibles a la población con discapacidad visual, fenómeno que incide en su desarrollo inclusivo, por esta razón, se está estudiando la ratificación del Tratado de Marrakech, para que las leyes de derechos de autor incluyan excepciones, que permitan que las entidades que promueven los derechos de las personas con discapacidad visual puedan producir dichas obras sin tener que solicitar permisos o pagar derechos para ponerla a disposición de esta población.

El presente artículo es abordado desde las ciencias de la gestión. El objetivo es hacer una revisión sobre la capacitación y su efecto en la calidad dentro de las organizaciones. Inicialmente se plantean algunos antecedentes relacionados con la calidad y capacitación, posteriormente se realiza una conceptualización de la capacitación como una manera de formación en la organización, y finalmente, se enfatiza en la capacitación como base de la gestión de calidad en las organizaciones. Se concluyó que la capacitación influye directamente en la calidad desde el desarrollo de conocimientos, habilidades y destrezas, coadyuvando al desarrollo de los sistemas de calidad en la organización.

La arquitectura de automatización PROSA es una descripción orientada hacia objetos que implementan sistemas de producción. Un enfoque basadoen sistemas para eventos discretos, detección de eventos y la teoría de control supervisorio, representa el comportamiento de una unidad de producción controlada. Para obtener la descripción orientada a objetosde esta unidad, se aplicó modelado conceptual y se utilizó el Lenguaje unificado de modelado.

El presente artículo presenta una arquitectura para la extracción de información de espacios urbanos, la extracción de información de espacios urbanos, la cual debe permitir la integración entre los sistemas de visión por computador que procesan imágenes o video con estrategias de bajo nivel, con la interpretación semántica que los humanos hacen de los espacios. En este documento también se presenta la estructura de esta arquitectura y las limitaciones que introducen los sistemas de adquisición con cámaras.

Con base en la caracterización de los números naturales a partir de la propiedad de recursión (ver [2]), probamos en forma general que para un conjunto dado las propiedades de recursión, inducción y buena fundación son equivalentes entre sí. El resultado lo extendemos a clases y lo utilizamos para dar otra prueba de la caracterización del conjunto de los naturales mediante recursión. Abstract. Based on the characterization of the set of natural numbers by the recursion property, developed in [2], we prove in a general setting that the properties of recursion, induction and well-foundedness are equivalent for a given set. This result is extended to classes and is used to give another proof of the characterization of the set of natural numbers by recursion.

Se identifica y se caracteriza en términos de: cantidad, tipo, localización y manifestación, los transportes, tiempos de espera, movimientos y procesos innecesarios en nueve pymes manufactureras de la ciudad de Medellín. El procedimiento constó de las etapas: selección de procesos a estudiar (uno por empresa), capacitación al personal operativo (7 mudas, 5S y gerencia visual), sesión en profundidad con administración de formulario de identificación del muda, verificación en el gemba, y resultados y análisis. Consolidando los hallazgos para las nueve empresas, 151 trabajadores fueron capacitados, los cuales contribuyeron a identificar 1.085 actividades que no aportan valor al cliente, con un promedio de 121 por proceso-empresa, la mayoría fueron transportes (31%) y movimientos innecesarios (29%). Se brindan elementos metodológicos que facilitan la comunicación entre el nivel operativo y los demás, así como la capacitación y la participación activa del mismo, posibilitando identificar oportunidades de mejora para las empresas. Se ofrece información de interés para la academia, el gobierno, los centros de desarrollo tecnológico y el sector productivo.Is identified and characterized in terms of: quantity, type, location and expression, transportation, waiting times, movements, and unnecessary processes, in nine manufacturing SMEs in the city of Medellin. The procedure consisted of the stages: selection of processes to be studied (one per company), operating personnel training (7 Wastes (Muda), 5S and visual management), deep session with management of the Muda identification form, verifying in the shop floor (Gemba), results and analysis. Consolidating the findings for the nine companies, 151 workers were trained, which helped to identify 1.085 activities that do not add value to the customer, with an average of 121 per process-company, most were transportation (31%) and unnecessary movements (29%). Methodological elements are provided to facilitate communication between the operational level and others, as well as training and active participation of the same, making it possible to identify opportunities for business improvement. It offers information of interest to academia, government, technology development centers and the productive sector.

Aunque el concepto de multifuncionalidad está plasmado, implícita o explícitamente, en el diseño de las políticas agrarias actuales, su consideración a la hora de analizar y evaluar sistemas agrarios es aún relativamente escasa en la literatura. Para tal fin se propone utilizar el Proceso Analítico Jerárquico (Analytic Hierarchy Process - AHP), técnica de decisión multicriterio discreta que se utiliza para la toma de decisiones complejas. La metodología AHP es expuesta junto con un procedimiento propuesto para medir el acuerdo relativo entre decisores y la uniformidad de las alternativas en la toma de decisiones en grupo. Finalmente, AHP es aplicado a la evaluación del olivar ecológico, integrado y convencional de Andalucía considerando criterios de distinta naturaleza "”económicos, técnicos, socioculturales y medioambientales"” con el fin de determinar la forma o formas de producción más interesantes globalmente en el medio-largo plazo para el conjunto de la sociedad en base al conocimiento de expertos en olivar.

El problema de tráfico tiene diferentes componentes que pueden ser analizados: los vehículos, los peatones y la interacción entre ellos. En este trabajo se propone un método de adquisición de variables de tráfico peatonal, utilizando técnicas de visión por computador. A partir de una secuencia de vídeo son detectados los peatones aislados, los grupos de peatones y los vehículos de la escena, utilizando un modelo del fondo. Los peatones son seguidos en la imagen por medio de características de su contorno y flujo óptico. El conteo de peatones es realizado sobre cualquier zona de la escena para estimar el flujo y la dirección de movimiento. El método propuesto puede ser configurado bajo diferentes perspectivas a partir de un conjunto de ejemplos. Los resultados experimentales en cruces peatonales demuestran que el método permite estimar las variables de interés en escenas complejas.

Extra-axial restriction on diffusion weighted imaging (DWI) is an unusual finding on brain magnetic resonance imaging (MRI). Intra-axial restriction on DWI, however, is common, and can represent brain parenchymal infarction, tumor, abscess, or toxic-metabolic process. The infrequency of extra-axial DWI restriction and the paucity of clinico-pathological correlation in the literature limit its differential diagnosis. Scant case reports suggest that extra-axial DWI restriction could be a lymphoma, neurenteric cyst, or, in one patient, subdural empyema [1–3]. We postulate that pus formation must be excluded first, because it can provoke an aggressive meningo-vasculitis with rapidly fatal, intra-axial infarctions. Our patient was a 45-year-old man, presenting to our hospital with left facial droop and right (contralateral) arm and leg weakness. Initial MRI revealed DWI restriction in the left lateral pons, consistent with a classic Millard-Gubler stroke. Also noted was a subtle, extra-axial area of curvilinear diffusion restriction in the left cerebellar-pontine angle’s subarachnoid space. Days later, the patient had a headache, and repeat MRI revealed extension of the two DWI lesions – both the intra-axial pontine infarction and the extra-axial area of restricted diffusion in the subarachnoid space. The patient became comatose, a third MRI revealed more extensive DWI restrictions, and he expired despite aggressive care. Autopsy revealed massive brainstem infarcts, a thick lymphoplasmacytic infiltrate, copious Gram-Positive cocci (likely MRSA) and arteries partially occluded with fibrointimal proliferation. This emphasizes the concept that extra-axial DWI restriction can represent pus development in the subarachnoid space – a radiographic marker to identify a patient at risk for demise due to septic, meningo-vasculitic infarctions.

Este artículo presenta la metodología utilizada para mejorar la línea de ensamble de asientos delanteros de una empresa autopartista, llevado a cabo mediante simulación dinámica de sistemas. Con dicha técnica se analiza la respuesta de la línea ante escenarios que consideran modificaciones en la cantidad y la distribución del talento humano y en las operaciones. Como resultado se obtiene un modelo de simulación que representa razonablemente la línea y se identifican dos estrategias de mejora. La primera, ya implementada con inversión casi nula, aumenta la productividad de la línea en 12% y reduce su tiempo ocioso en 44%. La segunda, denominada “integración de centros de trabajo”, rompe paradigmas de producción y permite obtener aún mayores beneficios. Dicha línea se convierte en la más productiva de la empresaIn this paper, a methodology to improve the assembly process front seat to cars is present. To improve this process the system dynamics simulation was used. The result of the assembly process in various experimental conditions was analyzed. Changes in workforce’s quantity and distribution and in jobs integration were simulated. As results of this study, a simulation model that reasonably represents the dynamic behaviour of the process and two improvement strategies were obtained. The strategy first with an investment few was implemented. As result of this, the process’s productivity in 12% was incremented and the personnel’s idle time in 44% was reduced. The strategy second “Integration of workplaces” was denominate and bests results to can obtains

In recent years there has been an increasing tendency to recycle the wastes generated by building companies in the construction industry, demolition wastes being the most important in terms of volume. The aim of this work is to study the possibility of using recycled aggregates from construction and demolition wastes in the preparation of precast non-structural concretes. To that purpose, two different percentages (15% and 30%) of natural aggregates were substituted by recycled aggregates in the manufacture of paving blocks and hollow tiles. Dosages used by the company have not been changed by the introduction of recycled aggregate. Precast elements have been tested by means of compressive and flexural strength, water absorption, density, abrasion, and slipping resistance. The results obtained show the possibility of using these wastes at an industrial scale, satisfying the requirements of the Spanish standards for these elements.