Papel y expectativas de los parques científicos como elementos de atracción y apoyo de empresas y emprendedores sociales: Un estudio FSQCA

Los parques científicos (PC) son uno de agentes más comunes, pero también más controvertidos, de las políticas públicas de innovación. Los resultados divergentes sobre su impacto y aportación de valor ponen de manifiesto que no ejercen un efecto homogéneo en todas las tipologías de empresa. Mediante este trabajo se ha querido explorar e identificar las vías por las que los PC crean valor para el emprendimiento social y mostrar su potencial relevancia como elementos dinamizadores de este tipo de emprendimientos. Este estudio busca determinar de forma exploratoria en qué medida ciertos atributos de los parques influyen en la percepción de valor y en las motivaciones de las empresas y entidades de economía social para ubicarse en estos espacios. Para ello se acomete un estudio empírico sobre una muestra de 25 empresas sociales ubicadas en cinco PC de España y se aplica un análisis fsQCA para vincular distintos perfiles de empresa social con los posibles beneficios percibidos por la ubicación en un PC. Nuestros resultados revelan que las empresas con una mayor motivación prosocial decidieron localizarse en un PC fundamentalmente atraídas por las facilidades de acceso a financiación pública y por las condiciones preferentes en el alquiler. Se identifican también los perfiles de empresas sociales más atraídas por la proximidad a la universidad y por los efectos de aglomeración que les aporta el parque donde se ubican

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

Anomaly Detection systems based on Machine and Deep learning are the most promising solutions to detect cyberattacks in the industry. However, these techniques are vulnerable to adversarial attacks that downgrade prediction performance. Several techniques have been proposed to measure the robustness of Anomaly Detection in the literature. However, they do not consider that, although a small perturbation in an anomalous sample belonging to an attack, i.e., Denial of Service, could cause it to be misclassified as normal while retaining its ability to damage, an excessive perturbation might also transform it into a truly normal sample, with no real impact on the industrial system. This paper presents a methodology to calculate the robustness of Anomaly Detection models in industrial scenarios. The methodology comprises four steps and uses a set of additional models called support models to determine if an adversarial sample remains anomalous. We carried out the validation using the Tennessee Eastman process, a simulated testbed of a chemical process. In such a scenario, we applied the methodology to both a Long-Short Term Memory (LSTM) neural network and 1-dimensional Convolutional Neural Network (1D-CNN) focused on detecting anomalies produced by different cyberattacks. The experiments showed that 1D-CNN is significantly more robust than LSTM for our testbed. Specifically, a perturbation of 60% (empirical robustness of 0.6) of the original sample is needed to generate adversarial samples for LSTM, whereas in 1D-CNN the perturbation required increases up to 111% (empirical robustness of 1.11)

Akt phosphorylation of HCV NS5B regulates polymerase activity and HCV infection

Hepatitis C virus (HCV) is a single-stranded RNA virus of positive polarity [ssRNA(+)] that replicates its genome through the activity of one of its proteins, called NS5B. This viral protein is responsible for copying the positive-polarity RNA genome into a negative-polarity RNA strand, which will be the template for new positive-polarity RNA genomes. The NS5B protein is phosphorylated by cellular kinases, including Akt. In this work, we have identified several amino acids of NS5B that are phosphorylated by Akt, with positions S27, T53, T267, and S282 giving the most robust results. Site-directed mutagenesis of these residues to mimic (Glu mutants) or prevent (Ala mutants) their phosphorylation resulted in a reduced NS5B in vitro RNA polymerase activity, except for the T267E mutant, the only non-conserved position of all those that are phosphorylated. In addition, in vitro transcribed RNAs derived from HCV complete infectious clones carrying mutations T53E/A and S282E/A were transfected in Huh-7.5 permissive cells, and supernatant viral titers were measured at 6 and 15 days post-transfection. No virus was rescued from the mutants except for T53A at 15 days post-transfection whose viral titer was statistically lower as compared to the wild type. Therefore, phosphorylation of NS5B by cellular kinases is a mechanism of viral polymerase inactivation. Whether this inactivation is a consequence of interaction with cellular kinases or a way to generate inactive NS5B that may have other functions are questions that need further experimental workMinisterio de Ciencia, Innovación y Universidades (MCIU), PI18/00210 from Instituto de Salud Carlos III, and S2018/BAA-4370 (PLATESA2 from Comunidad de Madrid/FEDER). CP was supported by the Miguel Servet program of the Instituto de Salud Carlos III (CPII19/00001), cofinanced by the European Regional Development Fund (ERDF). CG-C was supported by the predoctoral contract PRE2018-083422 from MCIU. CIBERehd (Centro de Investigación en Red de Enfermedades Hepáticas y Digestivas) was funded by the Instituto de Salud Carlos III. Institutional grants from the Fundación Ramón Areces and Banco Santander to the CBMS

Allotopic expression of mitochondrial-encoded genes in mammals: achieved goal, undemonstrated mechanism or impossible task?

Mitochondrial-DNA diseases have no effective treatments. Allotopic expression—synthesis of a wild-type version of the mutated protein in the nuclear-cytosolic compartment and its importation into mitochondria—has been proposed as a gene-therapy approach. Allotopic expression has been successfully demonstrated in yeast, but in mammalian mitochondria results are contradictory. The evidence available is based on partial phenotype rescue, not on the incorporation of a functional protein into mitochondria. Here, we show that reliance on partial rescue alone can lead to a false conclusion of successful allotopic expression. We recoded mitochondrial mt-Nd6 to the universal genetic code, and added the N-terminal mitochondrial-targeting sequence of cytochrome c oxidase VIII (C8) and the HA epitope (C8Nd6HA). The protein apparently co-localized with mitochondria, but a significant part of it seemed to be located outside mitochondria. Complex I activity and assembly was restored, suggesting successful allotopic expression. However, careful examination of transfected cells showed that the allotopically-expressed protein was not internalized in mitochondria and that the selected clones were in fact revertants for the mt-Nd6 mutation. These findings demonstrate the need for extreme caution in the interpretation of functional rescue experiments and for clear-cut controls to demonstrate true rescue of mitochondrial function by allotopic expression

Mitochondrial cristae shape determines respiratory chain supercomplexes assembly and respiratory efficiency

Respiratory chain complexes assemble into functional quaternary structures called supercomplexes (RCS) within the folds of the inner mitochondrial membrane, or cristae. Here, we investigate the relationship between respiratory function and mitochondrial ultrastructure and provide evidence that cristae shape determines the assembly and stability of RCS and hence mitochondrial respiratory efficiency. Genetic and apoptotic manipulations of cristae structure affect assembly and activity of RCS in vitro and in vivo, independently of changes to mitochondrial protein synthesis or apoptotic outer mitochondrial membrane permeabilization. We demonstrate that, accordingly, the efficiency of mitochondria-dependent cell growth depends on cristae shape. Thus, RCS assembly emerges as a link between membrane morphology and function.We thank A. Gross (Weizmann Institute) for anti-BID antibody, A. Latorre-Pellicer (CNIC) for mtDNA RT-PCR, and M. Albiero (VIMM) for tail vein injections. L.S. is a senior scientist of the Dulbecco-Telethon Institute. This work is supported by Telethon Italy (GGP12162, GPP10005B, and TCR02016), AIRC Italy, MOH Italy (GR 09.021), and Swiss National Foundation (31-118171). J.A.E. is supported by MINECO (SAF2012-32776 and CSD2007-00020), DGA (B55, PIPAMER O905), and CAM (S2011/BMD-2402). S.C. was supported by a Journal of Cell Science Travelling Fellowship. C.F. was supported by an AIRC Biennial Fellowship. The CNIC is funded by the Instituto de Salud Carlos III-MICINN and the Pro-CNIC Foundation.S

The long non-coding rna cerox1 is a post transcriptional regulator of mitochondrial complex i catalytic activity

To generate energy efficiently, the cell is uniquely challenged to co-ordinate the abundance of electron transport chain protein subunits expressed from both nuclear and mitochondrial genomes. How an effective stoichiometry of this many constituent subunits is co- ordinated post-transcriptionally remains poorly understood. Here we show that Cerox1, an unusually abundant cytoplasmic long noncoding RNA (lncRNA), modulates the levels of mitochondrial complex I subunit transcripts in a manner that requires binding to microRNA-488-3p. Increased abundance of Cerox1 cooperatively elevates complex I subunit protein abundance and enzymatic activity, decreases reactive oxygen species production, and protects against the complex I inhibitor rotenone. Cerox1 function is conserved across placental mammals: Human and mouse orthologues effectively modulate complex I enzymatic activity in mouse and human cells, respectively. Cerox1 is the first lncRNA demonstrated, to our knowledge, to regulate mitochondrial oxidative phosphorylation and, with miR-488-3p, represent novel targets for the modulation of complex I activity

Communities of farmers, shepherds and artisans. Usewear analysis of the working processes in Andalusian Neolithic

[EN] In this paper we present the results of twenty years of functional analysis carried out on lithic industries from Neolithic Andalusian sites. Data are presented from a diachronical perspective, individualizing two periods: Ancient and Recent Neolithic. Independently of their geographical situation and the specific nature of each settlement, we must stress the relative homogeneity of the activities documented in the ancient period. They are especially oriented to the exploitation of animal resources, perhaps because of the importance of livestock practices. In the following period the use-wear analysis shows a wider diversification of the working processes, together with the specialization of some sites in certain activities.[ES] En este trabajo se presentan los resultados de veinte años de análisis funcionales efectuados sobre materiales líticos tallados del Neolítico, procedentes de diversos yacimientos andaluces. Los datos se ofrecen con una perspectiva diacrónica, individualizando dos periodos: Neolítico Antiguo y Reciente. Con independencia de su situación geográfica y de la naturaleza específica de cada asentamiento, destaca la relativa homogeneidad de las actividades que se documentan en el periodo más antiguo, centradas fundamentalmente en la explotación de los recursos de origen animal, quizá por la importancia de las prácticas ganaderas. En la siguiente etapa se observa una mayor diversificación de los procesos de trabajo representados en las huellas de uso, así como la especialización de algunos sitios en ciertas actividades.Peer reviewe

31 Review of MADICS: A Methodology for Anomaly Detection in Industrial Control Systems

Diverse cyberattack detection systems have been proposed over the years in the context of Industrial Control Systems (ICS). However, the lack of standard methodologies to detect cyberattacks in industrial scenarios prevents researchers from accurately comparing proposals and results. In this work, we present MADICS, a methodology to detect cyberattacks in industrial scenarios that intends to be a guideline for future works in the field. In order to validate MADICS, we used the popular SWaT dataset, which was collected from a fully operational water treatment plant. The experiments showed that following MADICS, we achieved state-of-the-art precision of 0.984, as well as a recall of 0.750 and F1-score of 0.851, above the average of other works, proofing that the proposed methodology is suitable to be used in real industrial scenarios

SUSAN: A Deep Learning based anomaly detection framework for sustainable industry

Nowadays, sustainability is the core of green technologies, being a critical aspect in many industries concerned with reducing carbon emissions and energy consumption optimization. While this concern increases, the number of cyberattacks causing sustainability issues in industries also grows. These cyberattacks impact industrial systems that control and monitor the right functioning of processes and systems. Furthermore, they are very specialized, requiring knowledge about the target industrial processes, and being undetectable for traditional cybersecurity solutions. To overcome this challenge, we present SUSAN, a Deep Learning-based framework, to build anomaly detectors that expose cyberattacks affecting the sustainability of industrial systems. SUSAN follows a modular and flexible design that allows the ensembling of several detectors to achieve more precise detections. To demonstrate the feasibility of SUSAN, we implemented the framework in a water treatment plant using the SWaT testbed. The experiments performed achieved the best recall rate (0.910) and acceptable precision (0.633), resulting in an F1-score of 0.747. Regarding individual cyberattacks that impact the system’s sustainability, our implementation detected all of them, and, concerning the related work, it achieved the most balanced results, with 0.64 as the worst recall rate. Finally, a false-positive rate of 0.000388 makes our solution feasible in real scenarios