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In today’s technologically advanced landscape, sensors feed critical data for accurate decision-making and actions. Ensuring the integrity and reliability of sensor data is paramount to system performance and security. This paper introduces an innovative approach utilizing discrete wavelet transforms (DWT) embedded within microcontrollers to scrutinize sensor data meticulously. Our methodology aims to detect and isolate malfunctions, misuse, or any anomalies before they permeate the system, potentially causing widespread disruption. By leveraging the power of wavelet-based analysis, we embed computational intelligence directly into the microcontrollers, enabling them to monitor and validate their outputs in real-time. This proactive anomaly detection framework is designed to distinguish between normal and aberrant sensor behaviors, thereby safeguarding the system from erroneous data propagation. Our approach significantly enhances the reliability of embedded systems, providing a robust defense against false data injection attacks and contributing to overall cybersecurity.

Fibroblasts are versatile cells that play a major role in wound healing by synthesizing and remodeling the extracellular matrix (ECM). In cancers, fibroblasts play an expanded role in tumor progression and dissemination, immunosuppression, and metabolic support of cancer cells. In prostate cancer (PCa), fibroblasts have been shown to induce growth and increase metastatic potential. To further understand differences in the functions of human PCa associated fibroblasts (PCAFs) compared to normal prostate fibroblasts (PFs), we investigated the metabolic profile and ECM degradation characteristics of PFs and PCAFs using a magnetic resonance imaging and spectroscopy compatible intact cell perfusion assay. To further understand how PFs and PCAFs respond to hypoxic tumor microenvironments that are often observed in PCa, we characterized the effects of hypoxia on PF and PCAF metabolism, invasion and PD-L1 expression. We found that under normoxia, PCAFs displayed decreased ECM degradation compared to PFs. Under hypoxia, ECM degradation by PFs increased, whereas PCAFs exhibited decreased ECM degradation. Under both normoxia and hypoxia, PCAFs and PFs showed significantly different metabolic profiles. PD-L1 expression was intrinsically higher in PCAFs compared to PFs. Under hypoxia, PD-L1 expression increased in PCAFs but not in PFs. Our data suggest that PCAFs may not directly induce ECM degradation to assist in tumor dissemination, but may instead create an immune suppressive tumor microenvironment that further increases under hypoxic conditions. Our data identify the intrinsic metabolic, ECM degradation and PD-L1 expression differences between PCAFs and PFs under normoxia and hypoxia that may provide novel targets in PCa treatment.

Abstract Background Harnessing the power of the immune system by using immune checkpoint inhibitors has resulted in some of the most exciting advances in cancer treatment. The full potential of this approach has, however, not been fully realized for treating many cancers such as pancreatic and breast cancer. Cancer metabolism influences many aspects of cancer progression including immune surveillance. An expanded understanding of how cancer metabolism can directly impact immune checkpoints may allow further optimization of immunotherapy. We therefore investigated, for the first time, the relationship between the overexpression of choline kinase-α (Chk-α), an enzyme observed in most cancers, and the expression of the immune checkpoint PD-L1. Methods We used small interfering RNA to downregulate Chk-α, PD-L1, or both in two triple-negative human breast cancer cell lines (MDA-MB-231 and SUM-149) and two human pancreatic ductal adenocarcinoma cell lines (Pa09C and Pa20C). The effects of the downregulation were studied at the genomic, proteomic, and metabolomic levels. The findings were compared with the results obtained by the analysis of public data from The Cancer Genome Atlas Program. Results We identified an inverse dependence between Chk-α and PD-L1 at the genomic, proteomic, and metabolomic levels. We also found that prostaglandin-endoperoxide synthase 2 (COX-2) and transforming growth factor beta (TGF-β) play an important role in this relationship. We independently confirmed this relationship in human cancers by analyzing data from The Cancer Genome Atlas Program. Conclusions Our data identified previously unknown roles of PD-L1 in cancer cell metabolic reprogramming, and revealed the immunosuppressive increased PD-L1 effect of Chk-α downregulation. These data suggest that PD-L1 regulation of metabolism may be mediated through Chk-α, COX-2, and TGF-β. The observations provide new insights that can be applied to the rational design of combinatorial therapies targeting immune checkpoints and cancer metabolism.

Abstract Partial and/or heterogeneous irradiation of established (i.e., large, vascularized) tumors by α‐particles that exhibit only a 4–5 cell‐diameter range in tissue, limits the therapeutic effect, since regions not being hit by the high energy α‐particles are likely not to be killed. This study aims to mechanistically understand a delivery strategy to uniformly distribute α‐particles within established solid tumors by simultaneously delivering the same α‐particle emitter by two diverse carriers, each killing a different region of the tumor: (1) the cancer‐agnostic, but also tumor‐responsive, liposomes engineered to best irradiate tumor regions far from the vasculature, and (2) a separately administered, antibody, targeting any cancer‐cell's surface marker, to best irradiate the tumor perivascular regions. We demonstrate that on a prostate specific membrane antigen (PSMA)‐expressing prostate cancer xenograft mouse model, for the same total injected radioactivity of the α‐particle emitter Actinium‐225, any radioactivity split ratio between the two carriers resulted in better tumor growth inhibition compared to the tumor inhibition when the total radioactivity was delivered by any of the two carriers alone. This finding was due to more uniform tumor irradiation for the same total injected radioactivity. The killing efficacy was improved even though the tumor‐absorbed dose delivered by the combined carriers was lower than the tumor‐absorbed dose delivered by the antibody alone. Studies on spheroids with different receptor‐expression, used as surrogates of the tumors' avascular regions, demonstrated that our delivery strategy is valid even for as low as 1+ (ImmunoHistoChemistry score) PSMA‐levels. The findings presented herein may hold clinical promise for those established tumors not being effectively eradicated by current α‐particle radiotherapies.

The Internet of Things (IoT) represents a mean to share resources (memory, storage computational power, data, etc.) between computers and mobile devices, as well as buildings, wearable devices, electrical grids, and automobiles, just to name few. The IoT is leading to the development of advanced information services that will require large storage and computational power, as well as real-time processing capabilities. The integration of IoT with emerging technologies such as Fog Computing can complement these requirements with pervasive and cost-effective services capable of processing large-scale geo-distributed information. In any IoT application, communication availability is essential to deliver accurate and useful information, for instance, to take actions during dangerous situations, or to manage critical infrastructures. IoT components like gateways, also called Fog Nodes, face outstanding security challenges as the attack surface grows with the number of connected devices requesting communication services. These Fog nodes can be targeted by an attacker, preventing the nodes from delivering important information to the final users or to perform accurate automated actions. This paper introduces an Anomaly Behavior Analysis Methodology based on Artificial Neural Networks, to implement an adaptive Intrusion Detection System (IDS) capable of detecting when a Fog node has been compromised, and then take the required actions to ensure communication availability. The experimental results reveal that the proposed approach has the capability for characterizing the normal behavior of Fog Nodes despite its complexity due to the adaptive scheme, and also has the capability of detecting anomalies due to any kind of sources such as misuses, cyber-attacks or system glitches, with high detection rate and low false alarms.

Purpose – The General Society Survey(GSS) is a kind of government-funded survey which aims at examining the Socio-economic status, quality of life, and structure of contemporary society. GSS data set is regarded as one of the authoritative source for the government and organization practitioners to make data-driven policies. The previous analytic approaches for GSS data set are designed by combining expert knowledges and simple statistics. By utilizing the emerging data mining algorithms, we proposed a comprehensive data management and data mining approach for GSS data sets. Design/methodology/approach – The approach are designed to be operated in a two-phase manner: a data management phase which can improve the quality of GSS data by performing attribute pre-processing and filter-based attribute selection; a data mining phase which can extract hidden knowledge from the data set by performing data mining analysis including prediction analysis, classification analysis, association analysis and clustering analysis. Findings – According to experimental evaluation results, the paper have the following findings: Performing attribute selection on GSS data set can increase the performance of both classification analysis and clustering analysis; all the data mining analysis can effectively extract hidden knowledge from the GSS data set; the knowledge generated by different data mining analysis can somehow cross-validate each other. Originality/value – By leveraging the power of data mining techniques, the proposed approach can explore knowledge in a fine-grained manner with minimum human interference. Experiments on Chinese General Social Survey data set are conducted at the end to evaluate the performance of our approach.

El siguiente trabajo se enfoca en determinar los riesgos psicosociales existentes en la industria de software mexicana, específicamente la que se encuentra en teletrabajo debido a la contingencia de COVID-19 para explorar el impacto de las medidas de prevención, definir el origen de los riesgos, si provienen de la relación del empleado con la empresa o al cliente al que prestan servicios. Se tomó como base el cuestionario de la regulación NOM-035-STPS-2018 para el diagnóstico de riesgos psicosociales en una muestra de 183 empleados. Este estudio se realizó con un análisis factorial exploratorio obteniendo resultados que demostraron que los empleados perciben una relación positiva de parte del liderazgo proveniente de la empresa, pero observan una afectación en su vida personal derivado de las largas horas de trabajo con su cliente, las cuales pueden ser agravadas por el modelo de teletrabajo en el que se encuentran actualmente.

PurposeThe inhibition of immune checkpoints such as programmed cell death ligand-1 (PD-L1/CD274) with antibodies is providing novel opportunities to expose cancer cells to the immune system. Antibody based checkpoint blockade can, however, result in serious autoimmune complications because normal tissues also express immune checkpoints. As sequence-specific gene-silencing agents, the availability of siRNA has significantly expanded the specificity and range of “druggable” targets making them promising agents for precision medicine in cancer. Here, we have demonstrated the ability of a novel biodegradable dextran based theranostic nanoparticle (NP) to deliver siRNA downregulating PD-L1 in tumors. Optical imaging highlighted the importance of NP delivery and accumulation in tumors to achieve effective downregulation with siRNA NPs, and demonstrated low delivery and accumulation in several PD-L1 expressing normal tissues.MethodsThe dextran scaffold was functionalized with small molecules containing amine groups through acetal bonds. The NP was decorated with a Cy5.5 NIR probe allowing visualization of NP delivery, accumulation, and biodistribution. MDA-MB-231 triple negative human breast cancer cells were inoculated orthotopically or subcutaneously to achieve differences in vascular delivery in the tumors. Molecular characterization of PD-L1 mRNA and protein expression in cancer cells and tumors was performed with qRT-PCR and immunoblot analysis.ResultsThe PD-L1 siRNA dextran NPs effectively downregulated PD-L1 in MDA-MB-231 cells. We identified a significant correlation between NP delivery and accumulation, and the extent of PD-L1 downregulation, with in vivo imaging. The size of the NP of ~ 20 nm allowed delivery through leaky tumor vasculature but not through the vasculature of high PD-L1 expressing normal tissue such as the spleen and lungs.ConclusionsHere we have demonstrated, for the first time, the feasibility of downregulating PD-L1 in tumors using siRNA delivered with a biodegradable dextran polymer that was decorated with an imaging reporter. Our data demonstrate the importance of tumor NP delivery and accumulation in achieving effective downregulation, highlighting the importance of imaging in siRNA NP delivery. Effective delivery of these siRNA carrying NPs in the tumor but not in normal tissues may mitigate some of the side-effects of immune checkpoint inhibitors by sparing PD-L1 inhibition in these tissues.

We present an inventory of the amphibians and reptiles of the San Vito de Coto Brus region, including the Las Cruces Biological Station, in southern Costa Rica, which is the result of a survey of the herpetofauna occurring in mountain forest fragments, pastures, coffee plantations, and other disturbed areas. We found 67 species, included 26 species of amphibians and of 41of reptiles. We describe the distribution patterns of the community on the basis of the life zones, elevation, fragmentation, and degree of anthropogenic impact. We also provide some nouvelle data on the systematics of some select taxa, their geographical ranges, microhabitats, activity, and other relevant ecological and natural history features. Finally, we comment on the present conservation status of the herpetofauna in the region. Previous literature and collection records indicate a higher number of species occurring in this area, which suggests that some declines have occurred, especially of amphibians, in last decades. Rev. Biol. Trop. 56 (2): 755-778. Epub 2008 June 30.En este artículo se presenta un inventario de los anfibios y reptiles de la región de San Vito de Coto Brus incluyendo la Estación de Biología Las Cruces, en el sur de Costa Rica. Se llevó a cabo una evaluación de las poblaciones de anfibios y reptiles presentes en los parches de bosque, potreros, cafetales y otras áreas perturbadas de la región. Como resultado de esta evaluación se registraron 26 especies de anfibios y 41 de reptiles lo que suma un total de 67 especies. Asimismo se describen los patrones generales de distribución de las especies basándose en los tipos de vegetación así como en la altitud, fragmentación y grado de perturbación antrópica en el área. Se proporcionan algunos datos sobre la sistemática de las especies, su distribución geográfica, el microhábitat que ocupan, su actividad y otros datos ecológicos y biológicos relevantes. Finalmente, se presenta una breve discusión sobre la conservación de la herpetofauna en la región. Algunos registros de la literatura y de colecciones científicas muestran que el número de especies de la herpetofauna conocidos en esta región era probablemente mayor, lo que podría indicar que han ocurrido algunas declinaciones importantes de especies, especialmente de anfibios en las últimas décadas.

Purpose: Although active learning methodologies are recognized as an effective means to achieve expected educational demands, in practice, the teaching and learning processes are still widely characterized by traditional pedagogy aspects. As a result, teaching innovations in science, technology, engineering and math (STEM) education are carried out in isolation in specific disciplines, programs or departments. To addresses these challenges and to stimulate useful teaching innovations, this study aims to propose the capability maturity model to active learning (CMMAL) for assessing the maturity level of active learning methodologies in higher education institutions (HEIs). Design/methodology/approach: The CMMAL provides inputs for planning and decision-making, identifying variables such as the current state of teaching and learning processes, project management, team development, allocation of resources and infrastructure and the choice of evaluation and assessment methods. From the relevant literature, the primary aspects that impact on active learning were identified and incorporated into the structure of the model. Next, a survey was performed with 295 STEM professors and experts validating the scope of the model proposed. Findings: The findings demonstrated the contribution of the CMMAL mainly to (1) assess the maturity levels of active methodologies in higher education and (2) stimulate the institutionalization of active learning practices in HEIs to minimize some problems related to the dissemination of new teaching practices. Practical implications: The primary practical and academic contribution of our study is the proposition of an artifact with a scope compatible with the need of the HEIs for the implementation of active learning methodologies. This paper presents a different perspective of current literature in active learning in STEM education, introducing a model that contributes to open the dialogue with HEIs interested in better understand and improve the performance in student-centered pedagogy. Originality/value: The model also informs and leads to specific recommendations for HEIs seeking to enhance the performance of and alter the culture around active learning methodologies.

Airlift systems are widely used for mass, momentum, and energy transport, particularly in hydrothermal and oil extraction wells. Predicting the impact of nozzle design parameters, such as perforation diameters and air injection areas, remains challenging. This study experimentally investigates an annular airlift pump to understand the influence of various nozzle configurations on performance. Using radial and axial injection with different perforation counts, high-speed camera visualization categorized flow regimes (bubbly, slug, slug-churn) across different gas flow rates. Dimensional analysis assessed energy efficiency, revealing a strong dependence on submergence ratio and perforation-to-inlet pipe area ratio. A dimensionless number, analogous to a restriction coefficient, explained discrepancies with theoretical models at high Reynolds numbers. A specific dimensionless group unified the experimental results for large submergence ratios (greater than 0.8). This study provides insights into optimizing airlift pump performance by exploring the effects of nozzle configurations on transport phenomena. [ABSTRACT FROM AUTHOR]