Semantic query languages for knowledge-based web services in a construction context

Since the early 2000s, different frameworks were set up to enable web-based collaboration in building projects. Unfortunately, none of these initiatives was granted a long life. Recently, however, the use of web technologies in the building industry has been gaining momentum again, considered some promising technologies for reaching a more interoperable BIM practice. Specifically, this relates to (1) Linked Data and Semantic Web technologies, and (2) cloud-based applications. In order to combine these into a network of interlinked applications and datastores, an agreed-upon mechanism for automatic communication and data retrieval needs to be used. Apart from the W3C standard SPARQL, often considered too high a threshold for developers to implement, there are some recent GraphQL-based solutions that simplify the querying process and its implementation into web services. In this paper, we review two recent open source technologies based on GraphQL, that enable to query Linked Data on the web: GraphQL-LD and HyperGraphQL

A Datalog recognizer for almost affine lambda-CFGs

International audienceThe recent emergence of linguistic formalisms exclusively based on the simply-typed λ-calculus to represent both syntax and semantics led to the presentation of innovative techniques which apply to both the problems of parsing and generating natural languages. A common feature of these techniques consists in using strong relations between typing properties and syntactic structures of families of simply-typed λ-terms. Among significant results, an efficient algorithm based on Datalog programming is presented in [Kan07] for context-free grammar of almost linear λ-terms, which are linear λ-terms augmented with a restricted form of copy. We present an extension of this method to terms for which deletion is allowed

Selective Expression of the Vβ14 T Cell Receptor on Leishmania guyanensis-Specific CD8+ T Cells during Human Infection

Peripheral blood mononuclear cells from subjects never exposed to Leishmania were stimulated with Leishmania guyanensis. We demonstrated that L. guyanensis-stimulated CD8+ T cells produced interferon (IFN)-γ and preferentially expressed the Vb14 T cell receptor (TCR) gene family. In addition, these cells expressed cutaneous lymphocyte antigen and CCR4 surface molecules, suggesting that they could migrate to the skin. Results obtained from the lesions of patients with localized cutaneous leishmaniaisis (LCL) showed that Vβ14 TCR expression was increased in most lesions (63.5%) and that expression of only a small number of Vb gene families (Vβ1, Vβ6, Vβ9, Vβ14, and Vβ24) was increased. The presence of Vβ14 T cells in tissue confirmed the migration of these cells to the lesion site. Thus, we propose the following sequence of events during infection with L. guyanensis. After initial exposure to L. guyanensis, CD8+ T cells preferentially expressing the Vb14 TCR and secreting IFN-γ develop and circulate in the periphery. During the infection, these cells migrate to the skin at the site of the parasitic infection. The role of these Vβ14 CD8+ T cells in resistance to infection remains to be determined conclusivel

T Cell Reactivity against Mycolyl Transferase Antigen 85 of M. tuberculosis in HIV-TB Coinfected Subjects and in AIDS Patients Suffering from Tuberculosis and Nontuberculous Mycobacterial Infections

The mycolyl transferase antigen 85 complex is a major secreted protein family from mycobacterial culture filtrate, demonstrating powerful T cell stimulatory properties in most HIV-negative, tuberculin-positive volunteers with latent M.tuberculosis infection and only weak responses in HIV-negative tuberculosis patients. Here, we have analyzed T cell reactivity against PPD and Ag85 in HIV-infected individuals, without or with clinical symptoms of tuberculosis, and in AIDS patients with disease caused by nontuberculous mycobacteria. Whereas responses to PPD were not significantly different in HIV-negative and HIV-positive tuberculin-positive volunteers, responses to Ag85 were significantly decreased in the HIV-positive (CDC-A and CDC-B) group. Tuberculosis patients demonstrated low T cell reactivity against Ag85, irrespective of HIV infection, and finally AIDS patients suffering from NTM infections were completely nonreactive to Ag85. A one-year follow-up of twelve HIV-positive tuberculin-positive individuals indicated a decreased reactivity against Ag85 in patients developing clinical tuberculosis, highlighting the protective potential of this antigen

In Leishmaniasis due to Leishmania guyanensis infection, distinct intralesional interleukin-10 and foxp3 mRNA expression are associated with unresponsiveness to treatment

The presence of intralesional natural regulatory T cells, characterized by the expression of Foxp3 mRNA, was analyzed in patients with localized leishmaniasis due to Leishmania guyanensis infection that was unresponsive to treatment with pentamidine isethionate. Foxp3 mRNA levels were associated with unresponsiveness to treatment among patients with a lesion duration of ⩾1 month, but this association was not observed among patients with a lesion duration of <1 month. In conclusion, high intralesional expression of Foxp3 might be an indicator of poor response to treatment, depending on the duration of lesion

Data analytics for smart buildings: a classification method for anomaly detection for measured data

Abstract Data generated by the increasingly frequent use of sensors in housing provide the opportunity to monitor, manage and optimize the energy consumption of a building and the user comfort. These data are often strewn with rare or anomalous events, considered as anomalies (or outliers), that must be detected and ultimately corrected in order to improve the data quality. However, many approaches are used or might be used (for the most recent ones) to achieve this purpose. This paper proposes a classification methodology of anomaly detection techniques applied to building measurements. This classification methodology uses a well-suited anomaly typology and measurement typology in order to provide, in the future, a classification of the most adapted anomaly detection techniques for different types of building measurements, anomalies and needs

Deep learning models for building window-openings detection in heating season

The increasing use of monitoring systems such as Building Management System (BMS) or connected devices bring the opportunity to better evaluate, model or control both occupants’ comfort and energy consumed by an operated building thanks to the consequent amount of data provided (e.g., air temperature, CO2 concentration, electricity consumption). Occupants’ behavior and more specifically window-openings affect both occupants’ thermal comfort and building energy consumption and are therefore key components to consider. This paper presents a comparison of machine learning models applied on window-openings detection during the heating season such as: Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Random Forest Classifier (RFC) and two Recurrent Neural Network (RNN), namely, Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU). While some applications of Artificial Intelligence (AI) methods applied on window-openings detection exist in the literature, this Submitted to Building and Environment January 2023 study proposes a detailed comparison of the main methods and focuses on the impact of feature engineering process considering four different data transformations based on field expertise and more than 800 different combinations built on six indoor and outdoor measurements. Results show that some of the proposed transformations and combinations positively impact all models performances. The best performances on window-openings detection are attained by using indoor temperature and CO2 concentration on RNN models with an average F1-score of 0.78 while LDA, SVM and RFC models tend to provide satisfying but lower performance around 0.70-72. In addition, by using the right transformation, significant results can be achieved by detecting up to 84-88 % of window-opening times with the sole use of indoor air temperature measurements

Leishmaniavirus-dependent metastatic leishmaniasis is prevented by blocking IL-17A

Cutaneous leishmaniasis has various outcomes, ranging from self-healing reddened papules to extensive open ulcerations that metastasise to secondary sites and are often resistant to standard therapies. In the case of L. guyanensis (L.g), about 5-10% of all infections result in metastatic complications. We recently showed that a cytoplasmic virus within L.g parasites (LRV1) is able to act as a potent innate immunogen, worsening disease outcome in a murine model. In this study, we investigated the immunophenotype of human patients infected by L.g and found a significant association between the inflammatory cytokine IL-17A, the presence of LRV1 and disease chronicity. Further, IL-17A was inversely correlated to the protective cytokine IFN-γ. These findings were experimentally corroborated in our murine model, where IL-17A produced in LRV1+ L.g infection contributed to parasite virulence and dissemination in the absence of IFN-γ. Additionally, IL-17A inhibition in mice using digoxin or SR1001, showed therapeutic promise in limiting parasite virulence. Thus, this murine model of LRV1-dependent infectious metastasis validated markers of disease chronicity in humans and elucidated the immunologic mechanism for the dissemination of Leishmania parasites to secondary sites. Moreover, it confirms the prognostic value of LRV1 and IL-17A detection to prevent metastatic leishmaniasis in human patients

Autophagy protein 5 controls flow-dependent endothelial functions

Dysregulated autophagy is associated with cardiovascular and metabolic diseases, where impaired flow-mediated endothelial cell responses promote cardiovascular risk. The mechanism by which the autophagy machinery regulates endothelial functions is complex. We applied multi-omics approaches and in vitro and in vivo functional assays to decipher the diverse roles of autophagy in endothelial cells. We demonstrate that autophagy regulates VEGF-dependent VEGFR signaling and VEGFR-mediated and flow-mediated eNOS activation. Endothelial ATG5 deficiency in vivo results in selective loss of flow-induced vasodilation in mesenteric arteries and kidneys and increased cerebral and renal vascular resistance in vivo. We found a crucial pathophysiological role for autophagy in endothelial cells in flow-mediated outward arterial remodeling, prevention of neointima formation following wire injury, and recovery after myocardial infarction. Together, these findings unravel a fundamental role of autophagy in endothelial function, linking cell proteostasis to mechanosensing