Exploring lifted planning encodings in Essence Prime

This work is supported by UK EPSRC EP/P015638/1 and EP/V027182/1, by the MICINN/FEDER, UE (RTI2018-095609-B-I00), by the French Agence Nationale de la Recherche, reference ANR-19-CHIA-0013-01, and by Archimedes institute, Aix-Marseille University.State-space planning is the de-facto search method of the automated planning community. Planning problems are typically expressed in the Planning Domain Definition Language (PDDL), where action and variable templates describe the sets of actions and variables that occur in the problem. Typically, a planner begins by generating the full set of instantiations of these templates, which in turn are used to derive useful heuristics that guide the search. Thanks to this success, there has been limited research in other directions. We explore a different approach, keeping the compact representation by directly reformulating the problem in PDDL into ESSENCE PRIME, a Constraint Programming language with support for distinct solving technologies including SAT and SMT. In particular, we explore two different encodings from PDDL to ESSENCE PRIME, how they represent action parameters, and their performance. The encodings are able to maintain the compactness of the PDDL representation, and while they differ slightly, they perform quite differently on various instances from the International Planning Competition.Publisher PD

Relaxing non-interference requirements in parallel plans

Funding: UK EPSRC (EP/P015638/1).The aim of being able to reason about quantities, time or space has been the main objective of the many efforts on the integration of propositional planning with extensions to handle different theories. Planning modulo theories (PMTs) are an approximation inspired by satisfiability modulo theories (SMTs) that generalize the integration of arbitrary theories with propositional planning. Parallel plans are crucial to reduce plan lengths and hence the time needed to reach a feasible plan in many approaches. Parallelization of actions relies on the notion of (non-)interference, which is usually determined syntactically at compile time. In this paper we define a semantic notion of interference between actions in PMT. Apart from being strictly stronger than any syntactic notion of interference, we show how semantic interference can be easily and efficiently checked by calling an off-the-shelf SMT solver at compile time, constituting a technique orthogonal to the solving method.Publisher PDFPeer reviewe

Long-term azithromycin therapy in patients with severe COPD and repeated exacerbations

The aim of this study was to determine whether long-term intermittent azithromycin therapy reduces the frequency of exacerbation in severe chronic obstructive pulmonary disease (COPD). We retrospectively investigated the clinical benefits of long-term azithromycin (500 mg orally three times per week) over 12 months in patients with severe COPD and a minimum of four acute exacerbations (AECOPD) per year or chronic bronchial colonization by Pseudomonas aeruginosa, comparing the number of AECOPD, hospitalizations due to respiratory disease, days of hospital stay, and bacterial infections during azithromycin treatment and in the year prior to this therapy. Twenty patients who completed the 12-month treatment period were analyzed. No clinically significant adverse events were observed during azithromycin treatment. Compared with baseline data, azithromycin therapy significantly reduced the number of AECOPD (2.8 ± 2.5 versus 6.8 ± 2.8, P < 0.001), hospitalizations (1.4 ± 1.5 versus 3.6 ± 1.4, P < 0.001), and cumulative annual days of hospital stay (25 ± 32.2 versus 43.7 ± 21.4, P = 0.01). The improvement was particularly significant in patients with exacerbations caused by common potentially pathogenic microorganisms, who had 70% fewer AECOPD and hospitalizations. Patients colonized by P. aeruginosa had reductions of 43% in AECOPD and 47% in hospitalizations. Long-term azithromycin is well tolerated and associated with significant reductions in AECOPD, hospitalizations, and length of hospital stay in patients with severe COPD

The malaria system microApp: A new, mobile device-based tool for malaria diagnosis

Background: Malaria is a public health problem that affects remote areas worldwide. Climate change has contributed to the problem by allowing for the survival of Anopheles in previously uninhabited areas. As such, several groups have made developing news systems for the automated diagnosis of malaria a priority. Objective: The objective of this study was to develop a new, automated, mobile device-based diagnostic system for malaria. The system uses Giemsa-stained peripheral blood samples combined with light microscopy to identify the Plasmodium falciparum species in the ring stage of development. Methods: The system uses image processing and artificial intelligence techniques as well as a known face detection algorithm to identify Plasmodium parasites. The algorithm is based on integral image and haar-like features concepts, and makes use of weak classifiers with adaptive boosting learning. The search scope of the learning algorithm is reduced in the preprocessing step by removing the background around blood cells. Results: As a proof of concept experiment, the tool was used on 555 malaria-positive and 777 malaria-negative previously-made slides. The accuracy of the system was, on average, 91%, meaning that for every 100 parasite-infected samples, 91 were identified correctly. Conclusions: Accessibility barriers of low-resource countries can be addressed with low-cost diagnostic tools. Our system, developed for mobile devices (mobile phones and tablets), addresses this by enabling access to health centers in remote communities, and importantly, not depending on extensive malaria expertise or expensive diagnostic detection equipment.Peer ReviewedPostprint (published version

Per un millor tractament de la tuberculosi

El tractament de la tuberculosi, una malaltia que encara afecta a milions de persones a tot el món, no ha variat en la seva base en els darrers 50 anys. Aquest tractament utilitza la combinació de quatre fàrmacs durant 6 mesos. Una investigació de la UAB i la UB ha testat noves combinacions de fàrmacs que semblen ser adients ja que no presenten efectes perjudicials però mantenen l'efecte del fàrmacs individuals i, malgrat ser igual de efectives que la combinació tradicional, poden reduir el temps de tractament.El tratamiento de la tuberculosis, una enfermedad que aún afecta a millones de personas en todo el mundo, no ha variado en su base en los últimos 50 años. Este tratamiento utiliza la combinación de cuatro fármacos durante 6 meses. Una investigación de la UAB i la UB ha testado nuevas combinaciones de fármacos que parecen ser adecuadas ya que no presentan efectos perjudiciales pero mantienen el efecto de los fármacos individuales y, a pesar de ser igual de efectivas que la combinación tradicional, pueden reducir el tiempo de tratamiento

Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review

Deep learning; Malaria diagnosis; Microscopic examinationAprenentatge profund; Diagnòstic de malària; Examen microscòpicAprendizaje profundo; Diagnóstico de malaria; Examen microscópicoMalaria is an infectious disease caused by parasites of the genus Plasmodium spp. It is transmitted to humans by the bite of an infected female Anopheles mosquito. It is the most common disease in resource-poor settings, with 241 million malaria cases reported in 2020 according to the World Health Organization. Optical microscopy examination of blood smears is the gold standard technique for malaria diagnosis; however, it is a time-consuming method and a well-trained microscopist is needed to perform the microbiological diagnosis. New techniques based on digital imaging analysis by deep learning and artificial intelligence methods are a challenging alternative tool for the diagnosis of infectious diseases. In particular, systems based on Convolutional Neural Networks for image detection of the malaria parasites emulate the microscopy visualization of an expert. Microscope automation provides a fast and low-cost diagnosis, requiring less supervision. Smartphones are a suitable option for microscopic diagnosis, allowing image capture and software identification of parasites. In addition, image analysis techniques could be a fast and optimal solution for the diagnosis of malaria, tuberculosis, or Neglected Tropical Diseases in endemic areas with low resources. The implementation of automated diagnosis by using smartphone applications and new digital imaging technologies in low-income areas is a challenge to achieve. Moreover, automating the movement of the microscope slide and image autofocusing of the samples by hardware implementation would systemize the procedure. These new diagnostic tools would join the global effort to fight against pandemic malaria and other infectious and poverty-related diseases.The project is funded by the Microbiology Department of Vall d’Hebron Universitary Hospital, the Cooperation Centre of the Universitat Politècnica de Catalunya (CCD-UPC) and the Probitas Foundation

Single-locus-sequence-based typing of the mgpB gene reveals transmission dynamics in mycoplasma genitalium

Sexually transmitted infections (STIs) by Mycoplasma genitalium are a major problem worldwide, especially given their marked and rapid propensity for developing antimicrobial resistance. Since very few treatment options exist, clinicians face an important challenge in the management of the infection. In this scenario, little is known regarding the transmission dynamics of M. genitalium and the epidemiology of antimicrobial resistance. This mgpB-based molecular typing study, conducted among 54 asymptomatically infected individuals prospectively recruited from an STI screening service, reveals two distinct epidemiological clusters that significantly correlate with sexual conduct in heterosexuals and men who have sex with men (MSM), respectively. This well-defined structuration suggests the presence of two independent sexual networks with little connectivity between them. On the other hand, the study demonstrates the multiclonal feature of the emergence of antibiotic resistance in M. genitalium to both macrolides and fluoroquinolones. The high prevalence of macrolide resistance in M. genitalium among MSM, influenced by dense network connectivity and strong antibiotic selective pressure, may correspond to allodemics affecting other STIs such as gonorrhea, syphilis and enteric pathogens. Collaterally, the structural and functional impact of mutations in the mgpB gene, encoding the major adhesin P140 (MgpB), may require further investigation.This work was partially supported by an “Ayuda SEIMC” grant from the Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC)

Prevalence of Strongyloides stercoralis and Other Intestinal Parasite Infections in School Children in a Rural Area of Angola: A Cross-Sectional Study

Intestinal Parasite; School Children; AngolaParàsit Intestinal; Escolars; AngolaParásito Intestinal; Escolares; AngolaStrongyloides stercoralis is widely distributed in the tropics and subtropics. The aim of this study was to determine the prevalence of S. stercoralis and other intestinal parasites and identify the risk factors for infection with S. stercoralis in a rural area of Angola. A cross-sectional study was conducted in school-age children (SAC) in Cubal, Angola. A questionnaire collecting clinical and epidemiological variables was used, and two stool samples were collected. A concentration technique (Ritchie) and a technique for detection of larvae migration (Baermann) were performed. Of 230 SAC, 56.1% were female and the mean age was 9.3 years (SD 2.45). Severe malnutrition, according to body mass index (BMI)-for-age, was observed in 20.4% of the SAC, and anemia was found in 59.6%. Strongyloides stercoralis was observed in 28 of the 230 (12.8%) SAC. Eggs of other helminths were observed in 51 (22.2%) students: Hymenolepis spp. in 27 students (11.7%), hookworm in 14 (6.1%), Schistosoma haematobium in four (1.7%), Enterobius vermicularis in four (1.7%), Ascaris lumbricoides in three (1.3%), Taenia spp. in two (0.9%), and Fasciola hepatica in one (0.4%). Protozoa were observed in 17 (7.4%) students. Detection of S. stercoralis was higher using the Baermann technique versus using formol-ether (11.3 vs. 3%). Overall prevalence of S. stercoralis in the school population of 16 studied schools in the municipal area of Cubal was greater than 10%. This fact must be considered when designing deworming mass campaigns. The use of specific tests in larvae detection is needed to avoid overlooking this parasite

Antibody Response Induced by BNT162b2 and mRNA-1273 Vaccines against the SARS-CoV-2 in a Cohort of Healthcare Workers

The aim of this study was to characterize the antibody response induced by SARS-CoV-2 mRNA vaccines in a cohort of healthcare workers. A total of 2247 serum samples were analyzed using the Elecsys(®) Anti-SARS-CoV-2 S-test (Roche Diagnostics International Ltd., Rotkreuz, Switzerland). Sex, age, body mass index (BMI), arterial hypertension, smoking and time between infection and/or vaccination and serology were considered the confounding factors. Regarding the medians, subjects previously infected with SARS-CoV-2 who preserved their response to the nucleocapsid (N) protein showed higher humoral immunogenicity (BNT162b2: 6456.0 U/mL median; mRNA-1273: 2505.0 U/mL) compared with non-infected (BNT162b2: 867.0 U/mL; mRNA-1273: 2300.5 U/mL) and infected subjects with a lost response to N protein (BNT162b2: 2992.0 U/mL). After controlling for the confounders, a higher response was still observed for mRNA-1273 compared with BNT162b2 in uninfected individuals (FC = 2.35, p < 0.0001) but not in previously infected subjects (1.11 FC, p = 0.1862). The lowest levels of antibodies were detected in previously infected non-vaccinated individuals (39.4 U/mL). Clinical variables previously linked to poor prognoses regarding SARS-CoV-2 infection, such as age, BMI and arterial hypertension, were positively associated with increasing levels of anti-S protein antibody exclusively in infected subjects. The mRNA-1273 vaccine generated a higher antibody response to the S protein than BNT162b2 in non-infected subjects only

iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope

IntroductionMalaria is one of the most prevalent infectious diseases in sub-Saharan Africa, with 247 million cases reported worldwide in 2021 according to the World Health Organization. Optical microscopy remains the gold standard technique for malaria diagnosis, however, it requires expertise, is time-consuming and difficult to reproduce. Therefore, new diagnostic techniques based on digital image analysis using artificial intelligence tools can improve diagnosis and help automate it.MethodsIn this study, a dataset of 2571 labeled thick blood smear images were created. YOLOv5x, Faster R-CNN, SSD, and RetinaNet object detection neural networks were trained on the same dataset to evaluate their performance in Plasmodium parasite detection. Attention modules were applied and compared with YOLOv5x results. To automate the entire diagnostic process, a prototype of 3D-printed pieces was designed for the robotization of conventional optical microscopy, capable of auto-focusing the sample and tracking the entire slide.ResultsComparative analysis yielded a performance for YOLOv5x on a test set of 92.10% precision, 93.50% recall, 92.79% F-score, and 94.40% mAP0.5 for leukocyte, early and mature Plasmodium trophozoites overall detection. F-score values of each category were 99.0% for leukocytes, 88.6% for early trophozoites and 87.3% for mature trophozoites detection. Attention modules performance show non-significant statistical differences when compared to YOLOv5x original trained model. The predictive models were integrated into a smartphone-computer application for the purpose of image-based diagnostics in the laboratory. The system can perform a fully automated diagnosis by the auto-focus and X-Y movements of the robotized microscope, the CNN models trained for digital image analysis, and the smartphone device. The new prototype would determine whether a Giemsa-stained thick blood smear sample is positive/negative for Plasmodium infection and its parasite levels. The whole system was integrated into the iMAGING smartphone application.ConclusionThe coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases