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management --- education --- financing --- islamic education --- learning model --- madrasah

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In this value based world, life and health are probably the most essential things that should be left out of inequalities and injustice. Unfortunately, these differences arise even before the birth due to hazard, but also abilities to monitor the maternal pregnancy. As an example of pathology affecting the fetus, Intra Uterine Growth Restriction (IUGR) is a fetal condition defined as the abnormal rate of growth and causing fetal or neonatal morbidity and mortality.
Currently, clinicians can only suspect IUGR condition by estimating the birthweight with Ultra-Sound imaging. This prediction is only based on the weight estimationof the fetus but is not related to real fetus well-being. Thus, IUGR conditon can only be confirmed at birth. Hence, it would be interesting to have an additional tool related to fetal well-being allowing clinician to diagnose it during the pregnancy. 

Cardiotocography (CTG) is one of the most used technique to assess fetal well-being during pregnancy. In this project, we will use CTG signals and more specifically Fetal Heart Rate (FHR) signal to predict the fetal condition before labour (antepartum). The work will focus on IUGR pathology and build a framework allowing us to detect it. Based on the literature, a set of features interesting for the analysis was determined allowing us to characterise the FHR signal of each subject. These parameters were then analysed over 3 datasets coming from different sources Politecnico di Milano, Bloomlife and open-source data from Data in Brief [Signorini et al. 2019]. 

Finally, adjusted open-source data from 120 subjects (60 Healthy/ 60 IUGR) was used to implement and train 4 classification models and evaluate them. The selected model is a Bagged Ensemble composed of 5 decision trees. Analysis and optimization of the model were made on the training/validation dataset to improve its performance. As a final result, the model achieves to reach a global accuracy of 87% and a 96% sensibility on the validation dataset and succeed to classify 18 subjects over 20 on our test set with a 100% sensibility. 

As a perspective, a bigger annotated signals dataset could be used to implement and train a strong model based directly on raw FHR signals. This prediction model could be used to offer an easily accessible tool to detect IUGR during pregnancy and distinguish them from physiological Small for Gestational Age fetuses.

Fetal Heart Rate Monitoring --- Intra-Uterine Growth Restriction --- Signal Processing --- Physiology-based Parameters --- Feature Analysis --- Machine Learning Model --- Ingénierie, informatique & technologie > Ingénierie électrique & électronique

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This study tries to remedy the current lack of tax compliance research analyzing tax morale in 10 Eastern European countries that joined the European Union in 2004 or 2007. By exploring tax morale differences between 1999 and 2008, it shows that tax morale has decreased in 7 out of 10 Eastern European countries. This lack of sustainability may support the incentive based conditionality hypothesis that the European Union only has a limited ability to influence tax morale over time. The author observes that events and processes at the country level are crucial to understanding tax morale. Factors such as perceived government quality and trust in the justice system and the government are positively correlated with tax morale in 2008.

Debt Markets --- Emerging Markets --- Law and Development --- Macroeconomics and Economic Growth --- National Governance --- Social learning model --- Subnational Economic Development --- Tax administration reforms --- Tax compliance --- Tax morale --- Taxation & Subsidies --- Transition countries

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Perturbations linked to the direct and indirect impacts of human activities during the Anthropocene affect the structure and functioning of aquatic ecosystems to varying degrees. Some perturbations involve stress to aquatic life, including soil and water acidification, soil erosion, loss of base cations, release of trace metals/organic compounds, and application of essential nutrients capable of stimulating primary productivity. Superimposed onto these changes, climate warming impacts aquatic environments via altering species’ metabolic processes and by modifying food web interactions. The interaction stressors is difficult to predict because of the differential response of species and taxonomic groups, interacting additively, synergistically, or antagonistically. Whenever different trophic levels respond differently to climate warming, food webs are restructured; yet, the consequences of warming-induced changes for the food web structure and long-term population dynamics of different trophic levels remain poorly understood. Such changes are crucial in lakes, where food web production is mainly due to ectotherms, which are highly sensitive to changes in their surrounding environment. Due to its remarkable physical inertia, including thermal stability, global warming also has a profound effect on groundwater ecosystems. Combining contemporary and palaeo data is essential to understand the degree to which mechanisms of stressors impact on lake biological communities and lake ecosystem functioning. The degree to which alterations can affect aquatic ecosystem structure and functioning also requires functional diversity to be addressed at the molecular level, to reconstruct the role different species play in the transfer of material and energy through the food web. In this issue, we present examples of the impact of different stressors and their interaction on aquatic ecosystems, providing long-term, metabolic, molecular, and paleolimnological analyses.

multivariate analyses --- risk assessment --- aquatic insects --- crustaceans --- lab-microcosms --- nonmetric multidimensional scaling --- adaptation --- porous aquifer --- PERMANOVA --- Planktothrix rubescens --- species conservation --- distribution patterns of species --- Cyanobacteria --- fossil Cladocera --- high throughput sequencing --- machine learning model --- stability --- small lakes --- environmental factor --- non-metric multi-dimensional scaling (NMDS) --- stream ecosystem --- lake vulnerability --- PCA --- functional diversity --- ecological resilience --- nitrification --- deep lake --- metabolism --- South–North Water Diversion Project --- endemic species --- EPT taxa --- trophic interactions --- stable isotope analysis --- environmental change --- bioassessment --- generalized procrustes analysis --- freshwater pollution --- colonization --- paleolimnology --- Tychonema bourrellyi --- plankton --- subalpine lakes --- random forest model --- Danjiangkou Reservoir --- trophic degree --- multiple scale --- biodiversity --- copepods --- zooplankton --- groundwater --- genetic variability --- respirometry --- ammonium impact --- Stable Isotopes Analysis --- trophic gradient --- seasonality

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The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things.

History of engineering & technology --- atmospheric --- on-line monitoring --- LoRa --- embedded system --- smart environments --- Internet of Things --- indoor occupancy --- machine learning --- data analysis --- landslide susceptibility --- China-Nepal Highway --- LSTM --- remote sensing images --- IoT --- network traffic --- monitoring --- DDoS --- packet classification --- indoor localization --- channel state information --- device-free passive --- WiFi fingerprint --- naive Bayes classification --- feature fusion --- posture recognition --- indoor positioning --- wireless body area network --- Kalman filtering --- multi-sensor combination --- prognostic and health management --- integrative framework --- internet of things --- convolutional neural network --- conditioned-based maintenance --- IoT platform --- intelligent monitoring robot --- active CCTV --- learning model --- electrical devices --- classification --- energy management --- smart environment --- architecture --- blockchain --- communication constraints --- decentralized application --- Ethereum --- Internet of things --- sensing and control --- computational efficiency --- robotic manipulators --- hysteresis --- adaptive control --- wireless sensor network (WSN) --- energy --- ant colony optimization (ACO) --- routing algorithm --- quantum-inspired evolutionary algorithms