Context-aware recommender system for multi-user smart home

Smart home is one of the most important applications of the internet of things (IoT). Smart home makes life simpler, easier to control, saves energy based on user’s behavior and interaction with the home appliances. Many existing approaches have designed a smart home system using data mining algorithms. However, these approaches do not consider multiusers that exist in the same location and time (which needs a complex control). They also use centralized mining algorithm, then the system’s efficiency is reduced when datasets increase. Therefore, in this paper, we firstly build a context-aware recommender system that considers multi-user’s preferences and solves their conflicts by using unsupervised algorithms to deliver useful recommendation services. Secondly, we improve smart home’s responsive using parallel computing. The results reveal that the proposed method is better than existing approaches

The Yolk Sac Abnormalities, Maternal Serum Level of Cancer Antigen 125 (CA-125) and Beta Human Chorionic Gonadotropin (B-HCG) as an Early Predictors of First Trimester Pregnancy Loss in Patients with Threatened Miscarriage

Background: Pregnancy loss before 20 weeks is considered a miscarriage, as is the loss of a fetus weighing less than 500 grams before viability. A medical emergency, threatened miscarriage affects 15–25% of pregnancies. Aim and objectives: The goal of this study was to assess the predictive value of maternal blood levels of Cancer Antigen 125 (CA-125) and beta-human chorionic gonadotropin (B- HCG) in individuals at risk of miscarriage during the first trimester. Subjects and methods: This study was a prospective cohort study. This study included 120 pregnant women with threatened abortion between (6-11 weeks) and followed up till end of 14th week. Results: 36(30%) of pregnant women aborted, while 84(70%) of women continued till 14th weeks of pregnancy. At a cut-off value of 45 U/ml, the CA125 test was shown to have a sensitivity of 88.9% and a specificity of 77.5%, respectively, while also having a positive predictive value of 79.8% and a negative predictive value of 87.5%. At a cut-off value of 18.501 mlIU/ml, the B-HCG test's sensitivity and specificity were determined to be 96.3 and 88.9, respectively, with a positive predictive value of 89.7% and a negative predictive value of 96%. Conclusion: Even before fetal morphology can be investigated sonographically, abnormalities in the size of the yolk sac can be utilized as a good prognostic sign of early pregnancy loss. Pregnancy viability can be estimated from first trimester serum CA 125 and Beta HCG measurements

Physicochemical characterization of natural hydroxyapatite/ cellulose composite

The natural hydroxyapatite (HAp, activated at different temperatures)/ cellulose composites have been prepared by usingsonication method to improve the physical properties of the cellulose fibre. The molecular level interaction and the physicalproperties of the hydroxyapatite/cellulose composite are examined using FTIR, X-ray diffraction, SEM, and thermalanalysis. The absorption bands at around 660 cm1 confirm the O–P–O bending vibration in the HAp/cellulose composites.There is a difference in the d-spacing of the HAp /cellulose composite, indicating that the HAp is reactive towards cellulose.SEM indicates that HAp could penetrate the cellulose network structure to form particles that is helpful to improve themechanical properties of the cellulose. The porosities of HAp/cellulose composites decrease, and their compressive strengthincrease as compared to those of cellulose. Thermogravimetric analysis confirms the highest thermal stability of theprepared composites

Life cycle assessment of bacterial cellulose production

Purpose Bacterial cellulose (BC), obtained by fermentation, is an innovative and promising material with a broad spectrum of potential applications. Despite the increasing efforts towards its industrialization, a deeper understanding of the environmental impact related to the BC production process is still required. This work aimed at quantifying the environmental, health, and resource depletion impacts related to a production of BC. Methods An attributional life cycle assessment (LCA) was applied to a process design of production of BC, by static culture, following a cradle-to-gate approach. The LCA was modeled with GaBi Pro Software using the ReCiPe 2016 (H) methodology with environmental impact indicators at midpoint level. The functional unit was defined as 1 kg of BC (dry mass), in 138.8 kg of water. Results From the total used resources (38.9 ton/kg of BC), water is the main one (36.1 ton/kg of BC), most of which (98%) is returned to fresh waters after treatment. The production of raw materials consumed 17.8 ton of water/kg of BC, 13.8 ton/kg of BC of which was for the production of carton packaging, culture medium raw materials, and sodium hydroxide (for the washing of BC). The remaining consumed water was mainly for the fermentation (3.9 ton/kg) and downstream process (7.7 ton/kg). From the identified potential environmental impacts, the production of raw materials had the highest impact, mainly on Climate change, Fossil depletion, Human toxicity, non-cancer, and Terrestrial toxicity. The sodium dihydrogen phosphate production, used in the culture medium, showed the highest environmental impacts in Human toxicity, non-cancer and Terrestrial ecotoxicity, followed by corn syrup and carton production. The static culture fermentation and downstream process showed impact in Climate change and Fossil depletion. Conclusions Per se, the BC production process had a small contribution to the consumption of resources and environmental impact of the BC global life cycle.This study was supported by the Portuguese Foundation for Science and Technology (FCT) within the scope of the strate gic funding of UIDB/04469/2020 and UIDB/00511/2020 units and MultiBiorefinery project (SAICTPAC/0040/2015-POCI-01-0145- FEDER-016403). This study was also supported by The Navigator Company through the I&D no. 21874, “Inpactus-–Produtos e Tecno logias Inovadores a partir do Eucalipto”, funded through the European Regional Development Fund (ERDF) and the Programa Operacional Competitividade e Internacionalização (POCI) is greatly acknowl edged. The work by Belmira Neto was fnancially supported by Base Funding—UIDB/00511/2020 of the Laboratory for Process Engineer ing, Environment, Biotechnology and Energy—LEPABE—funded by national funds through the FCT/MCTES (PIDDAC).info:eu-repo/semantics/publishedVersio

A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing

Single-cell genomics is rapidly advancing our knowledge of the diversity of cell phenotypes, including both cell types and cell states. Driven by single-cell/-nucleus RNA sequencing (scRNA-seq), comprehensive cell atlas projects characterizing a wide range of organisms and tissues are currently underway. As a result, it is critical that the transcriptional phenotypes discovered are defined and disseminated in a consistent and concise manner. Molecular biomarkers have historically played an important role in biological research, from defining immune cell types by surface protein expression to defining diseases by their molecular drivers. Here, we describe a machine learning-based marker gene selection algorithm, NS-Forest version 2.0, which leverages the nonlinear attributes of random forest feature selection and a binary expression scoring approach to discover the minimal marker gene expression combinations that optimally capture the cell type identity represented in complete scRNA-seq transcriptional profiles. The marker genes selected provide an expression barcode that serves as both a useful tool for downstream biological investigation and the necessary and sufficient characteristics for semantic cell type definition. The use of NS-Forest to identify marker genes for human brain middle temporal gyrus cell types reveals the importance of cell signaling and noncoding RNAs in neuronal cell type identity.Neuro Imaging Researc

Feasibility studies of the time-like proton electromagnetic form factor measurements with PANDA at FAIR

The possibility of measuring the proton electromagnetic form factors in the time-like region at FAIR with the \PANDA detector is discussed. Detailed simulations on signal efficiency for the annihilation of $\bar p +p$ into a lepton pair as well as for the most important background channels have been performed. It is shown that precision measurements of the differential cross section of the reaction $\bar p +p \to e^++ e^-$ can be obtained in a wide angular and kinematical range. The individual determination of the moduli of the electric and magnetic proton form factors will be possible up to a value of momentum transfer squared of $q^2\simeq 14$ (GeV/c)$^2$. The total $\bar p +p\to e^++e^-$ cross section will be measured up to $q^2\simeq 28$ (GeV/c)$^2$. The results obtained from simulated events are compared to the existing data. Sensitivity to the two photons exchange mechanism is also investigated.Comment: 12 pages, 4 tables, 8 figures Revised, added details on simulations, 4 tables, 9 figure

The Complexity of Marriage in Rural Ethiopia: Parental Transfers and Postmarital Residence Choices

This paper examines the relationship between parental transfers and post-marital residence of children in rural Ethiopia. We investigate whether asset transfers to children are an avenue which parents use to secure old age. We model post-marital residence and transfers simultaneously in a two-stage probit least squares estimation framework. We find a positive relationship between transfers and post-marital residence, a 10 proxy for old age support. Children who receive more assets are more likely to stay at birth place after marriage and vice versa. In conditions of scarce or lacking social security mechanisms, parents make strategic transfers to ensure better old age

Feasibility studies of time-like proton electromagnetic form factors at PANDA at FAIR

Simulation results for future measurements of electromagnetic proton form factors at \PANDA (FAIR) within the PandaRoot software framework are reported. The statistical precision with which the proton form factors can be determined is estimated. The signal channel $\bar p p \to e^+ e^-$ is studied on the basis of two different but consistent procedures. The suppression of the main background channel, $\textit{i.e.}$ $\bar p p \to \pi^+ \pi^-$, is studied. Furthermore, the background versus signal efficiency, statistical and systematical uncertainties on the extracted proton form factors are evaluated using two different procedures. The results are consistent with those of a previous simulation study using an older, simplified framework. However, a slightly better precision is achieved in the PandaRoot study in a large range of momentum transfer, assuming the nominal beam conditions and detector performance