Search

Energy prediction is an important process in energy management, especially regarding demand response. Energy predictions are often carried out for load forecasting or energy generation forecasting of renewable energy. This paper explains the implementation of multi-variables in the development of recurrence neural network models to predict load energy and generation energy. The proposed main model is a multi-variate bidirectional GRU combined with a periodic feature pattern. The proposed model will also be compared with the fundamental bidirectional models of the GRU and LSTM models. For load prediction, the variables used are all energy supply data and periodic features. Meanwhile, for photovoltaic generation energy predictions, additional weather data is used because energy generation is very dependent on solar radiation and ambient conditions. Load prediction data is built using daily and hourly energy prediction data. Meanwhile, solar energy prediction is constructed with data every minute. The results show that the proposed model obtains the best prediction results for all test data on a daily, hourly, or minute basis. The model also shows the fastest execution time performance compared to other models.

This article delves into algebraic topology, specifically (co)homology theory, which is essential in various mathematical fields. It explores different types of (co)homology groups such as Hochschild, cyclic, reflexive, and dihedral, focusing on dihedral cohomology generated by the dihedral group operating on simplicial complexes. The text discusses when dihedral and reflexive cohomology vanishes and provides examples, along with proving a homomorphism between dihedral cohomology groups. Mathematical concepts like Banach spaces, C*-algebras, and tensor products are elucidated to understand the algebraic structures involved. Theorems and proofs establish the relationships and properties of these cohomology groups, culminating in a canonical isomorphism theorem for the product of two algebras. Overall, the article aims to provide a comprehensive exploration of dihedral cohomology and its interplay with other algebraic structures, offering insights into its applications and theoretical foundations. Additionally, it studies the (co)homology theory of C*-algebras, focusing on the triviality of cohomology groups of operator algebras and discovering the canonical isomorphism between any two unital K -algebras A and A′: HDn(A×A′)≅HDn(A)⊕HDn(A′).

In this paper, the (Co)homology theory of pure algebra will be studied. We aim to study the homological theory of cyclic homology and its properties. The triviality property of cohomology groups of algebras will be obtained. We will study the Mayer-Vietortis of cyclic homology. The long exact sequence of cyclic homology and the relation between cyclic homology and dihedral homology will be proved. We will introduce the proof of isomorphism HCn(A×A′)≅HCn(A)⊕HCn(A′) and the definition of Morita invariance for cyclic homology.

Background/Objectives: We aimed to establish biatrial and biventricular reference ranges using cardiac magnetic resonance (CMR) parameters in SCD patients without heart damage. Methods: This study compared CMR parameters, quantified by cine SSFP sequences, in 48 adult SCD patients without apparent cardiac involvement (defined by the absence of known risk factors, normal electrocardiogram, and no macroscopic myocardial fibrosis or significant cardiac iron on T2* CMR) to matched cohorts of 96 healthy controls and 96 thalassemia major (TM) patients without cardiac damage. Nine paediatric SCD patients were also analysed and compared to age- and gender-matched groups of nine TM patients and nine healthy subjects. Results: In all groups, studied males displayed higher biventricular volumes and mass indexes than females. Male SCD patients showed significantly higher left ventricular (LV) end-diastolic volume index (EDVI), LV end-systolic volume index (ESVI), LV stroke volume index (SVI), cardiac index, LV and right ventricular (RV) mass index, and atrial areas than healthy subjects. Females with SCD exhibited increased LV EDVI, LV SVI, RV mass index, and left atrial area index compared to healthy controls. SCD and TM patients showed comparable biatrial areas and biventricular volumes and function. When compared to TM, SCD males exhibited a larger mass index, while SCD females showed an increased RV mass index. CMR parameters were similar across all paediatric groups. Conclusions: By establishing the biatrial and biventricular reference ranges through CMR for adult male and female SCD patients, we aimed to prevent possible misdiagnosis of cardiomyopathy in this population by taking into account cardiac adaptation due to anaemia.

This paper demonstrates how artificial intelligence can be implemented in order to predict the energy needs of daily households using both multilinear regression (MLR) and single linear regression (SLR) methods. As a basic implementation, the SLR makes use of one input variable, which is the total amount of energy generated as an input. The MLR implementation involves multiple input variables being taken from various energy sources, including gas, coal, geothermal, wind, water, biomass, oil, etc. All of these variables are derived from detailed energy production data from the various energy sources. The purpose of this paper is to demonstrate that it is possible to analyze energy demand and supply directly together as a way to produce a more in-depth analysis. By analyzing energy production data from previous periods of time, a prediction of energy demand can be made. Compared to the SLR implementation, the MLR implementation is found to perform better because it is able to achieve a smaller error value. Furthermore, the forecasting pattern is carried out sequentially based on a periodic pattern, so this paper calls this method the recurrence multilinear regression (RMLR) method. This paper also creates a pre-clustering using the K-Means algorithm before the energy prediction to improve accuracy. Other models such as exponential GPR, sequential XGBoost, and seq2seq LSTM are used for comparison. The prediction results are evaluated by calculating the MAE, RMSE, MAPE, MAPA, and time execution for all models. The simulation results show that the fastest and best model that obtains the smallest error (3.4%) is the RMLR clustered using a weekly pattern period.

Background/Objectives: We aimed to establish biatrial and biventricular reference ranges using cardiac magnetic resonance (CMR) parameters in SCD patients without heart damage. Methods: This study compared CMR parameters, quantified by cine SSFP sequences, in 48 adult SCD patients without apparent cardiac involvement (defined by the absence of known risk factors, normal electrocardiogram, and no macroscopic myocardial fibrosis or significant cardiac iron on T2* CMR) to matched cohorts of 96 healthy controls and 96 thalassemia major (TM) patients without cardiac damage. Nine paediatric SCD patients were also analysed and compared to age- and gender-matched groups of nine TM patients and nine healthy subjects. Results: In all groups, studied males displayed higher biventricular volumes and mass indexes than females. Male SCD patients showed significantly higher left ventricular (LV) end-diastolic volume index (EDVI), LV end-systolic volume index (ESVI), LV stroke volume index (SVI), cardiac index, LV and right ventricular (RV) mass index, and atrial areas than healthy subjects. Females with SCD exhibited increased LV EDVI, LV SVI, RV mass index, and left atrial area index compared to healthy controls. SCD and TM patients showed comparable biatrial areas and biventricular volumes and function. When compared to TM, SCD males exhibited a larger mass index, while SCD females showed an increased RV mass index. CMR parameters were similar across all paediatric groups. Conclusions: By establishing the biatrial and biventricular reference ranges through CMR for adult male and female SCD patients, we aimed to prevent possible misdiagnosis of cardiomyopathy in this population by taking into account cardiac adaptation due to anaemia. [ABSTRACT FROM AUTHOR]

Maternal singing is considered vital to infant well-being. This study focuses on vocal emotion expressions in infant-directed singing among mothers in war conditions. It examines the questions: (a) how traumatic war events and mental health problems are associated with the content and valence of vocal emotion expressions and (b) how these emotion expressions are associated with infant development. The vocal material consists of songs sung by 50 Palestinian mothers who participated at delivery (T1) as well as when their infants were 6 (T2) and 18 (T3) months of age. These mothers reported traumatic war events (T1); depressive and post-traumatic stress disorder (PTSD) symptoms (T2-T3); and infants' emotional, sensorimotor, and cognitive development (T2-T3). Student judges evaluated the valence and content of vocal emotion expressions in maternal infant-directed singing (playfulness-vivacity, fear, joy, sadness, love-tenderness, anger, and tension). Severe traumatic war events and depressive symptoms were associated with low positive and high negative vocal emotion expressions. High levels of playfulness and joy, as well as low levels of fear and tension, were associated with infant positive affectivity, while low levels of fear, anger, and tension were associated with advanced infant language skills. Discussion focuses on the vocal markers of maternal mental health and infant development.

This paper demonstrates how artificial intelligence can be implemented in order to predict the energy needs of daily households using both multilinear regression (MLR) and single linear regression (SLR) methods. As a basic implementation, the SLR makes use of one input variable, which is the total amount of energy generated as an input. The MLR implementation involves multiple input variables being taken from various energy sources, including gas, coal, geothermal, wind, water, biomass, oil, etc. All of these variables are derived from detailed energy production data from the various energy sources. The purpose of this paper is to demonstrate that it is possible to analyze energy demand and supply directly together as a way to produce a more in-depth analysis. By analyzing energy production data from previous periods of time, a prediction of energy demand can be made. Compared to the SLR implementation, the MLR implementation is found to perform better because it is able to achieve a smaller error value. Furthermore, the forecasting pattern is carried out sequentially based on a periodic pattern, so this paper calls this method the recurrence multilinear regression (RMLR) method. This paper also creates a pre-clustering using the K-Means algorithm before the energy prediction to improve accuracy. Other models such as exponential GPR, sequential XGBoost, and seq2seq LSTM are used for comparison. The prediction results are evaluated by calculating the MAE, RMSE, MAPE, MAPA, and time execution for all models. The simulation results show that the fastest and best model that obtains the smallest error (3.4%) is the RMLR clustered using a weekly pattern period. [ABSTRACT FROM AUTHOR]

Aspek kognitif dan psikomotorik seringkali menjadi fokus utama yang ditingkatkan di banyak sekolah, sementara aspek afektif siswa yang berpengaruh terhadap sikap dan perilaku siswa sedikit kurang diperhatikan. Di MI Al Huda Malang, siswa tidak hanya dididik untuk menjadi individu yang berkarakter qurani melalui kegiatan ibadah dan muamalah, tetapi juga harus berjiwa pancasilais, serta tanggap dengan perubahan ilmu dan teknologi. Namun, sampai saat ini bentuk penyampaian kondisi sikap dan perilaku siswa masih dilakukan dengan cara konvensional, yaitu melalui surat dan pesan pribadi oleh guru/bagian konseling. Hal ini bisa menjadikan keterlambatan penyampaian dan kemungkinan tidak tersampaikan (surat hilang/ siswa lupa memberikan kepada orang tuanya) sangat besar. Salah satu penyebabnya karena belum terbentuk pemahaman dan keterampilan SDM tentang penggunaan sistem informasi tata tertib siswa ketika hendak diimplementasikan di sekolah MI-MTs Al Huda Malang. Oleh karena itu, diperlukan pengembangan sebuah sistem informasi tata tertib siswa untuk memantau perilaku dan sikap siswa di sekolah, serta sosialisasi dan pelatihan cara pemanfaatan sistem informasi tersebut. Kegiatan Pengabdian Kepada Masyarakat (PKM) ini bertujuan untuk mengembangkan sistem informasi, memberikan sosialisasi dan pelatihan kepada guru beserta tenaga pendidik tentang sistem informasi tata tertib siswa untuk memantau sikap dan perilaku siswa saat belajar di sekolah akan dilakukan. Tahapan-tahapan metode PKM yang digunakan adalah: 1) analisis kebutuhan dan situasi; 2) perencanaan dan pengembangan sistem informasi; 3) pengembangan buku pedoman penggunaan sistem informasi; 4) pengenalan dan pelatihan sistem informasi; dan 5) evaluasi hasil pelatihan. Kegiatan PKM ini menghasilkan sebuah sistem informasi yang dapat diakses secara online sebagai bentuk sarana informasi digital, serta peningkatan keahlian yang dimiliki oleh guru dan tenaga pendidik dalam mengelola dan mengembangkan sistem informasi di MI-MTs Al Huda, Kota Malang. Dengan demikian, diharapkan sikap dan perilaku siswa dapat terpantau dengan efektif dan efisien sehingga berdampak pada perbaikan dan perubahan perilaku siswa yang menjadi semakin lebih baik dan berakhlak.

Sickle cell disease (SCD) is a worldwide distributed hereditary red cell disorder characterized by recurrent acute vaso-occlusive crises (VOCs and anemia). Gold standard treatments are hydroxycarbamide (HC) and/or different red blood cell (RBC) transfusion regimens to limit disease progression. Here, we report a retrospective study on 1,579 SCD patients (median age 23 years; 802 males/777 females), referring to 34 comprehensive Italian centers for hemoglobinopathies. Although we observed a similar proportion of Caucasian (47.9%) and African (48.7%) patients, Italian SCD patients clustered into two distinct overall groups: children of African descent and adults of Caucasian descent. We found a subset of SCD patients requiring more intensive therapy with a combination of HC plus chronic transfusion regimen, due to partial failure of HC treatment alone in preventing or reducing sickle cell-related acute manifestations. Notably, we observed a higher use of acute transfusion approaches for SCD patients of African descent when compared to Caucasian subjects. This might be related to (i) age of starting HC treatment; (ii) patients' low social status; (iii) patients' limited access to family practitioners; or (iv) discrimination. In our cohort, alloimmunization was documented in 135 patients (8.5%) and was more common in Caucasians (10.3%) than in Africans (6.6%). Alloimmunization was similar in male and female and more frequent in adults than in children. Our study reinforces the importance of donor-recipient exact matching for ABO, Rhesus, and Kell antigen systems for RBC compatibility as a winning strategy to avoid or limit alloimmunization events that negatively impact the clinical management of SCD-related severe complications.Clinical Trial RegistrationClinicalTrials.gov, identifier: NCT03397017.

Abstract Sickle cell disease (SCD) is an inherited red blood cell disorder caused by a structural abnormality of hemoglobin called sickle hemoglobin (HbS). Clinical manifestations of SCD are mainly characterized by chronic hemolysis and acute vaso-occlusive crisis, which are responsible for severe acute and chronic organ damage. SCD is widespread in sub-Saharan Africa, in the Middle East, Indian subcontinent, and some Mediterranean regions. With voluntary population migrations, people harboring the HbS gene have spread globally. In 2006, the World Health Organization recognized hemoglobinopathies, including SCD, as a global public health problem and urged national health systems worldwide to design and establish programs for the prevention and management of SCD. Herein we describe the historical experience of the network of hemoglobinopathy centers and their approach to SCD in Italy, a country where hemoglobinopathies have a high prevalence and where SCD, associated with different genotypes including ß-thalassemia, is present in the native population.