Miracle-dz/UniFAR-FTUs huggingface dataset:
Internet of Things (IoT)-Based Wastewater Management in Smart Cities

Wastewater management is a mechanism that is used to extract and refine pollutants from wastewater or drainage that can be recycled to the water supply with minimal environmental effects. New methods and techniques are required to ensure safe and smart wastewater management systems in smart cities because of the present deteriorating environmental state. Wireless sensor networks and the Internet of Things (IoT) represent promising wastewater treatment technologies. The elaborated literature survey formulates a conceptual framework with an Internet of Things (IoT)-based wastewater management system in smart cities (IoT-WMS) using blockchain technology. Blockchain technology is now being used to store information to develop an incentive model for encouraging the reuse of wastewater. Concerning the quality and quantity of recycled wastewater, tokens are issued to households/industries in smart cities. Nevertheless, this often encourages tampering with the information from which these tokens are awarded to include certain rewards. Anomaly detector algorithms are used to identify the possible IoT sensor data which has been tampered with by intruders. The model employs IoT sensors together with quality metrics to measure the amount of wastewater produced and reused. The simulation analysis shows that the proposed method achieves a high wastewater recycling rate of 96.3%, an efficiency ratio of 88.7%, a low moisture content ratio of 32.4%, an increased wastewater reuse of 90.8%, and a prediction ratio of 92.5%.
Population Therapeutics & Clinical Pharmacology

The study extended from February 2022 to February 2023 in the main blood bank in Thi-Qar Province, with the aim of identifying HIV among blood donors, as the blood is one of the main ways of transmission of the virus. ELISA assay was used to screening 43,850 males and females blood donors. Thirty nine infections were recorded, all of them were males. The age group between 18 and 59 years, most of the cases of infection ranged between 30-39 years, with an infection rate of 0.12%. Most of the infection were from urban areas 0.09%. Blood group O was the highest percentage infection among the donors as it was recorded 0.12%. Also found highest infections among Rh+ with rate 0.09%.
An Intelligent Ovarian Ultrasound Image Generation Algorithm based on Generative Adversarial Networks

A deep learning framework based on generative adversarial networks (GAN) for ovarian ultrasound (US) images synthesis is investigated. This method offers an effective solution for addressing the issue of insufficient and unbalanced data in ovarian disease research. The proposed network, built on the Triple-GAN model, can synthesize a large number of medical ovarian US images which are difficult to distinguish from the real ones. This approach effectively increases the available volume of the ultrasound images of ovarian diseases and facilitates deep learning applications in ovarian ultrasound images. It provides reliable training data replacements. The generated data were validated through professional appraisal, classification method and image metrics. The results demonstrated high credibility and quality. The feasibility of using the generated data in the intelligent classification algorithm of ovarian diseases is verified, which has important practical significance for the research and development of artificial intelligence diagnosis algorithms for various diseases in the future.
Contrast Enhancement for Ring-Echo Image using Temporal Dynamic Bandpass Filter

A Ring-Echo ultrasound imaging system is a commercial ultrasound computed tomography system specialized in female breast imaging. The conventional practice for processing the received raw ultrasound signal before reconstructing the B-mode echo image involves passing it through a bandpass filter with a fixed passband, usually aligned with the specific bandwidth of the transmitted pulse. However, we found that the contrast of the echo image is insufficient for breast cancer detection. In this paper, we propose a temporal dynamic bandpass filter that utilizes the frequency-down-shift phenomenon in ultrasound imaging to enhance the contrast of the echo image. We applied the proposed method to clinical data to evaluate its performance. Compared with images passed through a fixed bandpass filter, those reconstructed after going through a dynamic bandpass filter exhibit a higher contrast. Since contrast is a key factor in breast cancer detection from the echo image, the proposed method has the potential to make the Ring-Echo system more efficient.
Modelo Analítico para os Momentos de Primeira e Segunda Ordens do Algoritmo Leaky FXLMS

Este trabalho propõe uma modelagem analítica para descrever os momentos de primeira e segunda ordens dos coeficientes de um filtro adaptativo FIR, utilizando o algoritmo Leaky LMS filtrado. Esse algoritmo é usualmente utilizado para reduzir efeitos não desejáveis (instabilidade) provenientes da etapa de implementação, por exemplo, erros decorrentes das operações aritméticas com precisão finita, problemas de overflow, condicionamento do sinal de entrada, dentre outros. Tem-se demonstrado que a teoria da independência, extensivamente utilizada na análise de filtros FIR-LMS, não mais se aplica ao caso filtrado. Assim, neste trabalho, os modelos desenvolvidos não invocam tal teoria. Dessa forma, os modelos analíticos obtidos apresentam um excelente casamento com os resultados de simulações.
A fast and accurate dihedral interpolation loop subdivision scheme

In this paper, we propose a fast and accurate dihedral interpolation Loop subdivision scheme for subdivision surfaces based on triangular meshes. In order to solve the problem of surface shrinkage, we keep the limit condition unchanged, which is important. Extraordinary vertices are handled using modified Butterfly rules. Subdivision schemes are computationally costly as the number of faces grows exponentially at higher levels of subdivision. To address this problem, our approach is to use local surface information to adaptively refine the model. This is achieved simply by changing the threshold value of the dihedral angle parameter, i.e., the angle between the normals of a triangular face and its adjacent faces. We then demonstrate the effectiveness of the proposed method for various 3D graphic triangular meshes, and extensive experimental results show that it can match or exceed the expected results at lower computational cost.
Forecasting PM2.5 in Malaysia Using a Hybrid Model

Predicting future PM 2.5 concentrations based on knowledge obtained from past observational data is very useful for predicting air pollution. This paper aims to develop a hybrid forecasting model using an Artificial Neural Network (ANN) and Triple Exponential Smoothing (TES) on clustered PM 2.5 data from a HPR (High Pollution Region), MPR (Medium Pollution Region), and LPR (Low Pollution Region) in Malaysia. Historical PM 2.5 concentrations in Malaysia from January 2018 to December 2019 were used to develop a hybrid model. The proposed hybrid model was then evaluated in terms of Mean Absolute Percentage Error (MAPE) values by comparing them with real PM 2.5 data from the year 2020 in the HPR, MPR and LPR. The results showed that the hybrid model of ANN and TES presented the lowest RMSE (Root Mean Squared Error) (4.25–8.56 µ g m –3 ), MAE (Mean Absolute Error) (2.51–4.95 µ g m –3 ), MAPE (0.13–0.2%), and MASE (Mean Absolute Scaled Error) (1.45–2.01) in different areas of pollution compared with other models. The comparison between the ANN and TES hybrid models and the real PM 2.5 data in 2020 showed that the models gave sufficient accuracy in the HPR and MPR with MAPE values of between 20% and 50%, while the LPR showed less accuracy due to the high value of MAPE of more than 50%. Overall, the hybrid model developed in this study opens up a new prediction method for air quality forecasting and is sufficiently accurate to be used as a tool for air quality management.
On the representation of incompressible Newtownian free-surface CFD flows

This paper presents an attempt to develop a comprehensive representation of two components incompressible Newtonian flows. The primary target is to have insight on how to improve the CFD simulations of free-surface flows so as to deal with very high density ratios. First, the Navier-Stokes equations of a fluid with two immiscible components is derived from the single component equations. In this case, the surface tension does not come from the equations and must be added externally. Second we shortly review the CahnHilliard and Allen-Cahn equations describing a phase separation process, and the phenomenological relation with surface-tension phenomena. Third, we build phase momentum equations which are consistent with the classical Navier-Stokes equations, but this time for miscible fluids. The concept of energy conservation applied separately to the phases is systematically used to build the phase momentum forces, with a particular regard to the surface tension. Fourth, by use of a dynamical equilibrium assumption and a specific splitting of the energies and their derived force, we retrieve the basic properties of the phase transport equations. The method is extended to the surface tension and to the baro-diffusion. The relation between the phase forces and diffusion fluxes is clarified. Finally, a complete and consistent set of equations is provided and discussed.
Emotional Intelligence and Grit among Young Adults: A Correlational Study

Emotional Intelligence (EI) is the ability to regulate one's moods, prevent distress from impairing thought, control impulse, delay gratification, and empathize which may affect Grit, the propensity to pursue long-term goals with persistence and unwavering passion. Aim : To explore the relationship between Emotional Intelligence and Grit among Young Adults. Method : The study comprised of 136 young adults (76 females and 60 males) who were selected through Convenience Sampling. The Brief Emotional Intelligence Scale (BEIS-10) and Grit Scale short (Grit-8) was administered on the participants. Results : The findings of the inferential statistics indicates that there was a significant positive correlation between Emotional Intelligence and Grit (r= .188; p<0.05) A significant gender difference exists in EI between Females (M= 33.42) and Males (M=28.95); t= 2.251, p= . 026; and in Grit between Females (M= 27.21) and Males (M=25.53); t= 2.009, p= . 047. Conclusion : It was concluded that Emotional Intelligence and Grit have a significant positive relationship. There is a significant gender difference in Emotional Intelligence and Grit among Young Adults.
Study on an optical encryption algorithm based on compressive ghost imaging and super-resolution reconstruction

Optical encryption schemes based on compressive ghost imaging (CGI) are associated with low-quality decrypted images and unsatisfactory security. In order to cope with these issues, we propose an optical encryption algorithm based on compressive ghost imaging and super-resolution reconstruction. A convolution neural network is established to reconstruct the images. Compared with CGI, the convolutional neural network super-resolution convolutional neural networks can not only restore the reconstructed image of the CGI to a HR image, but also realize secondary encryption by using the convolution kernel parameter of the convolutional neural network. Therefore, this algorithm can improve the resolution of the decrypted image and the security of the algorithm.
Preparation of Peanut Shell Cellulose Double-Network Hydrogel and Its Adsorption Capacity for Methylene Blue

To achieve optimal recovery and value-added utilisation of cellulose in peanut shells, the cellulose in peanut shells was ﬁ rst extracted using the sodium hydroxide-sodium chlorite method. Then, cellulose hydrogel was prepared by graft copolymerisation using N, N ’ -methylenebisacrylamide as the cross-linking agent, sodium persulfate as the initiator, and acrylic acid as the monomer. Orthogonal optimisation experiments were designed to obtain optimal process parameters for hydrogel preparation with the cellulose dosage of 0.40 g, initiator dosage of 0.20 g, poly-merisation temperature of 70°C, cross-linking agent of 0.25 g, and monomer dosage of 3.0 mL. The effect of initiator dosage on hydrogel synthesis was the most signi ﬁ cant, followed by monomer dosage and reaction temperature. Characterisation using X-ray diffraction analysis and scanning electron microscopy revealed that the hydrogel was amorphous and exhibited a distinct three-dimensional double network structure. Hydrogel swelling kinetic analysis showed that the hydrogel swelling process was divided into three stages, and ﬁ tted the Schott secondary swelling kinetic model. The prepared hydrogel had a good adsorption effect on methylene blue; the adsorption of methylene blue by the hydrogel was 1.259 mg/g at 25°C when the initial concentration of methylene blue was 5 mg/L. The adsorption kinetics of the hydrogel ﬁ t the pseudo-ﬁ rst-order kinetic model, pseudo-second-order kinetic model, Eovich model and particle diffusion model. The best ﬁ tting effect was obtained with the pseudo-second-order kinetic model. The adsorption isotherm analysis of methylene blue on hydrogel showed that the adsorption process was consistent with Langmuir and Freundlich models. The correlation coef ﬁ cient of the Freundlich isotherm model was higher, indicating that the adsorption of methylene blue on hydrogel was mainly chemisorption.
Fiber laser for application in phase sensitive optical time domain reflectometry

We have presented fiber laser configuration with an injection locked DFB (IL-DFB) laser for application in phase sensitive optical time domain reflectometry (φ-OTDR). A low-loss fiber optical ring resonator (FORR) is used as a high finesse filter for the self-injection locking of the DFB laser. We have used IL-DFB laser configuration for detection and localization of the vibrations in phase sensitive OTDR system. By applying moving differential processing algorithm for the Rayleigh backscattering traces we demonstrate accurate localization of the vibrations with a frequency ~50 Hz at a distance about 10 km with the same signal to noise ratio that is achievable with an ultra-narrow linewidth OEwaves laser (OE4020-155000-PA-00).
A sensitized variable selection control chart based on a classification algorithm for monitoring high‐dimensional processes

During the last decade, variable‐selection‐based (VS) control charts have gained much popularity for process monitoring and diagnosis. These charts have been proven efficient for the detection of sparse mean shifts in high‐dimensional processes. VS charts usually assume that in‐control (IC) data are the only information used to determine the control limits. In modern industrial processes, however, out‐of‐control (OC) data can be easily collected. Detecting a specific shift in a data‐rich environment without utilizing OC data information will limit the development of a process monitoring scheme. In this paper, a novel variable selection control chart that is combined with a classification algorithm is proposed, which is expected to benefit from both the classification and variable selection approaches. In contrast to alternative charts, the proposed sensitized variable selection chart can capture the potential shifted variables using both IC and OC information, which can improve the sensitivity of the chart in a specific direction. Extensive Monte Carlo simulations demonstrate that the proposed chart outperforms the alternatives in a data‐rich and high‐dimensional environment. A real‐life example of cellular localization is also included to support the findings of our study.
Un Algorithme Amélioré d'Itération de la Politique Approchée pour les Processus Décisionnels Semi-Markoviens Généralisés

La complexite des problemes de decision dans l'incertain dependant du temps provient sou-vent de l'interaction de plusieurs processus concurrents. Les Processus Decisionnels Semi-Markoviens Generalises (GSMDP) consituent un formalisme efficace et elegant pour representer a la fois les aspects de concurrence d'evenements et d'actions et d'incertitude. Nous proposons un formalisme GSMDP etendu a un temps observable et un espace d'etats hybride. Sur cette base, nous introduisons un nouvel algorithme inspire de l'iteration de la politique approchee afin de construire des politiques efficaces. Cet algorithme repose sur une exploration guidee par la simulation et utilise les techniques d'appren-tissage a vecteurs supports. Nous illustrons cet algorithme sur un exemple et en proposons une version amelioree qui compense sa principale faiblesse.
Demographic and clinical features of patients suffering acute intoxication with an emphasis on cardiovascular complications; an observational case series

Introduction: Acute intoxication is an ongoing health issue worldwide and one of the most prevalent causes of hospital admission. Investigation of the features of acute intoxication occurrence allows for effectively planning preventive measures and required health resources. Objectives: The current study investigated acute intoxication’s demographic and clinical characteristics in an Iranian province. Patients and Methods: An observational case-series study was designed to investigate patients suffering from acute intoxication and admitted to two referral tertiary teaching hospitals over six months. Demographic data, vital parameters comprising neurologic, respiratory, and hemodynamic status, clinical symptoms, and blood analysis data were prospectively recorded. Data analysis was conducted using SPSS version 21 software. Results: In total, 447 patients were included in the study (3.5% of all emergency admission). The mean age of patients was 33±16 (4-88) years, and 190 (42.6%) patients were female. Seventy percent of patients were under 40 years. The male patients were significantly older than the female ones (P=0.001). Hospital mortality was 2.7%. Circulatory shock and respiratory apnea occurred separately in 13 (2.9%) patients, and alteration in consciousness affected 30%. Reduced arterial blood saturation and visual acuity were observed in 14% and 3.6% of the patients. A cumulative prevalence of electrocardiogram anomalies of 38% was also observed. The most prevalent electrolyte disorder was hypocalcemia (12%), followed by hypokalemia (10%); 17 % of patients were affected by severe blood acidosis. Conclusion: Acute intoxication is a medical emergency with a high risk of death. A multi-organ-based diagnosis and therapeutic approach should be implemented to manage the potentially lethal complications as soon as possible. Effective preventive planning for reducing acute intoxication should be performed concerning the socioeconomic status of the targeted population.
Synergies between the VVVX Survey and the S-PLUS Galactic Survey

Abstract Two new Galactic Surveys started activities in 2016: the ESO Public VISTA Variables in the Vía Láctea eXtended Survey (VVVX) and the Southern Photometric Local Universe Survey Galactic Survey (S-PLUS GS). VVVX is the extension of the ESO VVV Survey ((Minniti et al. 2010) and will triple the observed area from 562 deg2 to 1700 deg2. The S-PLUS GS makes use of the T80-South robotic telescope in Cerro Tololo (Chile) to observe 1420 deg2 of the Galactic disk and bulge in the optical. The S-PLUS GS will cover 800 deg2 contemporaneously and overlapping with VVVX. Here we explore the synergy between these ongoing surveys and present illustrative examples combining the optical and infrared data.
Pertumbuhan Fitoplankton Coccolithophore Sp Di Wadah Terkontrol Dengan Kepadatan Inokulum Yang Berbeda

Fitoplankton merupakan pakan alami yang baik bagi larva ikan pada fase awal pengenalan makanan dan zooplankton. Salah satu jenis fitoplankton yang dibudidayakan sebagai pakan alami yaitu Coccolithophore sp, dimana pertumbuhan Coccolithophore sp dipengaruhi oleh salinitas, pH, suhu dan kepadatan inokulum. Inokulum adalah bibit kultur yang diperoleh dari stok bibit atau sering disebut stok starter tujuan penelitian adalah untuk mengamati pertumbuhan Coccolithophore sp dalam wadah terkontrol dengan kepadatan inokulum yang berbeda. Penelitian ini dilaksanakan pada bulan Maret 2011 di Laboratorium Pakan Alami Balai Budidaya Laut Ambon, dengan tiga perlakuan kepadatan inokulum yaitu: 1,6-2,2x10 6 sel/ml (A), 2,3-2,7x10 6 sel/ml (B) dan 2,8-3,2x10 6 sel/ml (C). Perhitungan kepadatan dilakukan setiap 24 jam selama 14 hari dengan menggunakan miksrokop NIKON SF pada pembesaran 400x. Hasil penelitian memperlihatkan perbedaan kepadatan sel serta waktu pencapaian puncak pertumbuhan, dimana perlakuan A dan B menggalami puncak pertumbuhan pada hari kesebelas dengan kepadatan sel pada perlakuan A sebesar 72,07 x10 6 sel/ml dan perlakuan B sebesar 63,36 x10 6 se/ml sedangkan perlakuan C mencapai puncak pertumbuhan pada hari kesepuluh sebesar 51,69 x10 6 sel/ml.
Lithium Hexastannate: A Potential Material for Energy Storage

The prediction of a new lithium compound, Li2Sn6O13, is made from a combined first‐principles and classical force‐field approach. The electronic, structural, and mechanical properties of monoclinic Li2SnO3, Li2Ti6O13, and Li2Sn6O13 are explored. The calculated results for the equilibrium lattice parameters are in agreement with the available experimental data. The thermodynamic stabilities of Li2Ti6O13 and Li2Sn6O13 are evaluated. Both compounds are demonstrated to be thermodynamically stable with standard molar formation enthalpies of −5553 and −6740 kJ mol−1, respectively. Reaction energies for delithiation of 6.41 and 6.90 eV atom−1 are also determined for Li2Sn6O13 and Li2Ti6O13, respectively. The predicted voltage of Li insertion/extraction process per Li+/Li is 1.6 V for Li2Sn6O13, comparable to its isostructural counterpart Li2Ti6O13. Electronic band structure calculations indicate the insulating character of Li2SnO3 with an indirect band gap of 4.4 eV, whereas both Li2Ti6O13 and Li2Sn6O13 appear to be semiconductor compounds with band gaps of 3.1 and 3.0 eV, respectivley. The energy barriers for Li+ migration amount to ≈0.5 eV for both materials. Elastic stiffness coefficients and bulk, shear and Young's moduli were also calculated. The Li2Sn6O13 derivative is mechanically stable and can be predicted to be a brittle compound that is more resistant to volume change than Li2Ti6O13. If the Li2Sn6O13 compound could experimentally be prepared by using ion exchange, it could potentially be an efficient material for anodes in lithium‐ion batteries.