Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Perovskite Solar Cells by Temperature Control in Single and Mixed Halide Precursor Solutions and Films

Thermal annealing and precursor composition play critical roles in crystallinity control and morphology formation of perovskite thin films for achieving higher photovoltaic performance. In this study we have systematically studied the role of annealing temperature on the crystallinity of perovskite (CHNH3PbI3) thin films cast from single (without PbCl2) and mixed (with PbCl2) halide precursors. Higher annealing temperature leads to agglomeration of perovskite crystals. The effects of annealing temperature on the performance of perovskite solar cells are different in single and mixed halide processed films. It is observed that the perovskite crystallinity and film formation can be altered with the addition of lead chloride in the precursor solution. We report that single halide perovskite solar cells show no change in morphology and crystal size with increase in annealing temperature, which was confirmed by UV–vis absorption spectroscopy, X-ray diffraction (XRD), and atomic force microscopy (AFM). However,.
To Decrease the Issue of False Alarm Rate by Providing Authentication & Thus Improving the Efficiency of Intrusion Detection System by Comparing the Result of Filtered Clusterer Algorithm & Make-Density Based Clustering Algorithm without Attribute Count

The Intrusion Detection System sends alerts when it detects doubtful activities while monitoring the network traffic and other known threats. In today’s time in the field of Cyber security Intrusion Detection is considered a brilliant topic that could be objective. But it might not remain objectionable for a longer period. For understanding Intrusion Detection, the meaning of Intrusion must be clear at first. According to the oxford’s learners dictionary “Intrusion is the act of entering a place that is private or where you may not be wanted”. For this article, here it defines intrusion as any un-possessed system or network festivity on one (or more) computer(s) or network(s). Here is the example of a faithful user trying to access the system taking more than the usual trial counts to complete his access to the particular account or trying to connect to an unauthorized remote port of a server. The ex-employee who was being fired lately can provoke intrusion or any authentic worker can also provoke intrusion or any other person from the outside world could perform it. In this clause, the average data is found as the attack which is considered as the case of false positive. In this paper, the main focus is on the illustration and a solution offered for the same problem. Here we are using the KDD CUP 1999 data set. According to the outcome, the anomaly class is the one that has a higher number of counts than this class. Even if it is the true user trying to get access but the outcome is an anomaly due to the high number of counts in the class. This paper introduces a solution for the detection of a true person and eradicates the false positive.
Appraisal of Heavy Metal Presence and Water Quality having Microbial Load and Associated Human Health Risk: A study on tube-well water in Nalitabari township of Sherpur district, Bangladesh

This article is based on a study aimed to determine physiochemical parameters, fecal coliform, total coliforms, heterotrophic plate count, arsenic, iron and lead of water to evaluate their effects on human health. Analysis was carried out on tube-well water collected from Nalitabari township of Sherpur District in Bangladesh. The dissolved oxygen (DO), total dissolved solids (TDS), salinity and electrical conductivity were in the ranges of 4.30 to 7.30 ppm, 350 to 792 mg/l, 0.2 to 0.5%, and 715 to 1,970 μS/cm. The pH values were slightly lesser or more than permissible value. Due to the vicinity to the latrines, 17 tube-wells’ water was contaminated by fecal coliforms. The highest heterotrophic plate count was 7.5×103 cfu/ml in ward-8 of the town. Eschericia coli and Vibrio cholerae were identified in ratio of 30.56% and 18.06%, respectively, in the tube-well water, resulting into diarrhea among children. About 6.94% of tube-well water was contaminated with arsenic. 3.25% and 4.5% respondents were suffering from skin diseases and headache, respectively. So, an alternative source of drinking water should be arranged for a better public health of present and next generations.
A GloVe-Based POI Type Embedding Model for Extracting and Identifying Urban Functional Regions

Points-of-interest (POIs) are an important carriers of location text information in smart cities and have been widely used to extract and identify urban functional regions. However, it is difficult to model the relationship between POIs and urban functional types using existing methods due to insufficient POIs information mining. In this study, we propose a Global Vectors (GloVe)-based, POI type embedding model (GPTEM) to extract and identify urban functional regions at the scale of traffic analysis zones (TAZs) by integrating the co-occurrence information and spatial context of POIs. This method has three main steps. First, we utilize buffer zones centered on each POI to construct the urban functional corpus. Second, we use the constructed corpus and GPTEM to train POI type vectors. Third, we cluster the TAZs and annotate the urban functional types in clustered regions by calculating enrichment factors. The results are evaluated by comparing them against manual annotations and food takeout delivery data, showing that the overall identification accuracy of the proposed method (78.44%) is significantly higher than that of a baseline method based on word2vec. Our work can assist urban planners to efficiently evaluate the development of and changes in the functions of various urban regions.
Detecting Imaging For Neoplastic Liver Masses in Hepatic Patients Who Received Direct Acting Antiviral Drugs

Background: Hepatocellular carcinoma makes up 75%-85% of all primary liver cancers and is the fourth most common cause of cancer related death worldwide. The aim of this study was to screen for hepatocellular carcinoma in hepatic patients who received direct acting antiviral drugs using different imaging modalities. Methods: This was a cross sectional study included 50 patients who were hepatic and received Direct Acting Antiviral '' DAA'' and were carried out at radiology department in Elobour Hospital for Health Insurance after obtaining written informed consent from all patients. Results: There were 31(62%) male, 19(38%) female, the mean age 52.28 years old with range (39-65), 35(70%) urban, 15(30%) rural. There were (70%) with duration of illness ≤ 5 years, (30%) with > 5 years, (100%) with DAA, (90%) easy to treat, (10%) difficult to treat. There were 35(70%) with average liver, 14(28%) with shrunken liver, 1(2%) with enlarged liver, 13(26%) with Bright pattern, 34(68%) with cirrhotic, and 3(6%) with coarse bright, the mean P.V diameter 14.68 mm (± 2.51 SD) with range (9-17 mm). There were (100%) with single focal lesion in RT lobe, the mean size was 4.47 mm with range (3.6-5.6), (33.3%) isochoric, (33.3%) with hypo echoic, (33.3%) with hyper echoic, and (66.7%) with malignancy. There were 3(100%) with typical CT enhancement, 1(33.3%) with P.V thrombosis. None were with affection on liver vascular, no one with intrahepatic biliary radicles, no one with L.N in porta hepatis. Conclusion: Based on our findings, we recommend for close imaging evaluations after DAA in cirrhotic patients.
Foreign Language Textbook for Teaching Atypical Students: Designing Didactic Materials

The article considers the need to develop author’s didactic materials as applications to modern foreign language textbooks, which is associated with the difficulty of creating a universal textbook taking into account the specifics of the limitations of a schoolchild who has problems in socialization, learning, development and education. The article highlights the peculiarity of preparing a future foreign language teacher for designing didactic support for sections of a foreign language textbook within university elective courses. The leading methods to study the problem of designing didactic support for atypical students are: 1) theoretical methods: analysis of psychological, pedagogical, methodological works of foreign and Russian authors on the problem under review, comparison, generalization, design, modeling, interpretation of the information received; 2) empirical methods: observation, testing, questionnaires, conversation with students, research of future Bachelors of Education project results; 3) methods of mathematical statistics (Microsoft Office Excel 2010). The scientific novelty lies in the justification of the didactic functions of provision for atypical students, establishing theoretical basis for the model of designing didactic support based on the principle of personalized learning as a gradual transfer of a student to the position of self-learner. The practical significance of the study results presented in the article lies in the development of a model for the design of didactic support for atypical students, the allocation of a step-by-step algorithm for this process, the development of elective courses and modular disciplines, in the creation of a training manual “Teacher's readiness to develop Individual Educational Plan for schoolchildren”.
Recent advances in single particle rotational tracking of plasmonic anisotropic gold nanoparticles under far-field optical microscopy

ABSTRACT The real-time tracking of rotational motions of biological molecules in live cells is of great importance for fundamental and mechanistic studies in biological systems. Recently, plasmonic anisotropic gold nanorods (AuNRs) have attracted a great deal of attention as optical orientation probes in live-cell imaging due to their unique size- and shape-induced optical properties, photostability, large scattering and absorption cross-sections, biocompatibility, and easy surface modi-fication. Furthermore, single particle rotational tracking techniques have seen rapid development in the past 10 years. In this article, we provide a brief introduction to various far-field optical imaging and spectroscopic techniques that can be used for visualizing plasmonic Au nanoparticles. We further discuss recent developments of single particle rotational tracking techniques in combination with the AuNR probes under far-field optical microscopy.
Phylogeography of Otaria flavescens (Carnivora: Pinnipedia): unravelling genetic connectivity at the southernmost limit of its distribution

The Pleistocene glacial period shaped the current genetic structure of numerous species. The last glacial dynamics has been proposed to have split the South American sea lion, Otaria flavescens, into two Evolutionarily Significant Units (ESUs), one on each side of the continent. However, previous studies have not provided genetic information on colonies found along 3000 km of coastline of the southernmost limit of the species distribution, where gene flow could occur. We conducted an exhaustive phylogeographical analysis of O. flavescens using a mtDNA marker, including, for the first time, data from colonies living south of latitude 45° S, in the Argentinian provinces of Santa Cruz and Tierra del Fuego. Our results indicated the presence of five Conservation Units across the distribution range of O. flavescens and suggest that the Patagonian population must have expanded about 150 000 BP. We found evidence for gene flow across the entire species range, supporting a scenario of secondary contact in Tierra del Fuego where representatives of the oldest lineages coexist. The presence of gene flow between oceans leads us to reject the assumption of complete reciprocal monophyly for mtDNA between the presumed ESUs, suggesting that the species constitutes a single Evolutionarily Significant Unit.
Identifying Temporal Aggregation Effect on Crash-Frequency Modeling

Aggregation of spatiotemporal data can encounter potential information loss or distort attributes via individual observation, which would influence modeling results and lead to an erroneous inference, named the ecological fallacy. Therefore, deciding spatial and temporal resolution is a fundamental consideration in a spatiotemporal analysis. The modifiable temporal unit problem (MTUP) occurs when using data that is temporally aggregated. While consideration of the spatial dimension has been increasingly studied, the counterpart, a temporal unit, is rarely considered, particularly in the traffic safety modeling field. The purpose of this research is to identify the MTUP effect in crash-frequency modeling using data with various temporal scales. A sensitivity analysis framework is adopted with four negative binomial regression models and four random effect negative binomial models having yearly, quarterly, monthly, and weekly temporal units. As the different temporal unit was applied, the result of the model estimation also changed in terms of the mean and significance of the parameter estimates. Increasing temporal correlation due to using the small temporal unit can be handled with the random effect models.
EXPECTED SHORTFALL PADA PORTOFOLIO OPTIMAL DENGAN METODE SINGLE INDEX MODEL (Studi Kasus pada Saham IDX30)

Stock investment is a commitment to a number of funds in marketable securities which shows proof of ownership of a company with the aim of obtaining profits in the future. For obtaining optimal returns from stock investments, investors are expected to form optimal portfolios. The optimal portfolio formation using the Single Index Model is based on the observation that a stock fluctuates in the direction of the market price. It shows that most stocks tend to experience price increases if the market share price rises, and vice versa. Selection of optimal portfolio-forming stocks on IDX30 using the Single Index Model method produces 4 stocks, that are BRPT (Barito Pacific Tbk.) with weight 31.134%, ICBP (Indofood CBP Sukses Makmur Tbk.) 17.138%, BBCA (Bank Central Asia Tbk.) 51.331% and SMGR (Semen Indonesia (Persero) Tbk. ) 0.397%. Every investment must have a risk, for that investors need to calculate the possible risks that occur before investing. To calculate risk, Expected Shortfall (ES) is used as a measure of risk that is better than Value at Risk (VaR) because ES fulfill the subadditivity. At the 95% confidence level, the ES value is 23.063% while the VaR value is 10.829%. This means that the biggest possible risk that an optimal portfolio investor will receive using the Single Index Model for the next five weeks is 23.063%. Keywords : Portfolio, Single Index Model, Expected Shortfall, Value at Risk.
Unsupervised Change Detection by Cross-Resolution Difference Learning

Change detection (CD) aims to identify the differences between multitemporal images acquired over the same geographical area at different times. With the advantages of requiring no cumbersome labeled change information, unsupervised CD has attracted extensive attention of researchers. Multitemporal images tend to have different resolutions as they are usually captured at different times with different sensor properties. It is difficult to directly obtain one pixelwise change map for two images with different resolutions, so current methods usually resize multitemporal images to a unified size. However, resizing operations change the original information of pixels, which limits the final CD performance. This article aims to detect changes from multitemporal images in the originally different resolutions without resizing operations. To achieve this, a cross-resolution difference learning method is proposed. Specifically, two cross-resolution pixelwise difference maps are generated for the two different resolution images and fused to produce the final change map. First, the two input images are segmented into individual homogeneous regions separately due to different resolutions. Second, each pixelwise difference map is produced according to two measure distances, the mutual information distance and the deep feature distance, between image regions in which the pixel lies. Third, the final binary change map is generated by fusing and binarizing the two cross-resolution difference maps. Extensive experiments on four datasets demonstrate the effectiveness of the proposed method for detecting changes from different resolution images.
Empirical evaluation of home-based reablement: A review

Home-based reablement (HBR) aims to restore or increase patients’ level of functioning, thereby increasing the patients’ self-reliance and consequently decreasing their dependence on healthcare services. To date, the evidence on whether HBR is an efficient method has not been comprehensively reviewed. The aim of this study was to provide a concise summary of relevant existing findings. In addition, we provide a critical constructive assessment of the publications reflecting the extant research. The relevant literature on this topic was identified through a systematic search of appropriate databases. Thereafter, we screened the studies, first by title, followed by abstract and then by assessing full-text eligibility. A checklist of 15 criteria was developed and used as the basis for the quality assessment. In total, 12 studies from Australia, New Zealand, the USA and Norway were included in the full-text review. The studies reported estimated cost differences between HBR and usual care after the intervention. All the studies indicated lower costs for HBR, but not all of them reported a significant difference. The same pattern was also found for other measures of physical functioning and quality of life. The assessment revealed one specific common pattern: None of the papers scrutinized provided sufficient information about the data or the statistics employed, and all lacked external validity. Some promising results have been reported with respect to HBR reducing the need for specialist or residential care. In short, the existing evidence regarding the effects of HBR is still inconclusive. The findings from the quality assessment should motivate a multidisciplinary approach for future research on HBR. Published: Online May 2021.
Structural damage detection method based on the complete ensemble empirical mode decomposition with adaptive noise: a model steel truss bridge case study

Signal processing is one of the essential components in vibration-based approaches and damage detection for structural health monitoring. Since signals in the real world are often nonlinear and non-stationary, especially in extended and complex structures, such as bridges, the Hilbert–Huang transform is used for damage assessment. In recent years, the empirical mode decomposition technique has been gradually used in structural health monitoring and damage detection. In this article, the application of complete ensemble empirical mode decomposition with adaptive noise technique is investigated to identify the presence, location, and severity of damage on a steel truss bridge model. The target is built at laboratory conditions and experimentally subjected to white noise excitations. By employing complete ensemble empirical mode decomposition with adaptive noise technique, four key features extracted from the intrinsic mode functions, including energy, instantaneous amplitude, unwrapped phase, and instantaneous frequency, are assessed to localization, quantification, and detection of damage both quantitatively and qualitatively. In addition, to further explore the sensitivity of the damage detection approach based on the complete ensemble empirical mode decomposition with adaptive noise technique method, several improved damage indices are proposed based on the combinations of two statistical time-history features, including kurtosis and entropy features with the energy and instantaneous amplitude features of the analyzed signal. The experimental results from the damage indices based on the extracted features demonstrate the robustness, superiority, and more sensitivity of the complete ensemble empirical mode decomposition with adaptive noise technique method in addressing the damage location, classifying the severity, and detecting the damage compared to empirical mode decomposition and ensemble empirical mode decomposition techniques.
A Multi‐Dimensional Decomposition Method of the Meteorology‐Driven and Emission‐Driven Effects on Year‐to‐Year Air Quality Variations

The annual assessment of emission control effects on air quality is essential for policy adjustments. However, this assessment is difficult as the inter‐annual changes in pollution are impacted by complex meteorological conditions. In this study, based on our wind‐pollution decomposition (WPD) method, which decomposes wind effects (wind‐driven) and nonwind effects, we established the meteorology‐pollution decomposition (MPD) method, which separates meteorological effects (met‐driven) and nonmeteorological effects by importing other meteorological parameters, to approximate the emission change effects (emission‐driven) by the nonmeteorological effects. The performance of the MPD method was assessed by comparing the results of the WPD and MPD methods at multiple representative stations in Hong Kong with the longest continuous data available in China from 2000 to 2018. The decomposed emission‐driven impact is also validated by using the gross domestic product growth rates data. The emission‐driven contributions determined by the WPD and MPD methods generally show agreement in trend, while the met‐driven effects are generally larger than the wind‐driven effects with the same or opposite trend. The results showed that the met‐driven effect from the MPD method is more reasonable than the wind‐driven effect from the WPD method in representing complex meteorological influences, which indicates a better representation of emission‐driven impacts by the nonmeteorological effects during the unusual meteorological years, such as El Niño‐Southern Oscillation events. The MPD method represents an independent approach, which is based only on regular observations, to quantify the long‐term trend in emission‐driven impacts as well as the integrated meteorological impacts on the atmospheric environment under the background of climate change.
Variational Fusion of Hyperspectral Data by Non-Local Filtering

The fusion of multisensor data has attracted a lot of attention in computer vision, particularly among the remote sensing community. Hyperspectral image fusion consists in merging the spectral information of a hyperspectral image with the geometry of a multispectral one in order to infer an image with high spatial and spectral resolutions. In this paper, we propose a variational fusion model with a nonlocal regularization term that encodes patch-based filtering conditioned to the geometry of the multispectral data. We further incorporate a radiometric constraint that injects the high frequencies of the scene into the fused product with a band per band modulation according to the energy levels of the multispectral and hyperspectral images. The proposed approach proved robust to noise and aliasing. The experimental results demonstrate the performance of our method with respect to the state-of-the-art techniques on data acquired by commercial hyperspectral cameras and Earth observation satellites.