Miracle-dz/UniFAR-FTUs huggingface dataset:
An ensemble artificial intelligence‐enabled MIoT for automated diagnosis of malaria parasite

Rapid advancements in Information and Communication Technologies (ICT) and artificial intelligence (AI) applications permeating to all spheres of life, including medical prognosis, have led modern clinical systems to tread the path of advanced Internet of Medical Things (IoMT) by infusing advanced learning technologies, particularly deep learning. Automated diagnosis of malarial infection using AI‐enabled IoMT holds the promise of sustainable prognosis by reducing diagnosis error significantly with improved recognition accuracy. Existing automated diagnostic systems usually employ classical deep learning models wherein setting parameter values such as automatic learning rate selection, weight management etc. are a major concern. To address these issues, this paper proposes a collaborative ensemble AI‐enabled IoMT automated diagnosis model to classify malaria parasitized from microscopic images. The proposed model consists of two main stages. In the first stage, a Snapshot ensemble learning model is conjured upon by a combination of three distinct layers of Convolutional, Batch Normalization, and Relu networks; that alters the learning rate aggressively during training phase thus providing different network weights that gives multiple models by training a single model. In the second stage, an ensemble of three transfer learning models is constructed, and finally the average ensemble result is obtained. The learning rates at both these stages are empirically selected through Cosine Annealing. Experiment on the malaria parasite image dataset demonstrates the superiority of the proposed model with respect to a baseline algorithm.
Combined Brooks-Corey/Burdine and van Genuchten/ Mualem Closed-Form Model for Improving Prediction of Unsaturated Conductivity

The performance of the widely used conventional closed-form models of Brooks and Corey and van Genuchten is restricted to soils characterized by a specific shape form of the water retention curve. Hence, the van Genuchten model more accurately describes “S”-shaped retention curves characterizing finer-textured soils, whereas the Brooks-Corey model is much better adapted for “J”-shaped retention curves characterizing relatively coarse-textured soils. In this work, a new closed-form soil hydraulic model is proposed. The suggested continuous-form function accurately describes soil retention curves irrespective of their specific shape form. New algebraic expressions based on Mualem’s statistical model and another new model that is a combination of the Mualem and Burdine theories were derived for the prediction of the unsaturated hydraulic conductivity function. Comparisons of ten soils known from international bibliography were performed. It is concluded that the proposed water retention curve expression as w.
Evaluation of Intravenous Immunoglobulin G treatment in Outpatients Rheumatology Practice

Objective: Intravenous immunoglobulin is an alternative therapeutic agent that can be used off-label in many autoimmune rheumatological diseases. The aim of this study is to evaluate the autoimmune rheumatological diseases characteristics in which intravenous immunoglobulin therapy is used and the efficacy and safety of this therapy. Methods and Methods: We performed a retrospective review of 133 patients with autoimmune rheumatological disease who received at least 1 course of intravenous immunoglobulin treatment at Hacettepe University Rheumatology Outpatient Clinic between January 2013 and December 2020. The autoimmune rheumatological disease demographic and clinical features, organ involvements, treatment phases (primary-secondary or infection), treatment responses and adverse effects were evaluated. Results: A total of 79% (n=105) patients were female and the mean±SD age was 45.5±16.9 years. The most common underlying rheumatic diseases were systemic lupus erythematosus (35%, n=47) and dermatomyositis/polymyositis (35%, n=47). Intravenous immunoglobulin therapy was most commonly used for resistant/relapsed myositis and haematological involvement. The median (IQR) intravenous immunoglobulin treatment course was 6.5 (13) and the duration of intravenous immunoglobulin treatment was 10.8 (24) months. Although it is used as second-line therapy in 77% of patients, complete clinical response was observed in 32% and partial response in 47%. There was a significant reduction in the median (IQR) steroid doses (methylprednisolone or equivalent dose) patients received from baseline after intravenous immunoglobulin treatment [30 (33) vs 8 (12), p<0.0001]. It was observed that the use of conventional disease-modifying antirheumatic drugs decreased after intravenous immunoglobulin treatment and the use of rituximab increased. Adverse effects associated with intravenous immunoglobulin treatment (10%) and discontinuation (4%) were found to be very low. Conclusion: Intravenous immunoglobulin treatment was commonly given in systemic lupus erythematosus and dermatomyositis/polymyositis patients because of hematological involvement and resistant/relapsed myositis in our study, respectively. Although it is mainly the second-line treatment, two-thirds of the patients achieved a complete/partial response. Side effects and related discontinuation due to intravenous immunoglobulin treatment are very few.
Hydrological Drought Assessment Based on the Standardized Streamflow Index: A Case Study of the Three Cape Provinces of South Africa

Global impacts of drought conditions pose a major challenge towards the achievement of the 2030 Sustainable Development Goals. As a result, a clarion call for nations to take actions aimed at mitigating the adverse negative effects, managing key natural resources and strengthening socioeconomic development can never be overemphasized. The present study evaluated hydrological drought conditions in three Cape provinces (Eastern, Western and Northern Cape) of South Africa, based on the Standardized Streamflow Index (SSI) calculated at 3- and 6-month accumulation periods from streamflow data spanning over the 3.5 decades. The SSI features were quantified by assessing the corresponding annual trends computed by using the Modified Mann–Kendall test. Drought conditions were also characterized in terms of the duration and severity across the three Cape provinces. The return levels of drought duration (DD) and drought severity (DS) associated with 2-, 5-, 10-, 20- and 50-year periods were estimated based on the generalized extreme value (GEV) distribution. The results indicate that hydrological drought conditions have become more frequent and yet exhibit spatial contrasts throughout the study region during the analyzed period. To this end, there is compelling evidence that DD and DS have increased over time in the three Cape provinces. Return levels analysis across the studied periods also indicate that DD and DS are expected to be predominant across the three Cape provinces, becoming more prolonged and severe during the extended periods (e.g., 20- and 50-year). The results of the present study (a) contribute to the scientific discourse of drought monitoring, forecasting and prediction and (b) provide practical insights on the nature of drought occurrences in the region. Consequently, the study provides the basis for policy- and decision-making in support of preparedness for and adaptation to the drought risks in the water-linked sectors and robust water resource management. Based on the results reported in this study, it is recommended that water agencies and the government should be more proactive in searching for better strategies to improve water resources management and drought mitigation in the region.
SEISMIC PERFORMANCE ASSESSMENT OF A TWO SPAN CONCRETE BRIDGE BY APPLYING INCREMENTAL DYNAMIC ANALYSIS

Bridges are key elements of transportation systems. Previous seismically induced damages to these structures revealed the necessity of seismic vulnerability assessment of them according to performance-based earthquake engineering philosophy. The purpose of this study is applying Incremental Dynamic Analysis for seismic assessment of a typical two span concrete bridge according to this philosophy. Incremental dynamic analysis consists of scaled time history analyses to gain structural performance under different levels of ground motion excitation. 2D model of the bridge structure was constructed in Open System for Earthquake Engineering Simulation. Peak Ground acceleration and column curvature ductility factor were chosen as intensity measure and seismic performance indicator, respectively. Eight time history records of past earthquakes were scaled and applied incrementally to the numerical model to evaluate seismic performance of the bridge. Damage states were defined as slight, moderate, extensive and collapse state. The resulted curves can be used to estimate mean annual frequency of exceeding each damage state.
Carbon and oxygen stable isotope record of upper Kimmeridgian shallow-marine ramp carbonates (Iberian Basin, NE Spain): the imprint of different burial and tectonic histories

Bulk carbon and oxygen stable isotopes of ancient shallow-marine carbonates can record the effects of multiple palaeoenvironmental factors, but also the imprint of several post-depositional processes, which may alter the original marine isotopic composition. In this study, carbon and oxygen stable isotope analyses were performed on bulk carbonate, bivalve calcitic-shell (Trichites) and calcite vein samples from two stratigraphic sections (Tosos and Fuendetodos, present-day distance 15km), representing proximal inner- and distal mid-ramp environments, respectively, of the uppermost Kimmeridgian ramp facies deposited in the northern Iberian Basin (NE Spain). These successions underwent different diagenetic pathways that altered the primary marine isotopic composition in each section in different ways. Different burial histories, tectonic uplift and a variable exposure to meteoric diagenesis from the end of the Kimmeridgian to the Cenozoic (following Alpine tectonic uplift) are reflected in the different alteration patterns of the carbon and oxygen stable isotope signatures. A significant deviation to lower values in both δ13O and δ18O is recorded in those carbonates mostly exposed to meteoric diagenesis (distal mid-ramp Fuendetodos section), because of post-depositional tectonic uplift (telogenesis). On the other hand, the deposits mainly affected by burial diagenesis (proximal inner-ramp Tosos section) only record low δ18O with respect to expected values for pristine Kimmeridgian marine carbonates. The different burial and tectonic uplift histories of these deposits in each sector, due to their different tectonic evolution in this part of the basin, resulted in a variable degree of diagenetic resetting. However, in spite of the different diagenetic resetting reported of the carbon and oxygen stable isotope signatures in each section, these carbonates show similar cement types in termsof fabrics and cathodoluminescence properties. The diagenetic resetting reported for these carbonates prevents the use of the δ13O and δ18O records for addressing palaeoenvironmental interpretations, but instead highlights useful features regarding the variable diagenetic overprint of the studied shallow-marine carbonate successions concerning their specific post-depositional history.
Virtual Screening of Adenylate Kinase 3 Inhibitors Employing Pharmacophoric Model, Molecular Docking, and Molecular Dynamics Simulations as Potential Therapeutic Target in Chronic Lymphocytic Leukemia

Adenylate kinase 3 (AK3) is an enzyme located in the mitochondrial matrix involved in purine homeostasis. This protein has been considered a potential therapeutic target in chronic lymphocytic leukemia (CLL), because the silencing of the AK3 gene has inhibited cell growth in CLL in vitro models. This study aimed to design potential AK3 inhibitors by applying molecular modeling techniques. Through the mapping of AK3 binding sites, essential interaction fields for pharmacophore design were identified. Online libraries were virtually screened by using a pharmacophore model, and 6891 compounds exhibited the functional groups for interaction with the target. These compounds underwent molecular docking simulations through Surflex and GOLD programs. After visual inspection, we selected 13 compounds for pharmacokinetic properties toxicology prediction via admetSAR and Protox web servers. Finally, six compounds were chosen for further analysis.
Die Sanktionspolitik der Arbeitsagenturen nach den Hartz- Reformen: Analyse der Wirkungen des Ersten Gesetztes für moderne Dienstleistungen am Arbeitsmarkt

Im Rahmen des 'Ersten Gesetzes fur moderne Dienstleistungen am Arbeitsmarkt' wurden die Zumutbarkeitskriterien verscharft und die Sperrzeitendauer reformiert, um die Sanktionsinstrumente der Bundesagentur fur Arbeit (BA) leichter anwenden zu konnen, den Missbrauch von Versicherungsleistungen zu reduzieren sowie den Abgang aus dem Leistungsbezug zu beschleunigen. Der vorliegende Beitrag analysiert die Wirkungen der Reformen auf die Sanktionspolitik der BA und ihrer regionalen Arbeitsagenturen. Dabei liegt das Hauptinteresse auf der Implementation der Sanktionen in den Arbeitsagenturen vor und nach den Hartz-Reformen. Der Fokus ist auf die Aussprache von Sperrzeiten, die den Bezug von Lohnersatzleistungen unterbrechen, gerichtet. Die Analysen basieren auf regionalen Geschaftsdaten der BA-Statistik, die fur den Zeitraum 2000 bis 2004 quartalsweise vorliegen, einer schriftlichen Befragung aller Arbeitsagenturen sowie qualitativen Interviews in zehn Agenturen. Die empirische Analyse beruht auf linearen Paneldatenmodellen.
An Outbreak in Pigeons Caused by the Subgenotype VI.2.1.2 of Newcastle Disease Virus in Brazil

Newcastle disease virus (NDV) can infect over 250 bird species with variable pathogenicity; it can also infect humans in rare cases. The present study investigated an outbreak in feral pigeons in São Paulo city, Brazil, in 2019. Affected birds displayed neurological signs, and hemorrhages were observed in different tissues. Histopathology changes with infiltration of mononuclear inflammatory cells were also found in the brain, kidney, proventriculus, heart, and spleen. NDV staining was detected by immunohistochemistry. Twenty-seven out of thirty-four tested samples (swabs and tissues) were positive for Newcastle disease virus by RT-qPCR test, targeting the M gene. One isolate, obtained from a pool of positive swab samples, was characterized by the intracerebral pathogenicity index (ICPI) and the hemagglutination inhibition (HI) tests. This isolate had an ICPI of 0.99, confirming a virulent NDV strain. The monoclonal antibody 617/161, which recognizes a distinct epitope in pigeon NDV strains, inhibited the isolate with an HI titer of 512. A complete genome of NDV was obtained using next-generation sequencing. Phylogenetic analysis based on the complete CDS F gene grouped the detected isolate with other viruses from subgenotype VI.2. 1.2, class II, including one previously reported in Southern Brazil in 2014. This study reports a comprehensive characterization of the subgenotype VI.2. 1.2, which seems to have been circulating in Brazilian urban areas since 2014. Due to the zoonotic risk of NDV, virus surveillance in feral pigeons should also be systematically performed in urban areas.
Agri-Tech Start-Ups: Using TCOP’s to Enhance Growth in the UK and Vietnam

With the increasing importance of the Agri-tech sector in helping the UK and Vietnam green economies both to grow, and to tackle the key challenges of self-sufficiency and sustainability, what role can the Communities of Practice play in supporting the Agri-tech start-ups? This study on the effectiveness of these temporal Communities of Practice, is paramount to support both the growth and sustainability of the two countries’ Agri-tech sector and its link to a green economy.
Income Elasticity of Driving and Regressivity of Emission Control Taxation Policies: Evidence from Massachusetts New Car Market

What is the distributional impact of emission control taxation policies on new car markets? This paper examines the relative regressivity of taxes on fuel and taxes on the low fuel economy of cars, conditioning on car purchases. To estimate how tax revenues change with income, I rely on nameplate-model fixed effects indicated in a rich panel of new cars sold in Massachusetts and exploit the correlation between driving patterns and average demographic characteristics at the ZIP Code level to identify flexible substitution patterns for new car buyers. The heterogeneity allowed in my model demonstrates that the difference between the elasticities of tax revenues with respect to income across the two policies lies in the income elasticity of driving. Theory shows that if the income elasticity of driving is positive, the elasticity of fuel tax revenues with respect to household income must be greater than that of taxes on low fuel economy. Policy counterfactuals confirm the theoretical result. Although wealthier people are less likely to purchase more fuel-efficient cars when facing trade-offs between vehicle fuel efficiency and other vehicle attributes, the fact that more affluent households drive more makes fuel taxes more progressive relative to taxes on low fuel economy. Moreover, I show that the loss in total consumer surplus from applying fuel taxes is smaller than that from applying taxes on low fuel economy for achieving the same level of externality reduction because fuel taxes have heterogeneous influences on consumers in different mileage groups. Therefore, this paper provides a framework for understanding the distributional consequences of regulating the market of energy-using durable goods with various policy instruments in the presence of usage heterogeneity.
A versatile linkage device for high-voltage ICs

A device operating as an integrated voltage-source for power supply and as a controllable current-source for level shifting in high-voltage integrated circuits has been designed and tested experimentally. Two-dimensional modelling results are in good agreement with the measurements. A SPICE macro-model useful for circuit design is presented and applications for smart power design are discussed.
Hearing Self-Assessment Questionnaire as Screening Tool for Hearing Impairment Among Elderly

Cilj rada bio je ispitati mogucnost probira ostecenja sluha u starijih osoba primjenom Upitnika za samoprocjenu slusanja (USS). USS sadrži 10 cestica koje ispituju ucestalost teskoca slusanja u svakodnevnim komunikacijskim situacijama i njihov psihosocijalni ucinak na skali od 5 stupnjeva. Njegova pouzdanost i valjnost provjerene su primjenom protokola RTT7, faktorske analize i diskriminativne analize rezultata samoprocjene slusanja 31 osobe s ostecenjem sluha (prosjecna dob 76 ; 7 godina) i 30 cujucih osoba (prosjecne dobi 74 ; 3 godine). Podaci su analizirani i deskriptivno, a klaster analizom ispitana je mogucnost klasifikacije teskoca slusanja skupine ispitanika s ostecenjem sluha. Rezultati ukazuju da USS ima potencijal da bude iskoristen za probir na ostecenje sluha među starijim osobama koje se javljaju u sustav primarne zdravstvene zastite, gdje može služiti kao jasan indikator potrebe audioloske obrade te da može biti iskoristen za stupnjevanje funkcionalnih teskoca slusanja na blage, umjerene i teske.
Processes controlling aggregate formation and distribution during the Arctic phytoplankton spring bloom in Baffin Bay

In the last decades, the Arctic Ocean has been affected by climate change, leading to alterations in the sea ice cover that influence the phytoplankton spring bloom, its associated food web, and therefore carbon sequestration. During the Green Edge 2016 expedition in the central Baffin Bay, the phytoplankton spring bloom and its development around the ice edge was followed along 7 transects from open water to the ice-pack interior. Here, we studied some of the processes driving phytoplankton aggregation, using aggregate and copepod distribution profiles obtained with an underwater vision profiler deployed at several stations along the transects. Our results revealed a sequential pattern during sea ice retreat in phytoplankton production and in aggregate production and distribution. First, under sea ice, phytoplankton started to grow, but aggregates were not formed. Second, after sea ice melting, phytoplankton (diatoms and Phaeocystis spp. as the dominant groups) benefited from the light availability and stratified environment to bloom, and aggregation began coincident with nutrient depletion at the surface. Third, maxima of phytoplankton aggregates deepened in the water column and phytoplankton cells at the surface began to degrade. At most stations, silicate limitation began first, triggering aggregation of the phytoplankton cells; nitrate limitation came later. Copepods followed aggregates at the end of the phytoplankton bloom, possibly because aggregates provided higher quality food than senescing phytoplankton cells at the surface. These observations suggest that aggregation is involved in 2 export pathways constituting the biological pump: the gravitational pathway through the sinking of aggregates and fecal pellets and the migration pathway when zooplankton follow aggregates during food foraging.
Explicit feature disentanglement for visual place recognition across appearance changes

In the long-term deployment of mobile robots, changing appearance brings challenges for localization. When a robot travels to the same place or restarts from an existing map, global localization is needed, where place recognition provides coarse position information. For visual sensors, changing appearances such as the transition from day to night and seasonal variation can reduce the performance of a visual place recognition system. To address this problem, we propose to learn domain-unrelated features across extreme changing appearance, where a domain denotes a specific appearance condition, such as a season or a kind of weather. We use an adversarial network with two discriminators to disentangle domain-related features and domain-unrelated features from images, and the domain-unrelated features are used as descriptors in place recognition. Provided images from different domains, our network is trained in a self-supervised manner which does not require correspondences between these domains. Besides, our feature extractors are shared among all domains, making it possible to contain more appearance without increasing model complexity. Qualitative and quantitative results on two toy cases are presented to show that our network can disentangle domain-related and domain-unrelated features from given data. Experiments on three public datasets and one proposed dataset for visual place recognition are conducted to illustrate the performance of our method compared with several typical algorithms. Besides, an ablation study is designed to validate the effectiveness of the introduced discriminators in our network. Additionally, we use a four-domain dataset to verify that the network can extend to multiple domains with one model while achieving similar performance.