Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure and Dynamics of High Mobility Group Box Protein 1 (HMGB1) Complexed With Inhibitors of Its Proinflammatory Activity: A Combined Nuclear Magnetic Resonance and Computational Chemistry Approach

High-mobility group box 1 protein (HMGB1) is a nuclear component, but extracellularly it serves as a signaling molecule involved in acute and chronic inflammation, for example in sepsis and arthritis. The identification of HMGB1 inhibitors is therefore of significant experimental and clinical interest. We show that glycyrrhizin, a natural antiinflammatory and antiviral triterpene in clinical use, inhibits HMGB1 chemoattractant and mitogenic activities, and has a weak inhibitory effect on its intranuclear DNA binding function. NMR and fluorescence studies indicate that glycyrrhizin (and its analogue carbenoxolone) binds directly to HMGB1 (Kd ~ 150 μM), interacting with two shallow concave surfaces formed by the two arms of both HMG boxes, altering the internal mobility of proteins (on the millisecond timescale for Box A, on the nanosecond timescale for Box B) without significantly altering their overall diffusive properties. Due to the reduced number of experimentally determined intermolecular contacts, by means of two different computational approaches (QRFF for the Box A - carbenoxolone complex, HADDOCK data driven docking for the glycyrrhizin containing complexes) it was possible to obtain an atomic level model of the protein-ligand interactions. The presented results explain in part the anti-inflammatory properties of glycyrrhizin, and might direct the design of new derivatives with improved HMGB1-binding properties.
The Morphological and Genetic Variation of a Species of Lettuce ( Lactuca undulata Ledeb.): Geographically Widespread but Locally Endangered

Lactuca undulata Ledeb. (Asteraceae) is an annual plant that has valuable compounds such as caffeic acid and its derivatives. This study aims to understand if there is detectable genetic diversity in the Iranian populations of L. undulata . For this purpose, the diversity of five L. undulata populations collected from different regions of Iran was evaluated based on the morphological characteristics and ISSR markers. A common garden experiment was conducted to assess the morphological variation of five L. undulata populations. The results of the study of morphological features showed that most of the studied traits have a high diversity among populations. In the PCoA performed, five populations of L. undulata were identified based on their morphological characteristics. In genetic analyses, using ISSR markers, a total of 60 bands were produced using four primers. The percentage of total polymorphism was 100% and no monomorphic band was obtained. The Nei gene diversity index (H) and Shannon diversity index (I) indicated high genetic diversity (0.24) in the populations. Analysis of molecular variance (AMOVA) showed that 73% of the genetic diversity was within the populations and another 27% was among the populations. The highest and the lowest genetic diversity were observed in Cheshmeh Ali and Qom populations, respectively. PCoA nearly separated genetically different populations into distinct groups. Five L. undulata populations were found to differ significantly in their morphological and genetic polymorphism. The studied populations were found in highly degraded habitats with a limited number of individuals. Degradation and loss of habitats are the major concerns in determining the conservation status of the species in general and at the population level in particular .
A fast but ill-conditioned formal inverse to Radon transforms in 2D and 3D

We present a formal inversion of the multiscale discrete Radon trasform, valid both for 2D and 3D. With the transformed data from just one of the four quadrants of the direct 2D Radon transform, or one of the twelve dodecants, in case of 3D Radon transform, we can invert ex- actly and directly, with no iterations, the whole domain. The computational complexity of the proposed algorithms will be O(N log N). With N the total size of the problem, either square or cubic. But this inverse transforms are extremely ill conditioned, so the presence of noise in the transformed domain turns them useless. Still we present both algorithms, and characterize its weakness against noise.
IoTAuth: IoT Sensor Data Analytics for User Authentication Using Discriminative Feature Analysis

The revolution of IoT highly impacts on different applications such as remote sensing, smart cities, and remote digital healthcare. People use IoT devices for performing business transactions, daily tasks, and healthcare monitoring. IoT devices generate huge amounts of data assets that have potential applications. Biometrics is a potential application of sensors data. The traditional biometric methods such as PINs, passwords are exposed to numerous attacks such as replication, repeated passwords, etc. Sensors’ data-based continuous authentication methods are suitable for maintaining users’ privacy and security in mobile IoT systems. Most of the existing authentication methods have applied motion-based sensors for building users’ identification profiles. The proposed method uses motion sensors and biomedical sensors for reliable and multi-factor user authentication. In this article, we have introduced an IoT sensors data analytics framework to construct user authentication models. We apply the fiducial points-based feature extraction method data for extracting discriminative features. These features act as unique user profiles for authentication purposes. We have performed a detailed analysis of the proposed approach using the publically available datasets. The experiments elaborate on the effectiveness of IoTauth for improved authentication results.
A Review on Sensing Technologies for High-Throughput Plant Phenotyping

The current epidemic, population growth, and decreasing arable lands lead to a severe food crisis, which calls for productive and efficient agricultural methods to ensure a sustainable food supply for mankind. Crop monitoring is considered to be a potential solution for the improvement of food production. Current crop monitoring combines agriculture methodologies with other advanced technologies, including sensing technology, geographical information systems (GIS), Internet of Things (IoT), information and communication technology (ICT), robotics, and drone techniques to increase production with low labor cost. The high-throughput plant phenotyping is crucial for crop monitoring on the data acquisition of large-scale crop characteristics. The high-throughput plant phenotyping studies aim to achieve fast and precise large-scale crop monitoring techniques with minimum environmental impact by applying special plant phenotyping platforms. The phenotyping platforms are integrated with various sensors and data communication systems, which can help to achieve automatic data acquisition and transmission. This paper reviews the current high-throughput plant phenotyping development in crop monitoring, including sensors, communication protocols, data management, and plant phenotyping platforms. State-of-art challenges are reviewed and discussed. Also, the paper provides discussions on the current situation, upcoming challenges, and possible future trends for researchers in this field.
Long-Lasting and Highly Efficient TRIAC Dimming LED Driver with a Variable Switched Capacitor

A triode for alternating current (TRIAC) dimming light emitting diode (LED) driver, which adopts a variable switched capacitor for LED dimming and LED power regulation, is proposed in this paper. The proposed LED driver is power efficient, reliable, and long lasting because of the TRIAC switch that serves as its main switch. Similar to previous TRIAC dimmers for lamps, turn-on timing of a TRIAC switch can be controlled by a volume resistor, which modulates the equivalent capacitance of the proposed variable switched capacitor. Thus, LED power regulation against source voltage variation and LED dimming control can be achieved by the proposed LED driver while meeting the global standards for power factor (PF) and total harmonic distortion (THD). The long life and high power efficiency of the proposed LED driver make it appropriate for industrial lighting applications, such as those for streets, factories, parking garages, and emergency stairs. The detailed analysis of the proposed LED driver and its design procedure are presented in this paper. A prototype of 80 W was fabricated and verified by experiments, which showed that the efficiency, PF, and THD at V s = 220 V are 93.8%, 0.95, and 22.5%, respectively; 65 W of LED dimming control was achieved with the volume resistor, and the LED power variation was well mitigated below 3.75% for 190 V s < 250 V.
In-situ calibration of underwater glider flight model using acoustic Doppler current profilers

The angle of attack (AOA) is the difference between the underwater glider’s path and pitch angle and is necessary to accurately estimate dead-reckoned position and depth-averaged velocity. The AOA is also important for any sensor measurements that are affected by the glider’s velocity through water, such as ocean turbulence measurement. A glider flight model is generally used to accurately estimate AOA and glider’s actual velocity based on the knowledge of lift and drag coefficients optimized for each glider. This paper examines the AOA of a Slocum glider using an acoustic Doppler current profiler (ADCP) to demonstrate a regression method to estimate these coefficients. Since the current shear was sufficiently small on average, it was reasonable to assume that the ADCP velocity at the nearest bin could capture the glider’s motion during flight and was used to calculate AOA. The lift and drag coefficients were optimized so the flight model estimated the observed pitch – AOA relationship derived from the ADCP and the glider’s pitch observations. The resultant coefficients also satisfied the vertical and horizontal constraints of glider motion and gave unbiased estimates of turbulence intensity derived from the flight model and ADCP. Our method was also applied to a SeaExplorer glider to derive the lift and drag coefficients for the first time. The observed pitch – AOA relationship was reasonably captured by the flight model with the resultant coefficients, suggesting that our method to estimate the lift and drag coefficient of underwater gliders can be applied to any type of underwater glider equipped with an ADCP.
SEMblog: An Ontology-Based Semantic Blogging Tool for Knowledge Identification, Organization, and Reuse

Information Technology (IT) is often employed to put knowledge management policies into operation. However, many of these tools require human intervention when it comes to deciding how the knowledge is to be managed. The Sematic Web may be an answer to this issue, but many Sematic Web tools are not readily available for the regular IT user. Another problem that arises is that typical efforts to apply or reuse knowledge via a search mechanism do not necessarily link to other pages that are relevant. Blogging systems appear to address some of these challenges but the browsing experience can be further enhanced by providing links to other relevant posts. In this chapter, the authors present a semantic blogging tool called SEMblog to identify, organize, and reuse knowledge based on the Sematic Web and ontologies. The SEMblog methodology brings together technologies such as Natural Language Processing (NLP), Sematic Web representations, and the ubiquity of the blogging environment to produce a more intuitive way to manage knowledge, especially in the areas of knowledge identification, organization, and reuse. Based on detailed comparisons with other similar systems, the uniqueness of SEMblog lies in its ability to automatically generate keywords and semantic links. DOI: 10.4018/978-1-4666-1993-7.ch012
Reconstruction of the Eukaryotic Communities in Beppu Bay Over the Past 50 Years Based on Sedimentary DNA Barcoding

Comprehensive reconstruction of changes in eukaryotic communities in the recent past is useful for determining the response of the local ecosystems to global changes during the Anthropocene. We used DNA barcoding technology to reconstruct the marine eukaryotic communities of Beppu Bay, the Seto Inland Sea, Japan, over the past 50 years based on a short sediment core. Highly vulnerable DNA fragments were preserved in the sediments, possibly due to seasonally euxinic conditions. Analysis of the 18S rRNA V9 gene region indicated the temporal variability in eukaryotic communities, which consisted mainly of dinoflagellates and diatoms, in response to changes in the nutrient regime. The dominant species in the dinoflagellate genus Alexandrium changed as the water temperature increased. In addition, enhanced contributions by terrestrial plants and mosses were detected in flood sediments. Our results suggest that DNA fragments can be used as a proxy for the paleoenvironmental and paleoecological conditions in Beppu Bay.
Rising Strategic Instability and Declining Prospects for Nuclear Disarmament in South Asia – A Pakistani Perspective

Growing instability marks the evolving security environment between Pakistan and India and hence modifies their strategic priorities. The prevailing security dynamics in the region, such as changing nature of conflicts, introduction of new technologies, evolving deterrent force postures, and suspension of Confidence Building Measures (CBMs), have increased states’ reliance on arms build-up and decreased their inclin-ation to arms control and disarmament. This paper offers a Pakistani perspective on how the prevailing regional environment seems less favorable to nuclear disarmament and more inclined to deterrent force modernization. To explain the above rationale, this study takes guidance from primary and secondary sources to assess disarmament challenges, and discusses the prospects for creating a new security environment in the region to promote a renewed consensus on nuclear disarmament.
Transient Electrothermal Modeling of Digital and Radio Frequency Circuits.

LUNIYA, SONALI R. Transient Electrothermal Modeling of Digital and Radio Frequency Circuits. (Under the direction of Professor Michael B. Steer). Simulator technology for the high dynamic range, electrothermal modeling of electronic circuits is developed and applied to digital, radio frequency (RF) and microwave circuits. High-dynamic range is achieved using a combination of device models based on state-variables and utilizing automatic differentiation, precise error determination, and time step control. State-variables enable simpler and faster development of models less prone to implementation error. Automatic differentiation yields error free evaluation of the derivatives of circuit quantities with respect to each other and so removes any uncertainty in establishing the precise circuit condition. In transient analysis precise error determination and time step control is achieved by comparing two nonlinear solutions at each time point. A two-tone test of an X-band GaAs MESFET MMIC (Gallium Arsenide, Metal Semiconductor Field Effect Transistor Monolithic Microwave Integrated Circuit) was used to investigate and validate dynamic range. In the determination of the third-order intermodulation product in a two tone test a dynamic range of 165 dB was demonstrated. This high dynamic range was achieved through precise evaluation of the derivatives, accurate time step control and the circuit state, which is important in long electrothermal transient simulations. This minimization of accumulated numerical error is especially important in long electrothermal transient simulations. The 3D compact thermal models of the X-band MMIC LNA developed were verified with thermal images of the MMIC LNA taken with an infra red camera. The thermal models predict the temperature rise on various spots of the MMIC with less than 5% error. To perform an coupled electrothermal simulation at RF frequencies, a linear RC network based thermal macromodel of the MMIC was developed. The high dynamic range capability helped detect the small changes in the output voltage of the MMIC, at elevated temperatures. This thermal macromodel was applied to electrothermal simulations of an 3D thermal test chip designed with a 0.18 μm Fully Depleted Silicon on Insulator (FDSOI) MOSFET (Metal Oxide Semiconductor Field Effect Transistor) technology. An experimentally validated state-variable based electrothermal model of a 0.18 μm FDSOI MOSFET is implemented.
Determinants of body image in perimenopausal and postmenopausal women

ABSTRACT Body image plays an important role in women’s well-being. The aim of our study was to determine the influence of selected variables (menopausal symptoms, depressive symptoms, sexual dysfunctions, health behaviours) on body image among perimenopausal and postmenopausal women. Six hundred eighty-eight women aged 45–65 served as participants. The Kupperman Index, Beck Depression Inventory, Female Sexual Function Index, Body Esteem Scale, and a questionnaire that we created (sociodemographic factors and health status) were used. Structural equation modelling with the maximum likelihood method was used to test a model examining the relations among variables. The resulting model was satisfactory in fit (p = 0.610). The model predicted a significant percentage of the variance in all components of body esteem, including 30.9% of the variation in physical condition, 23.9% of weight control, and 37.6% of sexual attractiveness. Results of the direct effects analysis indicated a significant role for sexual dysfunction (p < 0.001) and intensity of depressive (p < 0.001) and menopausal (p = 0.001) symptoms in predicting overall body self-esteem. Additionally, health-related behaviours affected both weight control (p < 0.001) and sexual attractiveness (p < 0.001).
Evaluation of Acetyl- and Butyrylcholinesterase Enzyme Inhibitory Activities and Cytotoxic Activities of Anthraquinone Derivatives

In this study, the enzyme activity of anthraquinone compounds which were synthesized beforehand by our research group was investigated. Molecular docking studies were performed for compounds 1-(4-aminophenylthio)anthracene-9,10-dione (3) and 1-(4-chlorophenylthio)anthracene9,10-dione (5). Compound 3 was synthesized from the reaction of 1-chloroanthraquinone (1) and 4aminothiophenol (2). Compound 5 was synthesized (1) from the reaction of 1-chloroanthraquinone (1) and 4-chlorothiophenol (4). Anthraquinone analogs (3, 5) were synthesized with a new reaction method made by our research group (2). Inhibitory effects of compounds 3 and 5 were investigated against acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) enzymes which are related to Alzheimer’s Disease (AD). Compounds 3 and 5 exhibited strong anti-acetyland butyryl-cholinesterase inhibition activities than galanthamine used as standard compound (92.11±1.08 and 80.95±1.77 %, respectively). The EHOMO-ELUMO values, molecular descriptors, and the calculated UV-Vis spectra of anthraquinone derivatives were computed by B3LYP/6-31+G(d,p) levels in the CHCl3 phase. Based on the fluorescence property of the anthraquinone skeleton, the fluorescence activity of the bioactive anthraquinone analogue (5) was investigated. MTT test was performed to determine the cytotoxic effects of thioanthraquinone molecules 3 and 5. In MTT analyses, 3 compounds showed the highest effect against Ishikawa cells at a dose of 10 μg/mL, while compound 5 showed the highest effect at a dose of 50 μg/mL. The cell viability for compound 3 was 84.18% for 10 μg/mL and the cell viability for compound 5 was 75.02% for 50 μg/mL.
Reviewing physical exercise in non-obese diabetic Goto-Kakizaki rats

There is a high incidence of non-obese type 2 diabetes mellitus (non-obese-T2DM) cases, particularly in Asian countries, for which the pathogenesis remains mainly unclear. Interestingly, Goto-Kakizaki (GK) rats spontaneously develop insulin resistance (IR) and non-obese-T2DM, making them a lean diabetes model. Physical exercise is a non-pharmacological therapeutic approach to reduce adipose tissue mass, improving peripheral IR, glycemic control, and quality of life in obese animals or humans with T2DM. In this narrative review, we selected and analyzed the published literature on the effects of physical exercise on the metabolic features associated with non-obese-T2DM. Only randomized controlled trials with regular physical exercise training, freely executed physical activity, or skeletal muscle stimulation protocols in GK rats published after 2008 were included. The results indicated that exercise reduces plasma insulin levels, increases skeletal muscle glycogen content, improves exercise tolerance, protects renal and myocardial function, and enhances blood oxygen flow in GK rats.
Product variety and distribution channel structure

We consider how a manufacturer’s product variety decision is affected by its distribution strategy. While offering product variety will generally lead to higher demand, it also has negative implications on production costs and demand uncertainty. We investigate how the manufacturer’s optimal product variety decision differs when selling directly to customers (centralised scenario) as compared to selling through a retailer (decentralised scenario). We find that the retailer’s power and the impact of product variety on demand significantly affect the attractiveness of product variety and determine under which distribution strategy the manufacturer should provide a higher level of variety.
Domain fusion based feature extraction for SAR ATR

The all-weather and light condition operability of synthetic aperture radar (SAR) imaging systems makes them the optimal choice for several civilian and military remote sensing applications. Deep learning methods have demonstrated state-ofthe-art classification performance on standard SAR datasets such as the Moving and Stationary Target Acquisition and Recognition (MSTAR) Standard Operating Conditions (SOC) 10-target dataset. However, high acquisition costs limit the availability SAR domain data, both in number and diversity for use in training neural networks. This in turn limits the performance of these networks when used to classify SAR images acquired using radar system specifications and imaging environments that differ from the specifications used to create the images used for training. In this work, Siamese Networks, made up of twin AlexNet-based CNNs, were trained using subsets of the Military Ground Target Dataset (MGTD) and MSTAR datasets to learn radar specification and imaging environment invariant features thereby increasing the classification performance on the MGTD test set by 4.17%.
MULTI-OBJECTIVE COMMUNITY DETECTION METHOD USING AN IMPROVED NSGA II ALGORITHM

Community detection methods provide help in understanding the structure and function of networks. Since single objective community detection methods are not able to detect multiple significant community structures, some methods formulate the community detection as multi-objective problems. This paper proposes a multi-objective approach using a combination of three objective functions in multi-objective framework that is able to discover wide specter of resulting partitions. The algorithm is based on the basic NSGA-II, and improvements are as follows. A hybrid model is established for population initialization and the mutation operator and the crossover operators compose only possible partitions of input network. Different three optimization functions are tested in order to detect a large spectrum of resulting partitions.