Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Personal Identification Using Wearable Devices Based on LSTM and CNN

Various studies exist to identify individuals. Personal identification research based on inertial data, that is, acceleration and angular velocity acquired with an inertial sensor, is also one of these efforts. In fact, when learning inertial data with convolutional neural network (CNN), it is known to be able to identify individuals with high accuracy. However, we found that the individual identification model using inertial data significantly lowers the performance of recognition from 99% to 81% when the shoes worn by the individual change. This paper deals with solving this problem by using a gait cycle extracted from inertial data. First, we study a method to detect the gait cycle using long short-term memory, a representative recurrent neural network model. Second, the CNN model using the gait cycle is implemented, and then the model is evaluated with the typical performance evaluation indicators such as accuracy, precision, recall, and F1-score. As a result, it is confirmed that the proposed model can identify individuals with more than 90% accuracy even when the shoes worn are different.
Use of Insect-Derived Chitosan for the Removal of Methylene Blue Dye from Wastewater: Process Optimization Using a Central Composite Design

Insects are a readily available source of chitosan due to their high reproductive rates, ease of breeding, and resistance to changes in their ecosystem. This study aimed to extract chitosan from several widespread insects: Blaps lethifera (CS-BL), Pimelia fernandezlopezi (CS-PF), and Musca domestica (CS-MD). The study was also extended to using the obtained chitosans in removing methylene blue dye (MB) from wastewater. The source of the chitosan, the initial concentration of MB dye, and the reaction time were chosen as the working parameters. The experiments were designed using a central composite design (CCD) based on the dye removal efficiency as the response variable. The experimental work and statistical calculation of the CCD showed that the dye removal efficiency ranged from 35.9% to 88.7% for CS-BL, from 18.8% to 47.1% for CS-PF, and from 10.3% to 29.0% for CS-MD at an initial MB concentration of 12.79 mg/L. The highest methylene blue dye removal efficiency was 88.7% for CS-BL at a reaction time of 120 min. This indicates that the extraction of chitosan from insects (Blaps lethifera) and its application in dye removal is a promising, environmentally friendly, economical, biodegradable, and cost-effective process. Furthermore, the CCD is a statistical experimental design technique that can be used to optimize process variables for removing other organic pollutants using chitosan.
Algicidal bacteria against cyanobacteria: Practical knowledge from laboratory to application

Abstract The use of algicidal bacteria has gained prominence as natural solution to control the worrying increase of harmful algal blooms worldwide. However, although cyanobacterial blooms (cyanoHABs) often dominate freshwater bodies, recent reviews on the subject have addressed cyanobacteria in the second place and focused more on bacteria-algae interactions. This article provides a critical review of the fundamental aspects of searching for, isolating and assaying candidate algicidal bacteria targeting cyanobacteria. Possible species-specific interactions and the different modes of action of bacteria against different species of cyanobacteria are also discussed. It has been observed that there is a clear bias in the literature toward the genus Microcystis, being by far the most studied and reviewed to date. This contrasts with the numerous studies showing cyanobacterial blooms dominated by other harmful species, such as the genera Planktothrix, Aphanizomenon or Raphidiopsis. To add new knowledge to the lack of current studies on these genera, a separate experimental section has been included in this review with research results on the sensitivity of nine harmful freshwater cyanobacteria and two green algae to different bacteria and algicidal compounds. Finally, certain ecological and biosafety risks that must be taken into account when applying algicidal bacteria as a bioaugmentation strategy are also highlighted. Overall, this review is presented as an attempt to outline the knowledge gathered over the last thirty years of research, while raising new questions and debates on key issues that remain poorly understood. Graphical abstract
AoI-Minimal Online Scheduling for Wireless-Powered IoT: A Lyapunov Optimization-Based Approach

This paper investigates the age of information (AoI)-based online scheduling in multi-sensor wireless powered communication networks (WPCNs) for time-sensitive Internet of Things (IoT). Specifically, we consider a typical WPCN model, where a wireless power station (WPS) charges multiple sensor nodes (SNs) by wireless power transfer (WPT), and then the SNs are scheduled in the time domain to transmit their sampled status information with their harvested energy to a mobile edge server (MES) for decision making. For such a system, we first derive a closed-form expression of the successful data transmission probability in Nakagami- ${m}$ fading channels. To pursue an efficient online scheduling policy that minimizes the Expected Weighted Sum AoI (EWSAoI) of the system, a discrete-time scheduling problem is formulated. As the problem is non-convex with non-explicit expression of the EWSAoI, we propose a Max-Weight policy based on the Lyapunov optimization theory, which schedules the SNs at the beginning of each time in terms of the one-slot conditional Lyapunov Drift. Simulations demonstrate our presented theoretical results and show that our proposed scheduling policy outperforms other baselines such as the greedy policy and random round-robin (RR) policy. Especially, when the number of SNs is relatively small, the gain achieved by the proposed policy compared to the greedy policy is considerable. Moreover, some interesting insights are also observed: 1) as the number of SNs increases, the EWSAoI also increases; 2) when the transmit power is relatively small, the larger the number of SNs, the smaller the EWSAoI; 3) the EWSAoI decreases with the increment of transmit power of the WPS and then tends to be flat; 4) the EWSAoI increases with the increment of the distance between the SNs and the MES.
Immune Checkpoint Inhibitors, Small-Molecule Immunotherapies and the Emerging Role of Neutrophil Extracellular Traps in Therapeutic Strategies for Head and Neck Cancer

Immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of many cancer types, including head and neck cancers (HNC). When checkpoint and partner proteins bind, these send an “off” signal to T cells, which prevents the immune system from destroying tumor cells. However, in HNC, and indeed many other cancers, more people do not respond and/or suffer from toxic effects than those who do respond. Hence, newer, more effective approaches are needed. The challenge to durable therapy lies in a deeper understanding of the complex interactions between immune cells, tumor cells and the tumor microenvironment. This will help develop therapies that promote lasting tumorlysis by overcoming T-cell exhaustion. Here we explore the strengths and limitations of current ICI therapy in head and neck squamous cell carcinoma (HNSCC). We also review emerging small-molecule immunotherapies and the growing promise of neutrophil extracellular traps in controlling tumor progression and metastasis.
A Multimode Vision Sensor With Temporal Contrast Pixel and Column-Parallel Local Binary Pattern Extraction for Dynamic Depth Sensing Using Stereo Vision

This article presents a 0.56/0.8 V multimode vision sensor for temporal and spatial information extraction with processing in sensor (PIS) technique. The proposed six transistors and one capacitor (6T1C) temporal contrast pixel (TCP) structure using the exposure compensation scheme (ECS) can realize in-pixel temporal contrast calculation and motion event reporting (ER) with global shutter exposure and seamless frame difference (FD) based on the pulsewidth modulation (PWM) operation. In addition, the column-parallel local binary pattern (LBP) extraction provides further spatial feature information without the power-consuming analog-to-digital conversion to meet the power-efficient requirement for always-on-edge devices. According to the temporal and spatial information extracted from FD and LBP modes, this work realizes the PIS operations for dynamic depth calculation of a stereo vision system, which filters out the static scene and provides the depth information of the dynamic objects only. To further alleviate the data transfer bandwidth, the region of interest (ROI) capability is also embedded in the sensor for data windowing and object locating. The prototyped vision sensor was fabricated in TSMC’s standard 0.18 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process and verified. The vision sensor provides five operating modes that can adapt to different tasks, which include the raw image mode (IM), FD mode, ER mode, LBP mode, and ROI mode. The measurement results show a maximum frame rate of 540/819/540 frames/s at a power consumption of 390/162.6/151.9 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> with an achieved iFoM of 45.5/12.5/17.7 pJ/pixel<inline-formula> <tex-math notation="LaTeX">$\cdot $ </tex-math></inline-formula>frame in IM/ER/LBP mode, respectively.
663 ESTANDARIZACIÓN DE FÁRMACOS ANTIINFLAMATORIOS NO ESTEROIDEOS ADMINISTRADOS A UN MODELO MÚRIDO PARA EVALUACIÓN DE ACTIVIDAD ANTIARTRÍTICA

La artritis reumatoide es una enfermedad inflamatoria cronica que afecta preferentemente a las articulaciones de forma simetrica. Entre los farmacos para aliviar el dolor y la inflamacion a corto plazo estan los antiinflamatorios no esteroideos (AINE). En el presente estudio se analizaron los AINE fenilbutazona e Indometacina (80 mg/kg y 0.7 mg/kg respectivamente) administrados via oral en ratas de la cepa wistar, machos y hembras artriticas, para comparar el efecto antiinflamatorio de estos farmacos considerando el genero. Se registro una actividad antiartritica significativa de la fenilbutazona en machos, manteniendose constante su actividad durante fase cronica. En el caso de la indometacina se registro una actividad antiiflamatoria significativa durante la fase aguda.
Second-order group consensus for linear multi-agent systems with average dwell time switching

This paper studies the group consensus problem of second-order multi-agent systems (MASs) with switching communication topology. Unlike most existing papers concerning the consensus issue of MASs under arbitrary switching topology or Markovian switching topology, our paper tries to design a switching signal such that MAS can achieve group consensus under a designed switching signal set. First, using a state transformation method, the group consensus problem of MASs can be equivalently transformed into the asymptotical stability of a corresponding switched system. Then, two sufficient criteria are established by using Lyapunov function method and average dwell time (ADT) approach, where the minimum ADT τ a is given clearly. Finally, simulation examples are given to show the effectiveness of our theoretical analysis.
Evaluation and Analysis of Long-term Environmental Noise Levels in 7 Major Cities of India

This paper describes the long-term noise monitoring data for ten consecutive years (2011–2020) acquired from the diversified National Ambient Noise Monitoring Network (NANMN) set up across 7 major cities of India and consisting of 70 stations for continuous noise monitoring throughout the year. The annual average ambient noise levels observed throughout these ten years in 70 locations under study, including 25 locations in commercial zones, 12 in industrial, 16 in residential, and 17 in silence zones, are described. The noise scenario in these ten years is compared and analyzed. It is observed that no site in residential or silence zones meets the ambient noise limits for the past ten years. The study suggests guidelines for a policy framework for environmental noise management and control to regulate noise pollution in Indian cities.
Negative-norm least-squares methods for axisymmetric Maxwell equations

Negative-norm Least-squares Methods for Axisymmetric Maxwell Equations. (May 2006) Dylan Matthew Copeland, B.S., Southeastern Louisiana University; M.S., Texas A&M University Chair of Advisory Committee: Dr. Joseph E. Pasciak We develop negative-norm least-squares methods to solve the three-dimensional Maxwell equations for static and time-harmonic electromagnetic fields in the case of axial symmetry. The methods compute solutions in a two-dimensional cross section of the domain, thereby reducing the dimension of the problem from three to two. To achieve this dimension reduction, we work with weighted spaces in cylindrical coordinates. In this setting, approximation spaces consisting of low order finite element functions and bubble functions are analyzed. In contrast to other methods for axisymmetric Maxwell equations, our leastsquares methods allow for discontinuous coefficients with large jumps and non-convex, irregular polygonal domains discretized by unstructured meshes. The resulting linear systems are of modest size, are symmetric positive definite, and can be solved very efficiently. Computations demonstrate the robustness of the methods with respect to the coefficients and domain shape.
Compact microstrip dual-narrowband bandpass filter with wider rejection band

ABSTRACT In this article, a new compact microstrip dual-narrowband bandpass filter is introduced with wide and strong rejection level in the first and last stopband. The location of the second passbands is controllable by a resonator without changing the center frequency of the first passband. The filter structure consists of coupled and stepped transmission lines and radial stubs. Also, fractional 3 dB bandwidth of the first and second passband are 2.35 and 1.62%. The last stopband of the proposed filter is wide. The overall size of the proposed filter is , where is the guided wavelength at the first center frequency.
Study of ageing and size effects in Nickel–Titanium shape memory alloy using molecular dynamics simulations

ABSTRACT The effect of ageing process at 1073.15 K on the athermal phase transformation in different nanograins (4.5, 6 and 9 nm) of Nickel–Titanium shape memory alloy is studied using molecular dynamics simulations. The martensitic transformation start temperature and transformed martensite volume decrease with decreasing grain size. The two-stage phase transformation with intermediate phase formation is observed only in the smallest grain (4.5 nm) where a single martensite variant is formed. On the contrary, larger grains show a self-accommodated twinned martensite variants with one-stage transformation from austenite to martensite. The ageing process hardly influences the morphology of the martensite phase, however, it rises the martensite start temperature and reduces the austenite start temperature. The nano grain size models demonstrate the constrained transformation due to the transformation barrier and the accumulation of internal stress, while the ageing process shows the tendency for stress relaxation.
Tailoring surface plasmon resonance and dipole cavity plasmon modes of scattering cross section spectra on the single solid-gold/gold-shell nanorod

Tunable surface plasmon resonance (SPR) and dipole cavity plasmon modes of the scattering cross section (SCS) spectra on the single solid-gold/gold-shell nanorod have been numerically investigated by using the finite element method. Various effects, such as the influence of SCS spectra under x- and y-polarizations on the surface of the single solid-gold/gold-shell nanorod, are discussed in detail. With the single gold-shell nanorod, one can independently tune the relative SCS spectrum width by controlling the rod length and rod diameter, and the surface scattering by varying the shell thickness and polarization direction, as well as the dipole peak energy. These behaviors are consistent with the properties of localized SPRs and offer a way to optically control and produce selected emission wavelengths from the single solid-gold/gold-shell nanorod. The electric field and magnetic distributions provide us a qualitative idea of the geometrical properties of the single solid-gold/gold-shell nanorod on plasmon resonance.
Some Topics concerning Graphs, Signed Graphs and Matroids

We discuss well-quasi-ordering in graphs and signed graphs, giving two short proofs of the bounded case of S. B. Rao’s conjecture. We give a characterization of graphs whose bicircular matroids are signed-graphic, thus generalizing a theorem of Matthews from the 1970s. We prove a recent conjecture of Zaslavsky on the equality of frustration number and frustration index in a certain class of signed graphs. We prove that there are exactly seven signed Heawood graphs, up to switching isomorphism. We present a computational approach to an interesting conjecture of D. J. A. Welsh on the number of bases of matroids. We then move on to study the frame matroids of signed graphs, giving explicit signed-graphic representations of certain families of matroids. We also discuss the cycle, bicircular and even-cycle matroid of a graph and characterize matroids arising as two different such structures. We study graphs in which any two vertices have the same number of common neighbors, giving a quick proof of Shrikhande’s theorem. We provide a solution to a problem of E. W. Dijkstra. Also, we discuss the flexibility of graphs on the projective plane. We conclude by mentioning partial progress towards characterizing signed graphs whose frame matroids are transversal, and some miscellaneous results.
Demonstration of New Microelectrode Design to Enhance Sensitivity of Dielectrophoretic Impedance Measurement

Dielectrophoretic impedance measurement (DEPIM) is a method using a microelectrode for measuring a target suspended in a solution by combining dielectrophoretic (DEP) trapping of the target and simultaneous measurement of impedance varied with the trapping. DEPIM can be utilized to detect bacteria and viruses without any chemical additive since DEPIM efficiency depends on the DEP trapping dominated by the microelectrode shape. This letter aims to demonstrate a new microelectrode design to increase bacteria detection efficiency instead of the conventional interdigitated microelectrode. The microelectrode having a serpentine gap as a sinusoidal waveform profile was proposed. The new microelectrode was compared with the interdigitated one in numerical simulation and experiments. The numerical simulation demonstrates that the serpentine microelectrode traps all the targets in a laminar flow in a microchannel. In contrast, the interdigitated one placed parallel to the microchannel does not because the target flowing away from the edges of the microelectrode cannot be trapped. The experiments using three kinds of bacteria were carried out. It was demonstrated that the serpentine microelectrode represented a sensitivity 104 times higher than the interdigitated one when a small amount of the sample solution was tested for a short time (1 min).
Effects of Single and Combined Drought and Salinity Stress on the Root Morphological Characteristics and Root Hydraulic Conductivity of Different Winter Wheat Varieties

Water shortages and crop responses to drought and salt stress are related to the efficient use of water resources and are closely related to food security. In addition, PEG or NaCl stress alone affect the root hydraulic conductivity (Lpr). However, the effects of combined PEG and NaCl stress on Lpr and the differences among wheat varieties are unknown. We investigated the effects of combined PEG and NaCl stress on the root parameters, nitrogen (N) and carbon content, antioxidant enzymes, osmotic adjustment, changes in sodium and potassium, and root hydraulic conductivity of Yannong 1212, Heng 4399, and Xinmai 19. PEG and NaCl stress appreciably decreased the root length (RL), root surface area (RS), root volume (RV), K+ and N content in shoots and roots, and Lpr of the three wheat varieties, while the antioxidant enzyme activity, malondialdehyde (MDA), osmotic adjustment, nonstructural carbon and Na+ content in shoots and roots, etc., remarkably remained increased. Furthermore, the root hydraulic conductivity had the greatest positive association with traits such as RL, RS, and N and K+ content in the shoots of the three wheat varieties. Moreover, the RL/RS directly and actively determined the Lpr, and it had an extremely positive effect on the N content in the shoots of wheat seedlings. Collectively, most of the root characteristics in the wheat seedlings decreased under stress conditions, resulting in a reduction in Lpr. As a result, the ability to transport nutrients—especially N—from the roots to the shoots was affected. Therefore, our study provides a novel insight into the physiological mechanisms of Lpr.
Development of Blood Glucose Monitoring System using Image Processing and Machine Learning Techniques

— Glucose concentration measurement is essential for diagnosis, monitoring and treatment of various medical conditions like diabetes mellitus, hypoglycemia, etc. This paper presents a novel image-processing and machine learning based approach for glucose concentration measurement. Experimentation based on Glucose oxidase - peroxidase (GOD/POD) method has been performed to create the database. Glucose in the sample reacts with the reagent wherein the concentration of glucose is detected using colorimetric principle. Colour intensity thus produced, is proportional to the glucose concentration and varies at different levels. Existing clinical chemistry analyzers use spectrophotometry to estimate the glucose level of the sample. Instead, this developed system uses simplified hardware arrangement and estimates glucose concentration by capturing the image of the sample. After further processing, its Saturation (S) and Luminance (Y) values are extracted from the captured image. Linear regression based machine learning algorithm is used for training the dataset consists of saturation and luminance values of images at different concentration levels. Integration of machine learning provides the benefit of improved accuracy and predictability in determining glucose level. The detection of glucose concentrations in the range of 10 – 400 mg/dl has been evaluated. The results of the developed system were verified with the currently used spectrophotometry based Trace40 clinical chemistry analyzer. The deviation of the estimated values from the actual values was found to be around 2-3%.
The Pupil Knows: Pupil Dilation Indexes and Their Inhibitory Ability in Normal Aging

Pupil dilation is considered an index of cognitive effort, as the pupil typically dilates as the cognitive load increases. In this paper, we evaluated whether older adults demonstrate increased pupil size when performing tasks requiring cognitive inhibition. We invited 44 older and 44 younger adults to perform the Stroop task while their pupil dilation was recorded with eye-tracking glasses. The dependent variables were the number of accurate responses on the Stroop task as well as pupil size in the three conditions of the task (i.e., color naming, word reading, and the interference condition). The results demonstrated less accurate responses in the interference condition than in the color-naming or word-reading conditions, in both older and younger adults. Critically, larger pupil dilation was observed in the interference condition than in the color-naming and word-reading conditions, in both older and younger adults. This study demonstrates that pupil dilation responds to cognitive effort in normal aging, at least in the interference condition of the Stroop task.