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In the present work, a strategic multi-scenario EV ultra-fast charging station (CS) planning framework is designed to provide advantages to charging station owners, Distribution Network Operators, and EV owners. Locations of CSs are identified using zonal division and the Voltage Stability Index strategy. The number of chargers is determined using the Harris Hawk Optimization (HHO) technique while minimizing the installation, operational costs of CS, and energy loss costs considering all the power system security constraints. To ensure a realistic planning model, uncertainties in EV charging behavior and electricity prices are managed through the 2m-Point Estimate Method. This method produces multiple scenarios of uncertain parameters, which effectively represent the actual dataset, thereby facilitating comprehensive multi-scenario planning. This study incorporates annual EV and system load growth in a long-term planning model of ten years, ensuring the distribution network meets future demand for sustainable transportation infrastructure. The proposed research work is tested on a 33-bus distribution network and a 51-bus real Indian distribution network. To evaluate the financial and environmental benefits of the planning, a cost-benefit analysis in terms of the Return-on-Investment index and a carbon emission analysis are performed, respectively. Furthermore, to prove the efficacy of the HHO technique, the results are compared with several existing algorithms.

Bio adsorbents have received tremendous attention due to their eco-friendly, cheap and non-toxic nature. Recently, bio-adsorbent-based membranes have been frequently employed for water treatment. The work reports the preparation of a novel adsorbent membrane from hierarchical zeolite, polyvinyl alcohol, carboxymethyl cellulose and agar. The fabricated membrane was characterized spectroscopically and microscopically with several techniques such as XRD, UTM, TGA, optical microscopy and FT-IR, as well as contact-angle studies. The result showed that the hierarchical-zeolite-loaded membrane is superior in terms of thermal stability, mechanical properties and surface roughness. The fabricated membrane was investigated for its efficiency in the removal of Congo red dye in aqueous conditions. The influence of pH, temperature, contact period and the initial concentration of dye and zeolite loading on the adsorption process are also explored. The adsorption results highlighted the maximum sorption property of Congo red on agar/zeolite/carboxymethyl cellulose/polymer biomembrane was found to be higher (15.30 mg/g) than that of zeolite powder (6.4 mg/g). The adsorption isotherms and kinetic parameters were investigated via Langmuir, Freundlich and pseudo-first order, pseudo-second order and the intraparticle diffusion model, respectively. The adsorption isotherms fitted well for both considered isotherms, whereas pseudo-second order fitted well for kinetics. The thermodynamic parameter, ΔG at 303 K, 313 K and 323 K was −9.12, −3.16 and −0.49 KJ/mol, respectively. The work further explores the antibacterial efficacy of the prepared membrane and its reusability.

Karst springs are an essential source of private water supply for about 10% of households in Tennessee. However, the water quality of these springs is unmonitored and unregulated even though many springs are highly productive yet vulnerable to contamination. This study assesses spatial patterns in the water quality of roadside springs in northeast Tennessee. Karst spring water samples collected from 50 springs were assessed using EPA Standard methods for pathogens, nutrients, radon, and physicochemical parameters. From statistical and spatial analyses, all but five samples contained E. coli, while all samples contained fecal coliform. High E. coli was spatially clustered (Local Moran’s I = 0.177, pseudo p-value = 0.012) in regions of high agricultural land use, resulting in a fecal contamination hot spot on the border of Washington and Sullivan Counties, Tennessee. Radon concentrations exceeded the 300 pCi/L proposed MCL in 29 (58%) of springs, with one spring in Unicoi County exceeding 1000 pCi/L. A radon hot spot was identified in northern Washington County (Local Moran’s I = 0.160, pseudo p-value = 0.014). Cokriging of E. coli with land use and radon with distance to mapped fault did not improve interpolation models for either parameter. Other parameters, including nitrate, pH, and total dissolved solids, were within recommended ranges for drinking water. This snapshot of spring water quality status identifies areas of poor spring water quality of which spring water users in the region should be aware, and establishes the need for longitudinal sampling of spring water quality in contamination hot spots.

The effect of isospin-dependent nuclear forces on the inner crust of neutron stars is modeled within the framework of Quantum Molecular Dynamics (QMD). To successfully control the density dependence of the symmetry energy of neutron-star matter below nuclear saturation density, a mixed vector-isovector potential is introduced. This approach is inspired by the baryon density and isospin density-dependent repulsive Skyrme force of asymmetric nuclear matter. In isospin-asymmetric nuclear matter, the system shows nucleation, as nucleons are arranged into shapes resembling nuclear pasta. The dependence of clusterization in the system on the isospin properties is also explored by calculating two-point correlation functions. We show that, as compared to previous results that did not involve such mixed interaction terms, the energy symmetry slope L is successfully controlled by varying the corresponding coupling strength. Nevertheless, the effect of changing the slope of the nuclear symmetry energy L on the crust-core transition density does not seem significant. To the knowledge of the authors, this is the first implementation of such a coupling in a QMD model for isospin asymmetric matter, which is relevant to the inner crust of neutron and proto-neutron stars.

We recently assisted in a revolution in the realm of fluorescence microscopy triggered by the advent of super-resolution techniques that surpass the classic diffraction limit barrier. By providing optical images with nanometer resolution in the far field, super-resolution microscopy (SRM) is currently accelerating our understanding of the molecular organization of bio-specimens, bridging the gap between cellular observations and molecular structural knowledge, which was previously only accessible using electron microscopy. SRM mainly finds its roots in progress made in the control and manipulation of the optical properties of (single) fluorescent molecules. The flourishing development of novel fluorescent nanostructures has recently opened the possibility of associating super-resolution imaging strategies with nanomaterials’ design and applications. In this review article, we discuss some of the recent developments in the field of super-resolution imaging explicitly based on the use of nanomaterials. As an archetypal class of fluorescent nanomaterial, we mainly focus on single-walled carbon nanotubes (SWCNTs), which are photoluminescent emitters at near-infrared (NIR) wavelengths bearing great interest for biological imaging and for information optical transmission. Whether for fundamental applications in nanomaterial science or in biology, we show how super-resolution techniques can be applied to create nanoscale images “in”, “of” and “with” SWCNTs.

As failures of rolling bearings lead to major failures in rotating machines, recent vibration-based rolling bearing fault diagnosis techniques are focused on obtaining useful fault features from the huge collection of raw data. However, too many features reduce the classification accuracy and increase the computation time. This paper proposes an effective feature selection technique based on intrinsic dimension estimation of compressively sampled vibration signals. First, compressive sampling (CS) is used to get compressed measurements from the collected raw vibration signals. Then, a global dimension estimator, the geodesic minimal spanning tree (GMST), is employed to compute the minimal number of features needed to represent efficiently the compressively sampled signals. Finally, a feature selection process, combining the stochastic proximity embedding (SPE) and the neighbourhood component analysis (NCA), is used to select fewer features for bearing fault diagnosis. With regression analysis-based predictive modelling technique and the multinomial logistic regression (MLR) classifier, the selected features are assessed in two case studies of rolling bearings vibration signals under different working loads. The experimental results demonstrate that the proposed method can successfully select fewer features, with which the MLR-based trained model achieves high classification accuracy and significantly reduced computation times compared to published research.

Owing to the significant roles of adenosine triphosphate (ATP) in diverse biological processes, ATP level is used to research and evaluate the physiological processes of organisms. Aptamer-based biosensors have been widely reported to achieve this purpose, which are superior in their flexible biosensing mechanism, with a high sensitivity and good biocompatibility; however, the aptamers currently used for ATP detection have a poor ability to discriminate ATP from adenosine diphosphate (ADP) and adenosine monophosphate (AMP). Herein, an ATP-specific aptamer was screened and applied to construct a fluorescent aptasensor for ATP by using graphene oxide (GO) and strand displacement amplification (SDA). The fluorescence intensity of the sensor is linearly related to the concentration of ATP within 0.1 μM to 25 μM under optimal experimental conditions, and the detection limit is 33.85 nM. The biosensor exhibits a satisfactory specificity for ATP. Moreover, the experimental results indicate that the biosensor can be applied to determine the ATP in human serum. In conclusion, the screened aptamer and the biosensor have promising applications in the determination of the real energy charge level and ATP content in a complex biological system.

The Coefficients H technique (also called the H-technique), developed by Patarin circa 1991, is a tool used to obtain the upper bounds on distinguishing advantages. This tool is known to provide relatively simple and (in some cases) tight bound proofs in comparison to some other well-known tools, such as the game-playing technique and random systems methodology. In this systematization of knowledge (SoK) paper, we aim to provide a brief survey on the H-technique. The SoK is presented in four parts. First, we redevelop the necessary nomenclature and tools required to study the security of any symmetric-key design, especially in the H-technique setting. Second, we provide a full description of the H-technique and some related tools. Third, we present (simple) H-technique-based proofs for some popular symmetric-key designs, across different paradigms. Finally, we show that the H-technique can actually provide optimal bounds on distinguishing advantages.

Multiple lines of evidence suggest that a deficiency of Fragile X Mental Retardation Protein (FMRP) mediates dysfunction of the metabotropic glutamate receptor subtype 5 (mGluR5) in the pathogenesis of fragile X syndrome (FXS), the most commonly known single-gene cause of inherited intellectual disability (ID) and autism spectrum disorder (ASD). Nevertheless, animal and human studies regarding the link between FMRP and mGluR5 expression provide inconsistent or conflicting findings about the nature of those relationships. Since multiple clinical trials of glutamatergic agents in humans with FXS did not demonstrate the amelioration of the behavioral phenotype observed in animal models of FXS, we sought measure if mGluR5 expression is increased in men with FXS to form the basis for improved clinical trials. Unexpectedly marked reductions in mGluR5 expression were observed in cortical and subcortical regions in men with FXS. Reduced mGluR5 expression throughout the living brains of men with FXS provides a clue to examine FMRP and mGluR5 expression in FXS. In order to develop the findings of our previous study and to strengthen the objective tools for future clinical trials of glutamatergic agents in FXS, we sought to assess the possible value of measuring both FMRP levels and mGluR5 expression in men with FXS. We aimed to show the value of measurement of FMRP levels and mGluR5 expression for the diagnosis and treatment of individuals with FXS and related conditions. We administered 3-[18F]fluoro-5-(2-pyridinylethynyl)benzonitrile ([18F]FPEB), a specific mGluR5 radioligand for quantitative measurements of the density and the distribution of mGluR5s, to six men with the full mutation (FM) of FXS and to one man with allele size mosaicism for FXS (FXS-M). Utilizing the seven cortical and subcortical regions affected in neurodegenerative disorders as indicator variables, adjusted linear regression of mGluR5 expression and FMRP showed that mGluR5 expression was significantly reduced in the occipital cortex and the thalamus relative to baseline (anterior cingulate cortex) if FMRP levels are held constant (F(7,47) = 6.84, p < 0.001).These findings indicate the usefulness of cerebral mGluR5 expression measured by PET with [18F]FPEB and FMRP values in men with FXS and related conditions for assessments in community facilities within a hundred-mile radius of a production center with a cyclotron. These initial results of this pilot study advance our previous study regarding the measurement of mGluR5 expression by combining both FMRP levels and mGluR5 expression as tools for meaningful clinical trials of glutamatergic agents for men with FXS. We confirm the feasibility of this protocol as a valuable tool to measure FMRP levels and mGluR5 expression in clinical trials of individuals with FXS and related conditions and to provide the foundations to apply precision medicine to tailor treatment plans to the specific needs of individuals with FXS and related conditions.

The aetiology of non-malaria vector-borne diseases in malaria-endemic, forested, rural, and tribal-dominated areas of Dhalai, Tripura, in north-east India, was studied for the first time in the samples collected from malaria Rapid Diagnostic Kit negative febrile patients by door-to-door visits in the villages and primary health centres. Two hundred and sixty serum samples were tested for the Dengue NS1 antigen and the IgM antibodies of Dengue, Chikungunya, Scrub Typhus (ST), and Japanese Encephalitis (JE) during April 2019–March 2020. Fifteen Dengue, six JE, twelve Chikungunya, nine ST and three Leptospirosis, and mixed infections of three JE + Chikungunya, four Dengue + Chikungunya, three Dengue + JE + Chikungunya, one Dengue + Chikungunya + ST, and one Dengue + ST were found positive by IgM ELISA tests, and four for the Dengue NS1 antigen, all without any travel history. True prevalence values estimated for infections detected by Dengue IgM were 0.134 (95% CI: 0.08–0.2), Chikungunya were 0.084 (95% CI: 0.05–0.13), Scrub were 0.043 (95% CI: 0.01–0.09), and Japanese Encephalitis were 0.045 (95% CI: 0.02–0.09). Dengue and Chikungunya were associated significantly more with a younger age. There was a lack of a defined set of symptoms for any of the Dengue, Chikungunya, JE or ST infections, as indicated by the k-modes cluster analysis. Interestingly, most of these symptoms have an overlapping set with malaria; thereby, it becomes imperative that malaria and these non-malaria vector-borne disease diagnoses are made in a coordinated manner. Findings from this study call for advances in routine diagnostic procedures and the development of a protocol that can accommodate, currently, in practicing the rapid diagnosis of malaria and other vector-borne diseases, which is doable even in the resource-poor settings of rural hospitals and during community fever surveillance.

Ever since the introduction of fifth generation (5G) mobile communications, the mobile telecommunications industry has been debating whether 5G is an “evolution” or “revolution” from the previous legacy mobile networks, but now that 5G has been commercially available for the past few years, the research direction has recently shifted towards the upcoming generation of mobile communication system, known as the sixth generation (6G), which is expected to drastically provide significant and evolutionary, if not revolutionary, improvements in mobile networks. The promise of extremely high data rates (in terabits), artificial intelligence (AI), ultra-low latency, near-zero/low energy, and immense connected devices is expected to enhance the connectivity, sustainability, and trustworthiness and provide some new services, such as truly immersive “extended reality” (XR), high-fidelity mobile hologram, and a new generation of entertainment. Sixth generation and its vision are still under research and open for developers and researchers to establish and develop their directions to realize future 6G technology, which is expected to be ready as early as 2028. This paper reviews 6G mobile technology, including its vision, requirements, enabling technologies, and challenges. Meanwhile, a total of 11 communication technologies, including terahertz (THz) communication, visible light communication (VLC), multiple access, coding, cell-free massive multiple-input multiple-output (CF-mMIMO) zero-energy interface, intelligent reflecting surface (IRS), and infusion of AI/machine learning (ML) in wireless transmission techniques, are presented. Moreover, this paper compares 5G and 6G in terms of services, key technologies, and enabling communications techniques. Finally, it discusses the crucial future directions and technology developments in 6G.

Open circuit failure mode in insulated-gate bipolar transistors (IGBT) is one of the most common faults in modular multilevel converters (MMCs). Several techniques for MMC fault diagnosis based on threshold parameters have been proposed, but very few studies have considered artificial intelligence (AI) techniques. Using thresholds has the difficulty of selecting suitable threshold values for different operating conditions. In addition, very little attention has been paid to the importance of developing fast and accurate techniques for the real-life application of open-circuit failures of IGBT fault diagnosis. To achieve high classification accuracy and reduced computation time, a fault diagnosis framework with a combination of the AC-side three-phase current, and the upper and lower bridges’ currents of the MMCs to automatically classify health conditions of MMCs is proposed. In this framework, the principal component analysis (PCA) is used for feature extraction. Then, two classification algorithms—multiclass support vector machine (SVM) based on error-correcting output codes (ECOC) and multinomial logistic regression (MLR)—are used for classification. The effectiveness of the proposed framework is validated by a two-terminal simulation model of the MMC-high-voltage direct current (HVDC) transmission power system using PSCAD/EMTDC software. The simulation results demonstrate that the proposed framework is highly effective in diagnosing the health conditions of MMCs compared to recently published results.

Satellite tropospheric propagation studies strongly rely on beacon receiver measurements. We were interested in performing a measurement campaign to characterize rain attenuation statistics. In this article, we outline some of the characteristics and drawbacks one faces when trying to perform a radio wave satellite beacon propagation experiment at the Ka-band with low-cost measurement equipment. We used an affordable beacon receiver consisting of a commercial low-noise block down-converter, an outdoor dual-reflector antenna, and a software-defined radio unit. To measure rain attenuation events, we needed to work out where the reference signal level was at all times. However, as we did not have a radiometer to remove the impact of gases and clouds, since it is a very expensive device, we used a procedure that involved the subtraction of a stable and reliable reference level (template) from the raw received beacon level. This template was extracted from observations during non-rainy periods. The procedure implemented for extracting the template was based on the same data processing methodology used by other authors in this field. Here, we describe through specific examples the main characteristics of the templates extracted on non-rainy days, as well as the impact of some meteorological parameters and unavoidable, but small antenna pointing errors.

In view of the fact that vibration signals of rolling bearings are much contaminated by noise in the early failure period, this paper presents a new denoising SVD-VMD method by combining singular value decomposition (SVD) and variational mode decomposition (VMD). SVD is used to determine the structure of the underlying model, which is referred to as signal and noise subspaces, and VMD is used to decompose the original signal into several band-limited modes. Then the effective components are selected from these modes to reconstruct the denoised signal according to the difference spectrum (DS) of singular values and kurtosis values. Simulated signals and experimental signals of roller bearing faults have been analyzed using this proposed method and compared with SVD-DS. The results demonstrate that the proposed method can effectively retain the useful signals and denoise the bearing signals in extremely noisy backgrounds.

Motivated by the sidewise motions of dynein motors shown in experiments, we use a variant of the exclusion process to model the multistep dynamics of dyneins on a cylinder with open ends. Due to the varied step sizes of the particles in a quasi-two-dimensional topology, we observe the emergence of a novel phase diagram depending on the various load conditions. Under high-load conditions, our numerical findings yield results similar to the TASEP model with the presence of all three standard TASEP phases, namely the low-density (LD), high-density (HD), and maximal-current (MC) phases. However, for medium- to low-load conditions, for all chosen influx and outflux rates, we only observe the LD and HD phases, and the maximal-current phase disappears. Further, we also measure the dynamics for a single dynein particle which is logarithmically slower than a TASEP particle with a shorter waiting time. Our results also confirm experimental observations of the dwell time distribution: The dwell time distribution for dyneins is exponential in less crowded conditions, whereas a double exponential emerges under overcrowded conditions.

The development of personalised paediatric dosage forms using 3D printing technologies has gained significant interest over the last few years. In the current study extruded filaments of the highly bitter Diphenhydramine Hydrochloride (DPH) were fabricated by using suitable hydrophilic carries such as hydroxypropyl cellulose (Klucel ELFTM) and a non-ionic surfactant (Gelucire 48/16TM) combined with sweetener (Sucralose) and strawberry flavour grades. The thermoplastic filaments were used to print 3D fruit-chew designs by Fused Deposition Modelling (FDM) technology. Physicochemical characterisation confirmed the formation of glass solution where DPH was molecularly dispersed within the hydrophilic carriers. DPH was released rapidly from the 3D printed fruit-chew designs with >85% within the first 30 min. Trained panellists performed a full taste and sensory evaluation of the sweetener intensity and the strawberry aroma. The evaluation showed complete taste masking of the bitter DPH and revealed a synergistic effect of the sweetener and the strawberry flavour with enhanced sweet strawberry, fruity and aftertaste perception. The findings of the study can be used for the development of paediatric dosage forms with enhanced organoleptic properties, palatability and medication adherence.

Study of accretion onto wormholes is rather rare compared to that onto black holes. In this paper, we consider accretion flow of cosmological dark energy modeled by barotropic fluid onto the celebrated Ellis–Bronnikov wormhole (EBWH) built by Einstein minimally coupled scalar field ϕ, violating the null energy condition. The accreting fluid is assumed to be phantom, quintessence, dust and stiff matter. We begin by first pointing out a mathematical novelty showing how the EBWH can lead to the Schwarzschild black hole under a complex Wick rotation. Then, we analyze the profiles of fluid radial velocity, density and the rate of mass variation of the EBWH due to accretion and compare the profiles with those of the Schwarzschild black hole. We also analyze accretion to the massless EBWH that has zero ADM mass but has what we call nonzero Wheelerian mass (“mass without mass”), composed of the non-trivial scalar field, that shows gravitational effects. Our conclusion is that the mass of SBH due to phantom accretion decreases consistently with known results, while, in contrast, the mass of EBWH increases. Exactly an opposite behavior emerges for non-phantom accretion to these two objects. Accretion to massless EBWH (i.e., to nonzero Wheelerian mass) shares the same patterns as those of the massive EBWH; hence there is no way to distinguish massive and massless cases by means of accretion flow. The contrasting mass variations due to phantom accretion could be a reflection of the distinct topology of the central objects.

Fault detection and classification are two of the challenging tasks in Modular Multilevel Converters in High Voltage Direct Current (MMC-HVDC) systems. To directly classify the raw sensor data without certain feature extraction and classifier design, a long short-term memory (LSTM) neural network is proposed and used for seven states of the MMC-HVDC transmission power system simulated by Power Systems Computer Aided Design/Electromagnetic Transients including DC (PSCAD/EMTDC). It is observed that the LSTM method can detect faults with 100% accuracy and classify different faults as well as provide promising fault classification performance. Compared with a bidirectional LSTM (BiLSTM), the LSTM can get similar classification accuracy, requiring less training time and testing time. Compared with Convolutional Neural Networks (CNN) and AutoEncoder-based deep neural networks (AE-based DNN), the LSTM method can get better classification accuracy around the middle of the testing data proportion, but it needs more training time.

The aim of this study was to understand the effect of high shear homogenization (HSH) and ultrasonication (US) on the physicochemical properties of blank and olanzapine loaded nanostructured lipid carriers (NLCs) along with their drug loading potential and drug release profiles from formulated particles. NLCs were prepared with different ratios of Compritol and Miglyol as the solid and liquid lipids, respectively, under changing HSH and US times between 0 to 15 min. The surfactants (Poloxamer 188 (P188) and tween 80) and the drug content was kept constant in all formulations. The prepared NLCs were evaluated for particle size, polydispersity index, zeta potential, drug crystallinity and chemical interactions between lipids and OLZ. The in-vitro drug release was performed using dialysis tube method in phosphate buffer solution (PBS) at pH 7.4. The formulated NLCs were negatively charged, spherically shaped and monodisperse, with particle sizes ranging from 112 to 191 nm. There was a significant influence of US time on the preparation of NLCs in comparison to HSH, where a significant reduction in the mean particle diameter was seen after 5 min of sonication. An increase of Miglyol content in NLCs led to an increase in particle size. In general, application of US led to decrease in particle size after HSH but an increase in particle diameter of low Miglyol containing preparation was also observed with longer sonication time. OLZ was successfully encapsulated in the NLCs and a total release of 89% was achieved in 24 h in PBS at pH 7.4.

Twin-screw granulation (TSG) is a pharmaceutical process that has gained increased interest from the pharmaceutical industry for its potential for the development of oral dosage forms. The technology has evolved rapidly due to the flexibility of the equipment design, the selection of the process variables and the wide range of processed materials. Most importantly, TSG offers the benefits of both batch and continuous manufacturing for pharmaceutical products, accompanied by excellent process control, high product quality which can be achieved through the implementation of Quality by Design (QbD) approaches and the integration of Process Analytical Tools (PAT). Here, we present basic concepts of the various twin-screw granulation techniques and present in detail their advantages and disadvantages. In addition, we discuss the detail of the instrumentation used for TSG and how the critical processing paraments (CPP) affect the critical quality attributes (CQA) of the produced granules. Finally, we present recent advances in TSG continuous manufacturing including the paradigms of modelling of continuous granulation process, QbD approaches coupled with PAT monitoring for granule optimization and process understanding.

The main difficulties in constructing a viable early Universe bouncing model are: to bypass the observational and theoretical no-go theorem, to construct a stable non-singular bouncing phase, and perhaps, the major concern of it is to construct a stable attractor solution which can evade the Belinsky–Khalatnikov–Lifshitz (BKL) instability as well. In this article, in the homogeneous and isotropic background, we extensively study the stability analysis of the recently proposed viable non-minimal bouncing theory in the presence of an additional barotropic fluid and show that, the bouncing solution remains stable and can evade BKL instability for a wide range of the model parameter. We provide the expressions that explain the behavior of the Universe in the vicinity of the required fixed point i.e., the bouncing solution and compare our results with the minimal theory and show that ekpyrosis is the most stable solution in any scenario.

In face-to-face and online learning, emotions and emotional intelligence have an influence and play an essential role. Learners’ emotions are crucial for e-learning system because they promote or restrain the learning. Many researchers have investigated the impacts of emotions in enhancing and maximizing e-learning outcomes. Several machine learning and deep learning approaches have also been proposed to achieve this goal. All such approaches are suitable for an offline mode, where the data for emotion classification are stored and can be accessed infinitely. However, these offline mode approaches are inappropriate for real-time emotion classification when the data are coming in a continuous stream and data can be seen to the model at once only. We also need real-time responses according to the emotional state. For this, we propose a real-time emotion classification system (RECS)-based Logistic Regression (LR) trained in an online fashion using the Stochastic Gradient Descent (SGD) algorithm. The proposed RECS is capable of classifying emotions in real-time by training the model in an online fashion using an EEG signal stream. To validate the performance of RECS, we have used the DEAP data set, which is the most widely used benchmark data set for emotion classification. The results show that the proposed approach can effectively classify emotions in real-time from the EEG data stream, which achieved a better accuracy and F1-score than other offline and online approaches. The developed real-time emotion classification system is analyzed in an e-learning context scenario.

Although feed cost is the greatest concern in aquaculture, the inclusion of carbohydrates in the fish diet, and their assimilation, are still not well understood in aquaculture species. We identified molecular events that occur due to the inclusion of high carbohydrate levels in the diets of genetically improved ‘Jayanti rohu’ Labeo rohita. To reveal transcriptional changes in the liver of rohu, a feeding experiment was conducted with three doses of gelatinized starch (20% (control), 40%, and 60%). Transcriptome sequencing revealed totals of 15,232 (4464 up- and 4343 down-regulated) and 15,360 (4478 up- and 4171 down-regulated) differentially expressed genes. Up-regulated transcripts associated with glucose metabolisms, such as hexokinase, PHK, glycogen synthase and PGK, were found in fish fed diets with high starch levels. Interestingly, a de novo lipogenesis mechanism was found to be enriched in the livers of treated fish due to up-regulated transcripts such as FAS, ACCα, and PPARγ. The insulin signaling pathways with enriched PPAR and mTOR were identified by Kyoto Encyclopedia of Genes and Genome (KEGG) as a result of high carbohydrates. This work revealed for the first time the atypical regulation transcripts associated with glucose metabolism and lipogenesis in the livers of Jayanti rohu due to the inclusion of high carbohydrate levels in the diet. This study also encourages the exploration of early nutritional programming for enhancing glucose efficiency in carp species, for sustainable and cost-effective aquaculture production.

System performance and efficiency depends on the stability criteria. The lower limb prosthetic model design requires some prerequisites such as hardware design functionality and compatibility of the building block materials. Effective implementation of mathematical model simulation symmetry towards the achievement of hardware design is the focus of the present work. Different postures of lower limb have been considered in this paper to be analyzed for artificial system design of lower limb movement. The generated polynomial equations of the sitting and standing positions of the normal limb are represented with overall system transfer function. The behavioral analysis of the lower limb model shows the nonlinear nature. The Euler-Lagrange method is utilized to describe the nonlinearity in the field of forward dynamics of the artificial system. The stability factor through phase portrait analysis is checked with respect to nonlinear system characteristics of the lower limb. The asymptotic stability has been achieved utilizing the most applicable Lyapunov method for nonlinear systems. The stability checking of the proposed artificial lower extremity is the newer approach needed to take decisions on output implementation in the system design.

The production and N-glycosylation of recombinant human butyrylcholinesterase (BChE), a model highly glycosylated therapeutic protein, in a transgenic rice cell suspension culture treated with kifunensine, a strong α-mannosidase I inhibitor, was studied in a 5 L bioreactor. A media exchange was performed at day 7 of cultivation by removing spent sugar-rich medium (NB+S) and adding fresh sugar-free (NB-S) medium to induce the rice α-amylase 3D (RAmy3D) promoter to produce rice recombinant human BChE (rrBChE). Using a 1.25X-concentrated sugar-free medium together with an 80% reduced working volume during the media exchange led to a total active rrBChE production level of 79 ± 2 µg (g FW)−1 or 7.5 ± 0.4 mg L−1 in the presence of kifunensine, which was 1.5-times higher than our previous bioreactor runs using normal sugar-free (NB-S) media with no kifunensine treatment. Importantly, the amount of secreted active rrBChE in culture medium was enhanced in the presence of kifunensine, comprising 44% of the total active rrBChE at day 5 following induction. Coomassie-stained SDS-PAGE gel and Western blot analyses revealed different electrophoretic migration of purified rrBChE bands with and without kifunensine treatment, which was attributed to different N-glycoforms. N-Glycosylation analysis showed substantially increased oligomannose glycans (Man5/6/7/8) in rrBChE treated with kifunensine compared to controls. However, the mass-transfer limitation of kifunensine was likely the major reason for incomplete inhibition of α-mannosidase I in this bioreactor study.

Numerous natural and synthetic clay minerals have proven to be excellent drug carriers for high drug-loaded and sustained release formulations due to their considerable ion exchange, adsorption, and swelling capacities. Moreover, the synthetic smectite clays have added advantages in terms of compositional purity and controlled cation exchange capacity in comparison to natural clays. This study involves the intercalation of theophylline (TP) in a synthetic clay, Laponite® (LP), followed by the inclusion of the resulting intercalates into sodium alginate (SA) beads to achieve pH-controlled drug release. Maximum intercalated drug incorporation of 68 mg/g was obtained by ion exchange at pH 1.2 and confirmed by an increase in basal spacing of the clay from 12.9 to 15.5 Å. TP release from the binary LP-TP intercalates in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) was found to be 40% and 70%, respectively. LP-TP particles were also incorporated in an SA matrix via polymer crosslinking using CaCl2(aq) to improve the pH selective release. The ternary polymer-clay-drug composite particles effectively prevented the release of TP at low pH in SGF and resulted in sustained release in SIF, with 40% dissolution within 120 min.

In this paper, we explore learning methods to improve the performance of the open-circuit fault diagnosis of modular multilevel converters (MMCs). Two deep learning methods, namely, convolutional neural networks (CNN) and auto encoder based deep neural networks (AE-based DNN), as well as stand-alone SoftMax classifier are explored for the detection and classification of faults of MMC-based high voltage direct current converter (MMC-HVDC). Only AC-side three-phase current and the upper and lower bridges’ currents of the MMCs are used directly in our proposed approaches without any explicit feature extraction or feature subset selection. The two-terminal MMC-HVDC system is implemented in Power Systems Computer-Aided Design/Electromagnetic Transients including DC (PSCAD/EMTDC) to verify and compare our methods. The simulation results indicate CNN, AE-based DNN, and SoftMax classifier can detect and classify faults with high detection accuracy and classification accuracy. Compared with CNN and AE-based DNN, the SoftMax classifier performed better in detection and classification accuracy as well as testing speed. The detection accuracy of AE-based DNN is a little better than CNN, while CNN needs less training time than the AE-based DNN and SoftMax classifier.

A carbon nano-onions (CNOs)–polystyrene (PS) composite-based Pt electrode was used for the voltammetric detection of cysteine (Cys) and methionine (Met). The electrochemical behaviors of Cys and Met were analyzed with Cyclic Voltammetry (CV) and Differential Pulse (DP) Voltammetry at different pHs. The modified CNOs–PS/Pt electrode shows an oxidation peak at +0.4V for Cys and +0.8V for Met, respectively. Admirable sensitivity, easy fabrication, and reproducible performance make the proposed electrode well functional and useful for the qualitative and quantitative detection of sulphur-containing amino acids.

The current COVID-19 pandemic is caused by the novel coronavirus SARS-CoV-2. The virus causes severe respiratory symptoms which manifest disproportionately in the elderly. Currently, there are over 6.5 million cases and 380,000 deaths reported. Given the current severity of the outbreak, there is a great need for antiviral therapies and vaccines to treat and prevent COVID-19. In this review, we provide an overview of SARS-CoV-2 and discuss the emerging therapies and vaccines that show promise in combating COVID-19. We also highlight potential viral targets that could be exploited by researchers and drug manufacturers.

With buildings being responsible for nearly a quarter of global greenhouse gas emissions, intensive building decarbonization programs are in place worldwide, with unintended consequences for historic buildings. To this end, national and international guidance on energy efficiency for historic buildings advocate for the adoption of a ‘whole house approach’ that integrates heritage values in energy efficiency plans. Most guidance, though, relies on non-evidence based, pre-assumptions of residents’ heritage values. And yet, unless we understand how and why residents negotiate their decisions between energy efficiency, thermal comfort, and heritage conservation, such guidance will not be applicable. Despite the urgency to decarbonize the building stock, research on how inhabitants of old buildings make such decisions is extremely limited. It is also case-study specific, often lacking the required depth. To address this gap, this paper offers the first international, in-depth study on the topic. It does so through a rigorous double-coded, thematic analysis of 59 in-depth semi-structured interviews (totaling 206,771 words) carried out in Greece, Mexico, and the UK. The thematic analysis is combined with system dynamic analysis, essential for unveiling what parameters affect inhabitants’ decisions over time. Drawing on theories on the dynamics of social practices, we conclude that the process of decision-making on energy efficiency, thermal comfort improvement, and heritage conservation is a socio-cultural, dynamic practice, the change and continuation of which depends on how the following elements are connected or disconnected: materials (e.g., original features), competencies (e.g., restoration skills), resources (e.g., costs), values, space/environment (e.g., natural light), senses (e.g., thermal comfort), and time (e.g., years living in the house). The connection or disconnection of those elements will depend on (a) the nature of the context (e.g., rural, urban, conservation area); (b) the listing status; (c) age and construction materials of building; (d) local climate; and (e) ownership status.

This study examines the relationship between gully erosion in channels, sidewalls, and interfluves, and precipitation parameters (duration, total accumulation, average intensity, and maximum intensity) annually and seasonally to determine seasonal drivers for precipitation-related erosion. Ordinary Least Square regression models of erosion using precipitation and antecedent precipitation at weekly lags of up to twelve weeks were developed for three erosion variables for each of three geomorphic areas: channels, interfluves, and sidewalls (nine models in total). Erosion was most pronounced in winter months, followed by spring, indicating the influence of high-intensity precipitation from frontal systems and repeated freeze-thaw cycles in winter; erosion in summer was driven by high-intensity precipitation from convectional storms. Annually, duration was the most important driver for erosion, however, during winter and summer months, precipitation intensity was dominant. Seasonal models retained average and maximum precipitation as drivers for erosion in winter months (dominated by frontal systems), and retained maximum precipitation intensity as a driver for erosion in summer months (dominated by convectional storms). In channels, precipitation duration was the dominant driver for erosion due to runoff-related erosion, while in sidewalls and interfluves intensity parameters were equally important as duration, likely related to rain splash erosion. These results show that the character of precipitation, which varies seasonally, is an important driver for gully erosion and that studies of precipitation-driven erosion should consider partitioning data by season to identify these drivers.

Development requires the careful orchestration of several biological events in order to create any structure and, eventually, to build an entire organism. On the other hand, the fate transformation of terminally differentiated cells is a consequence of erroneous development, and ultimately leads to cancer. In this review, we elaborate how development and cancer share several biological processes, including molecular controls. Transcription factors (TF) are at the helm of both these processes, among many others, and are evolutionarily conserved, ranging from yeast to humans. Here, we discuss four families of TFs that play a pivotal role and have been studied extensively in both embryonic development and cancer—high mobility group box (HMG), GATA, paired box (PAX) and basic helix-loop-helix (bHLH) in the context of their role in development, cancer, and their conservation across several species. Finally, we review TFs as possible therapeutic targets for cancer and reflect on the importance of natural resistance against cancer in certain organisms, yielding knowledge regarding TF function and cancer biology.

The authors wish to make the following corrections to this paper [...]

Ultrasonic Guided-wave (UGW) testing of pipelines allows long-range assessment of pipe integrity from a single point of inspection. This technology uses a number of arrays of transducers separated by a distance from each other to generate a single axisymmetric (torsional) wave mode. The location of anomalies in the pipe is determined by inspectors using the received signal. Guided-waves are multimodal and dispersive. In practical tests, nonaxisymmetric waves are also received due to the nonideal testing conditions, such as presence of variable transfer function of transducers. These waves are considered as the main source of noise in the guided-wave inspection of pipelines. In this paper, we propose a method to exploit the differences in the power spectrum of the torsional wave and flexural waves, in order to detect the torsional wave, leading to the defect location. The method is based on a sliding moving window, where in each iteration the signals are normalised and their power spectra are calculated. Each power spectrum is compared with the previously known spectrum of excitation sequence. Five binary conditions are defined; all of these need to be met in order for a window to be marked as defect signal. This method is validated using a synthesised test case generated by a Finite Element Model (FEM) as well as real test data gathered from laboratory trials. In laboratory trials, three different pipes with defects sizes of 4%, 3% and 2% cross-sectional area (CSA) material loss were evaluated. In order to find the optimum frequency, the varying excitation frequency of 30 to 50 kHz (in steps of 2 kHz) were used. The results demonstrate the capability of this algorithm in detecting torsional waves with low signal-to-noise ratio (SNR) without requiring any change in the excitation sequence. This can help inspectors by validating the frequency response of the received sequence and give more confidence in the detection of defects in guided-wave testing of pipelines.

N-glycosylation has been shown to affect the pharmacokinetic properties of several classes of biologics, including monoclonal antibodies, blood factors, and lysosomal enzymes. In the last two decades, N-glycan engineering has been employed to achieve a N-glycosylation profile that is either more consistent or aligned with a specific improved activity (i.e., effector function or serum half-life). In particular, attention has focused on engineering processes in vivo or in vitro to alter the structure of the N-glycosylation of the Fc region of anti-cancer monoclonal antibodies in order to increase antibody-dependent cell-mediated cytotoxicity (ADCC). Here, we applied the mannosidase I inhibitor kifunensine to the Nicotiana benthamiana transient expression platform to produce an afucosylated anti-CD20 antibody (rituximab). We determined the optimal concentration of kifunensine used in the infiltration solution, 0.375 µM, which was sufficient to produce exclusively oligomannose glycoforms, at a concentration 14 times lower than previously published levels. The resulting afucosylated rituximab revealed a 14-fold increase in ADCC activity targeting the lymphoma cell line Wil2-S when compared with rituximab produced in the absence of kifunensine. When applied to the cost-effective and scalable N. benthamiana transient expression platform, the use of kifunensine allows simple in-process glycan engineering without the need for transgenic hosts.

Ultrasonic guided wave (UGW) testing of pipelines allows long range assessments of pipe integrity from a single point of inspection. This technology uses a number of arrays of transducers, linearly placed apart from each other to generate a single axisymmetric wave mode. The general propagation routine of the device results in a single time domain signal, which is then used by the inspectors to detect the axisymmetric wave for any defect location. Nonetheless, due to inherited characteristics of the UGW and non-ideal testing conditions, non-axisymmetric (flexural) waves will be transmitted and received in the tests. This adds to the complexity of results’ interpretation. In this paper, we implement an adaptive leaky normalized least mean square (NLMS) filter for reducing the effect of non-axisymmetric waves and enhancement of axisymmetric waves. In this approach, no modification in the device hardware is required. This method is validated using the synthesized signal generated by a finite element model (FEM) and real test data gathered from laboratory trials. In laboratory trials, six different sizes of defects with cross-sectional area (CSA) material loss of 8% to 3% (steps of 1%) were tested. To find the optimum frequency, several excitation frequencies in the region of 30–50 kHz (steps of 2 kHz) were used. Furthermore, two sets of parameters were used for the adaptive filter wherein the first set of tests the optimum parameters were set to the FEM test case and, in the second set of tests, the data from the pipe with 4% CSA defect was used. The results demonstrated the capability of this algorithm for enhancing a defect’s signal-to-noise ratio (SNR).

Functional ZnO nanostructured surfaces are important in a wide range of applications. Here we report the simple fabrication of ZnO surface structures at near room temperature with morphology resembling that of sea urchins, with densely packed, μ m-long, tapered nanoneedles radiating from the urchin center. The ZnO urchin structures were successfully formed on several different substrates with high surface density and coverage, including silicon (Si), glass, polydimethylsiloxane (PDMS), and copper (Cu) sheets, as well as Si seeded with ZnO nanocrystals. Time-resolved SEM revealed growth kinetics of the ZnO nanostructures on Si, capturing the emergence of “infant„ urchins at the early growth stage and subsequent progressive increases in the urchin nanoneedle length and density, whilst the spiky nanoneedle morphology was retained throughout the growth. ε -Zn(OH)2 orthorhombic crystals were also observed alongside the urchins. The crystal structures of the nanostructures at different growth times were confirmed by synchrotron X-ray diffraction measurements. On seeded Si substrates, a two-stage growth mechanism was identified, with a primary growth step of vertically aligned ZnO nanoneedle arrays preceding the secondary growth of the urchins atop the nanoneedle array. The antibacterial, anti-reflective, and wetting functionality of the ZnO urchins—with spiky nanoneedles and at high surface density—on Si substrates was demonstrated. First, bacteria colonization was found to be suppressed on the surface after 24 h incubation in gram-negative Escherichia coli (E. coli) culture, in contrast to control substrates (bare Si and Si sputtered with a 20 nm ZnO thin film). Secondly, the ZnO urchin surface, exhibiting superhydrophilic property with a water contact angle ~ 0 ° , could be rendered superhydrophobic with a simple silanization step, characterized by an apparent water contact angle θ of 159° ± 1.4° and contact angle hysteresis Δ θ < 7°. The dynamic superhydrophobicity of the surface was demonstrated by the bouncing-off of a falling 10 μ L water droplet, with a contact time of 15.3 milliseconds (ms), captured using a high-speed camera. Thirdly, it was shown that the presence of dense spiky ZnO nanoneedles and urchins on the seeded Si substrate exhibited a reflectance R < 1% over the wavelength range λ = 200⁻800 nm. The ZnO urchins with a unique morphology fabricated via a simple route at room temperature, and readily implementable on different substrates, may be further exploited for multifunctional surfaces and product formulations.

In the past decade, guided-wave testing has attracted the attention of the non-destructive testing industry for pipeline inspections. This technology enables the long-range assessment of pipelines’ integrity, which significantly reduces the expenditure of testing in terms of cost and time. Guided-wave testing collars consist of several linearly placed arrays of transducers around the circumference of the pipe, which are called rings, and can generate unidirectional axisymmetric elastic waves. The current propagation routine of the device generates a single time-domain signal by doing a phase-delayed summation of each array element. The segments where the energy of the signal is above the local noise region are reported as anomalies by the inspectors. Nonetheless, the main goal of guided-wave inspection is the detection of axisymmetric waves generated by the features within the pipes. In this paper, instead of processing a single signal obtained from the general propagation routine, we propose to process signals that are directly obtained from all of the array elements. We designed an axisymmetric wave detection algorithm, which is validated by laboratory trials on real-pipe data with two defects on different locations with varying cross-sectional area (CSA) sizes of 2% and 3% for the first defect, and 4% and 5% for the second defect. The results enabled the detection of defects with low signal-to-noise ratios (SNR), which were almost buried in the noise level. These results are reported with regard to the three different developed methods with varying excitation frequencies of 30 kHz, 34 kHz, and 37 kHz. The tests demonstrated the advantage of using the information received from all of the elements rather than a single signal.

A better understanding of mechanistic insights into genes and enzymes implicated in rare diseases provide a unique opportunity for orphan drug development. Advances made in identification of synthetic lethal relationships between rare disorder genes with oncogenes and tumor suppressor genes have brought in new anticancer therapeutic opportunities. Additionally, the rapid development of small molecule inhibitors against enzymes that participate in DNA damage response and repair has been a successful strategy for targeted cancer therapeutics. Here, we discuss the recent advances in our understanding of how many rare disease genes participate in promoting genome stability. We also summarize the latest developments in exploiting rare diseases to uncover new biological mechanisms and identify new synthetic lethal interactions for anticancer drug discovery that are in various stages of preclinical and clinical studies.

Aptamers have been widely used as recognition elements for biosensor construction, especially in the detection of proteins or small molecule targets, and regarded as promising alternatives for antibodies in bioassay areas. In this review, we present an overview of reported design strategies for the fabrication of biosensors and classify them into four basic modes: target-induced structure switching mode, sandwich or sandwich-like mode, target-induced dissociation/displacement mode and competitive replacement mode. In view of the unprecedented advantages brought about by aptamers and smart design strategies, aptamer-based biosensors are expected to be one of the most promising devices in bioassay related applications.

Transient recombinant protein production is a promising alternative to stable transgenic systems, particularly for emergency situations in which rapid production of novel therapeutics is needed. In plants, Agrobacterium tumefaciens can be used as a gene delivery vector for transient expression. A potential barrier for plant-based production of human therapeutics is that different glycosylation patterns are found on plant and mammalian proteins. Since glycosylation can affect the efficacy, safety and stability of a therapeutic protein, methods to control glycan structures and distributions in plant-based systems would be beneficial. In these studies, we performed Agrobacterium-mediated transient expression in glycoengineered plant cell suspension cultures. To reduce the presence of plant-specific glycans on the product, we generated and characterized cell suspension cultures from β-1,2-xylosyltransferase and α-1,3-fucosyltransferase knockdown Nicotiana benthamiana. An anthrax decoy fusion protein was transiently produced in these glycoengineered plant cell suspension cultures through co-culture with genetically engineered Agrobacterium. The mass ratio of Agrobacterium to plant cells used was shown to impact recombinant protein expression levels. N-glycosylation analysis on the anthrax decoy fusion protein produced in glycoengineered N. benthamiana showed a dramatic reduction in plant-specific N-glycans. Overall, the results presented here demonstrate the feasibility of a simple, rapid and scalable process for transient production of recombinant proteins without plant-specific glycans in a glycoengineered plant cell culture host.

Kifunensine, a potent and selective inhibitor of class I α-mannosidases, prevents α-mannosidases I from trimming mannose residues on glycoproteins, thus resulting in oligomannose-type glycans. We report for the first time that through one-time vacuum infiltration of kifunensine in plant tissue, N-linked glycosylation of a recombinant protein transiently produced in whole-plants shifted completely from complex-type to oligomannose-type. Fc-fused capillary morphogenesis protein 2 (CMG2-Fc) containing one N-glycosylation site on the Fc domain, produced in Nicotiana benthamiana whole plants, served as a model protein. The CMG2-Fc fusion protein was produced transiently through vacuum agroinfiltration, with and without kifunensine at a concentration of 5.4 µM in the agroinfiltration suspension. The CMG2-Fc N-glycan profile was determined using LC-MS/MS with a targeted dynamic multiple reaction monitoring (MRM) method. The CMG2-Fc expression level in the infiltrated plant tissue and the percentage of oligomannose-type N-glycans for kifunensine treated plants was 874 mg/kg leaf fresh weight (FW) and 98.2%, respectively, compared to 717 mg/kg leaf FW and 2.3% for untreated plants. Oligomannose glycans are amenable to in vitro enzymatic modification to produce more human-like N-glycan structures that are preferred for the production of HIV-1 viral vaccine and certain monoclonal antibodies. This method allows glycan modifications using a bioprocessing approach without compromising protein yield or modification of the primary sequence, and could be expanded to other small molecule inhibitors of glycan-processing enzymes. For recombinant protein targeted for secretion, kifunensine treatment allows collection of glycoform-modified target protein from apoplast wash fluid (AWF) with minimal plant-specific complex N-glycan at higher starting purity and concentration than in whole-leaf extract, thus simplifying the downstream processing.

Gully erosion is a global problem that degrades land and reduces its utility for agriculture, development, and water quality. Quantification of sediment yield and control of sediment sources is essential for environmental protection. Five methods to evaluate erosion rates and sediment yield on an east Tennessee, USA, hillslope were compared: (1) physical measurement by removal of accumulated sediment using 10 L buckets; (2) repeated measurement of erosion pins in gully (erosional) and delta (depositional) areas; (3) geometric model using a combination trapezoidal prism-cylinder segment; (4) geometric model using a series of trapezoidal pyramids; and (5) 3D solid computer modeling. The 3D solid model created in SolidWorks was selected as the reference model and all other methods overestimated sediment yield to varying degrees. Erosion pin methods overestimated sediment yield by 368% in deltas and 123% in gullies. Volumetric measurement of sediment using buckets overestimated sediment yield by 160% due to void space in the buckets. The trapezoidal prism-cylinder segment model overestimated sediment yield by 66% and the trapezoidal pyramids method overestimated sediment yield by 5.7%. For estimation of sediment trapped behind an elliptical or circular silt fence dam, use of the trapezoidal pyramid method provides a good approximation comparable to 3D solid computer modeling.

Square wave voltammetry is used in this work to detect human islet amyloid polypeptide (hIAPP) by using the oxidized signal of the tyrosine residue in hIAPP. A detection limit of 1×10-6 M for hIAPP has been obtained. A kinetic study of the aggregation process has been carried out according to the relationship between the anodic peak current in the square wave voltammograms of hIAPP and the incubation period. The results show that the nucleation starts in the first hour of incubation and then, during the next two hours, aggregation may occur rapidly. hIAPP can therefore be monitored with a label-free electrochemical method with low detection limit and high sensitivity. This electrochemical method can be also utilized to study the kinetics of hIAPP aggregation, and it may be also employed to study the conformational changes of the polypeptide.

Anthrax toxin receptor-mediated drug development for blocking anthrax toxin action has received much attention in recent decades. In this study, we produced a secreted anthrax decoy fusion protein comprised of a portion of the human capillary morphogenesis gene-2 (CMG2) protein fused via a linker to the fragment crystallizable (Fc) domain of human immunoglobulin G1 in Nicotiana benthamiana plants using a transient expression system. Using the Cauliflower Mosaic Virus (CaMV) 35S promoter and co-expression with the p19 gene silencing suppressor, we were able to achieve a high level of recombinant CMG2-Fc-Apo (rCMG2-Fc-Apo) protein accumulation. Production kinetics were observed up to eight days post-infiltration, and maximum production of 826 mg/kg fresh leaf weight was observed on day six. Protein A affinity chromatography purification of the rCMG2-Fc-Apo protein from whole leaf extract and apoplast wash fluid showed the homodimeric form under non-reducing gel electrophoresis and mass spectrometry analysis confirmed the molecular integrity of the secreted protein. The N-glycosylation pattern of purified rCMG2-Fc-Apo protein was analysed; the major portion of N-glycans consists of complex type structures in both protein samples. The most abundant (>50%) N-glycan structure was GlcNAc2(Xyl)Man3(Fuc)GlcNAc2 in rCMG2-Fc-Apo recovered from whole leaf extract and apoplast wash fluid. High mannose N-glycan structures were not detected in the apoplast wash fluid preparation, which confirmed the protein secretion. Altogether, these findings demonstrate that high-level production of rCMG2-Fc-Apo can be achieved by transient production in Nicotiana benthamiana plants with apoplast targeting.

The addition of alloying elements is a crucial factor in improving the mechanical properties of pure copper, particularly in terms of enhancing its yield strength and hardness. This study examines the influence of scandium additions (up to 0.27 wt.%) on low-alloyed copper. Following the casting and solution-annealing processes, the alloys were quenched in water to maintain a supersaturated state. The mechanical properties were evaluated by tensile tests to measure the yield strength and the dynamic resonance method to determine the modulus of rigidity. Additionally, X-ray diffraction was utilized to analyze changes in lattice parameters, elucidating the structural modifications induced by scandium. This study dissects the parelastic and dielastic effects underlying the solid solution hardening mechanism, providing insights into how scandium alters copper’s mechanical properties. The findings align with the solid solution hardening theories proposed by Fleischer and Labusch, providing a comprehensive understanding of the observed phenomena.

Zinc oxide nanomaterials have been the cynosure of this decade because of their immense potential in different biomedical applications. It includes their usage in the prognosis and treatment of different infectious and cellular diseases, owing to their peculiar physiochemical properties such as variable shape, size, and surface charge etc. Increasing demand and usage of the ZnO nanomaterials raise concerns about their cellular and molecular toxicity and their biocompatibility with human cells. This review comprehensively details their physiochemical properties for usage in biomedical applications. Furthermore, the toxicological concerns of ZnO nanomaterials with different types of cellular systems have been reviewed. Moreover, the biomedical and biocompatible efficacy of ZnO nanomaterials for cancer specific pathways has been discussed. This review offers insights into the current scenario of ZnO nanomaterials usage and signifies their potential future extension usage on different types of biomedical and environmental applications.

Rhipicephalus microplus poses a substantial threat to livestock health and agricultural economies worldwide. Its remarkable adaptability to diverse environments and hosts is a testament to its extensive genetic diversity. This review delves into the genetic diversity of R. microplus, employing three pivotal genetic markers: the cytochrome c oxidase I (COX1) gene, ribosomal genes, and microsatellites. The COX1 gene, a crucial tool for genetic characterization and phylogenetic clustering, provides insights into the adaptability of ticks. Ribosomal genes, such as internal transcribed spacer regions (ITS-1 and2) as well as 18S and 28S, are routinely utilized for species differentiation. However, their use is limited due to indels (insertions and deletions). Microsatellites and minisatellites, known for their high polymorphism, have been successfully employed to study populations and genetic diversity across various tick species. Despite their effectiveness, challenges such as null alleles and marker variations warrant careful consideration. Bm86, a well-studied vaccine candidate, exhibits substantial genetic diversity. This diversity directly influences vaccine efficacy, posing challenges for developing a universally effective Bm86-based vaccine. Moreover, the review emphasizes the prevalence of genes associated with synthetic pyrethroid resistance. Identifying single nucleotide polymorphisms in the acaricide-resistant genes of R. microplus has facilitated the development of molecular markers for detecting and monitoring resistance against synthetic pyrethroids. However, mutations in sodium channels, the target site for synthetic pyrethroid, correlate well with the resistance status of R. microplus, which is not the case with other acaricide target genes. This study underscores the importance of understanding genetic diversity in developing effective tick management strategies. The choice of genetic marker should be tailored based on the level of taxonomic resolution and the group of ticks under investigation. A holistic approach combining multiple markers and integrating additional molecular and morphological data may offer a more comprehensive understanding of tick diversity and relationships. This research has far-reaching implications in formulating breeding programs and the development of vaccine against ticks and tick-borne diseases (TTBDs) as well as strategies for the management of resistant ticks.

Crassostrea is the most farmed oyster genus worldwide and has significant economic and social impacts with environmental benefits. Hatchery oyster seed production is a highly costly phase, and a fluidized nursery system can help reduce this cost and reduce seed production time. The present study evaluated the survival and growth of two oyster species (Crassostrea gasar and Crassostrea gigas) in a fluidized bed bottle nursery system. With C. gasar, two experiments were performed; one tested three stocking densities and the other three bialgae diets. With C. gigas, one experiment with a bialgae and monoalgae in an initial bottle occupation of 8.8% produced more seeds per bottle, but an initial bottle occupation of 2.2% produced bigger seeds. Also, the experiment with C. gasar and with C. gigas tested diets did not affect seed survival, but the diets with bialgae I. galbana and N. oculate promoted more seed growth. The fluidized bed bottle nursery system developed for this study was adequate for the seeds of the oysters C. gasar and C. gigas in the nursery phase.

Wind turbines are a crucial part of renewable energy generation, and their reliable and efficient operation is paramount in ensuring clean energy availability. However, the bearings in wind turbines are subjected to high stress and loads, resulting in faults that can lead to costly downtime and repairs. Fault detection in real time is critical to minimize downtime and reduce maintenance costs. In this work, a simple neural network model was designed and implemented on a Raspberry Pi for the real-time detection of wind turbine bearing faults. The model was trained to accurately identify complex patterns in raw sensor data of healthy and faulty bearings. By splitting the data into smaller segments, the model can quickly analyze each segment and generate predictions at high speed. Additionally, simplified algorithms were developed to analyze the segments with minimum latency. The proposed system can efficiently process the sensor data and performs rapid analysis and prediction within 0.06 milliseconds per data segment. The experimental results demonstrate that the model achieves a 99.8% accuracy in detecting wind turbine bearing faults within milliseconds of their occurrence. The model’s ability to generate real-time predictions and to provide an overall assessment of the bearing’s health can significantly reduce maintenance costs and increase the availability and efficiency of wind turbines.