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The objective of this study was the develop of fortified cookies enriched with oats flour and bitter gourd powder and monitoring the effects of these enrichments on the physicochemical, antioxidant, antimicrobial, and sensory attributes. This study was subjected to four treatments: control (0% oats flour and bitter gourd powder), T1 (10% oats flour), T2 (3% bitter gourd powder), and T3 (7% oats flour and 3% bitter gourd powder). Various physical properties of the cookies, including weight, thickness, diameter, spread ratio, baking loss, pH, and color values (L*, a*, and b*), were measured. Proximate analysis revealed moisture (4.23–4.70%), ash (1.17–1.67%), fat (13.62–15.09%), crude protein (7.02–7.36%), carbohydrate (71.78–72.97%), energy (442.62–452.40 kcal), and crude fiber (8.02–3.33%). Mineral contents included Na (787–754 mg/100g), Ca (873–435 mg/100g), and Zn (66.7–58.8 mg/100g). Additionally, DPPH free radical scavenging activity ranged from 13.14 to 75.51%, while TBARS activity varied from 0.78 to 1.33 mg MDA/kg. T2 cookies exhibited the highest antimicrobial activity, with control cookies showing the lowest. The 5-point hedonic scale indicated that T2 cookies had lower overall acceptability, while T3 cookies were better received. In conclusion, the study suggests that fortified cookies have a more significant impact than regular or control cookies. [ABSTRACT FROM AUTHOR]

Background: Cheilanthes tenuifolia (Burm.f.), commonly known as the Sword Fern or Narrow‐leaved Cloak Fern, is a little evergreen fern that belongs to the Pteridaceae family and is abundant in various bioactive compounds exerting promising medicinal properties. The current study is designed to evaluate in vivo analgesic and antidiarrheal activity of the methanol leaf extract of C. tenuifolia (MCT). Methods: For this purpose, Swiss albino mice were used to investigate the analgesic and antidiarrheal properties using acetic acid‐induced writhing and castor oil‐induced diarrhea methods, respectively. The mice were administered orally with different doses of MCT (125, 250, and 500 mg/kg). The vehicle performed as a negative control (NC), while diclofenac sodium (DCN) (25 mg/kg), loperamide (LOP) (3 mg/kg), bismuth subsalicylate (BSS) (10 mg/kg), and nifedipine (NDP) (2.5 mg/kg) were supplied as positive controls (PC) (p.o.). In both models, combination treatment of MCT (higher dose) and PC was also administered to different groups of animals for assessing potential antagonistic or synergistic activity. Results: Findings of the in vivo study demonstrated that MCT dose‐dependently significantly (p < 0.05) exhibited analgesic and antidiarrheal properties by reduction in the number of writhing and reductions in the total fecal output in contrast to the NC group. Moreover, in combination treatment, MCT significantly (p < 0.05) synergized the activity of PC in both models, exerting potential analgesic and antidiarrheal activity. Conclusion: In conclusion, MCT has analgesic and antidiarrheal activity; it might be beneficial for the management of pain and diarrhea. [ABSTRACT FROM AUTHOR]

Natural compounds and their derivatives have been identified as valuable sources of therapeutic ingredients for cancer treatment. The naturally occurring phytochemical palmatine (isoquinoline alkaloid) is extracted from plant parts (rhizomes, roots, stems, stem barks, and others) and has protective effects including antioxidant, anti‐inflammatory, and anticancer. This study aims to summarize the anticancer potential of palmatine and its derivatives in the treatment of numerous types of cancer with molecular mechanisms. We also include the pharmacokinetic features, botanical origin, and toxicological characteristics of palmatine and its derivatives. For this, data have been collected from plausible different electronic databases, including PubMed, Google Scholar, PubChem, Science Direct, Web of Science, Scopus, Springer Link, and Wiley Online. The findings demonstrate that palmatine and its derivatives have a protective anticancer effect against a variety of cancers, including breast, colorectal, gastric, ovarian, prostate, pancreatic, skin, hepatocellular cancer, and mammary gland tumors. They provoke their anticancer properties against various cancer cell lines via modifying molecular mechanisms like induction of oxidative stress, cytotoxicity, apoptosis, inhibition of cell invasion and migration, arresting the cell cycle at the S phase, antiproliferative, and antiangiogenic effects. It is suggested that palmatine and its derivatives may be a good option in the development of novel drugs for cancer therapy in the future. [ABSTRACT FROM AUTHOR]

Cancer is a collection of illnesses characterized by aberrant cellular proliferation that can infiltrate or metastasize to distant anatomical sites, posing a notable threat to human well‐being due to its substantial morbidity and death rates worldwide. The potential of plant‐derived natural compounds as anticancer medicines has been assessed owing to their favorable attributes of few side effects and significant antitumor activity. Mangrove plants and their derived compounds have been scientifically shown to exhibit many significant beneficial biological activities, such as anti‐inflammatory, immunomodulatory, antioxidant, neuroprotective, cardioprotective, and hepatoprotective properties. This study summarized mangrove plants and their derived compounds as potential anticancer agents, with an emphasis on the underlying molecular mechanisms. To explore this, we gathered data on the preclinical (in vivo and in vitro) anticancer effects of mangrove plants and their derived compounds from reputable literature spanning 2000 to 2023. We conducted thorough searches in various academic databases, including PubMed, ScienceDirect, Wiley Online, SpringerLink, Google Scholar, Scopus, and the Web of Science. The results demonstrated that mangrove plants and their derived compounds have promising anticancer properties in preclinical pharmacological test systems through various molecular mechanisms, including induction of oxidative stress and mitochondrial dysfunction, cytotoxicity, genotoxicity, cell cycle arrest, apoptosis, autophagy, antiproliferative, antimetastatic, and other miscellaneous actions. Upon thorough observation of the pertinent information, it is suggested that mangrove plants and their derived chemicals may serve as a potential lead in the development of novel drugs for cancer therapy. [ABSTRACT FROM AUTHOR]

Random Numbers are widely employed in cryptography and security applications. This paper presents a novel approach to generate high-quality random bitstreams by harnessing the inherent noise properties of ring oscillators. We implemented ring oscillators with varying numbers of stages (3, 5, and 7), different geometries and different startup voltages in Cadence and recorded their total output power, which includes the cumulative noise effects. Subsequently, we exported these power measurements to MATLAB, where we applied a Fast Fourier Transform (FFT)-based technique to extract the total noise characteristics for each ring oscillator. Using the obtained noise data, we generated separate random bitstreams of 10 million bits for the 3-stage, 5-stage, and 7-stage ring oscillators. The final random bitstream, consisting of 10 million bits, was created by performing a bitwise XOR operation on the bitstreams generated by each ring oscillator. The degree of randomness of the generated bitstreams was assessed using the NIST 800-22 statistical test suite. Remarkably, the final random bitstream exhibited strong robustness and suitability for cryptographic applications. This innovative approach leverages the noise properties of ring oscillators to create reliable random bitstreams, offering potential applications in secure communications and cryptography. The results highlight the feasibility of using ring oscillators as noise sources for random bit generation and underscore their effectiveness in meeting stringent randomness criteria. [ABSTRACT FROM AUTHOR]

Reservoir computing is a highly efficient machine learning framework for processing temporal data by extracting input features and mapping them into higher dimensional spaces. Physical reservoirs have been realized using spintronic oscillators, atomic switch networks, volatile memristors, etc. However, these devices are intrinsically energy‐dissipative due to their resistive nature, increasing their power consumption. Therefore, memcapacitive devices can provide a more energy‐efficient approach. Herein, volatile biomembrane‐based memcapacitors are leveraged as reservoirs to solve classification tasks and process time series in simulation and experimentally. This system achieves a 99.6% accuracy for spoken‐digit classification and a normalized mean square error of 7.81×10−4$7.81 \times \left(10\right)^{- 4}$ in a second‐order nonlinear regression task. Furthermore, to showcase the device's real‐time temporal data processing capability, a 100% accuracy for an epilepsy detection problem is achieved. Most importantly, it is demonstrated that each memcapacitor consumes an average of 41.5 fJ of energy per spike, regardless of the selected input voltage pulse width, while maintaining an average power of 415 fW for a pulse width of 100 ms, orders of magnitude lower than those achieved by state‐of‐the‐art devices. Lastly, it is believed that the biocompatible, soft nature of our memcapacitor renders it highly suitable for computing applications in biological environments. [ABSTRACT FROM AUTHOR]

Numerous previous studies reported that ferulic acid exerts anxiolytic activity. However, the mechanisms have yet to be elucidated. The current study aimed to investigate the anxiolytic effect of trans-ferulic acid (TFA), a stereoisomer of ferulic acid, and evaluated its underlying mechanism using in vivo and computational studies. For this, different experimental doses of TFA (25, 50, and 75 mg/kg) were administered orally to Swiss albino mice, and various behavioral methods of open field, hole board, swing box, and light–dark tests were carried out. Diazepam (DZP), a positive allosteric modulator of the GABAA receptor, was employed as a positive control at a dose of 2 mg/kg, and distilled water served as a vehicle. Additionally, molecular docking was performed to estimate the binding affinities of the TFA and DZP toward the GABAA receptor subunits of α2 and α3, which are associated with the anxiolytic effect; visualizations of the ligand-receptor interaction were carried out using various computational tools. Our findings indicate that TFA dose-dependently reduces the locomotor activity of the animals in comparison with the controls, calming their behaviors. In addition, TFA exerted the highest binding affinity (−5.8 kcal/mol) to the α2 subunit of the GABAA receptor by forming several hydrogen and hydrophobic bonds. Taken together, our findings suggest that TFA exerts a similar effect to DZP, and the compound exerts moderate anxiolytic activity through the GABAergic interaction pathway. We suggest further clinical studies to develop TFA as a reliable anxiolytic agent. [ABSTRACT FROM AUTHOR]

Reservoir Computing (RC) is a type of machine learning inspired by neural processes, which excels at handling complex and time-dependent data while maintaining low training costs. RC systems generate diverse reservoir states by extracting features from raw input and projecting them into a high-dimensional space. One key advantage of RC networks is that only the readout layer needs training, reducing overall training expenses. Memristors have gained popularity due to their similarities to biological synapses and compatibility with hardware implementation using various devices and systems. Chaotic events, which are highly sensitive to initial conditions, undergo drastic changes with minor adjustments. Cascade chaotic maps, in particular, possess greater chaotic properties, making them difficult to predict with memoryless devices. This study aims to predict 1D and 2D cascade chaotic time series using a memristor-based hierarchical RC system. [ABSTRACT FROM AUTHOR]

This paper presents a general method, called "self-parameterization", for designing one-dimensional (1-D) chaotic maps that provide wider chaotic regions compared to existing 1-D maps. A wide chaotic region is a desirable property, as it helps to provide robust performance by enlarging the design space in many hardware-security applications, including reconfigurable logic and encryption. The proposed self-parameterization scheme uses only one existing chaotic map, referred to as the seed map, and a simple transformation block. The effective control parameter of the seed map is treated as an intermediate variable derived from the input and control parameter of the self-parameterized map, under some constraints, to achieve the desired functionality. The widening of the chaotic region after adding self-parameterization is first demonstrated on three ideal map functions: Logistic; Tent; and Sine. A digitized version of the scheme was developed and realized in a field-programmable gate array (FPGA) implementation. An analog version of the proposed scheme was developed with very low transistor-count analog topologies for hardware-constrained integrated circuit (IC) implementation. The chaotic performance of both digital and analog implementations was evaluated with bifurcation plots and four established chaotic entropy metrics: the Lyapunov Exponent; the Correlation Coefficient; the Correlation Dimension; and Approximate Entropy. An application of the proposed scheme was demonstrated in a random number generator design, and the statistical randomness of the generated sequence was verified with the NIST test. [ABSTRACT FROM AUTHOR]

This article presents and develops a novel comprehensive simulation model for perimeter gated single-photon avalanche diode-based silicon photomultipliers (PGSPAD SiPMs). A PGSPAD is a modification of single-photon avalanche diodes (SPADs) that contains a third terminal to mitigate perimeter edge breakdown. It does this without excessively enlarging the device area. The applied gate voltage modulates the dynamic range, breakdown voltage, and dark current characteristics. The proposed PGSPAD SiPM model correctly mimics the current–voltage transfer function and the avalanche-quench process of the SiPM detector and is verified by the experimental measurements of a PGSPAD SiPM fabricated in a commercial 0.5- $\mu \text{m}$ CMOS process. The model includes the dark current of the PGSPAD device. This was not included in previous SiPM models. The effect of the number of triggered microcells versus the total number of microcells and the impact of different parameters on the PGSPAD SiPM performance with added gate terminal are evaluated. The photon–electron spectrum with the effect of an extra gate terminal has been studied. Simulation results show very good agreement with experimental measurements. [ABSTRACT FROM AUTHOR]

A physically unclonable and reconfigurable computing system is introduced which provides both logic locking and authentication of devices. A chaotic oscillator is required to generate the chaotic signals and can produce different Boolean functions using different tuning parameters, including a control bit, iteration number, threshold voltage, and bifurcation parameter. The aim of this article is to build a hybrid computing system with the mixed implementation of standard logic gates and reconfigurable chaos-based logic gates. The tuning parameters of the oscillator make up the secret key for logic locking. Process variation due to fabrication can be leveraged to generate unique keys for each chip. The whole computing system exhibits physical unclonable function (PUF) characteristics and can be used to generate challenge–response pairs (CRPs) for authenticating devices. We have used ISCAS’85 combinational benchmark circuits to demonstrate the results. The Hamming distance between correct and wrong outputs is calculated to ensure that 50% of the output bits are flipped when the wrong key is applied. A Boolean SAT attack has been carried out on the system and it displays exponential complexity with an increase in the total number of chaos gates and key size of each chaos gate. The hybrid system demonstrates near-ideal PUF metrics, including uniqueness, uniformity, and bit aliasing. Common machine learning attacks have been executed on the CRPs generated from the whole system and results show that the proposed chaos-based PUF is robust against modeling attacks. The hybrid system has significantly less overhead compared to traditional systems containing both logic locking and PUF circuitry. [ABSTRACT FROM AUTHOR]

Recent advances in resistive random access memory (RRAM) as high density, low power, and faster memory systems drive the need for devising a more lightweight integrity checking system for RRAM. In this paper, we design a new tag generation system for integrity checking of RRAM. A single read operation to a crossbar RRAM in the presence of sneak path currents can output a tag for the memory data that can be used for integrity checking. An analytical approach to model such a tag generation process is described in this paper. Security results predicted by the analytical model provide various design options leading to an optimal system from the perspective of considered security properties. The proposed design is simulated to investigate and verify the security properties of the system for a number of optimal design options predicted by the analytical model. Reliability of the proposed system is also measured for varying conditions of device parameters, operating temperatures, load resistances, and read voltage. Finally, the performance of the proposed system is compared against another existing lightweight tag generation method from the perspective of energy consumption, transistor count, and delay. [ABSTRACT FROM AUTHOR]

An efficient numerical model of silicon‐on‐insulator (SOI) four‐gate transistors (G4FET) and its implementation in circuit simulator is presented here. A set of available data for different operating conditions is used to empirically determine the parameters of this model and a different set of test data is used to verify its predictive accuracy. This DC model is used to express the drain current as a single multivariate regression polynomial with its validity spanning across different possible operating regions as long as the chosen independent variables lie within the range of data set used to develop the model. The continuity of the polynomial model and its derivatives makes it particularly suitable for implementation in a circuit simulator. Models for both n‐channel and p‐channel G4FETs have been developed and validated using TCAD and experimental data and are successfully implemented in SPICE simulator for simulating two experimentally demonstrated G4FET circuits. [ABSTRACT FROM AUTHOR]

This work presents multivariate regression polynomial as a versatile and efficient method for DC modeling of modern transistors with very different underlying physics including MOSFET (metal-oxide-semiconductor field-effect transistor), MESFET (metal–semiconductor field-effect transistor), HBT (heterojunction bipolar transistor), HEMT (High-electron-mobility transistor) and a novel silicon-on-insulator four-gate transistors (G4FET). A set of available data from analytic solution, TCAD simulation, and experimental measurements for different operating conditions is used to empirically determine the parameters of this model and a different set of test data is used to verify its predictive accuracy. The developed model expresses the drain current as a single multivariate regression polynomial with its validity spanning across different possible operating regions as long as the chosen independent variables lie within the range of training data set. The continuity of the resulting polynomial and its first and second order derivatives make it particularly suitable for implementation in a circuit simulator. The model also provides a method for further simplification based on prior knowledge of the underlying physical mechanism and shows excellent predictive capability for different kinds of devices. This can be very useful for modeling deep-submicron emerging devices for which any closed-form analytical solution is not yet available. [ABSTRACT FROM AUTHOR]

A macromodel of silicon-on-insulator (SOI) four-gate transistor (G4FET) is presented in this paper to aid circuit designers to explore innovative applications circuit with this multi-gate transistor. A number of works based on analytical solution, numerical simulation and experimental results of G4FET have been previously reported. However, designing new interesting circuits with G4FETs requires a SPICE model that will work sufficiently well throughout the desired operating regions. Although it is theoretically possible to solve coupled non-linear differential equations to explore different operating conditions, this will take an excessive amount of time making it unsuitable for useful circuit design. Therefore, a macromodel approach is adopted in this work to provide a reasonably fast and accurate circuit simulation. G4FET combines the functionality of MOSFET and JFET devices which already have robust, fast and reliable SPICE models. A macromodel approach which is capable of combining these existing models including the interactions between multiple gates will be beneficial for any circuit designer. The feasibility of the macromodel is justified by simulating several analog and digital circuits and comparing against available experimental results. [ABSTRACT FROM AUTHOR]

A perimeter gated SPAD (PGSPAD), a SPAD with an additional gate terminal, prevents premature perimeter breakdown in standard CMOS SPADs. At the same time, a PGSPAD takes advantage of the benefits of standard CMOS. This includes low cost and high electronics integration capability. In this work, we simulate the effect of the applied voltage at the perimeter gate to develop a consistent electric field distribution at the junction through physical device simulation. Additionally, the effect of the shape of the device on the electric field distribution has been examined using device simulation. Simulations show circular shape devices provide a more uniform electric field distribution at the junction compared to that of rectangular and octagonal devices. We fabricated PGSPAD devices in a sub-micron process (0.5 μm CMOS process and 0.5 μm high voltage CMOS process) and a deep-submicron process (180 nm CMOS process). Experimental results show that the breakdown voltage increases with gate voltage. The breakdown voltage increases by approximately 1.5 V and 2.5 V with increasing applied gate voltage magnitude from 0 V to 6 V for devices fabricated in 0.5 μm and 180 nm standard CMOS process respectively. [ABSTRACT FROM AUTHOR]

This letter proposes a compact physical model for electroforming in transition metal oxide memristors. The proposed model is based on oxide breakdown statistics and validated against experimental data and Monte Carlo simulations. The model is applied to the problem of area optimization of memristive crossbar array. It is shown that a tradeoff exists between the area of the cross-point and the area of the forming circuit. Reduction of the switching layer thickness and/or varying the local field enhancement may result in an appreciable reduction of the forming voltage which, in turn, alleviates the need for forming transistors and yields significant area reduction. On the other hand, these gains might be subdued by scaling the crossbar array itself. The proposed compact model is useful for designers wishing to explore circuit level impacts of forming. [ABSTRACT FROM AUTHOR]

In this letter, a new topology for divide-by-3 injection-locked frequency divider based on relaxation oscillator is reported. A prototype is designed and implemented in a 90 nm CMOS process technology. The measurement results demonstrate a locking range of 0.4–1.4 GHz with a power consumption of 30 \muW. [ABSTRACT FROM PUBLISHER]

Sleep disturbance causes many health problems in humans worldwide. This study evaluated the effects and possible mechanisms of sclareol (SCL) and/or linalool (LIN) through in vivo and in silico studies. For this, young chicks SCL (5, 10, and 20 mg/kg) and/or LIN (50 mg/kg) were orally administered thirty minutes before to the thiopental sodium (TS)-induced chicks with or without the standard drug diazepam (DZP: 3 mg/kg). Incidence, onset, and duration of sleep were then noted. The results suggest that SCL dose-dependently increased the onset and decreased the duration of sleep in animals. In contrast, LIN50 significantly (p < 0.05) decreased onset and increased sleep duration. SCL20 combined with LIN50 and/or DZP3 modulated the sleep parameters in animals. In combination, LIN50 showed better effects with DZP3, where the percentage decrease in latency and increase in sleep duration were 54.20 and 168.65 %, respectively. SCL20 when combined with LIN50 + DZP3 also modulated the onset and duration of sleep in animals. Further, in silico studies suggest that SCL and LIN have binding affinities with the 6X3X protein of the GABA A receptor (α1 and β2 subunits) of -6.9 and -6.8 kcal/mol, respectively. The standard drug DZP showed a binding affinity of -5.0 kcal/mol. Taken together, SCL may exert an angiogenic-like effect and antagonize LIN and/or DZP-mediated sedative effects in TS-induced chicks, possibly through the GABA A receptor α1 and β2 subunits interaction pathway., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Memristive physical reservoir computing is a promising approach for solving data classification and temporal processing tasks. This method exploits the nonlinear dynamics of physical, low-power devices to achieve high-dimensional mapping of input signals. Ion-channel-based memristors, which operate with similar voltages, currents, and timescales as biological synapses, are promising due to their rich dynamics, especially for use in biological edge settings. Accurate modeling of their dynamics is essential for optimizing network hyperparameters ex situ to save time and energy. Here, a generalized sigmoidal growth model of ion-channel memristor conductance is presented and shown to be more accurate in predicting dynamics than linear or logistic models. Using the exact solution of the proposed sigmoidal model, the MNIST handwritten digit classification task is optimized and trained ex situ , then tested in situ with the same trained weights. This approach achieved an experimental testing accuracy of 90.6%.

Citronellal, known as rhodinal, is a naturally occurring monoterpenoid aldehyde distinctly found in the distilled oils of Cymbopogon species including C. marginatus, C. citratus, C. validus and C. winterianus family Gramineae. It is also obtained from eucalyptus, mentha, melissa, cinnamomum and allium. It is traditionally used in air freshener, cleaner, floor polishing, deodorants, moisturizing hand/body lotion, perfumes, and adhesives due to its lemon characteristic fragrance and therapeutic benefits. This study aimed to summarize the pharmacological activities and underlying mechanisms of citronellal against different diseases, as well as its toxicological profile. The data was collected from various reliable and authentic literatures by searching different academic search engines, including PubMed, Springer Link, Scopus, Wiley Online, Web of Science, ScienceDirect, and Google Scholar. The findings imply that citronellal demonstrated several pharmacological effects in various preclinical and pharmacological experimental systems. The results indicated that citronellal demonstrated antioxidant, anti-inflammatory, antibacterial, antifungal, anthelminthic, and anticancer effects with beneficial effects in neurological and cardiovascular diseases. Our findings also indicated the toxic level of the phytochemical. In conclusion, it has been proposed that citronellal has the capability to serve as a hopeful therapeutic agent, so further extensive clinical research is necessary to develop it as a reliable drug., (© 2024 Wiley-VHCA AG, Zurich, Switzerland.)

The ability to recreate synaptic functionalities in synthetic circuit elements is essential for neuromorphic computing systems that seek to emulate the cognitive powers of the brain with comparable efficiency and density. To date, silicon-based three-terminal transistors and two-terminal memristors have been widely used in neuromorphic circuits, in large part due to their ability to co-locate information processing and memory. Yet these devices cannot achieve the interconnectivity and complexity of the brain because they are power-hungry, fail to mimic key synaptic functionalities, and suffer from high noise and high switching voltages. To overcome these limitations, we have developed and characterized a biomolecular memristor that mimics the composition, structure, and switching characteristics of biological synapses. Here, we describe the process of assembling and characterizing biomolecular memristors consisting of a 5 nm-thick lipid bilayer formed between lipid-functionalized water droplets in oil and doped with voltage-activated alamethicin peptides. While similar assembly protocols have been used to investigate biophysical properties of droplet-supported lipid membranes and membrane-bound ion channels, this article focuses on key modifications of the droplet interface bilayer method essential for achieving consistent memristor performance. Specifically, we describe the liposome preparation process and the incorporation of alamethicin peptides in lipid bilayer membranes, and the appropriate concentrations of each constituent as well as their impact on the overall response of the memristors. We also detail the characterization process of biomolecular memristors, including measurement and analysis of memristive current-voltage relationships obtained via cyclic voltammetry, as well as short-term plasticity and learning in response to step-wise voltage pulse trains.