Explore the vast range of titles available.

A modified monopole patch antenna for microwave-based hemorrhagic or ischemic stroke recognition is presented in this article. The designed antenna is fabricated on a cost-effective FR-4 lossy material with a 0.02 loss tangent and 4.4 dielectric constant. Its overall dimensions are 0.32 λ × 0.28 λ × 0.007 λ, where λ is the lower bandwidth 1.3 GHz frequency wavelength. An inset feeding approach is utilized to feed the antenna to reduce the input impedance (z = voltage/current). A total bandwidth (below −10 dB) of 2.4 GHz (1.3–3.7 GHz) is achieved with an effective peak gain of over 6 dBi and an efficiency of over 90%. A time-domain analysis confirms that the antenna produces minimal signal distortion. Simulated and experimental findings share a lot of similarities. Brain tissue is penetrated by the antenna to a satisfactory degree, while still exhibiting a safe specific absorption rate (SAR). The maximum SAR value measured for the head model is constrained to be equal to or below 0.1409 W/kg over the entire usable frequency band. Evaluation of theoretical and experimental evidence indicates the intended antenna is appropriate for Microwave Imaging (MWI) applications.

Electrical impedance tomography (EIT) is a low-cost noninvasive imaging method. The main purpose of this paper is to highlight the main aspects of the EIT method and to review the recent advances and developments. The advances in instrumentation and in the different image reconstruction methods and systems are demonstrated in this review. The main applications of the EIT are presented and a special attention made to the papers published during the last years (from 2015 until 2020). The advantages and limitations of EIT are also presented. In conclusion, EIT is a promising imaging approach with a strong potential that has a large margin of progression before reaching the maturity phase.

While numerous studies have investigated the impact of various nanoparticles (NPs) in polymer matrices for radiation shielding, there is a notable gap in the literature regarding a comprehensive examination of both individual and combined selected NPs with functional polymers. This study aims to address this gap by systematically evaluating the synergistic potential of multiple high-Z NPs and specialized polymer matrices in radiation shielding design, particularly for computed tomography (CT) applications. A single and mixture range of NPs, including Gd 2 O 3 , Sm 2 O 3 , CeO 2 , HfO 2 , IrO 2 , Bi 2 O 3 , and WO 3 , were combined with polymers such as chlorinated polyvinyl chloride (CPVC), polychlorostyrene (PCS), polytrifluorochloroethylene (PTFCE), polytetrafluoroethylene (PTFE), polyvinyl chloride (PVC), and polyvinylidene chloride (PVDC) which served as matrices. By means of Geant4 Monte Carlo simulations, the study assessed the shielding effectiveness of these nanocomposites at various X-ray energies (80, 100, 120, and 140 kVp). The results revealed that nanocomposites containing Sm 2 O 3 and Gd 2 O 3 exhibited superior X-ray attenuation at 80 and 100 kVp, while the HfO 2 nanocomposite demonstrated enhanced shielding at 120 and 140 kVp. Additionally, multi-filler nanocomposites with 30 wt% of Sm 2 O 3  + HfO 2 (SmHf) and Gd 2 O 3  + Bi 2 O 3 (GdBi) exhibited improved performance at 80 and 140 kVp, respectively. Notably, the 30 wt% Gd 2 O 3  + IrO 2 (GdIr) multi-filler nanocomposite outperformed others at 100 and 120 kVp. It is concluded that a combination of NPs with K-edge values close to the mean energy of the investigated X-ray spectra provide better shielding capabilities than single NPs, highlighting their potential for applications in radiation protection.

Cardiovascular disease (CVD) represents the leading cause of mortality worldwide. In order to diagnose CVDs, there are a range of detection methods, among them, the impedance cardiography technique (ICG). It is a non-invasive and low-cost method. In this paper, we highlight recent advances and developments of the CDVs diagnosis mainly by the ICG method. We considered papers published during the last five years (from 2017 until 2022). Based on this study, we expressed the need for an ICG database for the different CDVs.

Early detection of breast cancer saves lives. Existing detecting techniques are invasive. Electrical bioimpedance is a noninvasive technique and has a high diagnostic potential. An impedance value different from the normal can predict a physiological abnormality. The idea is to use a designed bioimpedance device to early detect breast cancer. A low-frequency current (1 kHz, 0.9 mA) is injected to each breast to measure the extracellular resistances. The resistances of the two breasts are then measured, and if there is a significant difference, warning is displayed. The performance was tested on a set of reference resistors, and the validation was done in vitro on (Na+Cl-) solutions and in vivo on a group of forty volunteer women. The results confirm that the electrical conductivity of an ionic solution is proportional to its concentration. The concentration and the resistance are strongly correlated (correlation coefficient of 0.97). The accuracy and the repeatability of the measures were satisfactory. Early detection means that we can detect small extracellular concentration variations into the breast (from 0.6 g/l). In vivo measurements made it possible to set the threshold at 50 ohm. If the difference between the two measured breast resistances is greater than this threshold, we advise the patient to consult a doctor promptly. The difference between measured resistances of the right and left breast is a pertinent parameter to early detect the presence of a cancer. The lowest resistance value (RR or RL) can provide information on the breast affected by the cancer (right or left). Various improvements in the system are possible but already the results are encouraging. In the future, this system could be integrated into a bra.

Chitosan films are increasingly being applied in the biomedical field owing to their biocompatibility, biodegradability, non-toxicity, mucoadhesive nature, hemostatic properties, antibacterial and biological activities. This study aimed to enhance the mechanical properties of chitosan films by doping niosomal sage nanoparticles (NS-SagNPs) at various concentrations (100–300 μ g). The NS-SagNPs were prepared by a thin-film hydration process with an average particle size of 21.5 nm. The doped chitosan films were fabricated through a simple casting method. FTIR and DSC measurements confirmed the successful incorporation of NS-SagNPs in the chitosan films. The mechanical properties of the doped films were improved and the most significant improvement was found in tensile strength and elasticity when the NS-SagNPs loading was increased to 300 μ g. Based on these results, chitosan films doped with NS-SagNPs have the advantageous feature of sage and show enhanced mechanical properties compared with pure chitosan, rendering them more suitable for biomedical applications.

A low-noise instrumentation amplifier dedicated to a nano- and micro-electro-mechanical system (M&NEMS) microphone for the use in Internet of Things (IoT) applications is presented. The piezoresistive sensor and the electronic interface are respectively, silicon nanowires and an instrumentation amplifier. To design an instrumentation amplifier for IoT applications, different trade-offs are discussed like power consumption, gain, noise and sensitivity. Because the most critical noisy block is the amplifier, a delay-time chopper stabilization (CHS) technique is implemented around it to eliminate its offset and 1/f noise. The low-noise instrumentation amplifier is implemented in a 65-nm CMOS (Complementary metal–oxide–semiconductor) technology. The supply voltage is 2.5 V while the power consumption is 0.4 mW and the core area is 1 mm2. The circuit of the M&NEMS microphone and the amplifier was fabricated and measured. From measurement results over a signal bandwidth of 20 kHz, it achieves a signal-to-noise ratio (SNR) of 77 dB.

Featured Application: Analysis of metrological velocity and temperature fields in gas flows in many areas of modern science and technology. Our Micro-Electro- Mechanical Systems (MEMS) calorimetric sensor is used in experimental studies in the field of fluid mechanics and thermodynamics, as well as in technical areas such as aerodynamics, aviation, automotive, climatology, ventilation and air conditioning, and refrigeration and heating. In this paper, a Micro-Electro-Mechanical Systems (MEMS) calorimetric sensor with its measurement electronics is designed, fabricated, and tested. The idea is to apply a configurable voltage to the sensitive resistor and measure the current flowing through the heating resistor using a current mirror controlled by an analog feedback loop. In order to cancel the offset and errors of the amplifier, the constant temperature anemometer (CTA) circuit is periodically calibrated. This technique improves the accuracy of the measurement and allows high sensitivity and high bandwidth frequency. The CTA circuit is implemented in a CMOS FD-SOI 28 nm technology. The supply voltage is 1.2 V while the core area is 0.266 [mm.sup.2]. Experimental results demonstrate the feasibility of the MEMS calorimetric sensor for measuring airflow rate. The developed MEMS calorimetric sensor shows a maximum normalized sensitivity of 117 mV/(m/s)/mW with respect to the input heating power and a wide dynamic flow range of 0-26 m/s. The high sensitivity and wide dynamic range achieved by our MEMS flow sensor enable its deployment as a promising sensing node for direct wall shear stress measurement applications. Keywords: MEMS calorimetric sensor; CTA circuit; amplifier; heating resistor; hot-wire anemometer

Emotion recognition is the automatic detection of a person’s emotional state through his or her non-physiological or physiological signals. The EEG-related technique was an effectual system, which is typically employed for recognizing feelings in real time. Artificial Intelligence (AI) can be a developing research field which had rapid growth particularly to constitute a bridge between technology and its implementation in solving real-time issues particularly those relevant to the healthcare domain. This study develops a new deep learning-based emotion detection based on EEG signal processing, named DLED-EEGSP technique. The presented DLED-EEGSP technique identifies the distinct kinds of emotions based on the sensors and EEG signals. To perform this, the presented DLED-EEGSP technique exploits multi-head attention based long short-term memory (MHA-LSTM) method for emotion recognition. The MHALSTM model recognizes the emotion states based on the higher order cross feature samples. The experimental result analysis of the DLED-EEGSP technique is investigated on a series of data. A wide-ranging simulation results reported the supremacy of the DLED-EEGSP technique over other existing models.

In this paper, a Micro-Electro-Mechanical Systems (MEMS) calorimetric sensor with its measurement electronics is designed, fabricated, and tested. The idea is to apply a configurable voltage to the sensitive resistor and measure the current flowing through the heating resistor using a current mirror controlled by an analog feedback loop. In order to cancel the offset and errors of the amplifier, the constant temperature anemometer (CTA) circuit is periodically calibrated. This technique improves the accuracy of the measurement and allows high sensitivity and high bandwidth frequency. The CTA circuit is implemented in a CMOS FD-SOI 28 nm technology. The supply voltage is 1.2 V while the core area is 0.266 mm2. Experimental results demonstrate the feasibility of the MEMS calorimetric sensor for measuring airflow rate. The developed MEMS calorimetric sensor shows a maximum normalized sensitivity of 117 mV/(m/s)/mW with respect to the input heating power and a wide dynamic flow range of 0–26 m/s. The high sensitivity and wide dynamic range achieved by our MEMS flow sensor enable its deployment as a promising sensing node for direct wall shear stress measurement applications.