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Abstract Background The pandemic of coronavirus disease–19 (COVID-19) has a profound influence on the health of the population. This study aimed to assess the weight changes and its relation to the dietary habits and physical activity among adult Egyptian population during the second wave of COVID-19 pandemic. Materials and methods This cross–sectional study was conducted using anonymous online questionnaire. The questionnaire was distributed across Egypt via community–based networks, social and institutional emailing lists, and professional organizations to collect data on sociodemographic, clinical history, dietary and lifestyle habits, physical activity, anthropometric measurements, and stressing factors. Results The study participants (n = 1000) had a median (interquartile range) age of 34.0 (23.0–40.0) years, with 18.7% males, 96.6% having university or postgraduate education. Among them, 69.1% reported weight gain, 21.3% no change, and 9.6% weight loss. Weight loss was predicted by following COVID-19 pandemic reports daily [adjusted odds ratio (AOR) = 0.50 (95% CI, 0.27–0.93), p = 0.03], monthly income change [AOR = 2.52 (95% CI, 1.51–4.22), p

This study examines the impact of compensation and work environment on employee job satisfaction at Al-Hoty Analytical Services in the Kingdom of Bahrain. In a competitive global market, optimizing workplace conditions is crucial for enhancing employee morale and organizational performance. A sample of 152 employees from various departments at Al-Hoty Analytical Services was surveyed using a structured questionnaire, applying saturated sampling within a quantitative research framework. Data analysis was conducted using SPSS version 26. The results indicate that the physical work environment significantly contributes to higher levels of job satisfaction, emphasizing the importance of a well-designed workspace. The social work environment, while positively correlated with satisfaction (p = 0.926), did not significantly impact overall satisfaction (β = 0.385, p < 0.001). In contrast, both direct and indirect compensation had significant positive effects on job satisfaction, with direct compensation having a stronger influence (β = 0.273, p < 0.001) than indirect compensation (β = 0.238, p = 0.001). The study provides practical insights for organizational leaders and contributes to the broader understanding of job satisfaction dynamics.

BackgroundHealth workers directly involved in the diagnosis, treatment, and care of patients with COVID-19 are at risk of developing mental health symptoms.ObjectiveThe study aimed to assess the quality of life (QoL) of healthcare workers at Prince Mohammed bin Nasser Tertiary Hospital in Jazan during the COVID-19 pandemic, with a focus on the relationship between QoL and stress, anxiety, and depression. Pandemic.MethodsThis was a cross-sectional study conducted among healthcare workers at Prince Mohammed bin Nasser Hospital in the Jazan. The study included a sample of 352 healthcare workers. Data was collected through a self-administered questionnaire pertaining to sociodemographic characteristics and the 21-item Depression Anxiety Stress Scale questionnaire, SF-36, for QoL. Descriptive statistics, frequencies, and percentages were used. A chi-squared test was performed to compare categorical data. A one-way ANOVA was performed to compare the effect of disorder variables on QoL. Multiple linear regression analyses were carried out to discern the differences between the different groups of participants in QoL measures.ResultsOur results showed a poor QoL among those with a chronic disease (p = 0.002), who worked in the COVID-19 department (p = 0.030) and those who experienced the death of relatives or friends due to COVID-19 (p = 0.003).ConclusionHealthcare workers, particularly those with chronic diseases or who had lost relatives to COVID-19, exhibited significantly lower QoL levels, especially those working directly in COVID-19 departments.

One of the most promising approaches to food quality assessments is the use of impedance spectroscopy combined with machine learning. Thereby, feature selection is decisive for a high classification accuracy. Physically based features have particularly significant advantages because they are able to consider prior knowledge and to concentrate the data into pertinent understandable information, building a solid basis for classification. In this study, we aim to identify physically based measurable features for muscle type and freshness classifications of bovine meat based on impedance spectroscopy measurements. We carry out a combined study where features are ranked based on their F1-score, cumulative feature selection, and t-distributed Stochastic Neighbor Embedding (t-SNE). In terms of features, we analyze the characteristic points (CPs) of the impedance spectrum and the model parameters (MPs) obtained by fitting a physical model to the measurements. The results show that either MPs or CPs alone are sufficient for detecting muscle type. Combining capacitance (C) and extracellular resistance (Rex) or the modulus of the characteristic point Z1 and the phase at the characteristic frequency of the beta dispersion (Phi2) leads to accurate separation. In contrast, the detection of freshness is more challenging. It requires more distinct features. We achieved a 90% freshness separation using the MPs describing intracellular resistance (Rin) and capacitance (C). A 95.5% freshness separation was achieved by considering the phase at the end of the beta dispersion (Phi3) and Rin. Including additional features related to muscle type improves the separability of samples; ultimately, a 99.6% separation can be achieved by selecting the appropriate features.

Background: Diabetes mellitus is one of the main causes of death due to the complications that involve many organs such as heart, kidney, retina and others. Mesenchymal stem cell (MSC) has been demonstrated to be effective in treatment of diabetes. Aim of the work: To evaluate the effect of stem cells in the treatment of diabetic cardiomyopathy clarifying their role in oxidative stress and inflammation. Material and methods: 30 adult male albino rats were equally divided into 3 groups: control group (group I): received 1ml saline by intra-peritoneal (IP) injection. Streptozotocin-treated group (group II): received Streptozotocin (STZ) (60mg/kg BW, I.P.) for induction of diabetes then were sacrificed after 4 weeks. Steptozotocin+ Stem cell-treated group (group III): received STZ for induction of diabetes and they were left for 4 weeks then they were injected once intravenously with 1 million units of MSC then were sacrificed after 4 weeks. The heart sections were examined Histologically with H&E and Masson’s Trichrome Stain and Immunohistochemically for endothelial Nitric Oxide Synthase (eNOS). A morphometric study and statistical analysis were performed. Results: DM caused inflammation, degeneration, fibrosis and decreased eNOS Immunoexpression of the cardiac muscle fibers. The administration of MSCs improved pathological changes and increased eNOS Immunoexpression in the heart. Conclusion: MSCs administration proved to have effective therapeutic role in treating diabetic cardiomyopathy

Monitoring changes in edema-associated intracranial pressure that complicates trauma or surgery would lead to improved outcomes. Implantable pressure sensors have been explored, but these sensors require post-surgical removal, leading to the risk of injury to brain tissue. The use of biodegradable implantable sensors would help to eliminate this risk. Here, we demonstrate a bioactive glass (BaG)-based hydration sensor. Fluorine (CaF2) containing BaG (BaG-F) was produced by adding 5, 10 or 20 wt.% of CaF2 to a BaG matrix using a melting manufacturing technique. The structure, morphology and electrical properties of the resulting constructs were evaluated to understand the physical and electrical behaviors of this BaG-based sensor. Synthesis process for the production of the BaG-F-based sensor was validated by assessing the structural and electrical properties. The structure was observed to be amorphous and dense, the porosity decreased and grain size increased with increasing CaF2 content in the BaG matrix. We demonstrated that this BaG-F chemical composition is highly sensitive to hydration, and that the electrical sensitivity (resistive–capacitive) is induced by hydration and reversed by dehydration. These properties make BaG-F suitable for use as a humidity sensor to monitor brain edema and, consequently, provide an alert for increased intracranial pressure.

For diagnosis of batteries and fuel cells based on impedance spectroscopy, excitation signals are required, including low frequencies down to the mHz range. This leads to a long measurement time and compromises the stability condition for impedance spectroscopy. Multisine excitation signals with logarithmic frequency distribution can significantly reduce the measurement time but need optimization of the crest factor to realize a high signal-to-noise ratio at all excitation frequencies and maintain at the same time the linearity and stability conditions of impedance spectroscopy. Crest factor optimization is challenging, as the obtained results strongly depend on the initial phase values and many trials are necessary. It takes a very long time and can not be easily performed automatically up to now. In this paper, we propose a time-efficient hybrid stochastic-deterministic crest factor optimization method for multisine signals with logarithmic frequency distribution. A sigmoid transform on the multisine signal gradually transforms the multi-frequency signal into a binary-alike signal. The crest factor is significantly decreased, but the phases of the singular frequency signals remain sub-optimal. Further optimization based on the Gauss-Newton algorithm can determine the final phases, realizing a lower crest factor. The proposed method is less sensitive to initial phase values and provides more reasonable results in a reasonable time. The validation on a Samsung INR-18650-25R Lithium-ion battery cell shows that the crest factor of the optimized multisine signals has a median of 3.62 ± 0.7 within 6 min of run time, which is significantly better than the best previous work in the state-of-the-art of 3.85 ± 0.11 for the same run time.

The aim of this study was to compare the mortality rates, re-intervention rates, and volumetric changes in aortas following surgery, in terms of the true lumen and false lumen changes, using conventional hemi-arch repair (CET) and frozen elephant trunk (FET) techniques. During the period from 2015 to 2018, 66 patients underwent surgical treatment for acute aortic dissection (Debakey type 1). Demographic and procedure-related data were evaluated. We measured volumetric change before surgical treatment, at discharge, and at 12- and 24-month time points based on computed tomography angiography. The study cohort was divided into two groups (FET vs. CET). The mean age of the patients was 56.9 ± 9.4 years in the FET group versus 63.6 ± 11 years in the CET group (p = 0.063). The mean follow-up time was 24 ± 6 and 25 ± 5 months for the FET and CET groups, respectively. There were no significant differences between the two groups in terms of the medical histories of the cohorts. The results showed a significant increase in true lumen volume after the FET procedure (within 24 months postoperatively; p = 0.005), and no significant changes in total (p = 0.392) or false lumen (p = 0.659) volumes were noted. After the CET procedure, there were significant increases in total and false lumen volumes (p = 0.013, p = 0.042), while no significant change in true lumen was observed (p = 0.219). The volume increase in true lumen after the FET procedure was higher compared to the CET group at all postoperative time points (at discharge, 12 months, and 24 months) without significant evidence (p = 0.416, p = 0.422, p = 0.268). At two years, the volume increase in false lumen was significantly higher among the CET group compared to the FET group (p = 0.02). The Kaplan–Meier curve analysis showed that patients who underwent the CET procedure underwent significantly more re-interventions due to false lumen expansion of the descending aorta (p = 0.047). Present study results indicate that the true and false lumen changes in the aorta following the FET and CET procedures were different. FET led to a significant increase in true lumen volume, while false lumen volume remained stable; however, after the CET procedure, significant false lumen enlargement was noted at mid-term follow-up time points. The re-intervention rate after CET was higher due to false lumen expansion.

Bioimpedance spectroscopy (BIS) is an advanced measurement method for providing information on impedance changes at several frequencies by injecting a low current into a device under test and analyzing the response voltage. Several methods have been elaborated for BIS measurement, calculating impedance with a gain phase detector (GPD), IQ demodulation, and fast Fourier transform (FFT). Although the measurement method has a big influence on the measurement system performance, a systematical comparative study has not been performed yet. In this paper, we compare them based on simulations and experimental studies. To maintain similar conditions in the implementation of all methods, we use the same signal generator followed by a voltage-controlled current source (VCCS) as a signal generator. For performance analysis, three DUTs have been designed to imitate the typical behavior of biological tissues. A laboratory impedance analyzer is used as a reference. The comparison addresses magnitude measurement accuracy, phase measurement accuracy, signal processing, hardware complexity, and power consumption. The result shows that the FFT-based system excels with high accuracy for amplitude and phase measurement while providing the lowest hardware complexity, and power consumption, but it needs a much higher software complexity.

For embedded impedance spectroscopy, a suitable method for analyzing AC signals needs to be carefully chosen to overcome limited processing capability and memory availability. This paper compares various methods, including the fast Fourier transform (FFT), the FFT with barycenter correction, the FFT with windowing, the Goertzel filter, the discrete-time Fourier transform (DTFT), and sine fitting using linear or nonlinear least squares, and cross-correlation, for analyzing AC signals in terms of speed, memory requirements, amplitude measurement accuracy, and phase measurement accuracy. These methods are implemented in reference systems with and without hardware acceleration for validation. The investigation results show that the Goertzel algorithm has the best overall performance when hardware acceleration is excluded or in the case of memory constraints. In implementations with hardware acceleration, the FFT with barycentre correction stands out. The linear sine fitting method provides the most accurate amplitude and phase determinations at the expense of speed and memory requirements.

Several studies show that impedance spectroscopy is a suitable method for online battery diagnosis and State-of-Health (SoH) estimation. However, the most common method is to model the acquired impedance spectrum with equivalent circuits and focus on the most sensitive parameters, namely the charge-transfer resistance. This paper introduces first a detailed model of a battery cell, which is then simplified and adapted to the observable spectrum behavior. Based on the physical meaning of the model parameters, we propose a novel approach for SoH assessment combining parameters of the impedance spectrum by building the ratio of the solid electrolyte interphase (SEI) resistance to the total resistance of SEI and the charge transfer. This ratio characterizes the charge-transfer efficiency at the electrodes’ surfaces and should decrease systematically with SoH. Four different cells of the same type were cycled 400 times for the method validation, and impedance spectroscopy was performed at every 50th cycle. The results show a systematic correlation between the proposed ratio and the number of cycles on individual cell parameters, which build the basis of a novel online method of SoH assessment.

This paper aimed to develop a portable, low-cost, and easy-to-use measurement system for oil quality degradation assessment. The main two chemical parameters affected by frying are the total polar compounds (TPC) and free fatty acids. The system should characterize the change of chemical parameters by measuring the changes in its dielectric parameters. The dielectric parameters, relative permittivity, and conductivity are measured by measuring the capacitance and resistance of a capacitive sensor dipped in oil. The main challenges are that the corresponding changes of the capacitance and resistance are very small and the presence of stray effects. For this reason, the measurement system should be able to detect changes in capacitance and resistance with high resolution and with good immunity to stray effects. The proposed measurement system is based on the conversion of impedance to voltage and time and combining, therefore, having two measurement methods in one circuit. In this way, it is possible to measure the dielectric and resistive parameters and not only the relative permittivity as was done in previous works. The results showed a strong correlation between the chemical and electrical parameters with a coefficient of determination in the range of 0.9.

Background: Lack of early ultrasound examination and proper antenatal care in rural areas explain why most ectopic pregnancies are presented to our center only after they become disturbed. However, this is almost always restricted to the first trimester. Case: A middle aged woman presented with acute abdomen and hemodynamic instability was admitted at our emergency department. History revealed an unexpected definite period of amenorrhea of 18 weeks and 2 days duration and pregnancy test was found positive. Ultrasound examination showed hemoperitoneum and a right large adnexal swelling with a viable fetus inside and as such immediate exploration was decided. Laparotomy revealed profound intra-abdominal and pelvic blood collection and an advanced right tubal pregnancy with intact gestational sac. Right salpingectomy was done and the patient had a smooth postoperative course until being discharged. Conclusion: According to this case, tubal pregnancy should always be considered even in the second trimester if the clinical presentation is relevant, and ultrasound examination is mandatory to identify pregnancy location.

Background: The pandemic of coronavirus disease–19 (COVID-19) has a profound influence on the health of the population. This study aimed to assess the weight changes and its relation to the dietary habits and physical activity among adult Egyptian population during the second wave of COVID-19 pandemic. Materials and methods: This cross–sectional study was conducted using anonymous online questionnaire. The questionnaire was distributed across Egypt via community–based networks, social and institutional emailing lists, and professional organizations to collect data on sociodemographic, clinical history, dietary and lifestyle habits, physical activity, anthropometric measurements, and stressing factors. Results: The study participants (n = 1000) had a median (interquartile range) age of 34.0 (23.0–40.0) years, with 18.7% males, 96.6% having university or postgraduate education. Among them, 69.1% reported weight gain, 21.3% no change, and 9.6% weight loss. Weight loss was predicted by following COVID-19 pandemic reports daily [adjusted odds ratio (AOR) = 0.50 (95% CI, 0.27–0.93), p = 0.03], monthly income change [AOR = 2.52 (95% CI, 1.51–4.22), p < 0.001], starting antidepressants [AOR = 3.57 (95% CI, 1.08–11.76), p = 0.03], and increase in social media use [AOR = 1.81 (95% CI, 1.05–3.13), p = 0.03]. Weight gain was predicted by starting a diet during the second wave of COVID-19 pandemic [AOR = 1.57 (95% CI, 1.11–2.21), p = 0.01], physical activity during the second wave of COVID-19 pandemic [AOR = 0.49 (95% CI, 0.35–0.69), p < 0.001], and unhealthy food intake [AOR = 0.40 (95% CI, 0.28–0.57), p < 0.001] Conclusions: More intervention programs aiming to improve dietary habits and increase physical activity should be rapidly implemented to reduce the consequences of the pandemic on the Egyptians to keep healthy weight. [ABSTRACT FROM AUTHOR]

Background: Health workers directly involved in the diagnosis, treatment, and care of patients with COVID-19 are at risk of developing mental health symptoms. Objective: The study aimed to assess the quality of life (QoL) of healthcare workers at Prince Mohammed bin Nasser Tertiary Hospital in Jazan during the COVID-19 pandemic, with a focus on the relationship between QoL and stress, anxiety, and depression. Pandemic. Methods: This was a cross-sectional study conducted among healthcare workers at Prince Mohammed bin Nasser Hospital in the Jazan. The study included a sample of 352 healthcare workers. Data was collected through a self-administered questionnaire pertaining to sociodemographic characteristics and the 21-item Depression Anxiety Stress Scale questionnaire, SF-36, for QoL. Descriptive statistics, frequencies, and percentages were used. A chi-squared test was performed to compare categorical data. A one-way ANOVA was performed to compare the effect of disorder variables on QoL. Multiple linear regression analyses were carried out to discern the differences between the different groups of participants in QoL measures. Results: Our results showed a poor QoL among those with a chronic disease (p = 0.002), who worked in the COVID-19 department (p = 0.030) and those who experienced the death of relatives or friends due to COVID-19 (p = 0.003). Conclusion: Healthcare workers, particularly those with chronic diseases or who had lost relatives to COVID-19, exhibited significantly lower QoL levels, especially those working directly in COVID-19 departments. [ABSTRACT FROM AUTHOR]

This study examined how transformational leadership affects work performance at Palestine's Ministry of Communications and Information Technology, focusing on psychological empowerment. We conducted a descriptive study on 350 full-time employees. We took a systematic sample of 183 people from this group. A systematic questionnaire collected quantitative and qualitative employee experiences. SPSS was used to analyze the data using descriptive and deductive methods. Data patterns and linkages were identified and displayed in frequency distribution tables and visual graphics. The study found that psychological empowerment mediates the relationship between transformational leadership and job performance at the Palestinian Ministry of Communications and Information Technology. Psychological empowerment greatly enhances transformational leadership's influence on workforce performance. Organizations ought to educate leaders and empower their staff to improve performance. The research found that transformational leadership combined with psychological empowerment tactics significantly improves employee engagement and performance. This study fills gaps in the literature and expands our understanding of how psychological empowerment affects work performance. The findings support the study's assumptions and emphasize the relevance of leadership strategies that empower people psychologically. This method improves job performance and suggests empowerment-focused leadership solutions for organizational leadership and policy creation to boost workplace engagement and productivity. [ABSTRACT FROM AUTHOR]

One of the most promising approaches to food quality assessments is the use of impedance spectroscopy combined with machine learning. Thereby, feature selection is decisive for a high classification accuracy. Physically based features have particularly significant advantages because they are able to consider prior knowledge and to concentrate the data into pertinent understandable information, building a solid basis for classification. In this study, we aim to identify physically based measurable features for muscle type and freshness classifications of bovine meat based on impedance spectroscopy measurements. We carry out a combined study where features are ranked based on their F1-score, cumulative feature selection, and t-distributed Stochastic Neighbor Embedding (t-SNE). In terms of features, we analyze the characteristic points (CPs) of the impedance spectrum and the model parameters (MPs) obtained by fitting a physical model to the measurements. The results show that either MPs or CPs alone are sufficient for detecting muscle type. Combining capacitance (C) and extracellular resistance (Rex) or the modulus of the characteristic point Z1 and the phase at the characteristic frequency of the beta dispersion (Phi2) leads to accurate separation. In contrast, the detection of freshness is more challenging. It requires more distinct features. We achieved a 90% freshness separation using the MPs describing intracellular resistance (Rin) and capacitance (C). A 95.5% freshness separation was achieved by considering the phase at the end of the beta dispersion (Phi3) and Rin. Including additional features related to muscle type improves the separability of samples; ultimately, a 99.6% separation can be achieved by selecting the appropriate features. [ABSTRACT FROM AUTHOR]

Background: Millions of people from a variety of demographic groups suffer from mental health conditions like anxiety and depression, which are among the main causes of disability globally. Although psychotherapy and medication are still the most common forms of treatment, their drawbacks--such as side effects, resistance to treatment, and relapse rates--have sparked interest in complementary therapies. Because omega-3 fatty acids have been shown to have neuroprotective, antiinflammatory, and neurotransmitter-modulating effects, they have become a promising adjuvant in nutritional therapy. Aim: this research is to investigate how omega-3 fatty acids can help cure depression and anxiety by looking at the molecular processes that underlie their therapeutic benefits and combining clinical data to evaluate how well they work as part of nutritional therapy. Methods: Peer-reviewed articles obtained from the Cochrane, PubMed, and Scopus databases were the main focus of a systematic review of the literature. Randomized controlled trials (RCTs), meta-analyses, and observational studies examining the impact of omega-3 fatty acids on depression and anxiety were among the research that qualified. To put clinical findings in context, mechanistic insights from preclinical studies were also examined. Results: indicate that omega-3 fatty acids, especially eicosapentaenoic acid (EPA), are highly effective in lowering depressive symptoms. These benefits are mediated through anti-inflammatory pathways, increased neuroplasticity, and changes in neurotransmitters such as dopamine and serotonin. Although the clinical evidence for anxiety is more mixed, it does point to advantages for people who have both generalized anxiety disorder and co-occurring depression symptoms. EPA-to-DHA ratios and the unique characteristics of each patient seem to be important factors in determining the best possible therapeutic results. Conclusion: omega-3 fatty acids have biological and clinical benefits that enhance conventional treatments, making them a promising supplementary therapy for depression and anxiety. Standardized dosing procedures, long-term efficacy evaluations, and the investigation of synergistic effects with current pharmacotherapies should be the top priorities of future study. [ABSTRACT FROM AUTHOR]

Introduction: Polycystic ovarian syndrome (PCOS) is prevalent among women, impacting health and quality of life. The present study aimed to investigate the effect of adding whole-body vibration (WBV) to the traditional treatment of PCOS. Material and methods: Forty-six women diagnosed with PCOS, aged 20 to 35 years, with BMI 25-29.9 kg/m², were randomly divided into two equal groups. The study group followed an iso-caloric, low-glycemic diet and performed aerobic exercises in addition to WBV, and the control group followed an iso-caloric, low-glycemic diet and performed aerobic exercise only (n = 23 each). Treatment lasted for eight weeks, three sessions per week. BMI, waist-hip ratio (WHR), and LH/FSH ratio were assessed pre- and post- treatment. Insulin resistance was assessed by HOMA-IR (Homeostatic Model Assessment for Insulin Resistance) pre- and post-treatment. Results: Significant decreases in weight, BMI, HOMA-IR, and LH/FSH ratio were noted between the two time points (before and after-treatment) in both groups (p < 0.05). However, WHR only showed a significant decrease in the study group (p < 0.05). Compared to the control group, the study group showed a significant reduction in weight (-8.08 kg vs. - 4.39 kg, p = 0.0009), BMI (-2.99 kg/m² vs. -1.6 kg/m², p = 0.004), WHR (-0.05 vs. -0.018, p = 0.009), HOMA-IR (-1.54 vs. - 0.77, p = 0.03), and LH/FSH ratio (-0.53 vs. -0.5, p = 0.02) after eight weeks of treatment. Conclusions: Adding WBV to aerobic exercise appears to have favourable outcomes for patients with PCOS. [ABSTRACT FROM AUTHOR]

Monitoring changes in edema-associated intracranial pressure that complicates trauma or surgery would lead to improved outcomes. Implantable pressure sensors have been explored, but these sensors require post-surgical removal, leading to the risk of injury to brain tissue. The use of biodegradable implantable sensors would help to eliminate this risk. Here, we demonstrate a bioactive glass (BaG)-based hydration sensor. Fluorine (CaF2) containing BaG (BaG-F) was produced by adding 5, 10 or 20 wt.% of CaF2 to a BaG matrix using a melting manufacturing technique. The structure, morphology and electrical properties of the resulting constructs were evaluated to understand the physical and electrical behaviors of this BaG-based sensor. Synthesis process for the production of the BaG-F-based sensor was validated by assessing the structural and electrical properties. The structure was observed to be amorphous and dense, the porosity decreased and grain size increased with increasing CaF2 content in the BaG matrix. We demonstrated that this BaG-F chemical composition is highly sensitive to hydration, and that the electrical sensitivity (resistive–capacitive) is induced by hydration and reversed by dehydration. These properties make BaG-F suitable for use as a humidity sensor to monitor brain edema and, consequently, provide an alert for increased intracranial pressure. [ABSTRACT FROM AUTHOR]

For diagnosis of batteries and fuel cells based on impedance spectroscopy, excitation signals are required, including low frequencies down to the mHz range. This leads to a long measurement time and compromises the stability condition for impedance spectroscopy. Multisine excitation signals with logarithmic frequency distribution can significantly reduce the measurement time but need optimization of the crest factor to realize a high signal-to-noise ratio at all excitation frequencies and maintain at the same time the linearity and stability conditions of impedance spectroscopy. Crest factor optimization is challenging, as the obtained results strongly depend on the initial phase values and many trials are necessary. It takes a very long time and can not be easily performed automatically up to now. In this paper, we propose a time-efficient hybrid stochastic-deterministic crest factor optimization method for multisine signals with logarithmic frequency distribution. A sigmoid transform on the multisine signal gradually transforms the multi-frequency signal into a binary-alike signal. The crest factor is significantly decreased, but the phases of the singular frequency signals remain sub-optimal. Further optimization based on the Gauss-Newton algorithm can determine the final phases, realizing a lower crest factor. The proposed method is less sensitive to initial phase values and provides more reasonable results in a reasonable time. The validation on a Samsung INR-18650-25R Lithium-ion battery cell shows that the crest factor of the optimized multisine signals has a median of 3.62 ± 0.7 within 6 min of run time, which is significantly better than the best previous work in the state-of-the-art of 3.85 ± 0.11 for the same run time. [ABSTRACT FROM AUTHOR]

Bioimpedance spectroscopy (BIS) is an advanced measurement method for providing information on impedance changes at several frequencies by injecting a low current into a device under test and analyzing the response voltage. Several methods have been elaborated for BIS measurement, calculating impedance with a gain phase detector (GPD), IQ demodulation, and fast Fourier transform (FFT). Although the measurement method has a big influence on the measurement system performance, a systematical comparative study has not been performed yet. In this paper, we compare them based on simulations and experimental studies. To maintain similar conditions in the implementation of all methods, we use the same signal generator followed by a voltage-controlled current source (VCCS) as a signal generator. For performance analysis, three DUTs have been designed to imitate the typical behavior of biological tissues. A laboratory impedance analyzer is used as a reference. The comparison addresses magnitude measurement accuracy, phase measurement accuracy, signal processing, hardware complexity, and power consumption. The result shows that the FFT-based system excels with high accuracy for amplitude and phase measurement while providing the lowest hardware complexity, and power consumption, but it needs a much higher software complexity. [ABSTRACT FROM AUTHOR]

Impedance spectroscopy is a powerful measurement method having decisive advantages in several application fields. It allows the measurements of non-accessible quantities, supports high measurement accuracy, and enables simultaneous measurements of more than one quantity. The method provides deep insights in systems and materials, is non-invasive, and is highly efficient, considering measurement time, measurement procedures and possibilities for implementation in embedded systems for in-field measurements. In this contribution, we point out the potential, recent advances and future trends of the method to provide insight into the powerfulness of the method for future applications. [ABSTRACT FROM AUTHOR]