bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of photocatalytic-proxone process performance in the degradation of toluene and ethyl benzene from polluted air
Authors: Mehralipour Jamal , Jonidi Jafari Ahmad , Gholami Mitra , Esrafili Ali , Kermani Majid 
Published: March 2023

AbstractIn this study, toluene and ethylbenzene were degraded in the photocatalytic-proxone process using BiOI@NH2-MIL125(Ti)/Zeolite nanocomposite. The simultaneous presence of ozone and hydrogen peroxide is known as the proxone process. Nanocomposite Synthesis was carried out using the solvothermal method. Inlet airflow, ozone concentrations, H2O2 concentrations, relative humidity, and initial pollutants concentrations were studied. The nanocomposite was successfully synthesized based on FT-IR, BET, XRD, FESEM, EDS element mapping, UV–Vis spectra and TEM analysis. A flow rate of 0.1 L min−1, 0.3 mg min−1 of ozone, 150 ppm of hydrogen peroxide, 45% relative humidity, and 50 ppmv of pollutants were found to be optimal operating conditions. Both pollutants were degraded in excess of 95% under these conditions. For toluene and ethylbenzene, the synergistic of mechanisms effect coefficients were 1.56 and 1.76, respectively. It remained above 95% efficiency 7 times in the hybrid process and had good stability. Photocatalytic-proxone processes were evaluated for stability over 180 min. The remaining ozone levels in the process was insignificant (0.01 mg min−1). The CO2 and CO production in the photocatalytic-proxone process were 58.4, 5.7 ppm for toluene and 53.7, and 5.5 ppm for ethylbenzene respectively. Oxygen gas promoted and nitrogen gas had an inhibitory effect on the effective removal of pollutants. During the pollutants oxidation, various organic intermediates were identified.
Post-traumatic stress disorder (PTSD) probability among parents who live in Kandahar, Afghanistan and lost at least a child to armed conflict
Authors: Rahimi Mohammad Paiman , Wafa Mohammad Hashim , Stanikzai Muhammad Haroon , Rahimi Bilal Ahmad 
Published: March 2023

AbstractThe last 4 decades of conflict in Afghanistan resulted in incalculable deaths, injuries, and millions of displacements. Although there are routine reports on casualties of the warfare, the information on its long-term psycho-social sequelae is somehow discounted. This study aimed to assess post-traumatic stress disorder (PTSD) probability and its associated factors among parents who live in Kandahar, the southern province of Afghanistan, and lost at least one child to armed conflict. We conducted a health-facility-based cross-sectional study involving 474 bereaved parents in Kandahar province from November/2020 to January/2021. The questionnaire was composed of sections on socio-demographic characteristics and mental and medical histories of the parent, features of the traumatic event and the time elapsed since then, age and gender of the lost child, and PCL-5. We performed multivariable logistic analysis to determine factors associated with PTSD probability in such parents. A staggering number of the parents (430; 90.72%) scored > 33 on PCL-5 denoting presence of probable PTSD. We noticed that several attributes of the bereaved parents (rural residence [AOR = 3.71 (95% CI 1.37–9.97)], older age [AOR = 2.41 (95% CI 1.03–5.57)], experiencing more than one traumatic event [AOR = 2.91 (95% CI 1.05–7.94)], pre-existing medical condition [AOR = 3.5 (95% CI 1.55–8.05)], and losing a < 5-years-old child [AOR = 2.38 (95% CI 1.16–4.70)] were significantly associated with PTSD probability. We assert that a very high number of bereaved parents are susceptible to probable PTSD. This finding signifies the eminent necessity of mental health services in such settings and provides implicit insights to relevant humanitarian assistance providers.
Mohand homotopy transform scheme for the numerical solution of fractional Kundu–Eckhaus and coupled fractional Massive Thirring equations
Authors: Luo Xiankang , Nadeem Muhammad 
Published: March 2023

AbstractIn this paper, Mohand homotopy transform scheme is introduced to obtain the numerical solution of fractional Kundu–Eckhaus and coupled fractional Massive Thirring equations. The massive Thirring model consists of a system of two nonlinear complex differential equations, and it plays a dynamic role in quantum field theory. We combine Mohand transform with homotopy perturbation scheme and show the results in the form of easy convergence. The accuracy of the scheme is considerably increased by deriving numerical results in the form of a quick converge series. Some graphical plot distributions are presented to show that the present approach is very simple and straightforward.
Altered sialin mRNA gene expression in type 2 diabetic male Wistar rats: implications for nitric oxide deficiency
Authors: Yousefzadeh Nasibeh , Jeddi Sajad , Zarkesh Maryam , Kashfi Khosrow , Ghasemi Asghar 
Published: March 2023

AbstractNitrate therapy has been suggested to boost nitric oxide (NO) levels in type 2 diabetes (T2D); however, little is known about nitrate transport across the membranes. This study aimed to assess changes in the mRNA expression of sialin, as a nitrate transporter, in the main tissues of rats with T2D. Rats were divided into two groups (n = 6/group): Control and T2D. A high-fat diet combined with a low dose of streptozotocin (STZ, 30 mg/kg) was used to induce T2D. At month 6, samples from the main tissues of rats were used to measure the mRNA expression of sialin and levels of NO metabolites. Rats with T2D had lower nitrate levels in the soleus muscle (66%), lung (48%), kidney (43%), aorta (30%), adrenal gland (58%), epididymal adipose tissue (eAT) (61%), and heart (37%) and had lower nitrite levels in the pancreas (47%), kidney (42%), aorta (33%), liver (28%), eAT (34%), and heart (32%). The order of sialin gene expression in control rats was: soleus muscle > kidney > pancreas > lung > liver > adrenal gland > brain > eAT > intestine > stomach > aorta > heart. Compared to controls, rats with T2D had higher sialin mRNA expressions in the stomach (2.1), eAT (2.0), adrenal gland (1.7), liver (8.9), and soleus muscle (3.4), and lower sialin expression in the intestine (0.56), pancreas (0.42), and kidney (0.44), all P values < 0.05. These findings indicate altered sialin mRNA expression in the main tissues of male T2D rats and may have implications for future NO-based treatment of T2D.
Slope monitoring optimization considering three-dimensional deformation and failure characteristics using the strength reduction method: A case study
Authors: Wang Jianxiu , Li HubBoqiang , Jiang Yunhua , Tian Puzhuo , Cao Ansheng , Long Yanxia , Liu Xiaotian , Si Pengfei 
Published: March 2023

AbstractThe potential deformation and failure of a slope with typical 3D shapes involve 3D characteristics, such that these factors cannot be simulated using 2D methods. If 3D characteristics are not considered in expressway slope monitoring, an excessive number of monitoring points may be arranged in the stable/safe part, whereas insufficient monitoring points may be arranged in the unstable/dangerous part. In this study, the 3D deformation and failure characteristics of the Lijiazhai slope of the Shicheng–Ji'an Expressway in Jiangxi Province, China were analyzed by 3D numerical simulations using the strength reduction method. The potential 3D slope surface displacement trends, initial position of failure, and maximum depth of potential slip surface were simulated and discussed. The deformation of Slope A was generally small. The slope ranging from the third platform to the slope top was located in Region I, where the deformation was approximately equal to zero. The deformation of Slope B was located in Region V, where the displacement generally was larger than 2 cm in the range from the first–third platforms to the slope top, and the deformation of the trailing edge exceeded 5 cm. The surface displacement monitoring points should be arranged in Region V. Monitoring was then optimized considering the 3D characteristics of the deformation and failure of a slope. Accordingly, surface and deep displacement monitoring networks were effectively arranged in the unstable/dangerous part of the slope. Results may be used as references for similar projects.
Prediction of prognosis in patients with severe COVID-19 pneumonia using CT score by emergency physicians: a single-center retrospective study
Authors: Oi Yasufumi , Ogawa Fumihiro , Yamashiro Tsuneo , Matsushita Shoichiro , Oguri Ayako , Utada Shusuke , Misawa Naho , Honzawa Hiroshi , Abe Takeru , Takeuchi Ichiro 
Published: March 2023

AbstractWe aimed to develop a method to determine the CT score that can be easily obtained from CT images and examine its prognostic value for severe COVID pneumonia. Patients with COVID pneumonia who required ventilatory management by intubation were included. CT score was based on anatomical information in axial CT images and were divided into three sections of height from the apex to the bottom. The extent of pneumonia in each section was rated from 0 to 5 and summed. The primary outcome was the prediction of patients who died or were managed on extracorporeal membrane oxygenation (ECMO) based on the CT score at admission. Of the 71 patients included, 12 (16.9%) died or required ECMO management, and the CT score predicted death or ECMO management with ROC of 0.718 (0.561–0.875). The death or ECMO versus survival group (median [quartiles]) had a CT score of 17.75 (14.75–20) versus 13 (11–16.5), p = 0.017. In conclusion, a higher score on our generated CT score could predict the likelihood of death or ECMO management. A CT score at the time of admission allows for early preparation and transfer to a hospital that can manage patients who may need ECMO.
Patient-centric synthetic data generation, no reason to risk re-identification in biomedical data analysis
Authors: Guillaudeux Morgan , Rousseau Olivia , Petot Julien , Bennis Zineb , Dein Charles-Axel , Goronflot Thomas , Vince Nicolas , Limou Sophie , Karakachoff Matilde , Wargny Matthieu , Gourraud Pierre-Antoine 
Published: March 2023

AbstractWhile nearly all computational methods operate on pseudonymized personal data, re-identification remains a risk. With personal health data, this re-identification risk may be considered a double-crossing of patients’ trust. Herein, we present a new method to generate synthetic data of individual granularity while holding on to patients’ privacy. Developed for sensitive biomedical data, the method is patient-centric as it uses a local model to generate random new synthetic data, called an “avatar data”, for each initial sensitive individual. This method, compared with 2 other synthetic data generation techniques (Synthpop, CT-GAN), is applied to real health data with a clinical trial and a cancer observational study to evaluate the protection it provides while retaining the original statistical information. Compared to Synthpop and CT-GAN, the Avatar method shows a similar level of signal maintenance while allowing to compute additional privacy metrics. In the light of distance-based privacy metrics, each individual produces an avatar simulation that is on average indistinguishable from 12 other generated avatar simulations for the clinical trial and 24 for the observational study. Data transformation using the Avatar method both preserves, the evaluation of the treatment’s effectiveness with similar hazard ratios for the clinical trial (original HR = 0.49 [95% CI, 0.39–0.63] vs. avatar HR = 0.40 [95% CI, 0.31–0.52]) and the classification properties for the observational study (original AUC = 99.46 (s.e. 0.25) vs. avatar AUC = 99.84 (s.e. 0.12)). Once validated by privacy metrics, anonymous synthetic data enable the creation of value from sensitive pseudonymized data analyses by tackling the risk of a privacy breach.
How the Charter Members of ASHA Responded to the Social and Political Circumstances of Their Time
Authors: Duchan Judith Felson , Hewitt Lynne E. 
Published: March 2023

Purpose:
This article examines the responses of the founders of the American Speech-Language-Hearing Association (ASHA; original name, the American Academy of Speech Correction) to the social trends of their day in the United States. Those trends included migrations from Europe and the rural South, the emergence of new scientific methodologies, and the birth of a professional class. Our aims are to reveal how the founders reacted to these select social changes, to show how their reactions served to shape the newly formed profession in and around 1925, and to describe how that profession is still grappling with their choices even today.

Method:
The writings of the founding members of ASHA were examined for evidence of their views in relation to 20th century historical trends, specifically examining their attitudes toward clients and clinical practice.

Results:
We identified elitist, ethnocentric, racist, regionalist, classist, and ableist statements in the writings of the founders. They promoted practices that denigrated those speaking dialects that were deemed nonstandard, including linguistic patterns originating from ethnic, racial, regional, and class differences. They also used ableist language in writing about people with communication disabilities, adopting a medical model that elevated the professional practitioner over the client.

Conclusions:
Our founders' response to social and political trends led to their creation of oppressive professional practices rather than to work within a more positive social model of professional practice, which was readily available to them at the time, one that would have embraced differences rather than seeking to erase them. Once again, we are experiencing sea changes in our society, ones that offer us the opportunity to reverse the practices shaped by our predecessors. We can learn from the missteps of our founders to create practices that empower and respect those with communication differences or disabilities.

Supplemental Material:

https://doi.org/10.23641/asha.22213738
Taylor‐based adaptive sliding mode control method for robot manipulators
Authors: Fateh Alireza , Momeni Hamidreza , Masouleh Mehdi Tale 
Published: March 2023

AbstractThis paper develops a novel Taylor‐based adaptive sliding mode control method (ASMC) for robot manipulators. In the first new scheme, sliding mode control (SMC) is effectively enhanced using the Taylor expansion for achieving a less conservative sign‐function gain that enables chattering attenuation. After that, a new Taylor‐based adaptive SMC scheme is proposed without prior knowledge of the upper bound of uncertainty and the Taylor expansion coefficients. Then, a new Taylor‐based boundary layer ASMC scheme is proposed for chattering attenuation. As a fact, no chattering is expected to be observed as long as the sliding surface remains an invariant set. However, the sliding surface will not be an invariant set unless the sign‐function is precisely determined on the sliding surface. It is verified that the sign‐function cannot be precisely determined on the sliding surface due to the presence of uncertainty, hence, the chattering phenomenon. In the new Taylor‐based boundary layer ASMC scheme, the conventional ASMC is modified by removing the sign‐function in the vicinity of the sliding surface and using the Taylor expansion to estimate and compensate for the uncertainty. Compared to a time‐delay ASMC applied to a robot manipulator, the Taylor‐based ASMC scheme exhibits a less conservative sign‐function gain resulting in chattering attenuation.
Photovoltaic model parameters identification using an innovative optimization algorithm
Authors: El‐Dabah Mahmoud A. , El‐Sehiemy Ragab A. , Hasanien Hany M. , Saad Bahaa 
Published: March 2023

AbstractAs it tackles electrical and non‐electrical losses, the triple‐diode model (TDM) of photovoltaic (PV) cells is highly exact. This paper employs a novel optimization method known as the innovative optimization algorithm (INFO) technique to correctly estimate the electrical characteristics of such TDM. To shift agents towards a better position, the INFO algorithm exploits the concept of weighted mean. The primary goal of INFO is to stress its performance features to solve some optimization difficulties that other approaches cannot effectively solve. In this paper, the objective function based on a combination of the absolute value of the current error, its squared value, and its quadrable value is employed, which the INFO optimizer minimizes to predict the optimum parameters of such TDM precisely. The proposed INFO algorithm is carried out on multi‐ and mono‐crystalline varieties, such as the Kyocera KC200GT and the Canadian Solar CS6K‐280 M. The simulation outcomes demonstrate the INFO's ability to extract the model parameters precisely. The INFO achieved the lowest ideal fitness values of 9.0738 × 10−06 and 5.7356 × 10−05 for the KC200GT and Canadian Solar CS6K‐280 M, respectively, throughout the optimization procedure. Under various environmental circumstances, experimental validation of the calculated parameters using the (INFO) optimizer is carried out, and the results are compared to the observed values from the laboratory experiments. The simulation results demonstrate the INFO's convergence time and accuracy advantage over competing optimization techniques. Additionally, statistical analysis shows that the INFO optimizer is resilient.
A novel automated demand response control using fuzzy logic for islanded battery‐operated rural microgrids
Authors: Azeem Fawad , Memon Zulfiqar Ali , Baig Sobia , Manzoor Tareq , Abbas Faisal , Shah Mohd Asif 
Published: March 2023

AbstractIslanded rural microgrid require continuous resource monitoring. Demand response schemes have been phenomenal in managing loads. However, urban demand response schemes are well equipped with market prices and peak time penalties to control deferrable loads. In rural microrids, regular loads such as fans, lights and water pumps are normally used that do not fall under category of deferrable loads. In addition, full liberty of utilizing regular load at any time, lack of awareness and no information of storage reserves make task of load management more complex. In this research fully automated two layered demand response scheme is designed for regular operating loads. The first layer control is load mode control. The mode of operation is decided on the state of charge (SoC) of battery. In second layer, fuzzy controller is designed on the consumer's routines, SoC and ambient temperature as membership function. Results are assessed in terms of consumers comfort and availablity of SoC. The load operation in automated demand response remained indentical to actual rutine operation as per consumer's desire with 5 to 7% deviation. In all modes of operation SoC levels remained 15% higher and heavy load operated 13.5% more compare to relevant study.
Robust networked power system load frequency control against hybrid cyber attack
Authors: Lv Xinxin , Sun Yonghui , Dinavahi Venkata , Zhao Xinlong , Qiao Feng 
Published: March 2023

AbstractModern network and communication technologies are essential for the implementation and operation of load frequency control (LFC) systems. The measurements of crucial LFC system parameters will be compromised by attackers, rendering data received by the defence inaccurate and causing frequency fluctuations or even system collapse. To detect the potential attack on measured data and keep the LFC performance, an adaptive event‐triggered scheme with fractional order global sliding mode control scheme is proposed in this paper. Furthermore, Markov theory is employed for the modelling process with energy storage to present a multi‐area LFC power system considering renewable energy and hybrid cyber attacks. Stability and stabilisation criteria are built by employing improved Lyapunov stability theory and second‐order Bessel‐Legendre inequality. Finally, a two‐area LFC system under hybrid cyber attacks and a modified IEEE 39‐bus New England test power system with 3 wind farms are simulated to explore the efficacy of the proposed method.
An embedded and intelligent anomaly power consumption detection system based on smart metering
Authors: Lazim Qaddoori Sahar , Ali Qutaiba Ibrahim 
Published: March 2023

AbstractUser behaviour, human mistakes, and underperforming equipment contribute to wasted energy in buildings and industries. Identifying anomalous consumption power behaviour can help to reduce peak energy usage and change undesirable user behaviour. Furthermore, decreasing energy consumption in buildings is difficult because usage patterns vary from one building to the next. So, the main contribution in this manuscript is to propose a lightweight architecture for smart meter to identify abnormalities in power consumption for each building individually using machine learning (ML) models and implement on a Single Board Computer. To detect daily and periodic pattern anomalies, two models of anomaly detection based on supervised and unsupervised ML algorithms are built and trained where numerous algorithms were utilised to select the best algorithm for each model. Also, the proposed approach enables iterative procedure modifications by retraining the two anomaly detection models on data aggregator server based on the received data meter from the specific smart meter to give better power service to clients while minimising provider losses. The effectiveness and efficiency of the suggested approach have been proven through extensive analysis.
Was Homöopathie in einem Fall von akuter Pankreatitis beim
Hund zu leisten vermag – ein Fallbericht
Authors: Jürgens Ellen 
Published: March 2023

ZusammenfasssungEs wird ein Hund vorgestellt, der unter einer Protein-losing enteropathy und
Pankreatitis leidet. Aus einem Zustand der totalen Schwäche heraus wird er
mithilfe von Q-Potenzen und organotropen homöopathischen Arzneimitteln vor
der drohenden Euthanasie bewahrt.
Hypertensive Disorders of Pregnancy and the Cardiovascular System: Causes, Consequences, Therapy, and Prevention
Authors: Baschat Ahmet A. , Darwin Kristin , Vaught Arthur J. 
Published: March 2023

Hypertensive disorders of pregnancy continue to be significant contributors to adverse perinatal outcome and maternal mortality, as well as inducing life-long cardiovascular health impacts that are proportional to the severity and frequency of pregnancy complications. The placenta is the interface between the mother and fetus and its failure to undergo vascular maturation in tandem with maternal cardiovascular adaptation by the end of the first trimester predisposes to hypertensive disorders and fetal growth restriction. While primary failure of trophoblastic invasion with incomplete maternal spiral artery remodeling has been considered central to the pathogenesis of preeclampsia, cardiovascular risk factors associated with abnormal first trimester maternal blood pressure and cardiovascular adaptation produce identical placental pathology leading to hypertensive pregnancy disorders. Outside pregnancy blood pressure treatment thresholds are identified with the goal to prevent immediate risks from severe hypertension >160/100 mm Hg and long-term health impacts that arise from elevated blood pressures as low as 120/80 mm Hg. Until recently, the trend for less aggressive blood pressure management during pregnancy was driven by fear of inducing placental malperfusion without a clear clinical benefit. However, placental perfusion is not dependent on maternal perfusion pressure during the first trimester and risk-appropriate blood pressure normalization may provide the opportunity to protect from the placental maldevelopment that predisposes to hypertensive disorders of pregnancy. Recent randomized trials set the stage for more aggressive risk-appropriate blood pressure management that may offer a greater potential for prevention for hypertensive disorders of pregnancy.
Key Points