bluuebunny/crossref_metadata_2025_split huggingface dataset:
Selection of a stealthy and harmful attack function in discrete event systems
Authors: Zhang Qi , Seatzu Carla , Li Zhiwu , Giua Alessandro 
Published: September 2022

AbstractIn this paper we consider the problem of joint state estimation under attack in partially-observed discrete event systems. An operator observes the evolution of the plant to evaluate its current states. The attacker may tamper with the sensor readings received by the operator inserting dummy events or erasing real events that have occurred in the plant with the goal of preventing the operator from computing the correct state estimation. An attack function is said to be harmful if the state estimation consistent with the correct observation and the state estimation consistent with the corrupted observation satisfy a given misleading relation. On the basis of an automaton called joint estimator, we show how to compute a supremal stealthy joint subestimator that allows the attacker to remain stealthy, no matter what the future evolution of the plant is. Finally, we show how to select a stealthy and harmful attack function based on such a subestimator.
Fuzzy-clustering and fuzzy network based interpretable fuzzy model for prediction
Authors: Wang Xiaowei , Chen Yanqiao , Jin Jiashan , Zhang Baohua 
Published: September 2022

AbstractInterpretability is the dominant feature of a fuzzy model in security-oriented fields. Traditionally fuzzy models based on expert knowledge have obtained well interpretation innately but imprecisely. Numerical data based fuzzy models perform well in precision but not necessarily in interpretation. To utilize the expert knowledge and numerical data in a fuzzy model synchronously, this paper proposed a hybrid fuzzy c-means (FCM) clustering algorithm and Fuzzy Network (FN) method-based model for prediction. The Mamdani rule-based structure of the proposed model is identified based on FCM algorithm from data and by expert-system method from expert knowledge, both of which are combined by FN method. Particle swarm optimization (PSO) algorithm is utilized to optimize the fuzzy set parameters. We tested the proposed model on 6 real datasets comparing the results with the ones obtained by using FCM algorithm. The results showed that our model performed best in interpretability, transparency, and accuracy.
Changes in preterm birth and birthweight during the SARS-CoV-2 pandemic: a nationwide study in South Korea
Authors: Hwang Jeongeun , Moon Seokjoo , Cho Kyu-Dong , Oh Min-Jeong , Hong Su Jung , Cho Geum Joon 
Published: September 2022

AbstractBirthweight is a strong determinant of a neonate’s health. The SARS-CoV-2 pandemic’s impact on birthweight has not been investigated in-depth, with inconsistent conclusions from initial studies. To assess changes in preterm birth and inappropriate birthweight between the SARS-CoV-2 pandemic and pre-pandemic periods. A nationwide birth micro-data consisted with exhaustive census of all births in 2011–2020 in South Korea was accessed to examine whether the mean birthweight and rates of under/overweight births changed significantly during the SARS-CoV-2 pandemic year (2020) compared to those of the pre-pandemic period (2011–2019). A total of 3,736,447 singleton births were analyzed. Preterm birth was defined as < 37 weeks of gestation. Low birthweight (LBW) and macrosomia were defined as birthweights < 2.5 kg and ≥ 4.0 kg, respectively. Small for gestational age (SGA) and large for gestational age (LGA) were defined as birthweights below the 10th and above 90th percentiles for sex and gestational age, respectively. Inappropriate birthweight was defined as one or more LBW, macrosomia, SGA, or LGA. Generalized linear models predicted birth outcomes and were adjusted for parental age and education level, marital status, parity, gestational age, and months from January 2011. There were 3,481,423 and 255,024 singleton births during the pre-pandemic and pandemic periods, respectively. Multivariable generalized linear models estimated negative associations between the pandemic and preterm birth (odds ratio [OR], 0.968; 95% confidence interval [CI] 0.958–0.978), LBW (OR: 0.967, 95% CI 0.956–0.979), macrosomia (OR: 0.899, 95% CI 0.886–0.912), SGA (OR: 0.974, 95% CI 0.964–0.983), LGA (OR: 0.952, 95% CI 0.945–0.959), and inappropriate birthweight (OR: 0.958, 95% CI 0.952–0.963), indicating a decline during the pandemic compared to pre-pandemic period. An 8.98 g decrease in birthweight (95% CI 7.98–9.99) was estimated during the pandemic. This is the largest and comprehensive nationwide study to date on the impact of the SARS-CoV-2 pandemic on preterm birth and inappropriate birthweight. Birth during the pandemic was associated with lower odds of being preterm, underweight, and overweight. Further studies are required to understand the dynamics underlying this phenomenon.
The compliance of head-mounted industrial PPE by using deep learning object detectors
Authors: Isailovic Velibor , Peulic Aleksandar , Djapan Marko , Savkovic Marija , Vukicevic Arso M. 
Published: September 2022

AbstractThe compliance of industrial personal protective equipment (PPE) still represents a challenging problem considering size of industrial halls and number of employees that operate within them. Since there is a high variability of PPE types/designs that could be used for protecting various body parts and physiological functions, this study was focused on assessing the use of computer vision algorithms to automate the compliance of head-mounted PPE. As a solution, we propose a pipeline that couples the head ROI estimation with the PPE detection. Compared to alternative approaches, it excludes false positive cases while it largely speeds up data collection and labeling. A comprehensive dataset was created by merging public datasets PictorPPE and Roboflow with author’s collected images, containing twelve different types of PPE was used for the development and assessment of three deep learning architectures (Faster R-CNN, MobileNetV2-SSD and YOLOv5)—which in literature were studied only separately. The obtained results indicated that various deep learning architectures reached different performances for the compliance of various PPE types—while the YOLOv5 slightly outperformed considered alternatives (precision 0.920 ± 0.147, and recall 0.611 ± 0.287). It is concluded that further studies on the topic should invest more effort into assessing various deep learning architectures in order to objectively find the optimal ones for the compliance of a particular PPE type. Considering the present technological and data privacy barriers, the proposed solution may be applicable for the PPE compliance at certain checkpoints where employees can confirm their identity.
Ultra-fast green microwave assisted synthesis of NaFePO4-C nanocomposites for sodium ion batteries and supercapacitors
Authors: Wazeer Wael , Nabil Marwa M. , Feteha Mohamed , Soliman Moataz B. , Kashyout Abd El-Hady B. 
Published: September 2022

AbstractSodium ion batteries are favored in stationary and large scale power storage due to their low cost and nontoxicity. As the lithium is replaced with sodium due to the cost motive, a cheap processing method is needed to maintain the cell price as low as possible. We report an ultra-fast synthesis method that utilizes the high microwave absorbance of silicon carbide content in rice straw ash. Amorphous/maricite mixtures of sodium iron phosphates-carbon composites (NaFePO4-C) are synthesized, crystallized, and carbon coated using one-step microwave heating. The sodium ion electroactive composites are prepared using different microwave heating durations ranging from 30 to 100 s. High purity inert gases are not needed during synthesis, processing, and even at cell assembly. The materials are characterized by elemental analysis techniques, X-ray diffraction (XRD), scanning/transmission electron microscope (SEM/TEM), and Raman spectroscopy. The electrochemical performance of the synthesized nanocomposites is examined as sodium ion battery cathode and as symmetric supercapacitors. The optimum synthesis time is 60 s for the application as sodium ion batteries and as a supercapacitor. The maximum specific capacity is 108.4 mA h g−1 at 0.2 C in the case of using it as a battery cathode. While the capacitance is 86 F g−1 at 0.5 A g−1 as a supercapacitor. The capacity retention is 92.85% after 40 cycles at 0.2 C as sodium ion battery electrode. For supercapacitor, the capacity retention is 81.7% after 1000 cycles.
Extraction of sensing data for desired scent impressions using mass spectra of odorant molecules
Authors: Debnath Tanoy , Nakamoto Takamichi 
Published: September 2022

AbstractMost of the olfactory perception works focused on forward prediction of odor impression, for example, given an odorant’s molecular structure parameters or the sensing data predict its odor impression. So far, mapping of mass spectrum of odorant molecules into the odor perception space (binary or continuous sensory space) has been successfully performed. However, it is difficult to predict odorant’s sensing data associated with binary odor descriptors (e.g., minty, peach, vanilla etc.). In this study, we have proposed a method to extract the corresponding sensing data (mass spectrum as sensing data) for a desired scent impression although one-to-one relationships are not usually guaranteed. Our target is to extract the sensing data for a given odor descriptor that will help perfumers to create scent. This study is first report for predicting sensing data for a given binary odor descriptor.
Variability of coil inductance measurements inside an interleaving structure
Authors: Mocholí Antonio , Mocholí Ferran , Milián-Sánchez Víctor , Guerra-Carmenate José , Iglesias-Martínez Miguel E. , Fernández de Córdoba Pedro , Castro-Palacio Juan C. , Sahu Sarira , Monsoriu Juan A. , Lorduy María , Gallardo Sergio , Verdú Gumersindo , Kolombet Valeriy A. , Panchelyuga Victor A. 
Published: September 2022

AbstractThe present article is a continuation of our previous works on the anomalies in the decay rates and the capacitance measurements inside a modified Faraday cage. Here we present the anomalous variations in the measurements of inductance when a coil is placed inside an interleaving structure of metal and organic material. The fluctuation in the inductance values was found to be in the range − 0.007 to 0.018 mH. Additionally, it was observed that the temperature coefficient which was 0.0062 mH/°C initially jumped to two distinct levels, 0.0095 mH/°C and 0.0145 mH/°C, respectively. A multiple factor analysis of our results revealed a very strong correlation (R2 = 95.2%) between the inductance and the combination of the temperature and the relative humidity both measured inside the cage, next to the inductor.
Deep language algorithms predict semantic comprehension from brain activity
Authors: Caucheteux Charlotte , Gramfort Alexandre , King Jean-Rémi 
Published: September 2022

AbstractDeep language algorithms, like GPT-2, have demonstrated remarkable abilities to process text, and now constitute the backbone of automatic translation, summarization and dialogue. However, whether these models encode information that relates to human comprehension still remains controversial. Here, we show that the representations of GPT-2 not only map onto the brain responses to spoken stories, but they also predict the extent to which subjects understand the corresponding narratives. To this end, we analyze 101 subjects recorded with functional Magnetic Resonance Imaging while listening to 70 min of short stories. We then fit a linear mapping model to predict brain activity from GPT-2’s activations. Finally, we show that this mapping reliably correlates ($$\mathcal {R}=0.50, p<10^{-15}$$R=0.50,p<10-15) with subjects’ comprehension scores as assessed for each story. This effect peaks in the angular, medial temporal and supra-marginal gyri, and is best accounted for by the long-distance dependencies generated in the deep layers of GPT-2. Overall, this study shows how deep language models help clarify the brain computations underlying language comprehension.
Safety and outcomes of short-term use of peripheral vasoactive infusions in critically ill paediatric population in the emergency department
Authors: Yeong Y. Q. , Chan J. M. F. , Chan J. K. Y. , Huang H. L. , Ong G. Y. 
Published: September 2022

AbstractEarly restoration of oxygen delivery to end organs in paediatric patients experiencing shock states is critical to optimizing outcomes. However, obtaining central access in paediatric patients may be challenging in non-intensive care settings. There is limited literature on the use of peripheral vasoactive infusions in the initial resuscitation of paediatric patients in the emergency department. The aims of this study were to report the associated complications of peripheral vasoactive infusions and describe our local experience on its use. This was a single-centre, retrospective study on all paediatric patients who received peripheral vasoactive infusions at our paediatric emergency department from 2009 to 2016. 65 patients were included in this study. No patients had any local or regional complications. The mean patient age was 8.29 years old (± 5.99). The most frequent diagnosis was septic shock (45, 69.2%). Dopamine was the most used peripheral vasoactive agent (71.2%). The median time to central agents was 2 h (IQR 1–4). 16(24.2%) received multiple peripheral infusions. We reported no complications of peripheral vasoactive infusions. Its use could serve as a bridge till central access is obtained. Considerations on the use of multiple peripheral vasoactive infusions in the emergency department setting needs further research.
Assessing momentary relaxation using the Relaxation State Questionnaire (RSQ)
Authors: Steghaus Sarah , Poth Christian H. 
Published: September 2022

AbstractStress is ubiquitous in everyday life and hazardous for mental and physical health. To prevent or ameliorate stress-related disease, relaxation exercises aim to counteract stress by inducing short-lasting states of relaxation on a regular basis. Critically, current assessments capture the mid- and long-term consequences of relaxation, however, cannot measure its short-term effects on an individual’s momentary psychological state. To address this problem, we developed the Relaxation State Questionnaire (RSQ). We assessed the psychometric quality of the questionnaire by investigating its item properties, reliability, and validity in an online study with 92 participants. Construct validity was examined through correlations with the Perceived Stress Questionnaire (PSQ; Fliege in https://doi.org/10.23668/PSYCHARCHIVES.2889, 2009). An exploratory factor analysis revealed four factors capturing the momentary state of muscle tension, sleepiness, cardiovascular activity, and general relaxation. In a second online study with 99 participants, we conducted a confirmatory factor analysis. Results revealed high item loadings (0.70–0.91), excellent reliability (α = 0.86) and excellent fit indices, and a good construct validity of the RSQ. These findings establish the RSQ as a tool to measure momentary states of relaxation. As such, the RSQ opens up research of the immediate subjective effects and the effectiveness of relaxation exercises.
Varactor-tuned wideband band-pass filter for 5G NR frequency bands n77, n79 and 5G Wi-Fi
Authors: Golestanifar Alireza , Karimi Gholamreza , Lalbakhsh Ali 
Published: September 2022

AbstractA wide-band band-pass filter (BPF) using coupled lines, rectangular stubs and Stepped-Impedance Resonators (SIRs) is presented in this paper. The proposed BPF operates over a large pass-band from 3.15 to 6.05 GHz covering 5G New Radio (NR) frequency Bands n77, n79 and 5G Wi-Fi, which includes the G band of US (3.3 to 4.2 GHz), 5G band of Japan (4.4 to 5 GHz) and 5G Wi-Fi (5.15 to 5.85 GHz). The presented filter has a maximum pass-band Insertion-Loss (IL) of 2 dB, a sharp roll-off rate and suppresses all the unwanted harmonics from 4.2 GHz up to 12 GHz with a 15 dB attenuation level. The performance of each section can be analyzed based on lumped-element circuit models. The electrical size of the BPF is 0.258 λg × 0.255 λg, where λgis the guided wavelength at the central frequency. The design accuracy is verified through implementing and testing the final BPF. The pass-band band-width can be controlled by adding the varactor diodes. A good relationship between the band-width and the varactor diodes are extracted by the curve fitting technique.
Synthesis, characterization and application of high adsorption performance of novel 1,4-polyketone
Authors: Sayed Marwa M. , Abd El-Hamid Islam S. , M. El-Bery Haitham , Farrag Mostafa , Abdelhakiem Alaa K. , Aly Kamal I. 
Published: September 2022

AbstractThis study aims to develop an alternating polyketone containing cationic groups in one and four alternating positions for increased functionality. A novel polyarylidene ketone was synthesized using simple condensation polymerization of terephthaldehyde and 2,5-hexane dione (PAK) The physicochemical properties of the resulting polymer were evaluated using Fourier-transform infrared spectroscopy, thermogravimetric analysis, X-ray diffraction, UV-Visible absorbance, fluorescence, and SEM investigations. The findings show that the polymer is amorphous, has good thermal stability, and emits red light. It can also be used as a dye adsorbent in aqueous solutions, with high selectivity for the cationic dye methylene blue (MB). The adsorbent efficiency of PAK was measured as a function of pH, dosage, and initial dye concentration; the greatest dye removal of 96 % was obtained at pH 10, 50 mg dosage, and initial dye concentration of 20 ppm. Kinetics and isotherms were studied, showing that the pseudo-second-order model described kinetic data better than Freundlich and Langmuir and revealed a satisfactory chemisorption process. This study suggests that PAK can purify MB dyeing wastewater, remove Zn2+, Cu2+, Ni2+, Co2+, Cd2+, Fe3+ metal ions well, and is selective for Fe3+ and Cu2+; ion adsorption is chelating-based.
Prevalence of cardiovascular risk factors in active tuberculosis in Africa: a systematic review and meta-analysis
Authors: Baluku Joseph Baruch , Ronald Olum , Bagasha Peace , Okello Emmy , Bongomin Felix 
Published: September 2022

AbstractPeople with tuberculosis (TB) are at risk of major adverse cardiovascular events. We estimated the prevalence of cardiovascular risk (CVR) factors among people with active TB in Africa. This was a systematic review and meta-analysis of studies from Africa. We searched EMBASE, MEDLINE through PubMed, Web of Science, the Cochrane Central Register of Controlled Trials, mRCTs, Clinical trials.gov, and International Clinical Trials Registry Platform from inception to 31st December 2021. Among 110 eligible studies, 79 (238,316 participants) were included in the meta-analysis for smoking, 67 (52,793 participants) for current alcohol use, 30 (31,450 participants) for hazardous alcohol use, 51 (37,879 participants) for diabetes mellitus (DM), 19 (18,211 participants) for hypertension and 18 (13,910 participants) for obesity. The pooled prevalence was 26.0% (95% confidence interval 22.0–29.0) for smoking, 30.0% (25.0–35.0) for any current alcohol use, 21.0% (17.0–26.0) for hazardous alcohol use, 14.0% (9.0–18.0) for hypertension, 7.0% (6.0–9.0) for DM, and 4.0% (2.0–5.0) for obesity. Cost-effective strategies are needed to screen for CVR factors among people with active TB in Africa.
Sharpening Our Tools: A Systematic Review to Identify Diagnostically Accurate Language Sample Measures
Authors: Ramos Michelle N. , Collins Penelope , Peña Elizabeth D. 
Published: September 2022

Purpose:
This systematic review provides a comprehensive summary of the diagnostic accuracy of English language sample analysis (LSA) measures for the identification of developmental language disorder.

Method:
An electronic database search was conducted to identify English publications reporting empirical data on the diagnostic accuracy of English LSA measures for children aged 3 years or older.

Results:
Twenty-eight studies were reviewed. Studies included between 18 and 676 participants ranging in age from 3;0 to 13;6 (years;months). Analyzed measures targeted multiple linguistic domains, and diagnostic accuracy ranged from less than 25% to greater than 90%. Morphosyntax measures achieved the highest accuracy, especially in combination with length measures, and at least one acceptable measure was identified for each 1-year age band up to 10 years old.

Conclusion:
Several LSA measures or combinations of measures are clinically useful for the identification of developmental language disorder, although more research is needed to replicate findings using rigorous methods and to explore measures that are informative for adolescents and across diverse varieties of English.

Supplemental Material:

https://doi.org/10.23641/asha.21183247
Optimal control and stabilization for NCSs with multiple memoryless channels and hold‐input compensation
Authors: Li Xueyang , Han Chunyan , Wang Wei 
Published: September 2022

AbstractThis paper investigates the optimal control problem for networked control systems over multiple Markovian packet loss channels under hold‐input compensation strategy. In this situation, the actuator receives the control signals from the controller via the individual channels. The system is transformed into a Markovian jump linear system by introducing a new Markovian jump variable. By giving a new maximum principle for such a system, a coupled difference Riccati‐type equation is developed, which in turn gives necessary and sufficient conditions for the solvability of optimal control problems in the finite horizon. Furthermore, for the infinite horizon case, the Markovian jump linear system is mean square stabilizable if and only if a set of coupled algebraic Riccati‐type equation has a particular solution. Finally, numerical simulations are presented to illustrate the control effects of the proposed optimal controllers.
Fuzzy model based fault estimation and fault tolerant control for flexible spacecraft with unmeasurable vibration modes
Authors: Li Yanbo , Xu Wei , Chang Lin 
Published: September 2022

AbstractThis paper investigates the problem of anti‐disturbance fault estimation and attitude tracking fault tolerant control for a flexible spacecraft subject to actuator faults, external disturbances, input saturation, and configuration misalignment. Different form the traditional methods, both the nonlinear dynamics subsystem and attitude control system are reconstructed into Takagi–Sugeno fuzzy models, where partial nonlinear term is remained to assist the design of fuzzy controller. A fuzzy fault estimation observer with proportional–integral adaptive laws is first designed. Without measuring any dynamic information of flexible appendages, estimated values of unknown actuator faults and vibration disturbances of flexible appendages can be obtained simultaneously. This is the most important advantage of the proposed fault estimation scheme over the previous methods. Then, a fuzzy sliding mode fault tolerant control scheme, based on fewer fuzzy rules and less computational burden, is developed under the framework of feedback linearisation and feedforward compensation. The actuator faults and vibration disturbances are counteracted in real time. Regional pole placement and virtual controller with input saturation are adopted to tune the control input and avoid the radical control torque scheduling. Finally, numerical simulations are given to illustrate the validity of the proposed fault estimation and fault tolerant control strategies.