bluuebunny/crossref_metadata_2025 huggingface dataset:
Constructing a Triangle Ensemble of Pt Clusters for Enhanced Direct-Pathway Electrocatalysis of Formic Acid Oxidation
Authors: Li Cheng , Tang Zheng , Shi Lanlan , Li Yongjia , Ji Yingjie , Zhang Kaixin , Yang Zhiyu , Yan Yi-Ming
Published: July 2023

The pursuit of operational advancements in direct formic acid fuel cells (DFAFCs) necessitates the development of high-performance platinum (Pt)-based catalysts for formic acid electrooxidation (FAOR). However, FAOR on Pt-based catalysts follows a dual pathway mechanism, in which the direct pathway is a preferred route due to its efficient dehydrogenation process. Conversely, the indirect pathway results in the generation of adsorbed CO species, a process that deleteriously poisons the active sites of the catalyst, with CO species only being oxidizable at higher potentials, causing a significant compromise in catalyst performance. Herein, we have successfully synthesized Pt-C3N4@CNT, where three Pt clusters are precisely dispersed in a triplet form within the C3N4 by virtue of the unique structure of C3N4. The mass activity for the direct pathway (0.44 V) delivered a current density of 1.91 A mgPt−1, while the indirect pathway (0.86 V) had no obvious oxidation peak. The selectivity of Pt-C3N4@CNT catalysts for the direct pathway of FAOR was improved due to the special structure of C3N4, which facilitates the dispersion of Pt tri-atoms in the structure and the electronic interaction with Pt. In this study, we provide a new strategy for the development of highly active and selective catalysts for DFAFCs.
Self-Compassion and Depressive Symptoms as Determinants of Sensitive Parenting: Associations with Sociodemographic Characteristics in a Sample of Mothers and Toddlers
Authors: Zvara Bharathi J. , Keim Sarah A. , Andridge Rebecca , Anderson Sarah E.
Published: July 2023

Parenting that is sensitive and responsive to children’s needs has been shown to support children’s optimal growth and development in many cultural contexts. Numerous studies suggest that self-compassion is positively related to sensitive parenting. Despite growing research interest linking self-compassion to responsive parenting, there are considerable gaps in the literature. The current study examined the associations between self-compassion, depressive symptoms, socioeconomic status, and sensitive parenting. Data was obtained from a cohort study of 300 families in central Ohio enrolled when children were a mean (SD) calendar age of 18.2 (0.7) months. Children of all gestational ages at birth are included, and 37% were born preterm (<37 weeks’ gestation). Observational protocols were used to determine maternal sensitivity in a semi-structured play setting. Self-compassion was assessed with the Self-Compassion Scale when children were 24 months old. Self-compassion was not associated with sociodemographic characteristics including maternal education, household income, child sex and gestational age. In unadjusted regression models, depressive symptoms were related to sensitive parenting (B = −0.036, SE = 0.016, p = 0.03), but self-compassion was not a statistically significant predictor (p = 0.35) of sensitivity, and neither self-compassion nor depressive symptoms were statistically significant predictors of sensitive parenting after adjustment for covariates. Considerations for future studies are discussed.
The Role of Working Memory in Early Literacy and Numeracy Skills in Kindergarten and First Grade
Authors: Shvartsman Marina , Shaul Shelley
Published: July 2023

The working memory system supports learning processes such as acquiring new information and the development of new skills. Working memory has been found to be related to both early literacy and early numeracy in kindergarten and to linguistic and mathematical academic skills at older ages, but the contribution of each of the memory components at these ages is not yet clear. The purpose of this study is to examine the unique connections among the various systems of WM, early literacy, and early numeracy using various assessment tests of simple WM and complex WM, as well as a variety of tasks in math and language skills administered to the same 250 children in kindergarten and 150 children in first grade. Consistent with the predictions, significant relations among all components of memory and mathematics and language knowledge at both ages were found, although these connections were differential for the different types of tasks and memory systems. The connection of complex WM was stronger in its contribution and more significant in first grade in both mathematics and language domains. Complex WM resources were more important in early literacy at kindergarten age, while simple WM seems to be important in early numeracy. The theoretical and educational implications of these results are discussed accordingly.
Exploring Co-Regulation-Related Factors in the Mothers of ADHD Children—Proof of Concept Study
Authors: Yaacoby-Vakrat Ruth , Pade Margalit , Bar-Shalita Tami
Published: July 2023

Background: Attention deficit hyperactivity disorder (ADHD) is a complex neurological condition interfering with family relationships and co-regulation capabilities. Therefore, exploring factors underpinning parental co-regulation ability is crucial for future fostering relationships in families of children with ADHD. Objective: This preliminary study aims to characterize and compare the executive-functions, anxiety, self-efficacy, and sensory modulation in mothers of children with and without ADHD. Method: Mothers of children with (study group) and without (control-comparison, group) ADHD completed online self-reports, measuring executive-functions; parental self-efficacy; anxiety; and sensory modulation. Results: The study group (N = 40) had lower self-efficacy compared to the control group (N = 27; p = 0.018), and the control group had lower sensory responsiveness (p = 0.025). Within both groups the Behavior Rating Inventory of Executive Function-Adult (BRIEF-A) Global Executive Function Composite score (GEC) and the Beck Anxiety Inventory (BAI) were moderately correlated. Further, within the study group correlations were found between the BRIEF-A-GEC and the Sensory Responsiveness Questionnaire (SRQ)-Aversive scores (r = 0.37, p ≤ 0.01), and between the BRIEF-A Behavioral-Rating-Index and the parental self-efficacy scores (r = 0.31, p ≤ 0.05). Within the control group, negative correlations were found between the BRIEF-A-GEC and SRQ-Hedonic scores (r= −0.44, p < 0.05). Conclusion: Self-efficacy, executive-functions, high sensory responsiveness and anxiety traits are interwoven and may impact parental co-regulation ability.
A Systematic Literature Review of the Teaching Considerations and Practices Provided to Children in an Education Setting with Comorbid Disability and Developmental Trauma
Authors: Collier Simone , Bryce India
Published: July 2023

Developmental trauma and disability are frequently co-occurring lived experiences for children and young people. The present research explores the considerations and practices for pedagogy provided to children with a disability and who have experienced developmental trauma in an educational setting. A systematic literature review was conducted to explore and synthesise the current evidence base that exists relating to the considerations for quality teaching practice for this cohort of students within schools. Findings revealed five key themes, which contribute to an understanding of considerations and practices for teaching students with childhood trauma experiences whilst considering an additional dimension intersecting with disabilities including mental ill-health. The findings of this study broaden the understanding of the complexities facing the education sector in ensuring inclusion principles are enacted to increase impact and improve outcomes for these students with multiple and complex needs.
Health Outcomes of Judo Training as an Organized Physical Activity for Children and Adolescents: A Literature Review
Authors: Kowalczyk Monika , Zgorzalewicz-Stachowiak Małgorzata , Kostrzewa Maciej
Published: July 2023

Judo, an organized physical activity for children and adolescents, has gained popularity worldwide. Physical activity is vital during times of rising obesity and a sedentary lifestyle in this age group. The article aims to review the current knowledge of the health benefits of judo-specific exercises for children and youth. Six international scientific databases (PubMed, Scopus, UpToDate, Web of Science, EBSCOhost, and Google Scholar) were searched from 1 January 2007 to 30 September 2022. The search focused on health-related factors regarding healthy preschool and school-aged judo practitioners. Sixteen original studies met the inclusion criteria. School-aged children aged 7–15 years were included in the analysis. The average training time was between two and six hours a week, with the judo intervention mainly ranging from nine months to three years. Most studies registered positive changes caused by judo training. The outcomes focused on maintaining or reducing body fat, increasing bone mineralization, and improving the function of the cardiorespiratory system compared to the non-practicing control group. However, there were no differences between judo and other sports groups. The main conclusions presented health benefits from judo-specific training in school-aged children and may support the World Health Organization recommendations concerning daily physical activity.
Potential Role of Occupational Therapist Intervention in Elementary School for Children with Additional Support Needs: A Systematic Review
Authors: Seoane-Martín Marta Elisa , Rodríguez-Martínez María Carmen
Published: July 2023

(1) Background: The main activity children engage with is learning through play or formal education. The aim of this systematic review is to analyze the role of occupational therapy in the school setting for children with additional support needs or disabilities. (2) Method: We conducted a systematic review using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. This systematic review was registered in PROSPERO (CDR42022314271). The search was performed in the following databases: ERIC, Dialnet Plus, PubMed, OTseeker, Cochrane, Scopus, CINAHL, and PsycINFO. (3) Results: In total, 1954 studies were identified, from which 18 articles were selected. These studies were heterogeneous and showed different types of intervention of the occupational therapist in school environments. (4) Conclusions: The main conclusions highlighted the effectiveness of the occupational therapist within the school environment, the importance of an interdisciplinary team to cover the special needs students within the school and the need for intrinsic motivation for an active and inclusive participation of the students with special needs. However, there is a need for more homogeneous studies with a larger sample size that specifically focus on the school context and include the involvement of occupational therapists in order to replicate the findings obtained.
Influence of NaCl Solution External Erosion on Corrosion Resistance of RPC Reinforced with Straw Fiber
Authors: Cao Zihao , Wang Kewei , Peng Xi , Wang Hui , Huang Rongming
Published: July 2023

Straw fiber, as a kind of waste if not properly treated, will pollute the environment. It can be used in cement-based materials as a plant fiber material. Agricultural solid-waste straw fiber has good tensile properties and is expected to be used as a fiber-reinforced material for reactive powder concrete (RPC) and to improve the corrosion resistance of RPC. In this paper, the ultrasonic velocity through specimens, the electrical resistance, the AC impedance spectroscopy and tafel curve were analyzed. The corrosion resistance of the steel bar under the chloride salt freeze–thaw cycles and dry–wet alternations was systematically studied. The result shows that adding a certain content of straw fiber can improve its corrosion resistance. Under the action of two chloride salt environments, the lowest mass loss rate was 0.82% for the sample with 3% straw fiber content and the mass growth rate of the specimens with 4% straw fiber is the highest aqt 0.9%. In terms of ultrasonic velocity, the lowest loss rate was 5.68% for specimens with fiber content of 2%. The specimens were subjected to 0 dry–wet alternations and freeze–thaw cycles; the highest electrical resistance is 19.96 kΩ when the fiber content is 1% and the lowest electrical resistance is 11.105 kΩ when the fiber content is 2%. Under the dry–wet alternations, the content of straw fiber and its corrosion resistance are: 1% > 4% > 0% > 3% > 2%. Under freeze–thaw cycles, the content of straw fiber and its corrosion resistance were as follows: 1% > 0% > 4% > 3% > 2%.
Hot Corrosion Behavior of Single-Layered Gd2Zr2O7, Sm2Zr2O7, and Nd2Zr2O7 Thermal Barrier Coatings Exposed to Na2SO4 + MgSO4 Environment
Authors: Khan Muhammad Jahangir , Moskal Grzegorz , Iqbal Amjad , Mikuśkiewicz Marta , Pawlik Tomasz , Olesik Piotr
Published: July 2023

Zirconates of rare earth elements have emerged as promising candidates for thermal barrier coatings (TBC). This study investigates the hot corrosion resistance of single-layered ceramic coatings composed of Gd2Zr2O7, Sm2Zr2O7, and Nd2Zr2O7. The coatings were prepared using air plasma spraying and applied to an Inconel [IN] 625 substrate. Experimental assessments were conducted to examine the hot corrosion behaviour by subjecting the coatings to pure magnesium sulfate (MgSO4) salt at 1000 °C for 24 h and a 50/50 mole percent Na2SO4 and MgSO4 mixture at 900 °C for cyclic durations of 5, 10, 15, and 20 h. This combination of salts creates a highly corrosive environment. This short test was carried out due to the necessity of the initial stages of the destruction process characterization. X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersion spectroscopy (EDS) techniques were utilized to identify and analyse the reaction products. At 1000 °C, no chemical reaction products were observed between MgSO4 and Gd2Zr2O7, Sm2Zr2O7, and Nd2Zr2O7. However, in the presence of the MgSO4 + Na2SO4 mixture, the zirconate coatings reacted, resulting in the formation of reaction products such as Gd(SO4)3, Gd2O2SO4, Gd2O3, Sm2O2SO4, Sm2(SO4)3, Sm2O3, MgO, Nd2(SO4)3, Na2O, and m-ZrO2. These compounds are formed due to the interaction of rare earth oxides with a low-temperature-melting eutectic Na2SO4+ (3MgSO4 × Na2SO4) melted at 666 °C. Despite the aggressive nature of the corrosive environment, the decomposition of rare earth zirconates was relatively limited, indicating satisfactory resistance to hot corrosion. Among the zirconate systems studied, Gd2Zr2O7 exhibited the lowest resistance to the MgSO4 + Na2SO4-based corrosive environment, while Sm2Zr2O7 and Nd2Zr2O7 demonstrated better corrosion resistance.
Features of Phase Formation in the CsOH–H2SO4–H3PO4–H2O System and the Growth of the Cs6(SO4)3(H3PO4)4 Crystals
Authors: Komornikov V. A. , Makarova I. P. , Timakov I. S. , Grebenev V. V.
Published: July 2023

In this paper, the conditions of phase formation in the system CsOH–H2SO4–H3PO4–H2O are considered for the first time. The phase formation of Cs6(SO4)3(H3PO4)4 at t = 50 °C has been studied extensively. The main concentration boundary conditions for this compound are considered for the first time. The solubility congruence of Cs6(SO4)3(H3PO4)4 is shown. Conditions and approaches for obtaining crystals by isothermal evaporation and saturated solution temperature reduction methods are considered. The results of obtaining Cs6(SO4)3(H3PO4)4 crystals with maximum dimensions of ~20 mm are presented.
The Unmet Diagnostic and Treatment Needs in Large Cell Neuroendocrine Carcinoma of the Lung
Authors: Buium Catalin , Negru Serban , Ionescu Diana N. , Dediu Mircea
Published: July 2023

Large cell neuroendocrine carcinoma of the lung (LCNEC) is currently classified as a rare lung cancer subtype, but given the high incidence of lung cancer, the overall number of cases is considerable. The pathologic diagnosis of LCNEC is mainly based on the microscopic appearance of the tumor cells, the mitotic rate, the amount of intra-tumoral necrosis, and the presence of positive neuroendocrine markers identified by immunohistochemistry. Recently, a subdivision into two main categories was proposed based on mutation signatures involving the RB1, TP53, KRAS, and STK11/LKB1 genes, into SCLC-like (small cell lung cancer-like) and NSCLC-like (non-small cell lung cancer-like) LCNEC. In terms of treatment, surgery is still the best option for resectable, stage I–IIIA cases. Chemotherapy and radiotherapy have conflicting evidence. Etoposide/platinum remains the standard chemotherapy regimen. However, based on the newly proposed LCNEC subtypes, some retrospective series report better outcomes using a pathology-driven chemotherapy approach. Encouraging outcomes have also been reported for immunotherapy and targeted therapy, but the real impact of these strategies is still being determined in the absence of adequate prospective clinical trials. The current paper scrutinized the epidemiology, reviewed the reliability of pathologic diagnosis, discussed the need for molecular subtyping, and reviewed the heterogeneity of treatment algorithms in LCNEC.
Histopathological Evaluation of Gastric Mucosal Atrophy for Predicting Gastric Cancer Risk: Problems and Solutions
Authors: Livzan Maria A. , Mozgovoi Sergei I. , Gaus Olga V. , Shimanskaya Anna G. , Kononov Alexei V.
Published: July 2023

Patients suffering from chronic gastritis and developing gastric mucosa atrophy are at increased risk of the development of gastric cancer. The diagnosis of chronic atrophic gastritis (CAG) is a complex procedure involving a detailed history taking, a thorough physical examination and the use of laboratory and instrumental diagnostic methods among which the endoscopy of the upper digestive tract is the cornerstone because it allows the assessment of the topography of gastritis and identification of erosions and areas of intestinal metaplasia with the use of NBI endoscopy. However, the diagnosis of CAG requires morphological examination of the gastric mucosa. So, in addition to assessing macroscopic changes in the gastric mucosa, it is necessary to take biopsy specimens in accordance with the protocols for their morphological and immunohistochemical examination. In the absence of specific diagnostic stigmas of CAG, close cooperation between a clinician, endoscopist and pathologist is necessary. The article presents systematized data on the histopathological assessment of the gastric mucosa atrophy to predict the risk of gastric cancer.
Nasal Cytology Changes in Head and Neck Cancer Treatment: A Systemic Review
Authors: Riva Giuseppe , Urbanelli Anastasia , Trossarello Marta , Piazza Federica , Pecorari Giancarlo
Published: July 2023

Nasal cytology is a non-invasive, low-cost exam that can help physicians in the diagnosis of allergic and nonallergic rhinitis, discriminating between different nasal disorders. The aim of this review is to summarize and analyze the current knowledge about nasal cytological examination in head and neck cancer, with a specific focus on the effects of different treatments. Indeed, nasal cytology is important to choose the best treatment for nasal complaints in each patient. A review of the English literature (PubMed, Scopus, Cochrane) was performed (5404 records screened). The inclusion criteria were clinical trials, cohort studies, case–control studies, case series, and case reports regarding nasal cytology in head and neck cancer treatment. Exclusion criteria were as follows: non-human studies, non-English literature, non-cytological evaluations. Two independent reviewers, working separately, extracted the data from all the eligible studies, which were subsequently cross-checked. Five studies were included in qualitative synthesis: three assessed mucosal disorders after radiation therapy and two after total laryngectomy. Radiotherapy can determine mucous or squamous cell metaplasia and neutrophil inflammation. Laryngectomees show hyperplasia of the basal zone cells and mucous cell metaplasia, and they do not develop inflammatory changes. The main limitation of this review is the low number and heterogeneity of studies present in the literature. In conclusion, nasal cytology is useful and allows for identifying mucosal disorders of the nasal cavities after surgery and/or radiotherapy for head and neck cancer. This can help physicians to better treat the nasal complaints of such patients.
The Role of Blood Pressure Load in Ambulatory Blood Pressure Monitoring in Adults: A Literature Review of Current Evidence
Authors: Eyal Ophir , Ben-Dov Iddo Z.
Published: July 2023

Background: The blood pressure load (BPL) is commonly defined as the percentage of readings in a 24-h ambulatory blood pressure monitoring (ABPM) study above a certain threshold, usually the upper normal limit. While it has been studied since the 1990s, the benefits of using this index have not been clearly demonstrated in adults. We present the first review on the associations of BPL with target organ damage (TOD) and clinical outcomes in adults, the major determinants for its role and utility in blood pressure measurement. We emphasize studies which evaluated whether BPL has added benefit to the average blood pressure indices on ABPM in predicting adverse outcomes. Methods: PubMed search for all English language papers mentioning ABPM and BPL. Results: While multiple studies assessed this question, the cumulative sample size is small. Whereas the associations of BPL with various TODs are evident, the available literature fails to demonstrate a clear and consistent added value for the BPL over the average blood pressure indices. Conclusions: There is a need for prospective studies evaluating the role of BPL in blood pressure measurement. The current literature does not provide sound support for the use of BPL in clinical decisions.
Histopathology of Budd–Chiari Syndrome
Authors: Quaglia Alberto
Published: July 2023

The histopathological changes in Budd–Chiari syndrome (BCS) overlap with those of sinusoidal obstruction syndrome (SOS) and of cardiac or pericardiac disorders resulting in right cardiac failure. These conditions, however, are different on both clinical and pathological grounds and need to be differentiated from BCS. This review is centred on the three main aspects of BCS in diagnostic liver histopathology: (1) general histopathology of BCS; (2) implications for liver biopsy interpretation; and (3) BCS in the liver allograft. The histological features of BCS form a complex spectrum which is shaped differently in each individual case according to the topographical distribution and chronological evolution of the obliterative insult, its upstream effect of the hepatic vascularisation and the consequent parenchymal injury, scarring and remodelling. Sampling variation limits the use of liver biopsy for prognostication in patients with BCS.
Pressure Pain Hypersensitivity and Ultrasound Changes in the Radial Nerve in Patients with Unilateral Lateral Epicondylalgia: A Case–Control Study
Authors: Cancela-Cilleruelo Ignacio , Rodríguez-Jiménez Jorge , Fernández-de-las-Peñas César , Cleland Joshua A. , Arias-Buría José L.
Published: July 2023

Some authors have proposed the potential role of the radial nerve in lateral epicondylalgia. The aims of this study were to investigate the presence of pressure pain hyperalgesia and nerve swelling (increased cross-sectional area) assessed with ultrasound imaging on the radial nerve in people with lateral epicondylalgia, and to investigate if an association exists between pressure pain sensitivity and cross-sectional area. A total of 37 patients with lateral epicondylalgia (43% women, age: 45.5 ± 9.5 years) and 37 age- and sex-matched pain-free controls were recruited for participation. Pressure pain thresholds (PPTs) were assessed bilaterally on the radial nerve at the spiral groove, the arcade of Frohse, and the anatomic snuffbox in a blinded design. Further, the cross-sectional area of the radial nerve at the spiral groove and antecubital fossa was also assessed. The results demonstrated lower PPTs on the radial nerve of the affected side in individuals with lateral epicondylalgia as compared with the unaffected side (p < 0.01) and with both sides in healthy controls (p < 0.001). Additionally, the cross-sectional area of the radial nerve on the affected side in patients was higher compared with the unaffected side (p < 0.01) and both sides in healthy controls (p < 0.001). The cross-sectional area of the radial nerve at the spiral groove was negatively associated with PPTs over the radial nerve at the spiral groove (r = −0.496, p = 0.002) and positively associated with function (r = 0.325, p = 0.045). Our findings revealed generalized pressure pain hyperalgesia and also nerve swelling of the radial nerve in people with lateral epicondylalgia, suggesting the presence of a widespread sensitization of nerve tissues in this population. The radial nerve could represent a potential peripheral drive to initial and maintain altered pain processing in lateral epicondylalgia.
Machine Learning in Antibody Diagnostics for Inflammatory Bowel Disease Subtype Classification
Authors: Sokollik Christiane , Pahud de Mortanges Aurélie , Leichtle Alexander B. , Juillerat Pascal , Horn Michael P.
Published: July 2023

Antibody testing in inflammatory bowel disease (IBD) can add to diagnostic accuracy of the main subtypes Crohn’s disease (CD) and ulcerative colitis (UC). Whether modern modeling techniques such as supervised and unsupervised machine learning are of value for finer distinction of subtypes such as IBD-unclassified (IBD-U) is not known. We determined the antibody profile of 100 adult IBD patients from the Swiss IBD cohort study with known subtype (50 CD, 50 UC) as well as of 76 IBD-U patients. We included ASCA IgG and IgA, p-ANCA, MPO- and PR3-ANCA, and xANCA measurements for computing different antibody panels as well as machine learning models. The AUC of an optimized antibody panel was 85% (95%CI, 78–92%) to distinguish CD from UC patients. The antibody profile of IBD-U patients was closely related to UC. No specific antibody profile was predictive for IBD-U nor for re-classification. The panel diagnostic was in favor of UC reclassification prediction with a correct assignment rate of 69.2–73.1% depending on the cut-off applied. Supervised machine learning could not distinguish between CD, UC, and IBD-U. More so, unsupervised machine learning suggested only two distinct clusters as a likely number of IBD subtypes. Antibodies in IBD are supportive in confirming clinical determined subtypes CD and UC but have limited capacity to predict IBD-U and reclassification during follow-up. In terms of antibody profiles, IBD-U is not a distinct subtype of IBD.
Hemorrhagic Transformation Assessment Based on Dual Energy CT of Immediately and Twenty-Four Hours after Endovascular Thrombectomy for Acute Ischemic Stroke
Authors: Wang Tianyu , Ding Weili , Chen Qing , Ding Zhongxiang
Published: July 2023

Background: Dual-energy CT (DECT) shows good performance in differentiating hemorrhage from contrast staining (CS). However, no guidelines have standardized the post-endovascular thrombectomy (EVT) examination time. We evaluated the value of performing DECT immediately and 24 h post-EVT in the diagnosis and prediction of hemorrhagic transformation (HT). Methods: Two readers evaluated simulated conventional CT (sCCT) images compared with a second reading with DECT, establishing the diagnosis of HT immediately and 24 h post-EVT. Another reader’s diagnosis 2–7 days post-EVT using non-contrast CT was identified as the final diagnostic criteria. Results: DECT performed immediately and 24 h post-EVT changed 22.4% (52/232) and 12.5% (29/232) of sCCT-based HT diagnoses, respectively (χ2 = 10.7, p < 0.05). The sensitivity, negative predictive value (NPV), and accuracy of DECT performed immediately post-EVT for predicting the final diagnosis of HT were 33.6%, 58.9%, and 65.9%, respectively, whereas those for DECT performed 24 h post-EVT were 82.4%, 84.3%, and 90.9%, respectively (χ2 = 58.0, χ2 = 42.9, χ2 = 13.6; p < 0.05). The specificity and positive predictive value were both 100.0%. Delayed HT occurred in 50.0% (78/156) and 42.2% (19/45) of patients with CS diagnosed immediately and 24 h post-EVT, respectively. Conclusions: DECT performed immediately post-EVT changed a greater proportion of real-time HT diagnoses, whereas that performed 24 h post-EVT had higher sensitivity, NPV, and accuracy in predicting the final diagnosis of HT. A substantial proportion of patients with CS diagnosed at these two post-EVT timepoints subsequently developed delayed HT.
Two Low-Complexity Efficient Beamformers for an IRS- and UAV-Aided Directional Modulation Network
Authors: Lin Yeqing , Shu Feng , Zheng Yuxiang , Liu Jing , Dong Rongen , Chen Xun , Wu Yue , Yan Shihao , Wang Jiangzhou
Published: July 2023

As excellent tools for aiding communication, an intelligent reflecting surface (IRS) and an unmanned aerial vehicle (UAV) can extend the coverage area, remove the blind area, and achieve a dramatic rate improvement. In this paper, we improve the secrecy rate (SR) performance of directional modulation (DM) networks using an IRS and UAV in combination. To fully explore the benefits of the IRS and UAV, two efficient methods are proposed to enhance the SR performance. The first approach computes the confidential message (CM) beamforming vector by maximizing the SR, and the signal-to-leakage-noise ratio (SLNR) method is used to optimize the IRS phase shift matrix (PSM), which is called Max-SR-SLNR. To reduce the computational complexity, the CM, artificial noise (AN) beamforming, and IRS phase shift design are independently designed in the following method. The CM beamforming vector is constructed based on the maximum ratio transmission (MRT) criteria along the channel from Alice-to-IRS, the AN beamforming vector is designed by null-space projection (NSP) on the remaining two channels, and the PSM of the IRS is directly given by the phase alignment (PA) method. This method is called the MRT-NSP-PA. The simulation results show that the SR performance of the Max-SR-SLNR method outperforms the MRT-NSP-PA method in the cases of small-scale and medium-scale IRSs, and the latter approaches the former in performance as the IRS tends to a larger scale.
Quantum Purity as an Information Measure and Nernst Law
Authors: Pennini F. , Plastino A.
Published: July 2023

We propose to re-express Nernst law in terms of a suitable information measure (IM) parameter. This is achieved by dwelling on the idea of adapting the notion of purity in the case of a thermal Gibbs environment, yielding what we might call the “purity” indicator (which we denote by the symbol D in the text). We find it interesting to define an extension of this D−IM indicator in a classical context. This generalization turns out to have useful conceptual consequences when used in conjunction with the classical Shannon entropy S. Implications for the Nernst law are discussed.
Research on User Behavior Based on Higher-Order Dependency Network
Authors: Qian Liwei , Dou Yajie , Gong Chang , Xu Xiangqian , Tan Yuejin
Published: July 2023

In the era of the popularization of the Internet of Things (IOT), analyzing people’s daily life behavior through the data collected by devices is an important method to mine potential daily requirements. The network method is an important means to analyze the relationship between people’s daily behaviors, while the mainstream first-order network (FON) method ignores the high-order dependencies between daily behaviors. A higher-order dependency network (HON) can more accurately mine the requirements by considering higher-order dependencies. Firstly, our work adopts indoor daily behavior sequences obtained by video behavior detection, extracts higher-order dependency rules from behavior sequences, and rewires an HON. Secondly, an HON is used for the RandomWalk algorithm. On this basis, research on vital node identification and community detection is carried out. Finally, results on behavioral datasets show that, compared with FONs, HONs can significantly improve the accuracy of random walk, improve the identification of vital nodes, and we find that a node can belong to multiple communities. Our work improves the performance of user behavior analysis and thus benefits the mining of user requirements, which can be used to personalized recommendations and product improvements, and eventually achieve higher commercial profits.
Multiparameter Estimation with Two-Qubit Probes in Noisy Channels
Authors: Conlon Lorcán O. , Lam Ping Koy , Assad Syed M.
Published: July 2023

This work compares the performance of single- and two-qubit probes for estimating several phase rotations simultaneously under the action of different noisy channels. We compute the quantum limits for this simultaneous estimation using collective and individual measurements by evaluating the Holevo and Nagaoka–Hayashi Cramér-Rao bounds, respectively. Several quantum noise channels are considered, namely the decohering channel, the amplitude damping channel, and the phase damping channel. For each channel, we find the optimal single- and two-qubit probes. Where possible we demonstrate an explicit measurement strategy that saturates the appropriate bound and we investigate how closely the Holevo bound can be approached through collective measurements on multiple copies of the same probe. We find that under the action of the considered channels, two-qubit probes show enhanced parameter estimation capabilities over single-qubit probes for almost all non-identity channels, i.e., the achievable precision with a single-qubit probe degrades faster with increasing exposure to the noisy environment than that of the two-qubit probe. However, in sufficiently noisy channels, we show that it is possible for single-qubit probes to outperform maximally entangled two-qubit probes. This work shows that, in order to reach the ultimate precision limits allowed by quantum mechanics, entanglement is required in both the state preparation and state measurement stages. It is hoped the tutorial-esque nature of this paper will make it easily accessible.
Validation of an Instrument to Measure Natural Science Teachers’ Self-Perception about Implementing STEAM Approach in Pedagogical Practices
Authors: Camacho-Tamayo Edison , Bernal-Ballen Andres
Published: July 2023

This study aims to describe the analysis of the validity and reliability of an instrument that determines the self-perception of natural science teachers using the STEAM approach regarding the planning, development, and evaluation of their pedagogical activities. For its design, empirical studies were obtained from a bibliographic review, theoretical criteria on self-perception and STEAM approach, and population characteristics. For the instrument quality assessment, content validity parameters were analyzed by experts, and construct validity and reliability were assessed with the help of the SPSS statistical package. Ten educational doctors served as expert judges and 143 teachers (pre-service and in-service) participated in the pilot test. As the main finding, the instrument applied to a sample presents a high reliability coefficient (Cronbach’s alpha = 0.920) and validity (KMO = 0.903) in three factors after performing a factor analysis. Thus, it is concluded that the instrument has structure and coherence both in its internal consistency and meaning grid, which facilitates progress in understanding the self-perception of using the STEAM approach in didactic practices in natural sciences.
Task Offloading of Deep Learning Services for Autonomous Driving in Mobile Edge Computing
Authors: Jang Jihye , Tulkinbekov Khikmatullo , Kim Deok-Hwan
Published: July 2023

As the utilization of complex and heavy applications increases in autonomous driving, research on using mobile edge computing and task offloading for autonomous driving is being actively conducted. Recently, researchers have been studying task offloading algorithms using artificial intelligence, such as reinforcement learning or partial offloading. However, these methods require a lot of training data and critical deadlines and are weakly adaptive to complex and dynamically changing environments. To overcome this weakness, in this paper, we propose a novel task offloading algorithm based on Lyapunov optimization to maintain the system stability and minimize task processing delay. First, a real-time monitoring system is built to utilize distributed computing resources in an autonomous driving environment efficiently. Second, the computational complexity and memory access rate are analyzed to reflect the characteristics of the deep learning applications to the task offloading algorithm. Third, Lyapunov and Lagrange optimization solves the trade-off issues between system stability and user requirements. The experimental results show that the system queue backlog remains stable, and the tasks are completed within an average of 0.4231 s, 0.7095 s, and 0.9017 s for object detection, driver profiling, and image recognition, respectively. Therefore, we ensure that the proposed task offloading algorithm enables the deep learning application to be processed within the deadline and keeps the system stable.
Jointly Optimize Partial Computation Offloading and Resource Allocation in Cloud-Fog Cooperative Networks
Authors: Bai Wenle , Wang Ying
Published: July 2023

Fog computing has become a hot topic in recent years as it provides cloud computing resources to the network edge in a distributed manner that can respond quickly to intensive tasks from different user equipment (UE) applications. However, since fog resources are also limited, considering the number of Internet of Things (IoT) applications and the demand for traffic, designing an effective offload strategy and resource allocation scheme to reduce the offloading cost of UE systems is still an important challenge. To this end, this paper investigates the problem of partial offloading and resource allocation under a cloud-fog coordination network architecture, which is formulated as a mixed integer nonlinear programming (MINLP). Bring in a new weighting metric-cloud resource rental cost. The optimization function of offloading cost is defined as a weighted sum of latency, energy consumption, and cloud rental cost. Under the fixed offloading decision condition, two sub-problems of fog computing resource allocation and user transmission power allocation are proposed and solved using convex optimization techniques and Karush-Kuhn-Tucker (KKT) conditions, respectively. The sampling process of the inner loop of the simulated annealing (SA) algorithm is improved, and a memory function is added to obtain the novel simulated annealing (N-SA) algorithm used to solve the optimal value offloading problem corresponding to the optimal resource allocation problem. Through extensive simulation experiments, it is shown that the N-SA algorithm obtains the optimal solution quickly and saves 17% of the system cost compared to the greedy offloading and joint resource allocation (GO-JRA) algorithm.
An Underwater Dense Small Object Detection Model Based on YOLOv5-CFDSDSE
Authors: Wang Jingyang , Li Yujia , Wang Junkai , Li Ying
Published: July 2023

Underwater target detection is a key technology in the process of exploring and developing the ocean. Because underwater targets are often very dense, mutually occluded, and affected by light, the detection objects are often unclear, and so, underwater target detection technology faces unique challenges. In order to improve the performance of underwater target detection, this paper proposed a new target detection model YOLOv5-FCDSDSE based on YOLOv5s. In this model, the CFnet (efficient fusion of C3 and FasterNet structure) structure was used to optimize the network structure of the YOLOv5, which improved the model’s accuracy while reducing the number of parameters. Then, Dyhead technology was adopted to achieve better scale perception, space perception, and task perception. In addition, the small object detection (SD) layer was added to combine feature information from different scales effectively, retain more detailed information, and improve the detection ability of small objects. Finally, the attention mechanism squeeze and excitation (SE) was introduced to enhance the feature extraction ability of the model. This paper used the self-made underwater small object dataset URPC_UODD for comparison and ablation experiments. The experimental results showed that the accuracy of the model proposed in this paper was better than the original YOLOv5s and other baseline models in the underwater dense small object detection task, and the number of parameters was also reduced compared to YOLOv5s. Therefore, YOLOv5-FCDSDSE was an innovative solution for underwater target detection tasks.
Dynamic Fall Detection Using Graph-Based Spatial Temporal Convolution and Attention Network
Authors: Egawa Rei , Miah Abu Saleh Musa , Hirooka Koki , Tomioka Yoichi , Shin Jungpil
Published: July 2023

The prevention of falls has become crucial in the modern healthcare domain and in society for improving ageing and supporting the daily activities of older people. Falling is mainly related to age and health problems such as muscle, cardiovascular, and locomotive syndrome weakness, etc. Among elderly people, the number of falls is increasing every year, and they can become life-threatening if detected too late. Most of the time, ageing people consume prescription medication after a fall and, in the Japanese community, the prevention of suicide attempts due to taking an overdose is urgent. Many researchers have been working to develop fall detection systems to observe and notify about falls in real-time using handcrafted features and machine learning approaches. Existing methods may face difficulties in achieving a satisfactory performance, such as limited robustness and generality, high computational complexity, light illuminations, data orientation, and camera view issues. We proposed a graph-based spatial-temporal convolutional and attention neural network (GSTCAN) with an attention model to overcome the current challenges and develop an advanced medical technology system. The spatial-temporal convolutional system has recently proven the power of its efficiency and effectiveness in various fields such as human activity recognition and text recognition tasks. In the procedure, we first calculated the motion along the consecutive frame, then constructed a graph and applied a graph-based spatial and temporal convolutional neural network to extract spatial and temporal contextual relationships among the joints. Then, an attention module selected channel-wise effective features. In the same procedure, we repeat it six times as a GSTCAN and then fed the spatial-temporal features to the network. Finally, we applied a softmax function as a classifier and achieved high accuracies of 99.93%, 99.74%, and 99.12% for ImViA, UR-Fall, and FDD datasets, respectively. The high-performance accuracy with three datasets proved the proposed system’s superiority, efficiency, and generality.
The Indoor Positioning Method Time Difference of Arrival with Conic Curves Utilizing a Novel Networking RFID System
Authors: Wang Xize , Ding Haiyu , Luo Zhenghu , Xu Xiaodong , Wei Yinghui , Li Yuanhang , Wang Qing , Jia Qianfan
Published: July 2023

At present, the demand for accurate indoor positioning at a low cost is increasing. Based on the architecture of networking passive radio frequency identification (RFID) systems, research into passive location algorithms is important for finding a location solution with ultra-low cost, easy implementation, and no required maintenance. In this paper, TDACC (time difference of arrival with conic curves) based on signal propagation time is proposed, which breaks down the positioning problem into solving the intersection of an ellipse and a hyperbola. The results indicate that this method has a positioning error of 0 m in the absence of signal interference. When the time delay fluctuates to 1 ns and 2 ns, the average errors of TDACC are 0.19 m and 0.33 m, respectively. Different from other time-based localization methods, the proposed method only requires two distribution nodes without time synchronization, which reduces the system cost. These results will help to promote the deeper semantic communication level fusion of passive RFID. By improving the coordinate positioning in the semantic prior knowledge base, this method will lead to more efficient and accurate industry applications.
Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic Sensors
Authors: Sarcevic Peter , Csík Dominik , Pesti Richard , Stančin Sara , Tomažič Sašo , Tadic Vladimir , Rodriguez-Resendiz Juvenal , Sárosi József , Odry Akos
Published: July 2023

Terrain classification provides valuable information for both control and navigation algorithms of wheeled mobile robots. In this paper, a novel online outdoor terrain classification algorithm is proposed for wheeled mobile robots. The algorithm is based on only time-domain features with both low computational and low memory requirements, which are extracted from the inertial and magnetic sensor signals. Multilayer perceptron (MLP) neural networks are applied as classifiers. The algorithm is tested on a measurement database collected using a prototype measurement system for various outdoor terrain types. Different datasets were constructed based on various setups of processing window sizes, used sensor types, and robot speeds. To examine the possibilities of the three applied sensor types in the application, the features extracted from the measurement data of the different sensors were tested alone, in pairs and fused together. The algorithm is suitable to operate online on the embedded system of the mobile robot. The achieved results show that using the applied time-domain feature set the highest classification efficiencies on unknown data can be above 98%. It is also shown that the gyroscope provides higher classification rates than the widely used accelerometer. The magnetic sensor alone cannot be effectively used but fusing the data of this sensor with the data of the inertial sensors can improve the performance.
Wind Turbine Blade Icing Prediction Using Focal Loss Function and CNN-Attention-GRU Algorithm
Authors: Tao Cheng , Tao Tao , Bai Xinjian , Liu Yongqian
Published: July 2023

Blade icing seriously affects wind turbines’ aerodynamic performance and output power. Timely and accurately predicting blade icing status is crucial to improving the economy and safety of wind farms. However, existing blade icing prediction methods cannot effectively solve the problems of unbalanced icing/non-icing data and low prediction accuracy. In order to solve the above problems, this paper proposes a wind turbine blade icing prediction method based on the focal loss function and CNN-Attention-GRU. First, the recursive feature elimination method combined with the physical mechanism of icing is used to extract features highly correlated with blade icing, and a new feature subset is formed through a sliding window algorithm. Then, the focal loss function is utilized to assign more weight to the ice samples with a lower proportion, addressing the significant class imbalance between the ice and non-ice categories. Finally, based on the CNN-Attention-GRU algorithm, a blade icing prediction model is established using continuous 24-h historical data as the input and the icing status of the next 24 h as the output. The model is compared with advanced neural network models. The results show that the proposed method improves the prediction accuracy and F1 score by an average of 6.41% and 4.27%, respectively, demonstrating the accuracy and effectiveness of the proposed method.