bluuebunny/crossref_metadata_2025 huggingface dataset:
Reflections on a Scholarly Career in Sport and Exercise Psychology: The Influence of Significant Others on the Psychosocial Well-Being of Children, Adolescents, and Young Adults
Authors: Horn Thelma S.
Published: December 2021

This paper is based on a Senior Scholar presentation delivered at the 2020 annual meeting of the North American Society for the Psychology of Sport and Physical Activity. The paper begins with a summary of the research work completed by the author and coinvestigators in regard to the influences that significant others (parents, peers, and coaches) exert on the psychosocial well-being of individuals in sport and physical activity. In each of these three areas, illustrative research studies are summarized in a predominantly chronological order with a commentary at the end of each section that identifies unanswered questions and suggests future research directions. In the second section, four particular lessons learned by the author over the course of a scholarly career are identified and explained.
Implications of Optimal Feedback Control Theory for Sport Coaching and Motor Learning: A Systematic Review
Authors: van Andel Steven , Pieper Robin , Werner Inge , Wachholz Felix , Mohr Maurice , Federolf Peter
Published: December 2021

Best practice in skill acquisition has been informed by motor control theories. The main aim of this study is to screen existing literature on a relatively novel theory, Optimal Feedback Control Theory (OFCT), and to assess how OFCT concepts can be applied in sports and motor learning research. Based on 51 included studies with on average a high methodological quality, we found that different types of training seem to appeal to different control processes within OFCT. The minimum intervention principle (founded in OFCT) was used in many of the reviewed studies, and further investigation might lead to further improvements in sport skill acquisition. However, considering the homogenous nature of the tasks included in the reviewed studies, these ideas and their generalizability should be tested in future studies.
The developmental origins of heterodonty and acrodonty as revealed by reptile dentitions
Authors: Salomies Lotta , Eymann Julia , Ollonen Joni , Khan Imran , Di-Poï Nicolas
Published: December 2021

Analysis of reptile models reveals the developmental origins and diversification of tooth identity in extant and fossil taxa.
Noradrenergic terminal short-term potentiation enables modality-selective integration of sensory input and vigilance state
Authors: Gray Shawn R. , Ye Liang , Ye Jing Yong , Paukert Martin
Published: December 2021

Sensory-driven cross-talk between interneurons and noradrenergic terminals conveys modality selectivity to neural modulation.
Supplemental Material: Geologic map of southern Panamint Valley, southern Panamint Range and central Slate Range, California, USA
Authors: Andrew J.E.
Published: December 2021

Digital map data files in ArcGIS shapefile format for data collection points, geologic contacts, and geologic unit polygons.
Synthesis and Complexation Properties of 2-Hydroxy-5-methoxyphenylphosphonic Acid (H3L1). Crystal Structure of the [Cu(H2L1)2(Н2О)2] Complex
Authors: Tsebrikova G. S. , Rogacheva Yu. I. , Ivanova I. S. , Ilyukhin A. B. , Soloviev V. P. , Demina L. I. , Baulin V. E. , Tsivadze A. Yu.
Published: December 2021

2-Hydroxy-5-methoxyphenylphosphonic acid (H3L1) and the complex [Cu(H2L1)2(H2O)2] were synthesized and characterized by IR spectroscopy, thermogravimetry, and X-ray diffraction analysis. The polyhedron of the copper atom is an axially elongated square bipyramid with oxygen atoms of phenolic and of monodeprotonated phosphonic groups at the base and oxygen atoms of water molecules at the vertices. The protonation constants of the H3L1 acid and the stability constants of its Cu2+ complexes in water were determined by potentiometric titration. The protonation constants of the acid in water are significantly influenced by the intramolecular hydrogen bond and the methoxy group. The H3L1 acid forms complexes CuL‒ and CuL24‒ with Cu2+ in water.
Clinical impact of a gastrointestinal PCR panel in children with infectious diarrhoea
Authors: Truong Jeanne , Cointe Aurélie , Le Roux Enora , Bidet Philippe , Michel Morgane , Boize Julien , Mariani-Kurkdjian Patricia , Caseris Marion , Hobson Claire Amaris , Desmarest Marie , Titomanlio Luigi , Faye Albert , Bonacorsi Stéphane
Published: December 2021

Objectives

Multiplex gastrointestinal PCR (GI-PCR) allows fast and simultaneous detection of 22 enteric pathogens (includingCampylobacter, Salmonella,Shigella/enteroinvasiveEscherichia coli (EIEC), among other bacteria, parasites and viruses). However, its impact on the management of children with infectious diarrhoea remains unknown.

Patients/Design

All children eligible for stool culture from May to October 2018 were prospectively included in a monocentric study at Robert-Debré University-Hospital.

Intervention

A GI-PCR (BioFire FilmArray) was performed on each stool sample.

Main measures

Data on the children’s healthcare management before and after GI-PCR results were collected. Stool culture results were also reported.

Results

172 children were included. The main criteria for performing stool analysis were mucous/bloody diarrhoea and/or traveller’s diarrhoea (n=130). GI-PCR’s were positive for 120 patients (70%). The main pathogens were enteroaggregativeE. coli(n=39; 23%), enteropathogenicE. coli(n=34; 20%),Shigella/EIEC (n=27; 16%) andCampylobacter(n=21; 12%). Compared with stool cultures, GI-PCR enabled the detection of 21 vs 19Campylobacter,12 vs 10Salmonella,27Shigella/EIEC vs 13Shigella, 2 vs 2Yersinia enterocolitica, 1 vs 1Plesiomonas shigelloides,respectively. Considering the GI-PCR results and before stool culture results, the medical management was revised for 40 patients (23%): 28 initiations, 2 changes and 1 discontinuation of antibiotics, 1 hospitalisation, 2 specific room isolations related toClostridioides difficileinfections, 4 additional test prescriptions and 2 test cancellations.

Conclusion

The GI-PCR’s results impacted the medical management of gastroenteritis for almostone-fourth of the children, and especially the prescription of appropriate antibiotic treatment before stool culture results.
Adaptation of the Texas Christian University Organisational Readiness for Change Short Form (TCU-ORC-SF) for use in primary health facilities in South Africa
Authors: Brooke-Sumner Carrie , Petersen-Williams Petal , Wagener Emma , Sorsdahl Katherine , Aarons Gregory A , Myers Bronwyn
Published: December 2021

Objectives

The Texas Christian University Organisational Readiness for Change Scale (TCU-ORC) assesses factors influencing adoption of evidence-based practices. It has not been validated in low-income and middle-income countries (LMIC). This study assessed its psychometric properties in a South African setting with the aim of adapting it into a shorter measure.

Methods

This study was conducted in 24 South African primary healthcare clinics in the Western Cape Province. The TCU-ORC and two other measures, the Organisational Readiness to Change Assessment (ORCA) and the Checklist for Assessing Readiness for Implementation (CARI) were administered. The questionnaire was readministered after 2 weeks to obtain data on test–retest reliability. Three hundred and ninety-five surveys were completed: 281 participants completed the first survey, and 118 recompleted the assessments.

Results

We used exploratory factor analysis (EFA) to identify latent dimensions represented in the data. Cronbach’s alpha for each subscale was assessed and we examined the extent to which the subscales and total scale scores for the first and retest surveys correlated. Convergent validity was assessed by the correlation coefficient between the TCU-ORC, ORCA and CARI total scale scores. EFA resulted in a three-factor solution. The three subscales proposed are Clinic Organisational Climate (8 items), Motivational Readiness for Change (13 items) and Individual Change Efficacy (5 items) (26 items total). Cronbach’s alpha for each subscale was >0.80. The overall shortened scale had a test–retest correlation of r=0.80, p<0.01, acceptable convergent validity with the ORCA scale (r=0.56, p<0.05), moderate convergence with the CARI (r=39, p<0.05) and strong correlation with the original scale (r=0.79, p<0.05).

Conclusions

This study presents the first psychometric data on the TCU-ORC from an LMIC. The proposed shortened tool may be more feasible for use in LMICs.

Trial registration number

Results stage. Project MIND trial. Pan-African Clinical Trials Registry. PACTR201610001825405.
Background incidence rates of hospitalisations and emergency department visits for thromboembolic and coagulation disorders in Ontario, Canada for COVID-19 vaccine safety assessment: a population-based retrospective observational study
Authors: Nasreen Sharifa , Calzavara Andrew J , Sundaram Maria E , MacDonald Shannon E , Righolt Christiaan H , Pai Menaka , Field Thalia S , Zhou Lily W , Wilson Sarah E , Kwong Jeffrey C
Published: December 2021

Objective

The objective of this study was to estimate background rates of selected thromboembolic and coagulation disorders in Ontario, Canada.

Design

Population-based retrospective observational study using linked health administrative databases. Records of hospitalisations and emergency department visits were searched to identify cases using International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada diagnostic codes.

Participants

All Ontario residents.

Primary outcome measures

Incidence rates of ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, deep vein thrombosis, pulmonary embolism, idiopathic thrombocytopaenia, disseminated intravascular coagulation and cerebral venous thrombosis during five prepandemic years (2015–2019) and 2020.

Results

The average annual population was 14 million with 51% female. The mean annual rates per 100 000 population during 2015–2019 were 127.1 (95% CI 126.2 to 127.9) for ischaemic stroke, 22.0 (95% CI 21.6 to 22.3) for intracerebral haemorrhage, 9.4 (95% CI 9.2 to 9.7) for subarachnoid haemorrhage, 86.8 (95% CI 86.1 to 87.5) for deep vein thrombosis, 63.7 (95% CI 63.1 to 64.3) for pulmonary embolism, 6.1 (95% CI 5.9 to 6.3) for idiopathic thrombocytopaenia, 1.6 (95% CI 1.5 to 1.7) for disseminated intravascular coagulation, and 1.5 (95% CI 1.4 to 1.6) for cerebral venous thrombosis. Rates were lower in 2020 than during the prepandemic years for ischaemic stroke, deep vein thrombosis and idiopathic thrombocytopaenia. Rates were generally consistent over time, except for pulmonary embolism, which increased from 57.1 to 68.5 per 100 000 between 2015 and 2019. Rates were higher for females than males for subarachnoid haemorrhage, pulmonary embolism and cerebral venous thrombosis, and vice versa for ischaemic stroke and intracerebral haemorrhage. Rates increased with age for most of these conditions, but idiopathic thrombocytopaenia demonstrated a bimodal distribution with incidence peaks at 0–19 years and ≥60 years.

Conclusions

Our estimated background rates help contextualise observed events of these potential adverse events of special interest and to detect potential safety signals related to COVID-19 vaccines.
Can SBAR be implemented with high fidelity and does it improve communication between healthcare workers? A systematic review
Authors: Lo Lisha , Rotteau Leahora , Shojania Kaveh
Published: December 2021

Objective

To characterise the extent to which health professionals perform SBAR (situation, background, assessment, recommendation) as intended (ie, with high fidelity) and the extent to which its use improves communication clarity or other quality measures.

Data sources

Medline, Healthstar, PsycINFO, Embase and CINAHL to October 2020 and handsearching selected journals.

Study selection and outcome measures

Eligible studies consisted of controlled trials and time series, including simple before-after design, assessing SBAR implementation fidelity or the effects of SBAR on communication clarity or other quality measures (eg, safety climate, patient outcomes).

Data extraction and synthesis

Two reviewers independently abstracted data according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses on study features, intervention details and study outcomes. We characterised the magnitude of improvement in outcomes as small (<20% relative increase), moderate (20%–40%) or large (>40%).

Results

Twenty-eight studies (3 randomised controlled trials, 6 controlled before-after studies, and 19 uncontrolled before-after studies) met inclusion criteria. Of the nine studies assessing fidelity of SBAR use, four occurred in classroom settings and three of these studies reported large improvements. The five studies assessing fidelity in clinical settings reported small to moderate effects. Among eight studies measuring communication clarity, only three reported large improvements and two of these occurred in classroom settings. Among the 17 studies reporting impacts on quality measures beyond communication, over half reported moderate to large improvements. These improvements tended to involve measures of teamwork and culture. Improvements in patient outcomes occurred only with intensive multifaceted interventions (eg, early warning scores and rapid response systems).

Conclusions

High fidelity uptake of SBAR and improvements in communication clarity occurred predominantly in classroom studies. Studies in clinical settings achieving impacts beyond communication typically involved broader, multifaceted interventions. Future efforts to improve communication using SBAR should first confirm high fidelity uptake in clinical settings rather than assuming this has occurred.

PROSPERO registration number

CRD42018111377.
Femoroacetabular translation in female athletes and dancers assessed by dynamic hip ultrasonography
Authors: Scott Charles P , d'Hemecourt Pierre A , Miller Patricia E , Sugimoto Dai , Jackson Sarah S , Kobelski Greggory P , Whitney Kristin E , Stracciolini Andrea
Published: December 2021

Objective

To compare femoroacetabular (FA) translation between dancers and athletes with hip pain and between dancers with and without hip pain.

Methods

In this cross-sectional study, 171 female athletes and dancers with hip pain underwent dynamic hip ultrasound (DHUS) of FA translation in three positions: neutral (N), neutral with contralateral hip flexion (NF), apprehension position with contralateral hip flexion (EER-F). Multivariable linear regression analysis was used to assess variation in FA translation between dancers and athletes in the presence of age, Beighton score/hypermobility, BMI, radiographic markers of acetabular dysplasia and femoral version angles. Symptomatic dancers were matched to asymptomatic dancer controls on age, height and BMI, and comparison analyses of FA translation were conducted controlling for matched propensity score and Beighton score.

Results

In the symptomatic cohort, dancers were younger, had higher Beighton scores and were more hypermobile than non-dancers. Dancers also showed greater NF, EER-F and max US–min US (delta) compared with non-dancers (mean 5.4 mm vs 4.4 mm, p=0.02; mean 6.3 mm vs 5.2 mm, p=0.01; 4.2 mm vs 3.6 mm, p=0.03, respectively). Symptomatic dancers showed greater NF and EER-F compared with asymptomatic dancers (mean 5.5 mm vs 2.9 mm, p<0.001; mean 6.3 mm vs 4.2 mm, p<0.001, respectively). Comparison of symptomatic dancers with and without hip dysplasia showed no difference in DHUS measurements.

Conclusion

DHUS measurements of FA translation are greater in female dancers with hip pain relative to female non-dancer athletes with hip pain and asymptomatic female dancers.
The heritability of amyloid burden in older adults: the Older Australian Twins Study
Authors: Koncz Rebecca , Thalamuthu Anbupalam , Wen Wei , Catts Vibeke S , Dore Vincent , Lee Teresa , Mather Karen A , Slavin Melissa J , Wegner Eva A , Jiang Jiyang , Trollor Julian N , Ames David , Villemagne Victor L , Rowe Christopher C , Sachdev Perminder S
Published: December 2021

Objective

To determine the proportional genetic contribution to the variability of cerebral β-amyloid load in older adults using the classic twin design.

Methods

Participants (n=206) comprising 61 monozygotic (MZ) twin pairs (68 (55.74%) females; mean age (SD): 71.98 (6.43) years), and 42 dizygotic (DZ) twin pairs (56 (66.67%) females; mean age: 71.14 (5.15) years) were drawn from the Older Australian Twins Study. Participants underwent detailed clinical and neuropsychological evaluations, as well as MRI, diffusion tensor imaging (DTI) and amyloid PET scans. Fifty-eight participants (17 MZ pairs, 12 DZ pairs) had PET scans with 11Carbon-Pittsburgh Compound B, and 148 participants (44 MZ pairs, 30 DZ pairs) with 18Fluorine-NAV4694. Cortical amyloid burden was quantified using the centiloid scale globally, as well as the standardised uptake value ratio (SUVR) globally and in specific brain regions. Small vessel disease (SVD) was quantified using total white matter hyperintensity volume on MRI, and peak width of skeletonised mean diffusivity on DTI. Heritability (h2) and genetic correlations were measured with structural equation modelling under the best fit model, controlling for age, sex, tracer and scanner.

Results

The heritability of global amyloid burden was moderate (0.41 using SUVR; 0.52 using the centiloid scale) and ranged from 0.20 to 0.54 across different brain regions. There were no significant genetic or environmental correlations between global amyloid burden and markers of SVD.

Conclusion

Amyloid deposition, the hallmark early feature of Alzheimer’s disease, is under moderate genetic influence, suggesting a major environmental contribution that may be amenable to intervention.
Autonomy-based criticisms of the patient preference predictor
Authors: Jardas EJ , Wasserman David , Wendler David
Published: December 2021

The patient preference predictor (PPP) is a proposed computer-based algorithm that would predict the treatment preferences of decisionally incapacitated patients. Incorporation of a PPP into the decision-making process has the potential to improve implementation of the substituted judgement standard by providing more accurate predictions of patients’ treatment preferences than reliance on surrogates alone. Yet, critics argue that methods for making treatment decisions for incapacitated patients should be judged on a number of factors beyond simply providing them with the treatments they would have chosen for themselves. These factors include the extent to which the decision-making process recognises patients’ freedom to choose and relies on evidence the patient themselves would take into account when making treatment decisions. These critics conclude that use of a PPP should be rejected on the grounds that it is inconsistent with these factors, especially as they relate to proper respect for patient autonomy. In this paper, we review and evaluate these criticisms. We argue that they do not provide reason to reject use of a PPP, thus supporting efforts to develop a full-scale PPP and to evaluate it in practice.
Recognising and managing eating disorders in the emergency department
Authors: Jafar Anisa Jabeen Nasir , Jafar Wisam Jalal Jawad , Everitt Emma Kathleen , Gill Ian , Sait Hannah Maria , Tan Jacinta
Published: December 2021

Compared with other mental health conditions or psychiatric presentations, such as self-harm, which may be seen in emergency departments, eating disorders can seem relatively rare. However, they have the highest mortality across the spectrum of mental health, with high rates of medical complications and risk, ranging from hypoglycaemia and electrolyte disturbances to cardiac abnormalities. People with eating disorders may not disclose their diagnosis when they see healthcare professionals. This can be due to denial of the condition itself, a wish to avoid treatment for a condition which may be valued, or because of the stigma attached to mental health. As a result their diagnosis can be easily missed by healthcare professionals and thus the prevalence is underappreciated. This article presents eating disorders to emergency and acute medicine practitioners from a new perspective using the combined emergency, psychiatric, nutrition and psychology lens. It focuses on the most serious acute pathology which can develop from the more common presentations; highlights indicators of hidden disease; discusses screening; suggests key acute management considerations and explores the challenge of mental capacity in a group of high-risk patients who, with the right treatment, can make a good recovery.
Identification of biological risk factors for persistent postoperative pain after total knee arthroplasty
Authors: Sideris Alexandra , Malahias Michael-Alexander , Birch George , Zhong Haoyan , Rotundo Valeria , Like Brian J , Otero Miguel , Sculco Peter K , Kirksey Meghan
Published: December 2021

Background

There is growing evidence that cytokines and adipokines are associated with osteoarthritis (OA) severity, progression, and severity of associated pain. However, the cytokine response to total knee arthroplasty (TKA) and its association with persistent postoperative pain is not well understood. This study aims to describe the perioperative systemic (plasma) and local (synovial fluid) cytokine profiles of patients who do and do not develop persistent pain after TKA.

Methods

Patients undergoing primary unilateral TKA for end-stage OA were prospectively enrolled. Demographic and clinical data were gathered preoperatively and postoperatively. Synovial fluid was collected pre arthrotomy and plasma was collected at multiple time points before and after surgery. Persistent postoperative pain (PPP) was defined as Numerical Rating Score≥4 at 6 months. Cytokine levels were measured using the V-Plex Human Cytokine 30-Plex Panel (Mesoscale—Rockville, Maryland, USA). Cytokine levels were compared between PPP and minimal pain groups. Given that the study outcomes are exploratory, no adjustment was performed for multiple testing.

Results

Incidence of persistent pain at 6 months post TKA was 15/162 (9.3%). Postoperative plasma levels of four cytokines were significantly different in patients who developed persistent postoperative pain: interleukin (IL)-10, IL-1β, vascular endothelial growth factor, and IL12/IL23p40. Significantly lower IL-10 levels in the prearthrotomy synovial fluid were associated with development of postoperative persistent pain.

Conclusions

This prospective cohort study described a distinct acute perioperative inflammatory response profile in patients who developed persistent post-TKA pain, characterized by significant differences in four cytokines over the first 2 postoperative days. These results support the growing evidence that the patient-specific biologic response to surgery may influence longer-term clinical outcomes after TKA.

Trial registration number

Clinicaltrials.gov NCT02626533.
Volcano-sedimentary processes at Las Derrumbadas rhyolitic twin domes, Serdán-Oriental Basin, Eastern Trans-Mexican Volcanic Belt
Authors: Guilbaud Marie-Noëlle , Chédeville Corentin , Molina-Guadarrama Ángel Nahir , Pineda-Serrano Julio Cesar , Siebe Claus
Published: December 2021

The eruption of the
c.
10 km
3
rhyolitic Las Derrumbadas twin domes about 2000 years ago generated a wide range of volcano-sedimentary deposits in the Serdán-Oriental lacustrine basin, Trans-Mexican Volcanic Belt. Some of these deposits have been quarried, creating excellent exposures. In this paper we describe the domes and related products and interpret their mode of formation, reconstructing the main phases of the eruption as well as syn- and post-eruptive erosional processes. After an initial phreatomagmatic phase that built a tuff ring, the domes grew as an upheaved plug, lifting a thick sedimentary pile from the basin floor. During uplift, the domes collapsed repeatedly to form a first generation of hetero-lithologic hummocky debris avalanche deposits. Subsequent dome growth produced a thick talus and pyroclastic density currents. Later, the hydrothermally altered over-steepened dome peaks fell to generate second-generation, mono-lithologic avalanches. Subsequently, small domes grew in the collapse scars. From the end of the main eruptive episode onwards, heavy rains remobilized parts of the dome carapaces and talus, depositing lahar aprons. The Las Derrumbadas domes are still an important source of sediments in the basin, and ongoing mass-wasting processes are associated with hazards that should be assessed, given their potential impact on nearby populations.
Tectonic control on the palaeogeographical evolution of the Miocene Seaway along the Western Alpine foreland basin
Authors: Kalifi Amir , Sorrel Philippe , Leloup Philippe-Hervé , Galy Albert , Spina Vincenzo , Huet Bastien , Russo Séverine , Pittet Bernard , Rubino Jean-Loup
Published: December 2021

The Miocene of the Western Alpine foreland basin were deposited in a north–south seaway along the active alpine orogenic front. In the subalpine massifs and the southern Jura mountains, the revised Miocene stratigraphy documents a detailed chronology of thrust propagation at the western alpine front, where tectonic activity had a primary influence on seaway palaeogeographical evolution. Here we propose nine palaeogeographical maps during the Miocene, the first of which depicts the initial Miocene transgression at
c.
21.0 Ma. Between
c.
18.05 and
c.
12.0 Ma, a westward retreat of the Miocene Sea occurred in response to activation of the basal thrust of the Belledonne massif, which in turn triggered successive fault zones from east to west. At
c.
10.0 Ma, a major uplift phase intervened and induced a rapid southward retreat of the Miocene Sea. The reconstructed palaeogeographical maps outline the main controls on the foreland basin seaway evolution: (1) the timing of the main thrusts; (2) the inherited palaeotopography; and (3) eustatic sea-level changes during the Miocene. These reconstructions are integrated at the basin scale, highlighting the southward- to westward-directed seaway migration in response to the Belledonne thrust activity that deeply shaped the palaeogeographical evolution during the early to middle Miocene.
Artificial intelligence across company borders
Authors: Fink Olga , Netland Torbjørn , Feuerriegelc Stefan
Published: December 2021

Enabling effective cross-company AI without data disclosure.
NeRF
Authors: Mildenhall Ben , Srinivasan Pratul P. , Tancik Matthew , Barron Jonathan T. , Ramamoorthi Ravi , Ng Ren
Published: December 2021

We present a method that achieves state-of-the-art results for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views. Our algorithm represents a scene using a fully connected (nonconvolutional) deep network, whose input is a single continuous 5D coordinate (spatial location (
x
,
y
,
z
) and viewing direction (
θ, ϕ
)) and whose output is the volume density and view-dependent emitted radiance at that spatial location. We synthesize views by querying 5D coordinates along camera rays and use classic volume rendering techniques to project the output colors and densities into an image. Because volume rendering is naturally differentiable, the only input required to optimize our representation is a set of images with known camera poses. We describe how to effectively optimize neural radiance fields to render photorealistic novel views of scenes with complicated geometry and appearance, and demonstrate results that outperform prior work on neural rendering and view synthesis.
Investigation of the Chemical Composition and Antioxidant and Antimicrobial Activities of Lobularia maritima: Potent Therapeutic Applications
Authors: Kouidhi Soumaya , Zidi Oumaima , Abdelwahed Soukaina , Souissi Yasmine , Trabelsi Najla , Redissi Alaeddine , Hamdi Manel , Trabelsi Emna , Amara Yosra , Bhiri Taher , Khrouf Rim , Selmi Boulbaba , Achour Sami , Cherif Ameur , Mnif Wissem , Mosbah Amor
Published: December 2021

Lobularia maritima, commonly known as sweet alyssum, is an annual ornamental halophyte widely spread along the Tunisian seashore. However, little is known about the phytochemical, antioxidant, and antimicrobial activities of Lobularia maritima. The present study aimed to investigate the potential biological properties of different parts (flowers, leaves, roots, and stems) of Tunisian L. maritima using diverse extraction methods. Extracts were then studied for their antioxidant properties, and the highest antioxidant activity was presented in the roots’ fractions. Added to this, flower, leaf, and root fractions showed interesting antimicrobial and antifungal activities against different Gram+ and Gram− bacteria and against Aspergillus ochraceus. Finally, the most active fractions (presenting the highest biological activities) were analyzed using silica gel purification and mass spectrometry coupled to gas chromatography (GC-MS) analysis, and different compounds were identified such as camphor, amide of oleic acids, tributyl acetylcitrate, betulinaldehyde, menthol, 1′-(butyn-3-one-1-yl)-, (1S, 2S, 5R), benzyl benzoate, 7-acetyl-6-ethyl-1,1,4,4-tetramethyltetralin, 2,4-heptadienal, (E,E), and nootkaton-11,12-epoxide. This work represents the first in-depth investigation of the content of bioactive compounds from Lobularia maritima. This species could potentially be a promising source of useful compounds for therapeutic applications.
Clinical Efficacy of Fuzheng Guben Anticancer Decoction Combined with Taxol in Treating Ovarian Carcinoma and Its Effect on Complication Incidence
Authors: Li Pinger , Lou Yinmei
Published: December 2021

Objective. To investigate the clinical value of Fuzheng Guben anticancer decoction combined with taxol in treating ovarian carcinoma (OC). Methods. The medical records of 80 OC patients treated in the First People’s Hospital of Fuyang Hangzhou (January 2018–January 2021) were retrospectively analyzed, and the patients were split into the control group and the experimental group according to the treatment regimen, with 40 cases each. Those in the control group accepted the taxol chemotherapy, and on this basis, those in the experimental group took the Fuzheng Guben anticancer decoction, so as to compare its clinical efficacy and complication incidence. Results. No statistical between-group differences in patients’ general information were observed

P
>
0.05

; compared with the control group, the disease objective remission rate of the experimental group was greatly higher

P
<
0.05

; before and after treatment, the changes in CD8+ were not significant, indicating no statistically significant between-group differences

P
>
0.05

, and after treatment, CD3+, CD4+, and CD4+/CD8+ were obviously higher than before and were obviously higher in the experimental group than in the control group

P
<
0.05

; after treatment, the CA125, CA199, and CEA levels were obviously lower than before and were significantly lower in the experimental group than in the control group

P
<
0.05

; the mean survival of the experimental group was significantly higher than that of the control group (19.80 ± 5.84 vs. 14.075 ± 5.12 months,

P
<
0.05

); and between the two groups, the incidence rate of adverse reactions of the experimental group was remarkably lower

P
<
0.05

. Conclusion. On the basis of taxol chemotherapy, jointly applying Fuzheng Guben anticancer decoction can significantly improve the clinical efficacy of OC, help to improve patients’ immune function, lower the complication incidence rate, and prolong the mean survival.
Digital Media Hotspot Mining Algorithm Implementation with Complex Systems in the Mobile Internet Environment
Authors: Jia Yufeng , Tsai Sang-Bing
Published: December 2021

With the development of the Internet, the amount of information present on the network has grown rapidly, leading to increased difficulty in obtaining effective information. Especially for individuals, enterprises, and institutions with a large amount of information, it is an almost impossible task to integrate and analyze Internet information with great difficulty just by human resources. Internet hot events mining and analysis technology can effectively solve the above problems by alleviating information overload, integrating redundant information, and refining core information. In this paper, we address the above problems and research hot event topic sentence generation techniques in the field of hot event mining and design a hybrid event candidate set construction algorithm based on topic core word mapping and event triad selection. The algorithm uses the PAT‐Tree technique to extract high‐frequency core words in topic hotspots and maps the high‐frequency words into sentences to generate a part of event core sentences. The other part of event core sentences is extracted from the topic hotspots by making event triples as candidate elements, and sentences containing event elements are extracted from the topic hotspots. The sets of event core sentences generated by the two methods are mixed and filtered and sorted to obtain the candidate set, which can be used to build a word graph‐based main service channel (MSC) model. In this paper, we also propose an improved word graph‐based MSC model and use it for the extraction of event topic sentences. Based on the above research, a hot event analysis system is implemented. The system analyzes the existing topic data and uses the event topic sentence generation algorithm studied in this paper to generate the titles of hot spots, that is, hot events. At the same time, the topics are displayed from different dimensions, and data visualization is completed. The visualization includes the trend change of event hotness, trend change of event sentiment polarity, and distribution of event article sources.
Game Teaching Method in Preschool Education Based on Big Data Technology
Authors: Bai Rui
Published: December 2021

The traditional preaching way of imparting knowledge can only stifle children’s imagination, creativity, and learning initiative a little bit, which is harmful to children’s healthy and happy growth. This paper combines big data technology to evaluate the effect of game teaching method in preschool education, analyzes the teaching effect of game teaching method in preschool education, and combines big data technology to find problematic teaching points. Based on the collaborative filtering algorithm of preschool children, this paper estimates the current preschool children’s score for the game by referring to the scores of neighbor preschool children on the predicted game and constructs an intelligent model. Finally, this paper combines experimental research to verify the model proposed in this paper. From the experimental research, it can be seen that the method proposed in this paper has a certain effect.
Research on Default Prediction for Credit Card Users Based on XGBoost-LSTM Model
Authors: Gao Jing , Sun Wenjun , Sui Xin
Published: December 2021

The credit card business has become an indispensable financial service for commercial banks. With the development of credit card business, commercial banks have achieved outstanding results in maintaining existing customers, tapping potential customers, and market share. During credit card operations, massive amounts of data in multiple dimensions—including basic customer information; billing, installment, and repayment information; transaction flows; and overdue records—are generated. Compared with preloan and postloan links, user default prediction of the on-loan link has a huge scale of data, which makes it difficult to identify signs of risk. With the recent growing maturity and practicality of technologies such as big data analysis and artificial intelligence, it has become possible to further mine and analyze massive amounts of transaction data. This study mined and analyzed the transaction flow data that best reflected customer behavior. XGBoost, which is widely used in financial classification models, and Long-Short Term Memory (LSTM), which is widely used in time-series information, were selected for comparative research. The accuracy of the XGBoost model depends on the degree of expertise in feature extraction, while the LSTM algorithm can achieve higher accuracy without feature extraction. The resulting XGBoost-LSTM model showed good classification performance in default prediction. The results of this study can provide a reference for the application of deep learning algorithms in the field of finance.
Research on the Time-Frequency Spillover Effect of High-Frequency Stock Price and Economic Policy Uncertainty
Authors: Zhu Shuzhen , He Zhen , Wang Suxue
Published: December 2021

Through the construction of wavelet coherence analysis and frequency-domain spillover framework, this paper makes a comparative study of the volatility spillover effects of international economic policy uncertainty (EPU) on China’s Shanghai and Hong Kong stock market from a time-frequency perspective. To fully reflect the international EPU, this paper selects China, the United States, Australia, and the United Kingdom and uses the monthly EPU index of these countries and regions. China chooses China’s EPU index and Hong Kong’s EPU index. At the same time, the 5-minute high-frequency volatility of the Shanghai Composite Index (SSEC) and the Hang Seng Index (HSI) is selected to represent the Shanghai and Hong Kong’s stock market, respectively. It is found that there are obvious differences between the EPU and the dependence of the stock market in time domain and frequency domain, and the lead-lag relationship between them has time-varying characteristics. Static and dynamic spillover effects play a dominant role in the analysis of medium- and long-term spillover effects. In particular, the EPU and the risk spillover of the Hong Kong stock market are stronger than those of the Shanghai stock market, and the dynamic frequency-domain net risk spillover between them has frequency characteristics, and there are two-way and asymmetric risk spillovers. This provides a certain reference for policy makers to improve the safety management of financial markets and for market investors to optimize their portfolios.
Sensor Fault Diagnosis of Locomotive Electro‐Pneumatic Brake Using an Adaptive Unscented Kalman Filter
Authors: Gao Dianzhu , Peng Jun , Lu Yunyou , Zhang Rui , Yang Yingze , Huang Zhiwu
Published: December 2021

Normal operation of the pressure sensor is important for the safe operation of the locomotive electro‐pneumatic brake system. Sensor fault diagnosis technology facilitates detection of sensor health. However, the strong nonlinearity and variable process noise of the brake system make the sensor fault diagnosis become challenging. In this paper, an adaptive unscented Kalman filter‐ (UKF‐) based fault diagnosis strategy is proposed, aimed at detecting bias faults and drift faults of the equalizing reservoir pressure sensor in the brake system. Firstly, an adaptive UKF based on the Sage‐Husa method is applied to accurately estimate the pressure transients in the equalizing reservoir of the brake system. Then, the residual is generated between the estimated pressure by the UKF and the measured pressure by the sensor. Afterwards, the Sequential Probability Ratio Test is used to evaluate the residual so that the incipient and gradual sensor faults can be diagnosed. An experimental prototype platform for diagnosis of the equalizing reservoir pressure control system is constructed to validate the proposed method.
Research on the Application of Generative Adversarial Networks in the Generation of Stock Market Forecast Trend Images
Authors: Xiao Daiyou
Published: December 2021

Investors make capital investment by buying stocks and expect to get a certain income from the stock market. When buying stocks, they need to draw up investment plans based on various information such as stock market historical transaction data and related news data of listed companies and collect and analyze these data. The data are relatively cumbersome and require a lot of time and effort. If you only rely on subjective analysis, the reference factors are often not comprehensive enough. At the same time, Internet social media, such as the speech in stock forums, also affect the judgment and behavior of investors, and investor sentiment will have a positive or negative effect on the stock market. This has an impact on the trend of stock prices. Therefore, this article proposes a stock market prediction model that uses data preprocessing technology based on past stock market transaction data to establish a stock market prediction model, and secondly, an image description generation model based on a generative confrontation network is designed. The model includes a generator and a discriminator. A time-varying preattention mechanism is proposed in the generator. This mechanism allows each image feature to pay attention to the image features of other stock markets to predict stock market trends so that the decoder can better understand the relational information in the image. The discriminator is based on the recurrent neural network and considers the degree of matching between the input sentence and the 4 reference sentences and the image features. Experiments show that the accuracy of the model is higher than that of the stock pretrend forecast model based on historical data, which proves the effectiveness of the data used in this paper in the stock price trend forecast.
Stock Price Prediction Methods based on FCM and DNN Algorithms
Authors: Wang Wennan , Liu Wenjian , Zhu Linkai , Luo Ruijie , Li Guang , Dai Shugeng
Published: December 2021

With the rapid economic development and the continuous expansion of investment scale, the stock market has produced increasing amounts of transaction data and market public opinion information, making it further difficult for investors to distinguish effective investment information. With the continuous enrichment of artificial intelligence achievements, the status and influence of artificial intelligence researchers in academia and society have been greatly improved. Expert system, as an important part of artificial intelligence, has made breakthrough progress at this stage. Expert system is based on a large amount of professional knowledge and experience for a specific field. Computers of this system can be used to simulate the decision-making process of experts to provide a decision-making basis for solving some complex problems. This research mainly discusses stock price prediction methods on the basis of artificial intelligence (AI) algorithms. Fuzzy clustering is a data mining tool that has been developed in recent years and is widely used. Using this method to process super large-scale databases with various data attributes has the characteristics of high efficiency and small amount of information loss. Theoretically speaking, the use of fuzzy clustering technology and related index method can effectively reduce the massive financial fundamentals of listed companies. By analyzing the influencing factors of stock value investment, we specifically select from the financial statements of listed companies the five aspects that can reflect their profitability, development ability, shareholder profitability, solvency, and operating ability. The full text runs through a variety of AI methods that is the characteristic of the research method used in this article, which pays special attention to verifying the theoretical method model. Doing so ensures its effectiveness in practical applications. In stock value portfolio research, a portfolio optimization model, which integrates the dual objectives of portfolio risk and returns into the risk-adjusted return of capital single objective constraints and solves the portfolio, is established. The accuracy and recall of the FCM model are relatively stable, with accuracies of 0.884 and 0.001, respectively. This research can help improve the number and quality of listed companies.
Deformation Mechanism of the Coal ahead of Fully Mechanized Caving Face under High‐Intensity Mining Condition
Authors: Zhao Can , Chen Liang , Wu Bing , Zhang Jingui , Yan Dahe , Li Yang , Cheng Zhiheng
Published: December 2021

In order to study the coal deformation and failure mechanism in fully mechanized caving face under the high‐intensity mining, based on the equivalent mechanical model of transversely isotropic cylindrical coal with fractures, the equivalent equations for axial, radial, and volume strains of coal sample loaded in linear elastic and plastic stages were derived in this paper. The equivalent mechanical model shows good reliability through the conventional triaxial experiment. Taking the N1206 workface in Yuwu coal mine of Luan group as the example, we have simulated the stress concentration factor of the coal body ahead of the working face with FLAC and divided three regions according to stress distribution in coal mining. Mathematical equations were derived to express the horizontal and vertical stress, which provide theoretical guidance of the stress paths in triaxial experiment about real mining stress environment simulation. Experimental results show that the volume strain’s value is about 0.4% in the coal mass deformation progress of axial compression increasing slowly area. In axial compression increasing rapidly area, the volume strain’s value varies from 0.41% to 0.27%, and the radical strain changes from compression deformation to expansion deformation gradually. The volume strain of coal sample increases sharply in axial compression releasing rapidly area; meanwhile, there are good linear relationships between Poisson’s ratio and axial strain and radial strain.
Research on Parallel Support Vector Machine Based on Spark Big Data Platform
Authors: Huimin Yao
Published: December 2021

With the development of cloud computing and distributed cluster technology, the concept of big data has been expanded and extended in terms of capacity and value, and machine learning technology has also received unprecedented attention in recent years. Traditional machine learning algorithms cannot solve the problem of effective parallelization, so a parallelization support vector machine based on Spark big data platform is proposed. Firstly, the big data platform is designed with Lambda architecture, which is divided into three layers: Batch Layer, Serving Layer, and Speed Layer. Secondly, in order to improve the training efficiency of support vector machines on large-scale data, when merging two support vector machines, the “special points” other than support vectors are considered, that is, the points where the nonsupport vectors in one subset violate the training results of the other subset, and a cross-validation merging algorithm is proposed. Then, a parallelized support vector machine based on cross-validation is proposed, and the parallelization process of the support vector machine is realized on the Spark platform. Finally, experiments on different datasets verify the effectiveness and stability of the proposed method. Experimental results show that the proposed parallelized support vector machine has outstanding performance in speed-up ratio, training time, and prediction accuracy.