bluuebunny/crossref_metadata_2025 huggingface dataset:
Awareness, perceptions, and characteristics of internal medicine residents as role models
Authors: Toro‐Tobon David , Thornton Sarah
Published: September 2022

Background

Role modelling is an essential component of medical education in which trainees incorporate observed characteristics into their personal behaviour and practice style. Data on residents as role models is limited. There are no previous quantitative studies addressing residents as role models from the resident's perspective.

Objective

This study aimed to dissect the awareness, perception, and positive characteristics of internal medicine (IM) residents as role models.

Methods

This was a cross sectional study, in which 59 medical students (MS) and 64 IM residents from Medstar Georgetown University Hospital completed a questionnaire on role modelling. Descriptive and comparative analyses between both groups were conducted.

Findings

Most participants perceived IM residents as role models, but MS were more likely to report that IM residents lack awareness of their role model status. While MS perceived spending more hours with residents, the residents perceived dedicating more of the time spent together to teaching. Most participants denied previous training in role modelling but expressed interest in receiving formal role modelling training. Most participants reported MS behaviours were modified based on their observations of IM residents; however, while most of these behaviours were positive, there were also negative behaviours reported.

Conclusion

There was a discrepancy between perception and awareness of residents as role models. This characterisation of IM residents as role models sets the ground for the design of interventions to increase awareness and create educational interventions aimed to support residents in their teaching role.
Health‐related quality of life after restrictive versus liberal RBC transfusion for cardiac surgery: Sub‐study from a randomized clinical trial
Authors: Hu Raymond T. , Royse Alistair G. , Royse Colin , Scott David A. , Bowyer Andrea , Boggett Stuart , Summers Peter , Mazer Cyril David
Published: September 2022

Background

Transfusion Requirements in Cardiac Surgery III (TRICS III), a multi‐center randomized controlled trial, demonstrated clinical non‐inferiority for restrictive versus liberal RBC transfusion for patients undergoing cardiac surgery. However, it is uncertain if transfusion strategy affects long‐term health‐related quality of life (HRQOL).

Study Design and Methods

In this planned sub‐study of Australian patients in TRICS III, we sought to determine the non‐inferiority of restrictive versus liberal transfusion strategy on long‐term HRQOL and to describe clinical outcomes 24 months postoperatively. The restrictive strategy involved transfusing RBCs when hemoglobin was <7.5 g/dl; the transfusion triggers in the liberal group were: <9.5 g/L intraoperatively, <9.5 g/L in intensive care, or <8.5 g/dl on the ward. HRQOL assessments were performed using the 36‐item short form survey version 2 (SF‐36v2). Primary outcome was non‐inferiority of summary measures of SF‐36v2 at 12 months, (non‐inferiority margin: −0.25 effect size; restrictive minus liberal scores). Secondary outcomes included non‐inferiority of HRQOL at 18 and 24 months.

Results

Six hundred seventeen Australian patients received allocated randomization; HRQOL data were available for 208/311 in restrictive and 217/306 in liberal group. After multiple imputation, non‐inferiority of restrictive transfusion at 12 months was not demonstrated for HRQOL, and the estimates were directionally in favor of liberal transfusion. Non‐inferiority also could not be concluded at 18 and 24 months. Sensitivity analyses supported these results. There were no differences in quality‐adjusted life years or composite clinical outcomes up to 24 months after surgery.

Discussion

The non‐inferiority of a restrictive compared to a liberal transfusion strategy was not established for long‐term HRQOL in this dataset.
CT and MRI characterization of presumed persistent ossiculum terminale in dogs
Authors: Bourbos Alexandros , Rowan Conor , Cinti Filippo , Pisani Guido , Piola Valentina
Published: September 2022

Anecdotally, during the review of CT and MRI studies of canine patients including the cranial cervical spine, authors have identified a small osseous structure between the atlas (C1) and axis (C2) with no relevant clinical signs. This structure appeared comparable to a “persistent ossiculum terminale” in humans. The aim of this retrospective, multi‐center, case series study was to describe the CT and MRI features of presumed persistent ossiculum terminale in a group of dogs presented with unrelated medical conditions.  Two databases (the imaging database of the teleradiology service VetCT Specialists and the clinical database of the University of Vienna) were scrutinized by different approaches. Medical records of dogs that underwent imaging investigation (CT and/or MRI) that included the atlanto‐axial junction were reviewed. Data collected included signalment, sex, breed, age, presenting symptoms, and final diagnosis. Eighteen dogs met the inclusion criteria. Mean age was 85 months (6–166) and breed variation was present. A total of 20 imaging studies were evaluated: CT was performed in 17 dogs; MRI in three dogs; two dogs had both MRI and CT performed. In all cases the presence of at least one small osseous body on the cranial aspect of the odontoid process compatible with a persistent ossiculum terminale was identified as a possible incidental finding without any overt clinical implications. Findings indicated that a small osseous body on the cranial aspect of the odontoid process (presumed persistent ossiculum terminale) in CT and MRI studies may be present in dogs with no clinical signs of neurologic disease.
Ultrasonographic and contrast‐enhanced CT imaging diagnosis of idiopathic renal hematuria with bilateral hydronephrosis and hydroureter in a dog
Authors: Choi Mihyun , Kim Yongsun
Published: September 2022

A 5‐year‐old spayed female Maltese presented with a 1‐week history of severe hematuria. Abdominal ultrasonography and thoracic, and abdominal computed tomography identified bilateral hydronephrosis and hydroureter due to an obstruction at the left ureter and urinary bladder lesion with no evidence of metastasis. After surgical removal of the material and placement of a temporary ureteral stent, the patient was able to urinate normally. Histological examination revealed a massive blood clot. Based on our review of the literature, this is the first published report describing the imaging diagnosis of obstructive hydronephrosis and hydroureter induced by idiopathic renal hematuria in a dog.
Digital divide among individuals with acquired brain injury: a scoping review protocol
Authors: Chuah Sarah L. , Whiting Diane L. , Simpson Grahame K.
Published: September 2022

Objective:

This scoping review will identify literature pertaining to individuals with an acquired brain injury and digital divide; specifically, examining personal access and use of internet-enabled information and communication technologies. The review will identify the information and communication technologies used by individuals with an acquired brain injury as well as the determinants of technology use. The review will also identify and create a taxonomy of information and communication technologies utilized in relation to cognitive and psychosocial outcomes for individuals with an acquired brain injury in community and outpatient settings.

Introduction:

Internet-enabled technologies are increasingly central to all aspects of living, including health care and community participation; however, gaps in the access to and use of information and communication technologies among individuals with an acquired brain injury may limit the utility of a digitalized society.

Inclusion criteria:

Studies that focus on access to or use of internet-enabled information and communication technologies among individuals with an acquired brain injury (including stroke, infection, tumor, disease, hypoxia, or traumatic brain injury) will be considered in this review.

Methods:

Primary peer-reviewed studies published in English from 2001 onward will be considered for inclusion. Six electronic databases will be searched: Embase, MEDLINE, Web of Science Core Collection, Google Scholar, CINAHL, and APA PsycINFO. Gray literature searches for government and nongovernment organization reports and data, and dissertation theses will be conducted via advanced Google searches. Two reviewers will independently screen titles, abstracts, and full texts of articles based on the “population, concept, context” inclusion criteria. Relevant data will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR).
Psychosocial interventions that facilitate adult cancer survivors’ reintegration into daily life after active cancer treatment: a scoping review protocol
Authors: Murnaghan Sarah , Scruton Sarah , Urquhart Robin
Published: September 2022

Objective:

This scoping review will map the extent and type of evidence related to psychosocial supports and interventions that facilitate adult cancer survivors’ reintegration into daily life and activities after active cancer treatment.

Introduction:

Cancer and its treatment have substantial late and long-term adverse impacts on survivors despite enhanced prospects for survival. Cancer survivors have unmet psychosocial care needs, and recent studies show a lack of focus in survivorship research on outcomes important to survivors. Reintegration is an emerging concept, identified as important to cancer survivors, that focuses on returning to a “new normal” after cancer treatment. This study will explore the available evidence on psychosocial interventions that are targeted toward this outcome.

Inclusion criteria:

The population of interest is adult survivors (18 years and older at diagnosis) of any cancer type. Concepts of interest include psychosocial interventions targeting the outcome and reintegration into daily life after cancer treatment. Interventions addressing clinical depression or anxiety and interventions treating physical needs that are largely medically focused will be excluded.

Methods:

A scoping review of the literature will be conducted in MEDLINE, CINAHL, and Embase. Gray literature will be searched using ProQuest Dissertations and Theses. Studies will be screened at the title/abstract and full-text levels, and data will be extracted by 2 independent reviewers. Disagreements that cannot be resolved will be settled by a third reviewer. Findings will be summarized narratively and in tabular format.

Scoping review registration:

Open Science Framework (https://osf.io/r6bmx)
The effect of leading edge porosity on airfoil turbulence interaction noise
Authors: Bowen Luke , Celik Alper , Zhou Beckett , Westin Michelle Fernandino , Azarpeyvand Mahdi
Published: September 2022

Airfoil turbulence interaction noise and the flow field up to and over the porous leading edge is experimentally studied. The porous leading edges were of the same base triply periodic minimal surface structure with varying porosity to enable us to understand how the porosity, permeability, and pore size affect the generated turbulence interaction noise. The turbulent flow was generated by means of a passive turbulence grid that does not affect the normal background noise of the wind tunnel. Far-field noise results were obtained from a polar microphone array to assess the directivity of the sound as well as the narrowband frequency contributions. Far-field noise results demonstrate that increasing porosity reduces the turbulence interaction noise over low-to-mid frequencies, with a penalty of a high frequency noise increase. Flow measurement results indicate hydrodynamic penetration of the flow into the porous structure at the leading edge. Furthermore, the two-point correlation analysis of the velocity fluctuations approaching the leading edge shows that the turbulent structures approaching the solid leading edge appear to deform into more two-dimensional structures, whereas in the case of the porous leading edge, the turbulent structures appear to retain a strong spanwise coherence up to the point of hydrodynamic penetration.
Incivility and Washington’s NFL Franchise: Exploring Uncivil Discourse in Sports Blog Comment Sections
Authors: Bingaman James
Published: September 2022

The current study sought to explore the prevalence of uncivil discourse surrounding the Washington NFL team’s removal of offensive Native American imagery and later rebranding as the Washington Commanders. The study employed a quantitative content analysis to assess comment sections of news stories on a sports blog between 2014 and 2022. In addition to uncivil discourse, contextual elements such as popularity, reciprocity, and directionality of incivility were also examined. Dovetailing with existing research, roughly one quarter of all comments featured an element of uncivil discourse, with derogatory slurs toward Native Americans being particularly common. Additionally, contextual elements served important roles in the facilitation of incivility. Taken together, the results point to some of the antisocial behavior that can occur in seemingly innocuous online spaces that often reflect broader social and political turmoil related to Native American imagery in sport.
Avoiding conflict with strigolactones
Authors: VanHook Annalisa M.
Published: September 2022

Plants detect and respond to neighbors with root-produced hormones.
Iron Acquisition Mechanisms and Their Role in the Virulence of Acinetobacter baumannii
Authors: Cook-Libin Shoshana , Sykes Ellen M. E. , Kornelsen Vanessa , Kumar Ayush
Published: September 2022

Iron is an essential element for survival of most organisms. One mechanism of host defense is to tightly chelate iron to several proteins to limit its extracellular availability.
A Unique Role of the Human Cytomegalovirus Small Capsid Protein in Capsid Assembly
Authors: Borst Eva Maria , Harmening Sarah , Sanders Saskia , Caragliano Enrico , Wagner Karen , Lenac Roviš Tihana , Jonjić Stipan , Bosse Jens Bernhard , Messerle Martin
Published: September 2022

Human cytomegalovirus (HCMV) is a ubiquitous pathogen causing life-threatening disease in immunocompromised individuals. Virus-specific processes such as capsid assembly and genome packaging can be exploited to design new antiviral strategies.
Shotgun Metagenomic Survey of the Diseased and Healthy Maize (Zea mays L.) Rhizobiomes
Authors: Babalola Olubukola Oluranti , Dlamini Siphiwe Prudence , Akanmu Akinlolu Olalekan
Published: September 2022

The effective functioning of the rhizosphere microbiome significantly contributes to plant development, disease resistance, and agricultural sustainability. Hence, it is a major predictor of plant health. This study evaluated the microbial diversities and functions associated with healthy and diseased maize rhizosphere at selected farms in North West Province, South Africa.
Infectivity of Symptomatic Patients and Their Contribution for Infectiousness of Mosquitoes following a Membrane Feeding Assay in Ethiopia
Authors: Abate Andargie , Kedir Soriya , Bose Mitiku , Hassen Jifar , Dembele Laurent , Golassa Lemu
Published: September 2022

Malaria remains one of the most devastating infectious diseases globally, and transmission-blocking activities are needed.Plasmodiumtransmission from human to mosquitoes is poorly studied, particularly in endemic countries, and the membrane feeding assay allows it to be determined. In this study, we demonstrated human infectious reservoirs of malaria.
Comparative Genomics of
Listeria
Species Recovered from Meat and Food Processing Facilities
Authors: Mafuna T. , Matle I. , Magwedere K. , Pierneef R. E. , Reva O. N.
Published: September 2022

This study provides genomic insights into the recently expanded genus in order to gain valuable information about the evolution of the virulence and stress tolerance properties of the genus
Listeria
and the distribution of these genetic elements pertinent to the pathogenic potential across
Listeria
spp. and clonal lineages in South Africa (SA).
Distinct Features of Sedimentary Archaeal Communities in Hypoxia and Non-Hypoxia Regions off the Changjiang River Estuary
Authors: Zou Dayu , Li Hongliang , Du Ping , Wang Bin , Lin Hua , Liu Hongbin , Chen Jianfang , Li Meng
Published: September 2022

In this study, the sedimentary archaeal community composition and abundance were detailed revealed and quantified based on 16S rRNA genes off the Changjiang River Estuary. We found that the community composition was distinct between hypoxia and non-hypoxia regions, while
Thaumarchaeota
and
Bathyarchaeota
dominated in non-hypoxia and hypoxia samples, respectively.
Understanding the association between admission source and in-hospital delirium: A cross-sectional study
Authors: Thomas Meghan K , Heincelman Marc E , Zhang Jingwen , Marsden Justin , Dulin Jennifer , Robbins Patrick , Hunt Kelly , Mauldin Patrick , Moran William P , Kalivas Benjamin
Published: September 2022

Patients admitted via interhospital transfer (IHT) experience increased risk-adjusted mortality, adverse events, length of stay, and discharge to facility; however, the etiology is not well understood. We hypothesize that IHTs are more likely to experience in-hospital delirium as compared with admissions to the hospital via the emergency department (ED) and clinic. This is a cross-sectional study of all adult admissions to medical, surgical, neurological, and obstetrics and gynecology services at an academic medical center who were screened for delirium between August 2018 and January 2020. Unit of analysis was admission source (IHT vs ED vs clinic) as the independent variable and the primary outcome was in-hospital delirium, assessed with initial brief confusion assessment method (bCAM) screening. 30,100 hospitalizations were included in this study with 3925 admissions (13.0%) screening positive for delirium at the initial bCAM assessment. The prevalence of delirium was much higher in IHTs at 22.3% (1334/5971) when compared with clinic at 5.8% (244/4214) and ED at 11.8% (2347/19,915) admissions. Multivariable logistic regression adjusting for demographics and comorbidities showed that IHT admissions had higher odds (OR 1.91, 95% CI 1.74 to 2.10) and clinic admissions had lower odds (OR 0.56, 95% CI 0.48 to 0.64) of in-hospital delirium compared with ED admissions. Increased odds of delirium in IHT admissions may contribute to the observed increased length of stay, discharge to facility, and mortality. These results emphasize the importance of routine screening and possible intervention prior to patient transfer.
Historical view of medical Spanish instruction in a medical school at the US–Mexico border region
Authors: Cervantes Jorge , Francis Mark L , Nigro Kirsten F , Sánchez-Llorente Lucía , Garcia Gilberto , Rios Daniel , Munoz Arely , Delarosa Jose Manuel
Published: September 2022

With a growing speaking Spanish population in the USA, it is necessary to help meet their healthcare needs. The Paul L. Foster School of Medicine is located in El Paso at the US–Mexico border. The medical Spanish curriculum is required for all medical students and begins on their first day of medical school, with conversational Spanish and medical Spanish through the preclerkship years. One of the key elements to the success of this course is the use of instructors with expertise in language instruction with an emphasis on task-based instruction. In addition to language instruction, this course also emphasizes instruction and experience in the culture of the US–Mexico border region. While taught medical Spanish, students are also prompted to understand when their skills are not adequate for the situation, in which case they need to enlist a skilled translator. Students report that, on a daily basis, they productively use what they learned in this preclerkship curriculum.
Thermal brachistochrone for harmonically confined Brownian particles
Authors: Patrón Antonio , Prados Antonio , Plata Carlos A.
Published: September 2022

The overdamped Brownian dynamics of a harmonic oscillator is a paradigmatic system in non-equilibrium statistical mechanics, which reliably models relevant stochastic systems such as colloidal particles submitted to optical confinement. In this work, optimal thermal protocols are tailored to minimise the connection time between equilibrium states of overdamped d-dimensional oscillators. Application of control theory reveals that these optimal protocols are of bang-bang type, that is, the temperature of the bath has to take alternatively the minimum and maximum values allowed. Minimum connection times increase with the considered dimension d. Remarkably, this is the case even for symmetric oscillators, for example, with spherical symmetry—in which the degeneracy of the elastic constant along the d possible directions seems to imply a minimum connection time equal to that for the one-dimensional case. This surprising unavoidable price to pay when increasing dimension is thoroughly investigated and understood on a physical basis. Moreover, information theory tools such as the thermodynamic length and its divergence are analysed over the brachistochrone.
Significance of variable thermal conductivity and nonuniform heating Source for Burgers nanofluid flow subject to modified thermal laws
Authors: Khan Sami Ullah , Al-Khaled Kamel , Gasmi Hatem , Hamdi Essaieb , Ouazir Abderrahmane , Ghazouani Nejib.
Published: September 2022

The thermal conductivity attributes a major role to the thermal transportation and engineering processes where the fluid is used as an energy source. It has been commonly noted that much attention of research towards the heat and fluid flow is intended by keeping the fluctuation of thermal conductivity as a constant. However, experimental results shows that most of the times, thermal conductivity changes in variation of temperature, pressure or different configurations. The prime attention of current research is to explore the role of variable thermal conductivity for thermal transport of Burgers nanofluid due to inclined surface. The Buongiorno nanofluid model is used to illustrate the Brownian motion and thermophoresis properties. The heat transfer phenomenon is analyzed by incorporating the modified Cattaneo–Christov (CC) theories. Moreover, to maintain the improved heat transfer rate, the novel nonuniform heat source applications are also utilized. After altering the governing problem into dimensionless system, homotopy analysis scheme is used with excellent accuracy. The physical pattern of velocity, heat transfer rate and concentration phenomenon are observed in view of involved parameters. It is noted that the presence of variable thermal conductivity enhanced the thermal process more effectively as compared to constant thermal conductivity assumptions. Both heat and mass transfer phenomenon enhances for Deborah number. The declining concentration change is observed with variation of concentration relaxation number.
Optimized Neural Network with Refined Features for Categorization of Motor Imaginary Signals
Authors: Wankhade Megha M. , Chorage Suvarna S.
Published: September 2022

Motor imaginary (MI) is an attractive research field in the brain–computer interfaces (BCIs) function, in which the system is directed by the imaginary arm movement of the subject. This attention is due to the monstrous potential for its pertinence in neurorestoration, neuroprosthetics, and gaming, where the client’s considerations of envisioned developments should be decoded. An electroencephalography (EEG) device is regularly utilized for monitoring frontal cortex movements in BCI frameworks. The EEG signals are perceived through the two fundamental processes such as feature extraction and characterization process. This research concentrates on developing a predominant MI categorization model utilizing deep learning techniques. The prominence of this research relies on the combined features + proposed PROA-based RideNN process known as holo-entropy-based WPD, which extracts the most dominant feature from the EEG signals. The extracted features enhance the performance of the RideNN classifier. The analysis is done by utilizing the BCI Competition-IV-2a, -2b, and GigaScience datasets with respect to performance parameters, such as specificity, accuracy, and sensitivity. The analysis revealed the effective performance of the proposed method with respect to the existing state-of-art methodologies.
Mechanical response and deterioration mechanism of sandstone with intermittent joints under cyclic drying–saturation
Authors: Chen Guangbo , Li Yuan , Li Tan , Zhang Guohua
Published: September 2022

A drying–saturation cyclic water–rock interaction test simulating the periodic fluctuation of reservoir water level was designed. The results are as follows. (1) With increasing number of cycles, the compressive strength of a sandstone joint gradually decreases. The compressive strength decreases rapidly for the first four cycles and a deterioration effect is obvious. As the joint dip angle increases, the compressive strength of the sandstone joint shows a U-shaped distribution. (2) With increasing number of cycles, the elastic modulus of the sandstone joint gradually decreases. With increasing joint inclination angle, the elastic modulus shows a V-shaped trend of change. (3) With increasing number of cycles, the brittleness of the sample obviously decreases and the sample shows the characteristics of looseness and weakness. With the increase of joint inclination, the failure mode of the sample gradually changes from tensile failure to tensile-shear failure to tensile failure. (4) The mechanical properties of an intermittent sandstone joint under circulating water–rock interaction show obvious deterioration effects, which are the result of physical, chemical and mechanical actions occurring inside the sandstone joint.
Machine-learning-driven Architectural Selection of Adders and Multipliers in Logic Synthesis
Authors: Cheng Jiawen , Xiao Yong , Shao Yun , Dong Guanghai , Lyu Songlin , Yu Wenjian
Published: September 2022

Designing high-performance adders and multiplier components for diverse specifications and constraints is of practical concern. However, selecting the best architecture for adder or multiplier, which largely affects the performance of synthesized circuits, is difficult. To tackle this difficulty, a machine-learning-driven approach is proposed for automatic architectural selection of adders and multipliers. It trains a machine learning model for classification through learning a number of existing design schemes and their performance data. Experimental results show that the proposed approach based on a multi-perception neural network achieves as high as 94% prediction accuracy with negligible inference time. On a CPU server, the proposed approach runs about 4× faster than a brute-force approach trying four candidate architectures and consumes 10%~20% less runtime than the DesignWare datapath generator for obtaining the optimal adder/multiplier circuit. The adder (multiplier) generated with the proposed approach achieves performance metrics close to the optimal and has 1.6% (5.2%) less area and 2.2% (7.1%) more worst negative slack averagely than that generated with the DesignWare datapath generator. Our experiment also shows that the proposed approach is not sensitive to the size of training subset.
1-to-1 or 1-to-n? Investigating the Effect of Function Inlining on Binary Similarity Analysis
Authors: Jia Ang , Fan Ming , Jin Wuxia , Xu Xi , Zhou Zhaohui , Tang Qiyi , Nie Sen , Wu Shi , Liu Ting
Published: September 2022

Binary similarity analysis is critical to many code-reuse-related issues, where function matching is its fundamental task. “1-to-1” mechanism has been applied in most binary similarity analysis works, in which one function in a binary file is matched against one function in a source file or binary file. However, we discover that the function mapping is a more complex problem of “1-to-n” (one binary function matches multiple source functions or binary functions) or even “n-to-n” (multiple binary functions match multiple binary functions) due to the existence offunction inlining, different from traditional understanding.

In this article, we investigate the effect of function inlining on binary similarity analysis. We carry out three studies to investigate the extent of function inlining, the performance of existing works under function inlining, and the effectiveness of existing inlining-simulation strategies. Firstly, a scalable and lightweight identification method is designed to recover function inlining in binaries. 88 projects (compiled in 288 versions and resulting in 32,460,156 binary functions) are collected and analyzed to construct four inlining-oriented datasets for four security tasks in the software supply chain, including code search, OSS (Open Source Software) reuse detection, vulnerability detection, and patch presence test. Datasets reveal that the proportion of function inlining ranges from 30–40% when using O3 and sometimes can reach nearly 70%. Then, we evaluate four existing works on our dataset. Results show most existing works neglect inlining and use the “1-to-1” mechanism. The mismatches cause a 30% loss in performance during code search and a 40% loss during vulnerability detection. Moreover, most inlined functions would be ignored during OSS reuse detection and patch presence test, thus leaving these functions risky. Finally, we analyze two inlining-simulation strategies on our dataset. It is shown that they miss nearly 40% of the inlined functions, and there is still a large space for promotion. By precisely recovering when function inlining happens, we discover that inlining is usually cumulative when optimization increases. Thus, conditional inlining and incremental inlining are recommended to design a low-cost and high-coverage inlining-simulation strategy.
Detecting Thresholds of Ecological Change in the Anthropocene
Authors: Spake Rebecca , Barajas-Barbosa Martha Paola , Blowes Shane A. , Bowler Diana E. , Callaghan Corey T. , Garbowski Magda , Jurburg Stephanie D. , van Klink Roel , Korell Lotte , Ladouceur Emma , Rozzi Roberto , Viana Duarte S. , Xu Wu-Bing , Chase Jonathan M.
Published: September 2022

Ecological thresholds comprise relatively fast changes in ecological conditions, with respect to time or external drivers, and are an attractive concept in both scientific and policy arenas. However, there is considerable debate concerning the existence, underlying mechanisms, and generalizability of ecological thresholds across a range of ecological subdisciplines. Here, we usethe general concept of scale as a unifying framework with which to systematically navigate the variability within ecological threshold research. We review the literature to show how the observational scale adopted in any one study, defined by its organizational level, spatiotemporal grain and extent, and analytical method, can influence threshold detection and magnitude. We highlight a need for nuance in synthetic studies of thresholds, which could improve our predictive understanding of thresholds. Nuance is also needed when translating threshold concepts into policies, including threshold contingencies and uncertainties.
Nanosheet-MoO3/Ti Porous Membrane Electrode for Dye Wastewater Treatment
Authors: Hui Hongsen , Liu Jinhua , Dong Guoqiang , Wang Jiao , Li Jiaxin , Tang Chunxiang , Zhao Tong , Pei Hongchang , Zhang Lei , Li Zhongfang , Zhang Yujun
Published: September 2022

Membrane coupling with electrochemical processes has proven to be an effective way for wastewater treatment. However, it still suffering from high energy consumption and low operational stability. Three different forms nanosheet-MoO3 were prepared by hydrothermal synthesis method via adjusting various additives to ammonium heptamolibdate. MoO3 loaded porous Ti membranes was employed as anode to constitute fixed-bed electrocatalytic reactor (FBER) for synthetic dye wastewater treatment to overcome the drawback of three different forms. The electrochemical properties of MoO3/Ti membranes were investigated, results showed that the MoO3/Ti membranes with hexadecyltrimethylammonium bromide (CTAB) additive exhibited the best electrochemical performance. Meanwhile, three MoO3/Ti membranes were used to constitute FBER for 100 mg l−1 MO wastewater treatment, the MO and COD removal rate of MoO3/Ti without additive, MoO3/Ti with CrCl3 additive and MoO3/Ti with CTAB additive were 78.6% and 65.3%, 83.2% and 72.9%, 90.3% and 81.6%, respectively. Furthermore, the energy consumption of MoO3/Ti with CTAB additive was only 0.76 kWh·kg−1·COD. After 3 repeated stabilities experiment of 12 h MO wastewater treatment, the removal rate of MO and COD remained above 97.2% and 88.6%. In sum, the FBER exhibits a great potential in the dye wastewater treatment with high efficiency and excellent stability.
Pulse Electrodeposition of Interconnected Porous Si-Cu Composites as Anodes for Lithium-Ion Batteries
Authors: Li Guomin , Fan Chenming , Wang Heng , Zhan Xiaoqiang , You Jinglin , Li Bing
Published: September 2022

Si-Cu composites composed of an alternate Si-rich layer and Cu layer were obtained by two-potential pulse electrodeposition of −1900 mV and −1600 mV in 0.002 mol l−1 Cu(TfO)2−1 mol l−1 SiCl4(saturated)-[BMP]Tf2N ionic liquid at room temperature. The potential lasting time ratios for −1900 mV and −1600 mV changed from 0.5 s/0.5 s to 4 s/0.5 s, respectively. All the Si-Cu composites showed an interconnected porous structure caused by the SiCl4 bubbles templates formation during electrodeposition. Especially, the Si-Cu 4–1 composite prepared at −1900 mV/−1600 mV for 2 s/0.5 s within 1 h, presented an interconnected mesoporous and macropore structure. And the Si-Cu 4–1 composite exhibited the best rate and cycle performances as anode of lithium-ion battery, with the initial capacity of 1589.2 mAh g−1 and capacity retention ratio of 72.6% after 1000 cycles at 1 C. This is attributed to the lowest charge transfer resistance and fastest Li+ transfer ability due to the beneficial porosity-structure. This finding provides a new idea for the directly designing of interconnected porous material by pulse electrodeposition.
Design and Implementation of Sports Industry Information Service Management System Based on Data Mining
Authors: Zhang Hang
Published: September 2022

With the continuous development of sports in China, the tentacles of the sports industry have extended to all walks of life in China. At the same time, with the development of information and network, the information exchange between enterprises and between enterprises and between enterprises and customers is also increasing. How to use the existing information technology to provide enterprises and customers with special information about the sports industry has become a focus of the author’s thinking. Combining the development of our city’s sports industry, based on B/S mode, with ASP.NET for the development of technology, designed specifically for sports enterprises and users to provide an information exchange platform, this paper studies the user-based collaborative filtering recommendation algorithm and its application in sports industry information service management system, to design and develop the corresponding sports industry information service management system.
Research on Network Data Monitoring and Legal Evidence Integration Based on Cloud Computing
Authors: Ge Li , YanLi Peng
Published: September 2022

In today’s society, technologies such as social network, mobile Internet, and Internet of things are developing by leaps and bounds, and data are growing at an unprecedented rate. How to manage and reasonably use such data sources has become the most popular research topic, and cloud computing technology can provide powerful computing and storage capabilities for data sources, further enhance the comprehensive processing capacity of big data, and realize the real value of data sources. Based on this point, this paper focuses on the nature of data network delivery and its requirements for real-time accuracy and performance monitoring, and studies the key computing flow technology for network data monitoring. The main achievement is to build a data processing and analysis platform based on computing flow, and design and implement the overall structure of the platform and data anomaly monitoring model. Finally, this paper uses big data technology to design and build an integrated auxiliary legal service system. The system can help judges and prosecutors fully understand the progress and research results of guiding cases, and provide them with a series of applicable laws and regulations, so as to maximize work efficiency. The system can also help implement the investment of legal education, so as to provide basic legal services for the public, integrate legal evidence, and timely implement public opinion guidance for some public opinion media on legal topics and cases, so as to minimize social risks. This paper combines cloud computing technology with network data detection and applies it to the research field of legal auxiliary services, which greatly promotes the development of legal evidence integration technology.
[Retracted] Evaluation System of Music Art Instructional Quality Based on Convolutional Neural Networks and Big Data Analysis
Authors: Lan Qingwei , Fan Ning
Published: September 2022

In order to speed up the process of high‐quality education and improve the level of education quality among the general public, people have pushed for the use of music art education in recent years. In this respect, this study covers the CNN‐based assessment of the quality of music art teaching and creates a set of evaluation indices for that quality. The model architecture, network topology, learning parameters, and learning algorithm are all determined using this information, which also acts as the basis for the NN assessment model. The MATLAB simulation tool uses the CNN assessment model to train and learn a predetermined quantity of instructional quality data. The training experiment shows that this system can outperform other comparative systems in prediction accuracy by roughly 95%. Additionally, both the training and prediction accuracy of the model are completely acceptable. The evaluation findings and analytical data of the music art instructional quality assessment system created in this study can be used as a guide for determining the music art instructional quality and for making judgments regarding it.
An Adaptive Reinforcement Learning-Based Scheduling Approach with Combination Rules for Mixed-Line Job Shop Production
Authors: Zhu Haihua , Zhang Yi , Liu Changchun , Shi Wei
Published: September 2022

Affected by economic globalization and market diversification, more manufacturing enterprises realize that large-scale production cannot adapt to the current market environment. The new trend of multivariety customized mixed-line production brings a higher level of disturbances and uncertainties to production planning. Traditional methods cannot be directly applied to the classic flexible job shop scheduling problem (FJSP). Therefore, this paper presents an adaptive scheduling method for mixed-line job shop scheduling. First, the scheduling problem caused by combined processing constraints is studied and transformed by introducing the definition of virtual operation. According to the situation of the coexistence of trial-production and batch production, the disturbance processing mechanism is established. And a scheduling decision model is established based on contextual bands (CBs) in reinforcement learning to overcome the shortcoming of poor performance of traditional single dispatching rule strategy. Through continuous trial and error learning, each scheduler can select the most suitable scheduling rules according to the environment state. Finally, we benchmark the performance of the scheduling algorithm with scheduling methods based on a variety of single scheduling rules. The results show that the proposed algorithm not only improves the performance in the mixed production scheduling problem but also effectively copes with emergency trial-production orders.
Research on the Coordinated Development of New Rural Production and Living Civilization Construction from the Perspective of Green Transformation and Development
Authors: Li Xiaoyan
Published: September 2022

In order to improve the collaborative development effect of new rural production and living civilization construction, this article studies the collaborative development of rural production and living civilization construction combined with intelligent data processing algorithms and builds a model from the perspective of green transformation and development. In order to find as many and evenly distributed points as possible on the Pareto interface, a coevolution operator is designed in this article. The Pareto solutions of the two populations exchange information through the action of the co-occurrence operator and the absorption operator, so that the algorithm can find more and better noninferior solutions. The research shows that the collaborative development model of new rural production and living civilization construction has a certain effect, and it has a certain role in promoting the collaborative development of new rural production and living civilization construction.
Mobile Robot Application with Hierarchical Start Position DQN
Authors: Erkan Emre , Arserim Muhammet Ali
Published: September 2022

Advances in deep learning significantly affect reinforcement learning, which results in the emergence of Deep RL (DRL). DRL does not need a data set and has the potential beyond the performance of human experts, resulting in significant developments in the field of artificial intelligence. However, because a DRL agent has to interact with the environment a lot while it is trained, it is difficult to be trained directly in the real environment due to the long training time, high cost, and possible material damage. Therefore, most or all of the training of DRL agents for real-world applications is conducted in virtual environments. This study focused on the difficulty in a mobile robot to reach its target by making a path plan in a real-world environment. The Minimalistic Gridworld virtual environment has been used for training the DRL agent, and to our knowledge, we have implemented the first real-world implementation for this environment. A DRL algorithm with higher performance than the classical Deep Q-network algorithm was created with the expanded environment. A mobile robot was designed for use in a real-world application. To match the virtual environment with the real environment, algorithms that can detect the position of the mobile robot and the target, as well as the rotation of the mobile robot, were created. As a result, a DRL-based mobile robot was developed that uses only the top view of the environment and can reach its target regardless of its initial position and rotation.
Effects of Oral Administration of Lactiplantibacillus Plantarum APsulloc 331261 (GTB1TM) Isolated from Green Tea on Atopic Dermatitis (AD)-like Skin Lesion Mouse Models
Authors: Kim Su-Young , Lee Jung Ok , Kim Yu-Jin , Jang You Na , Lee Jung Min , Park A. Yeon , Yoo Kwang-Ho , Kim Beom Joon
Published: September 2022

Background. Probiotics are known to improve atopic dermatitis (AD) by inhibiting T helper 2 (Th2)-related reactions, restoring the Th2/T helper1 (Th1) cytokine ratio. The most popular probiotic is Lactiplantibacillus plantarum (L. plantarum), which is widely used in the food and pharmaceutical industries. L. plantarum APsulloc 331261 (GTB1) used in this study was isolated from green tea. Materials and Methods. The effectiveness of oral GTB1 administration in improving AD was evaluated by visual evaluation, comparison of the lymph node sizes and spleen weights, histological evaluation, RT-qPCR, ELISA, and IHC analysis in the mouse model. Results. GTB1 improved AD symptoms, reduced epidermal thickness and mast cell numbers, decreased lymph node size and the spleen weight, increased filaggrin and loricrin protein levels, downregulated Th2 expression, and upregulated Th1 expression in a colony-forming unit-dependent manner. Conclusion. Oral administration of GTB1 isolated from green tea (Camellia sinensis) improved the AD symptoms, reduced hypersensitivity reaction, and increased the skin barrier function. Finally, it is involved in AD improvement by restoring the Th2/Th1 cytokine balance.
Research on the Intelligent Cloud Animal Husbandry Platform
Authors: Wang Buyu , Qi Jingwei
Published: September 2022

Aiming at the problem that the traditional talent training mode is difficult to cultivate the intelligent animal husbandry compound talents needed by the implementation of the rural revitalization strategy, a cloud animal husbandry platform is designed to cultivate “Understand Agriculture, devote to Rural Community and Be Sincere to Farmers” compound talents. The platform adopts the two-wing multilevel architecture design of the concept of the cloud side, which is composed of three parts: the data center platform, resource sharing platform, and business cloud service platform. The data center platform is responsible for the collection, processing, integration, and asset management of the four-dimensional real data and provides computing, storage, and data asset services for the cloud livestock platform. The resource sharing platform provides sharing services from resources and development kits to carriers. Livestock cloud service platform is to carry out the integration of industry, education, and science and education, the design and implementation of cloud teaching, cloud scientific research, and cloud breeding business cloud services. Through its practical application in many universities and enterprises, the platform is verified to be safe, effective, and reliable in teaching, scientific research, and social services and has both operational and promotional value.
The Quality Assessment of Pavement Performance Using the Entropy Weight-Variable Fuzzy Sets Model
Authors: Li Y. , Wang Y. H. , Wu Q. H. , Gu X. B.
Published: September 2022

As the assessment of pavement performance has considerable repercussions for the construction quality of roads, the study of the assessment procedure used is extremely critical. Riding quality index (RQI), pavement condition index (PCI), pavement structure strength index (PSSI), skid resistance index (SRI), and antirutting index (ARI) are selected as the assessment indexes of pavement performance. Then, the entropy weight-variable fuzzy sets model is introduced. Second, a relative membership degree matrix for the variable fuzzy sets is established, and the entropy weight method is used to determine the weight coefficients considering the uncertainty in the assessment indices. Finally, the quality level of pavement performance is determined by using the mean ranking feature value. The conclusions demonstrate a very accurate rate for the quality assessment of the pavement performance based on the variable fuzzy sets model compared to that based on the current specification, and the proposed method is feasible for the quality assessment of pavement performance, thus providing a novel means of assessing the quality level of pavement performance in the future.