bluuebunny/crossref_metadata_2025 huggingface dataset:
Beverage consumption and mortality among adults with type 2 diabetes: prospective cohort study
Authors: Ma Le , Hu Yang , Alperet Derrick J , Liu Gang , Malik Vasanti , Manson JoAnn E , Rimm Eric B , Hu Frank B , Sun Qi
Published: April 2023

Objective

To investigate the intake of specific types of beverages in relation to mortality and cardiovascular disease (CVD) outcomes among adults with type 2 diabetes.

Design

Prospective cohort study.

Setting

Health professionals in the United States.

Participants

15 486 men and women with a diagnosis of type 2 diabetes at baseline and during follow-up (Nurses’ Health Study: 1980-2018; and Health Professionals Follow-Up Study: 1986-2018). Beverage consumption was assessed using a validated food frequency questionnaire and updated every two to four years.

Main outcome measures

The main outcome was all cause mortality. Secondary outcomes were CVD incidence and mortality.

Results

During an average of 18.5 years of follow-up, 3447 (22.3%) participants with incident CVD and 7638 (49.3%) deaths were documented. After multivariable adjustment, when comparing the categories of lowest intake of beverages with the highest intake, the pooled hazard ratios for all cause mortality were 1.20 (95% confidence interval 1.04 to 1.37) for sugar sweetened beverages (SSBs), 0.96 (0.86 to 1.07) for artificially sweetened beverages (ASBs), 0.98 (0.90 to 1.06) for fruit juice, 0.74 (0.63 to 0.86) for coffee, 0.79 (0.71 to 0.89) for tea, 0.77 (0.70 to 0.85) for plain water, 0.88 (0.80 to 0.96) for low fat milk, and 1.20 (0.99 to 1.44) for full fat milk. Similar associations were observed between the individual beverages and CVD incidence and mortality. In particular, SSB intake was associated with a higher risk of incident CVD (hazard ratio 1.25, 95% confidence interval 1.03 to 1.51) and CVD mortality (1.29, 1.02 to 1.63), whereas significant inverse associations were observed between intake of coffee and low fat milk and CVD incidence. Additionally, compared with those who did not change their consumption of coffee in the period after a diabetes diagnosis, a lower all cause mortality was observed in those who increased their consumption of coffee. A similar pattern of association with all cause mortality was also observed for tea, and low fat milk. Replacing SSBs with ABSs was significantly associated with lower all cause mortality and CVD mortality, and replacing SSBs, ASBs, fruit juice, or full fat milk with coffee, tea, or plain water was consistently associated with lower all cause mortality.

Conclusions

Individual beverages showed divergent associations with all cause mortality and CVD outcomes among adults with type 2 diabetes. Higher intake of SSBs was associated with higher all cause mortality and CVD incidence and mortality, whereas intakes of coffee, tea, plain water, and low fat milk were inversely associated with all cause mortality. These findings emphasize the potential role of healthy choices of beverages in managing the risk of CVD and premature death overall in adults with type 2 diabetes.
Whole person assessment for family medicine: a systematic review
Authors: Thomas Hayley Robyn , Best Megan , Chua David , King David , Lynch Johanna
Published: April 2023

Objectives

To identify and evaluate clinical approaches to whole person assessment (WPA) that are translatable to family medicine regarding feasibility, quality and alignment with theoretical models of whole person care (WPC).

Design

Systematic literature review.

Data sources

MEDLINE, CINAHL, PsycINFO and ATLA Religion databases were searched through 9 March 2020, with additional handsearches.

Eligibility criteria

English language clinical assessments of multiple domains; which involve patient–clinician interaction and are translatable to general practice (GP); from the fields of medicine, allied health, nursing, mental health and pastoral care. Tools designed for single diseases or symptoms, for outcome rather than clinical assessment or with outdated classification systems were excluded.

Data extraction and synthesis

We appraised the quality of included papers using Johanna Briggs’ Institute Checklists and Terwee’s criteria for validation studies. Clinical assessments’ alignment with theoretical WPC, feasibility for adaptation to GP and quality were examined. We analysed extracted data using framework synthesis.

Results

Searches retrieved 7535 non-duplicate items. Fifty-nine were included after screening, describing 42 WPA methods and representing multiple disciplines, purposes and formats. All included assessments aligned partially with models of WPC, but most did not adequately encompass all aspects of WPC. Robustness varied significantly and was often inadequately described. We judged none of the identified assessments to be ideal as a multipurpose WPA in GP. Some could be used for specific purposes, such as elicitation of patient perspectives or complexity assessment.

Conclusions

While no WPAs were found that were sufficient for broad implementation in GP, some approaches may be suitable with adaptation and evaluation. Strengths of existing approaches could inform WPA development in future.

PROSPERO registration number

CRD42020164417.
Well-being focused interventions for caregivers of children with developmental disabilities: a scoping review protocol
Authors: Abeasi Doreen Asantewa , Nkosi Nokuthula Gloria , Suglo Joseph Ngmenesegre
Published: April 2023

Introduction

Children with developmental disability (DD) may depend on their family caregivers to fulfil their complex health needs. Family caregivers are generally described as persons providing unpaid for services for the child with DD at home who need to be supported in a manner that supports and promotes his/her well-being. This review aims to identify and map the range of interventions available for caregivers of children between the ages of 5–16 with DD.

Methods and analysis

The methodological framework for conducting scoping review as published by Arksey and O’Malley and the Joanna Briggs Institute’s guidelines will used in this study. Primary research articles will be obtained through a systematic search of CINAHL, Psych INFO, PubMed, ERIC and COCHRANE Library. Further grey literature will be obtained from Google Scholar search. Study selection process will be done by two independent researchers based on a predetermined inclusion criteria. Review findings comprising interventions, intervention components and outcomes will be presented using tables and narrative text.

Discussion

The proposed scoping review will give an extensive review of interventions aimed at improving the well-being of caregivers of children with DD. This scoping review would provide recommendations on interventions that have significantly improved the well-being caregivers of children with DD. Additionally, the review would guide future work on intervention development and primary research in this field.

Registration

This scoping review protocol has been registered with the Open Science Framework (https://osf.io/tkbrh).
SARS-CoV-2 seroprevalence and living conditions in Bamako (Mali): a cross-sectional multistage household survey after the first epidemic wave, 2020
Authors: Cissoko Mady , Landier Jordi , Kouriba Bourema , Sangare Abdoul Karim , Katilé Abdoulaye , Djimde Abdoulaye A , Berthé Ibrahima , Traore Siriman , Thera Ismaila , Hadiata Maiga , Sogodogo Elisabeth , Coulibaly Karyn , Guindo Abdoulaye , Dembele Ousmane , Sanogo Souleymane , Doumbia Zoumana , Dara Charles , Altmann Mathias , Bonnet Emmanuel , Balique Hubert , Sagaon-Teyssier Luis , Vidal Laurent , Sagara Issaka , Bendiane Marc-Karim , Gaudart Jean
Published: April 2023

Objectives

In low-income settings with limited access to diagnosis, COVID-19 information is scarce. In September 2020, after the first COVID-19 wave, Mali reported 3086 confirmed cases and 130 deaths. Most reports originated from Bamako, with 1532 cases and 81 deaths (2.42 million inhabitants). This observed prevalence of 0.06% appeared very low. Our objective was to estimate SARS-CoV-2 infection among inhabitants of Bamako, after the first epidemic wave. We assessed demographic, social and living conditions, health behaviours and knowledges associated with SARS-CoV-2 seropositivity.

Settings

We conducted a cross-sectional multistage household survey during September 2020, in three neighbourhoods of the commune VI (Bamako), where 30% of the cases were reported.

Participants

We recruited 1526 inhabitants in 3 areas, that is, 306 households, and 1327 serological results (≥1 years), 220 household questionnaires and collected answers for 962 participants (≥12 years).

Primary and secondary outcome measures

We measured serological status, detecting SARS-CoV-2 spike protein antibodies in blood sampled. We documented housing conditions and individual health behaviours through questionnaires among participants. We estimated the number of SARS-CoV-2 infections and deaths in the population of Bamako using the age and sex distributions.

Results

The prevalence of SARS-CoV-2 seropositivity was 16.4% (95% CI 15.1% to 19.1%) after adjusting on the population structure. This suggested that ~400 000 cases and ~2000 deaths could have occurred of which only 0.4% of cases and 5% of deaths were officially reported. Questionnaires analyses suggested strong agreement with washing hands but lower acceptability of movement restrictions (lockdown/curfew), and mask wearing.

Conclusions

The first wave of SARS-CoV-2 spread broadly in Bamako. Expected fatalities remained limited largely due to the population age structure and the low prevalence of comorbidities. Improving diagnostic capacities to encourage testing and preventive behaviours, and avoiding the spread of false information remain key pillars, regardless of the developed or developing setting.

Ethics

This study was registered in the registry of the ethics committee of the Faculty of Medicine and Odonto-Stomatology and the Faculty of Pharmacy, Bamako, Mali, under the number: 2020/162/CA/FMOS/FAPH.
Association between hysterectomy and hypertension among Indian middle-aged and older women: a cross-sectional study
Authors: Mustafa Akif
Published: April 2023

Objective

To examine the association between hysterectomy and hypertension among middle-aged and older women in India, as well as to determine if the association differs across different age groups.

Design

A cross-sectional exploratory study.

Setting and participants

Nationally representative population-based data of the Longitudinal Ageing Study in India (2017–2018) were used in this study. The sample included 32 460 women aged 45 years and above.

Outcome measures

Self-reported hypertension was the outcome variable. The variable was a binary variable, with 1 representing hypertensive and 0 representing not hypertensive.

Methods

Entropy balance method, along with logistic regression analysis, was used to meet the objectives.

Results

31.3% of the women without hysterectomy and 42.5% of the women with hysterectomy were hypertensive. A perfect covariate balance was achieved between the treatment and control groups using the entropy balance method. Women with hysterectomy had 36% (OR 1.36; 95% CI 1.26 to 1.48) higher odds of hypertension than women without hysterectomy. The OR was 1.23 (95% CI 1.03 to 1.47) for the age group 45–49, whereas, for the age group 80+, it was 1.87 (95% CI 1.18 to 2.97), showing that the magnitude of the association between hysterectomy and hypertension varied with age.

Conclusion

The findings of this study suggest that hysterectomy and hypertension have a significant association in middle-aged as well as older women in India.
Role of neuromodulation in acute pain settings
Authors: Tsui Ban C H , Gupta Rajnish K
Published: April 2023

Peripheral nerve stimulation (PNS), a type of neuromodulatory technique, is increasingly used to treat chronic pain syndromes. PNS has also recently gained popularity as a viable adjunct analgesic modality in acute pain settings, where the practice primarily relies on using boluses or infusion of local anesthetics for nerve blockade, followed by stimulation to extend the analgesia. There is some early promise in PNS for perioperative analgesic control, but considerable obstacles must be addressed before it can be implemented into standard practice. In this daring discourse, we explore the possibilities and constraints of using the PNS paradigm in acute pain.
Role of peripheral nerve stimulation in treating chronic neuropathic pain: an international focused survey of pain medicine experts
Authors: Li Alice Huai-Yu , Bhatia Anuj , Gulati Amit , Ottestad Einar
Published: April 2023

Interventional pain management (IPM) options for refractory neuropathic pain (NP) have recently increased with availability of peripheral nerve stimulation (PNS) equipment and expertise. Given a lack of high-quality evidence and guidelines on this topic, we sought to understand the perception of physicians with expertise in treating NP regarding IPM and the role of PNS. We emailed a survey in March 2022 to international NP experts including pain medicine physicians, researchers, and leaders of 11 professional pain societies. No representatives from vendors of PNS systems were included in the design of the survey nor as respondents. Among 24 respondents (67% of those contacted), the distal common peroneal, tibial, and sural nerves were most frequently targeted (60%) with PNS. Persistent postsurgical pain of more than 3 months was the most common indication for PNS (84%). The aggregate NP treatment algorithm in order of median rank was non-opioid medications as first line, IPM including epidural/perineural steroid injections tied with transcutaneous electrical nerve stimulation as second line, pulsed radiofrequency (RF) tied with RF ablation/denervation as third line, temporary then permanent PNS as fourth line, followed by spinal cord stimulation, opioids, cryoablation, botulinum, peripheral nerve field stimulation, intrathecal targeted drug delivery, and others. Before offering PNS, 12 respondents (50%) indicated their preference for trialing non-neuromodulation treatments for 1–3 months. Twenty-two respondents (92%) agreed PNS should be offered early in the treatment of neuropathic pain. The most common barriers to PNS use were cost, lack of high-quality evidence in support of its use, lack of exposure to PNS in training programs, and lack of familiarity with the use of ultrasound guidance. PNS appears to have an increasing role in the treatment of NP but more research is needed on the outcomes of PNS to elucidate its role.
Spatial prediction of rockhead profile using the Gaussian process regression method
Authors: Deng Zhi-Ping , Pan Min , Niu Jing-Tai , Jiang Shui-Hua , Wu Bang-bin , Li Shuang-long
Published: April 2023

The spatial distribution of rockhead profile has a significant impact on the design and construction of geotechnical engineering structures. Limited by the economic and technical conditions, the borehole data of specific sites are often sparse, which brings great challenges to the accurate prediction of rockhead profile. In this study, a Gaussian process regression (GPR) method is used to predict the rockhead profile. Borehole data from a construction site in Hong Kong are used to evaluate the ability of the GPR method to predict rockhead profile. Besides, the influences of the amount of borehole data on the accuracy of the GPR model and the spatial prediction results of rockhead are investigated. The results indicate that the GPR model based on the square exponential and the Matérn covariance function can obtain more accurate prediction results, and the GPR model with limited borehole data can provide a reasonable prediction interval for rockhead depth. With the increase of borehole data, the generalization ability and prediction accuracy of the GPR model gradually improves. In engineering practice, the prediction accuracy and uncertainty degree of the GPR model can be used to judge whether it is necessary to continue to increase borehole data.
The effects of moose browsing on balsam fir and forest recovery vary with bioclimatic and human use across the island of Newfoundland
Authors: Buchkowski Robert W. , Leroux Shawn J. , Yan Youpei , Entem Alicia , Schmelzer Isabelle , Fenichel Eli P.
Published: April 2023

Moose present a complex management problem because they generate a mixture of benefits and costs to humans, some of which are caused by browsing of regenerating trees. We developed a Lotka–Volterra model, parameterized by moose management areas, to link moose browsing to spruce and balsam fir dynamics on the island of Newfoundland. The model predicts the distribution of moose, adult fir, and spruce well. Empirical estimates of juvenile fir biomass were variable, and our model predicted its biomass poorly. Our model predicts a small negative effect of moose on adult fir biomass (−0.06%) and juvenile fir biomass (−1.65%) and a small positive effect on spruce biomass (+0.02%) under baseline assumptions, but larger effects (±10%–60%) if moose browse commercial softwoods preferentially. Small effects of moose on trees at steady state do not fully reflect the importance of moose because moose parameters (e.g., growth rate and harvesting rate) impacted the return time of our model from disturbance. Our model analysis demonstrates one way to add animal effects into vegetation growth models and suggests that parameterizing ecological models by management unit is useful when the data to support more detailed models are not available.
Anisotropic compact stellar solution in general relativity
Authors: Baskey Lipi , Ray Saibal , Das Shyam , Majumder Shreya , Das Ananya
Published: April 2023

We present herein a new class of singularity-free interior solutions to describe realistic anisotropic compact stellar objects with spherically symmetric matter distribution. A specific form of anisotropy is assumed to obtain the exact solution for the field equation. Smooth matching of interior solutions thus obtained with the Schwarzschild exterior metric over the bounding surface of a compact star, together with the condition that the radial pressure vanishes at the boundary, is used to obtain the mathematical form for the model parameters. The pulsar 4U1608-52 with its current estimated data (mass $$=1.57 ~M\odot $$

=
1.57

M
⊙

and radius $$=9.8 \pm 0.8$$

=
9.8
±
0.8

 km; Özel et al. in ApJ 820:28, 2016) is used to study the model graphically.
Large scale analysis of gender bias and sexism in song lyrics
Authors: Betti Lorenzo , Abrate Carlo , Kaltenbrunner Andreas
Published: April 2023

We employ Natural Language Processing techniques to analyse 377,808 English song lyrics from the “Two Million Song Database” corpus, focusing on the expression of sexism across five decades (1960–2010) and the measurement of gender biases. Using a sexism classifier, we identify sexist lyrics at a larger scale than previous studies using small samples of manually annotated popular songs. Furthermore, we reveal gender biases by measuring associations in word embeddings learned on song lyrics. We find sexist content to increase across time, especially from male artists and for popular songs appearing in Billboard charts. Songs are also shown to contain different language biases depending on the gender of the performer, with male solo artist songs containing more and stronger biases. This is the first large scale analysis of this type, giving insights into language usage in such an influential part of popular culture.
Reap what you sow? Competitive diffusion in social networks with heterogeneous opinions and relationships
Authors: Li Pei , Wang Mian , He Tingqin , Yu Jianyong
Published: April 2023

Nowadays, an increasing number of people use social networks to receive up-to-date information and express their personal opinions, and popular social networks have become important platforms to conduct viral-marketing for many companies. However, due to the existences of negative opinions and hostile relationships, some spreading behaviors will receive much more undesired responses. To study this process of competitive diffusion, we consider heterogeneous opinions (positive and negative ones) and heterogeneous relationships (friendly and hostile ones), and assume the reaction of a user after receiving a message is determined by the received message type, his/her own opinion and the type of relationship between him/her and the neighbor who sends this message. We then modify the duplicate forwarding model to characterize the diffusion dynamics in competitive diffusion, and define the term positive (negative) user influence which is the mean number of positive (negative) messages received by users after a user generates a message. These user influences and the corresponding diffusion threshold can be analyzed theoretically, which are verified by simulations. We then study the impacts of different factors on user influences on some real networks, and observe that messages of some type are easier to be forwarded and received in a given network if the message spreading intensity approaches the diffusion threshold and users of this type have a larger average homophily factor. These findings can help to explain why a large number of boycotts may be attracted if a user or company publishes a post or advertisement in a social network, and we believe this analysis framework will be of use for advertisers to conduct viral-marketing.
A hybrid model of neural network with VMD–CNN–GRU for traffic flow prediction
Authors: Huang Xiaoting , Ma Changxi , Zhao Yongpeng , Wang Ke , Meng Wei
Published: April 2023

An effective traffic flow prediction can serve as a foundation for control decisions on intelligent transportation. However, in view of the nonstationarity and complexity of traffic flow sequences, it is impossible to fully extract the dynamic change laws of time-series based on traditional forecasting models. Traffic flow data are often disturbed by noise during the collection. The existence of noise data may affect the features of the sequence itself or cover the real change trend of the series, resulting in the decline of prediction reliability. A hybrid prediction model based on variational mode decomposition–convolutional neural network–gated recurrent unit (VMD–CNN–GRU) is presented to increase the predictability of traffic flow, which is combined by VMD, CNN and GRU. First, the original time-series is decomposed into K components by VMD, and the noise part is eliminated to improve the modeling accuracy. Next, the time characteristics of traffic flow are mined by constructing the CNN–GRU network in Keras, a deep learning framework. Each sub-sequence is trained and predicted separately as an input vector. The total expected value of traffic flow is then calculated by superimposing the predicted value of each subsequence. The model performance is verified by the open-source dataset of actual England highways. The results show that compared with other models, the hybrid model established in this paper significantly raises the precision of traffic flow forecasting. The results could offer some useful insights for predicting traffic flow.
Procurement Contract Design Under Asymmetric Information of Random Yield
Authors: Ji Qingkai , Liu Feng , Zhuang Jun
Published: April 2023

Unreliable suppliers may pose a substantial threat to supply chains, especially when they hold private information of their reliability. We consider a dyadic supply chain where the information of supplier reliability (in the form of random production yield) is asymmetric. We propose a new mechanism-design model and derive the buyer’s optimal procurement contract menu offered to suppliers with private information. We prove that the contract menu is as simple as offering two different inflated order amounts and setting the procuring price sufficiently low to let the suppliers earn zero reservation profits. These results are derived analytically under uniform distribution. We test them numerically under beta distribution and find them hold as well. However, the informational rent will become positive when the supplier’s reservation profit is positive. Positive informational rent is also found when we consider another structure of the supplier’s production cost. This paper provides some new insights into supply chain management under asymmetric information of uncertain supply.
On a weak version of S-Noetherianity
Authors: El Khalfi Abdelhaq , Mahdou Najib , Moussaoui Sanae , Moutui Moutu Abdou Salam
Published: April 2023

In this paper, we introduce a new class of ring called [Formula: see text]-[Formula: see text]-Noetherian ring, which is a weak version of [Formula: see text]-Noetherian ring property and study the transfer of this notion to various context of commutative ring extensions such as direct product, trivial ring extensions and amalgamation of rings. Furthermore, we define the concept of nonnil [Formula: see text]-[Formula: see text]-Noetherian ring property which is a generalization of the [Formula: see text]-[Formula: see text]-Noetherian domain property and establish a characterization of this notion using pullbacks.
On algebras of Ωn-finite and Ω∞-infinite representation type
Authors: Barrios Marcos , Mata Gustavo
Published: April 2023

Co-Gorenstein algebras were introduced by Beligiannis in [A. Beligiannis, The homological theory of contravariantly finite subcategories: Auslander–Buchweitz contexts, Gorenstein categories and co-stabilization, Comm. Algebra 28(10) (2000) 4547–4596]. In [S. Kvamme and R. Marczinzik, Co-Gorenstein algebras, Appl. Categorical Struct. 27(3) (2019) 277–287], the authors propose the following conjecture (co-GC): if [Formula: see text] is extension closed for all [Formula: see text], then [Formula: see text] is right co-Gorenstein, and they prove that the generalized Nakayama conjecture implies the co-GC, also that the co-GC implies the Nakayama conjecture. In this paper, we characterize the subcategory [Formula: see text] for algebras of [Formula: see text]-finite representation type. As a consequence, we characterize when a truncated path algebra is a co-Gorenstein algebra in terms of its associated quiver. We also study the behavior of Artin algebras of [Formula: see text]-infinite representation type. Finally, an example of a non-Gorenstein algebra of [Formula: see text]-infinite representation type and an example of a finite dimensional algebra with infinite [Formula: see text]-dimension are presented.
Bounds on the minimal number of generators of the dual module
Authors: Mishra Ankit , Mondal Dibyendu
Published: April 2023

Let [Formula: see text] be a Cohen–Macaulay local ring. Let [Formula: see text] be a finitely generated [Formula: see text]-module and let [Formula: see text] denote the [Formula: see text]-dual of [Formula: see text]. Furthermore, if [Formula: see text] is a maximal Cohen–Macaulay [Formula: see text]-module, then we prove that [Formula: see text], where [Formula: see text] is the cardinality of a minimal generating set of [Formula: see text] as an [Formula: see text]-module and [Formula: see text] is the multiplicity of the local ring [Formula: see text]. Furthermore, if [Formula: see text] is a reflexive [Formula: see text]-module then [Formula: see text]. As an application, we study the bound on the minimal number of generators of specific modules over two-dimensional normal local rings. We also mention some relevant examples.
Semantic guided level-category hybrid prediction network for hierarchical image classification
Authors: Wang Peng , Chen Jingzhou , Qian Yuntao
Published: April 2023

Hierarchical classification (HC) assigns each object with multiple labels organized into a hierarchical structure. The existing deep learning-based HC methods usually predict an instance starting from the root node until a leaf node is reached. However, in the real world, images impaired by noise, occlusion, blur, or low resolution may not provide sufficient information for the classification at subordinate levels. To address this issue, we propose a novel Semantic Guided level-category Hybrid Prediction Network (SGHPN) that can jointly perform the level and category prediction in an end-to-end manner. SGHPN comprises two modules: a visual transformer that extracts feature vectors from the input images, and a semantic guided cross-attention module that uses categories word embeddings as queries to guide learning category-specific representations. In order to evaluate the proposed method, we construct two new datasets in which images are at a broad range of quality and thus are labeled to different levels (depths) in the hierarchy according to their individual quality. Experimental results demonstrate the effectiveness of our proposed HC method.
Geometric Schrödinger microfluidic modeling for spherical ferromagnetic mKdV flux
Authors: Körpinar Talat , Körpinar Zeliha , Korkmaz Erdal
Published: April 2023

In this paper, we present a different technique for investigating spherical [Formula: see text]-microfluidic optical mKdV electromotive [Formula: see text] forces in [Formula: see text] Then, we give some relations for ferromagnetic spherical [Formula: see text]-microfluidic optical mKdV magnetic [Formula: see text] flux density. Ferromagnetic spherical [Formula: see text]-microfluidic optical mKdV magnetic [Formula: see text] flux surface model. Finally, we obtain spherical [Formula: see text]-microfluidic optical mKdV magnetic [Formula: see text] flux density.
Cohesive Zone Model to Investigate Complex Soft Adhesive Failure: State-of-the-Art Review
Authors: Yang Zhuoran , Xia Yan , Zhu Zhongmeng , Yao Chengbin , Jiang Han
Published: April 2023

Soft adhesives are widely used in soft robotics, biomedicine, flexible electronics and other fields. In practical applications, soft adhesives are frequently subjected to monotonic loading, static loading and cyclic loading. It is extremely important but challenging to analyze the failure behavior of soft adhesives due to their complicated mechanical properties and failure mechanisms, as well as the effect of different loading conditions. In this paper, the methodology of developing the cohesive zone model (CZM) for understanding the failure behavior of soft adhesives is systematically reviewed. First, for the one-time failure of soft adhesives, the establishment of the CZM considering the effect of loading rate, fibrillation, and mixed-mode loading is summarized. Second, the delayed failure of soft adhesives is studied. The development of the corresponding CZM considering the creep behavior under constant force and various potential mechanisms to explain the delayed failure under displacement holding is discussed. Then, for the fatigue failure of soft adhesives, remarks for CZM that are capable of expressing the loading-unloading process under the high cycle fatigue process and addressing the effect of viscoelasticity on fatigue damage have been provided. Finally, based on the application of soft adhesives in the frontier areas, the challenges and prospects faced for future research are presented.
Comparison of point detection and area detection for point-scanning structured illumination microscopy
Authors: Wu Wenshuai , Chen Jiajie , Wang Meiting , Wang Lei , Zheng Xiaomin , Li Jia , Qu Junle , Gao Bruce Zhi , Shao Yonghong
Published: April 2023

Structured illumination microscopy (SIM) is suitable for biological samples because of its relatively low-peak illumination intensity requirement and high imaging speed. The system resolution is affected by two typical detection modes: Point detection and area detection. However, a systematic analysis of the imaging performance of the different detection modes of the system has rarely been conducted. In this study, we compared laser point scanning point detection (PS-PD) and point scanning area detection (PS-AD) imaging in nonconfocal microscopy through theoretical analysis and simulated imaging. The results revealed that the imaging resolutions of PS-PD and PS-AD depend on excitation and emission point spread functions (PSFs), respectively. Especially, we combined the second harmonic generation (SHG) of point detection (P-SHG) and area detection (A-SHG) with SIM to realize a nonlinear SIM-imaging technique that improves the imaging resolution. Moreover, we analytically and experimentally compared the nonlinear SIM performance of P-SHG with that of A-SHG.
Using slurry TBM data to assess the variability of weathered Kowloon Granite
Authors: Shirlaw J. Nick , Henderson Tom O. , Haryono Ivan S. , Dudouit Francois , Salisbury David
Published: April 2023

Parallel running tunnels were driven by a 7.46 m-diameter slurry tunnel boring machine (TBM) through weathered Kowloon Granite in Hong Kong for MTR Contract SCL 1103. The final part of the tunnelling was in a full face of Grade III or Grade II rock, up to 50 m below the rockhead. Using the data obtained during the tunnelling, the average strength of the rock was calculated for every ring of advance. The distribution of the rock strength calculated from the two drives was similar, and comparable with the data from the ground investigation. The strength assessed from the TBM data showed a notably sawtooth profile along each drive, with large changes in strength over relatively short distances. The change in strength between each advance averaged 13 MPa, and locally reduced by 80% over 9 m. The changes in strength indicate that the rock had been weakened locally by weathering, consistent with the early stages of the formation of a corestone weathering profile. The focus of the weathering was on a set of inferred joints spaced at an average of about 17 m that represented a small proportion of the joints encountered during tunnelling.
The Alpi Apuane and their surroundings: a tale of the origins of modern Italian geological maps and of a missed ‘early recognition’ of nappes in the Apennines
Authors: Molli Giancarlo
Published: April 2023

The northernmost coastal sector of the Italian peninsula from the La Spezia Gulf to Monte Pisano, including the Alpi Apuane mountain range, represents a special morpho-structural domain of the inner northwestern Apennines. Described by naturalists since the Roman age, its location on the land and sea track of the Italian Grand Tour makes it a special zone in the Italian peninsula that was visited by some of the most eminent European geologists of the nineteenth century, including Brongniart, Buckland, De la Beche, Hoffman, Escher von der Linth, Murchison and Lyell. The area has been also the homeland of naturalists and scientists who played a significant role during the nineteenth century in the advancement of geological studies in Italy. Thanks to Capellini's ‘Geological map of the La Spezia Gulf and surroundings’ (1863) and Zaccagna's ‘Geological maps of the Alpi Apuane’ (1879–97), the area became central in the history of the foundations of modern Italian geological maps. However, the opportunities provided by early mapping and palaeontological discoveries for developing tectonic concepts were squandered by Italian Apennines geologists, who remained stuck on explanations of autochthonism, thus missing an early recognition of nappe tectonics that was only accepted in the middle of the twentieth century.
SelfCF: A Simple Framework for Self-supervised Collaborative Filtering
Authors: Zhou Xin , Sun Aixin , Liu Yong , Zhang Jie , Miao Chunyan
Published: April 2023

Collaborative filtering (CF)
is widely used to learn informative latent representations of users and items from observed interactions. Existing CF-based methods commonly adopt negative sampling to discriminate different items. That is, observed user-item pairs are treated as positive instances; unobserved pairs are considered as negative instances and are sampled under a defined distribution for training. Training with negative sampling on large datasets is computationally expensive. Further, negative items should be carefully sampled under the defined distribution, in order to avoid selecting an observed positive item in the training dataset. Unavoidably, some negative items sampled from the training dataset could be positive in the test set. Recently,
self-supervised learning (SSL)
, has emerged as a powerful tool to learn a model without negative samples. In this paper, we propose a
self-supervised collaborative filtering framework (SelfCF)
, that is specially designed for recommender scenario with implicit feedback. The proposed SelfCF framework simplifies Siamese networks and can be easily applied to existing deep-learning based CF models, which we refer to as backbone networks. The main idea of SelfCF is to augment the latent embeddings generated by backbone networks instead of the raw input of user/item ids. We propose and study three embedding perturbation techniques that can be applied to different types of backbone networks including both traditional CF models and graph-based models. The framework enables learning informative representations of users and items without negative samples, and is agnostic to the encapsulated backbones. We conduct experimental comparisons on four datasets, one self-supervised framework, and eight baselines to show that our framework may achieve even better recommendation accuracy than the encapsulated supervised counterpart with a 2×–4× faster training speed. The results also demonstrate that SelfCF can boost up the accuracy of a self-supervised framework BUIR by 17.79% on average and shows competitive performance with baselines.
On-Line Multi-Time Scale Adaptive Parameter Identification Based on Improved Lithium-Ion Batteries Hysteresis Characteristic-Electrical Equivalent Circuit Modeling
Authors: Qi Chuangshi , Wang Shunli , Cao Wen , Xie Yanxin , Lei Mingdong
Published: April 2023

Accurate identification of model parameters is a key aspect of lithium battery state estimation. To accurately identify battery model parameters, this paper establishes Hysteresis Characteristic-Electrical Equivalent Circuit (HC-EEC) modeling by analyzing the influence of the hysteresis effect on the battery State of Charge (SOC). For the high-precision identification of battery model parameters, an Online Multi-Time Scale Adaptive Parameter Identification Strategy (OM-TSAPIS) is proposed in this paper. According to the different dynamic response links in the HC-EEC model, the strategy performs parameter identification through different time scale links and uses the adaptive step size as the starting identification condition for the multi-time scale links, thereby improving the parameter identification accuracy of the HC-EEC model. The absolute average error of OM-TSAPIS was 0.0437 mV and 0.298 mV under the Urban Dynamometer Driving Schedule (UDDS) and Beijing Bus Dynamic Street Test (BBDST) conditions, respectively. Simulation results show that the identification accuracy of the proposed algorithm is high.
Battery State of Health Model Estimation Based on Variable Projection Algorithm Using Steffensen Acceleration Method
Authors: Cheng Lianyuan , Chen Jing , Pu Yan , Yin Xia
Published: April 2023

In this paper, the variable projection based Steffensen acceleration (VP-SA) algorithm is proposed for battery state of health (SOH) estimation. The VP-SA algorithm exploits the separability of variables to reduce the dimensionality of the parameters, which can improve the estimation efficiency. In addition, based on the Steffensen acceleration method, the convergence rates of the VP algorithm can be increased. The simulation example shows the effectiveness of the proposed algorithm.
Artisanal model replaces animal use for ultrasound-guided fine needle puncture practice in medical sciences teaching
Authors: Alencar Jennifer Leme , Prado Marcela Roberta , Ercolin Anna Carolina Mazeto , Pires Sâmara Turbay , Disselli Tamiris , Stanquini Camila Silveira , de Andrade Amanda Moura Rocha , Hage Maria Cristina Ferrarini Nunes Soares
Published: April 2023

This study describes an artisanal simulator made with gelatin to teach ultrasound-guided fine needle puncture during practical classes in veterinary or medical sciences education. A three-phase experimental set allowed the students to practice ultrasound-guided fine needle puncture, aspiration, and injection in three different target structures. This cost-effective simulator may be an alternative to the use of expensive devices or the use of live animals during practical classes.
Unpacking the homeostasis core concept in physiology: an Australian perspective
Authors: Beckett Elizabeth A. H. , Gaganis Voula , Bakker Anthony J. , Towstoless Michelle , Hayes Alan , Hryciw Deanne H. , Lexis Louise , Tangalakis Kathy ,   Task Force
Published: April 2023

The homeostasis core concept of physiology was defined and unpacked by an Australian team with the goal of constructing a resource that will improve learning and teaching of this core physiology concept in an Australian Higher Education context.
Contact-free assessments of respiratory rate and volume with load cells under the bed legs in ventilated patients: a prospective exploratory observational study
Authors: Inada Azusa , Inaba Shin , Matsumura Yosuke , Sugiyama Takuya , Hanaoka Noriyuki , Fujiyoshi Naohiko , Nozaki-Taguchi Natsuko , Sato Yasunori , Isono Shiroh
Published: April 2023

We previously discovered that four load cells placed under the bed legs capture a centroid shift during respiration in bedridden human subjects. In 14 ICU patients under mechanical ventilation, this study evidenced that contact-free measurements of respiratory rate, tidal volume, and minute ventilation with the load cells correlated well with those measured by pneumotachograph. Possible clinical usefulness of this approach as a new clinical respiratory monitor is indicated.
A Pedestrian Evacuation Model with Leaders during the Smoke Dispersion Based on a Social Force Model
Authors: Makmul J.
Published: April 2023

The pedestrian evacuation process during the propagation of smoke in case with and without guider is investigated. The effects of leaders on the evacuation are considered. The model is based on the social force model for pedestrians’ motions. The advection–diffusion equation is applied for the dispersion of smoke. The movement direction of a guider is guided by the solution of the Eikonal equation. It relies on the desired speed and the smoke density. A pedestrian who is not a guider follows the rule termed ‘flow with the stream’ and ‘following the wall’. We perform different numerical experiments in a room with one and two exits. The results show that the guiders effect on the evacuation time when they are large number of individuals in simulation. It can help to increase the number of evacuees. With small number of individuals in the experiment, the effect of guiders on evacuation time is not obvious. Further, simulation results are found that the domain with two exits provides higher number of outside pedestrians than the domain with a single door. Longer evacuation time period can increase the number of evacuees. The visibility range of a pedestrian is reduced when an additional smoke source is added to the system. It decreases the number of evacuees. The results of the proposed model are discussed and compared with the existing models.
Biosynthesis of Iron Oxide Nanoparticles Using Leaf Extract of Ruellia tuberosa: Mechanical and Dynamic Mechanical Behaviour Kevlar-Based Hybrid Epoxy Composites
Authors: Natrayan L. , Rao Yenda Srinivasa , Vaidya Gayatri , Bhattacharya Sumanta , Kaliappan S. , Patil Pravin P. , Paramasivam Prabhu
Published: April 2023

One of the more enticing, ecologically responsible, as well as safe and sustainable methodologies is eco-friendly nanomaterial synthesis. Vegetation materials will be used as reductants instead of toxic substances for synthesising nanoparticles. The current study used Ruellia tuberosa (RT) leaf extract digest to synthesise FeO nanomaterials, which were then characterised using XRD. Following that, microbially produced FeO molecules were mixed with a Kevlar-based polymeric matrix to study the blended consequences. To examine the interbreeding, the current experimental analyses were performed, including both static and dynamic mechanical characteristics. The addition of FeO nanofillers improved the elastic modulus, tensile strength, and storage modulus of the nanocomposite. Impact force uptake has been raised to a certain extent by the addition of nanoparticles. The findings of this research show that incorporating FeO nanofillers into Kevlar fabrics is a promising technique for increasing the mechanical characteristics of hybrid laminated composites. As per DMA evaluation, the sample without nanomaterials had a more volcanic lava response, which is a useful thing for body systems for missile use. Another critical aspect of a nanoparticles-filled nanocomposite that must be addressed is the relatively uniform scattering of padding as well as the development of interfacial adhesion in such a combination. The presence of FeO fillers in polymeric composites is confirmed by XRD analysis.
Antifungal Activity of Bioactive Compounds Produced by the Endophytic Fungus Paecilomyces sp. (JN227071.1) against Rhizoctonia solani
Authors: Hawar Sumaiya Naeema , Taha Zainab K. , Hamied Atyaf Saied , Al-Shmgani Hanady S. , Sulaiman Ghassan M. , Elsilk Sobhy E.
Published: April 2023

Biologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%, 30%, 45%, and 60%, for which the percentages of inhibition of the radial growth were 37.5, 50, 52.5, and 56.25%, respectively. The dual culture method was conducted on PDA medium to observe the antagonistic nature of the antibiotic impacts of Paecilomyces sp. towards the pathogenic fungus. The strength of the antagonistic impacts was manifested by a 76.25% inhibition rate, on a scale of 4 antagonistic levels. Ethyl acetate extract of Paecilomyces sp. was obtained by liquid-liquid partition of the broth containing the fungus. Gas chromatography-mass spectrometry (GC-MS) analysis identified the presence of important chemical components e.g., (E) 9, cis-13-Octadecenoic acid, methyl ester (48.607), 1-Heptacosanol, 1-Nonadecene, Cyclotetracosane (5.979), 1,2-Benzenedicarboxylic acid, butyl 2-methylpropyl ester, di-sec-butyl phthalate (3.829), 1-Nonadecene, n-Nonadecanol-1, Behenic alcohol (3.298), n-Heptadecanol-1, 1-hexadecanol, n-Pentadecanol (2.962), Dodecanoic acid (2.849), 2,3-Dihydroxypropyl ester, oleic acid, 9-Octadecenal, and (Z)-(2.730). These results suggest that secondary metabolites of the endophytic Paecilomyces possess antifungal properties and could potentially be utilized in various applications, such as environmental protection and medicine.