bluuebunny/crossref_metadata_2025 huggingface dataset:
A mixed methods study to develop a tool to assess institutional readiness to conduct knowledge translation activities in low-income and middle-income countries
Authors: Kalbarczyk Anna , Rao Aditi , Alonge Olakunle
Published: October 2021

Objective

This paper describes the development of a tool for assessing organisational readiness to conduct knowledge translation (KT) among academic institutions in low-income and middle-income countries (LMICs).

Design

A literature review and stakeholder consultation process were conducted to identify constructs relevant for assessing KT readiness in LMICs. These were face-validated with LMIC stakeholders and organised into a Likert-scale questionnaire.

Participants

The questionnaire was distributed to researchers based at six LMIC academic institutions and members of a global knowledge-to-action thematic working group.

Outcome measures

An exploratory factor analysis was used to identify underlying dimensions for assessing institutional readiness to conduct KT.

Results

111 respondents with varied KT experiences from 10 LMICs were included in the analysis. We selected 5 factors and 23 items, with factor loadings from 0.40 to 0.77. These factors include (1) institutional climate, (2) organisation change efficacy, (3) prioritisation and cosmopolitanism, (4) self-efficacy, and (5) financial resources. These factors accounted for 69% of the total variance, with Cronbach’s alpha coefficients of 0.78, 0.73, 0.62, 0.68 and 0.52, respectively.

Conclusions

This study identifies a tool for assessing readiness of LMIC academic institutions to conduct KT and unique opportunities for building capacity. The organisational focus of these factors underscores the need for strategies that address organisational systems and structures in addition to individual skills. Future research will be conducted to understand determinants of these factors and develop a comprehensive set of capacity building strategies responsive to academic institutions in LMICs.
Measuring functional ability in healthy ageing: a nationwide cross-sectional survey in the Philippine older population
Authors: Moreno-Agostino Dario , Prina Matthew , Chua Kia-Chong , Jotheeswaran Amuthavalli Thiyagarajan , Sadana Ritu , Officer Alana , Kamenov Kaloyan , Cieza Alarcos
Published: October 2021

Objectives

To analyse the empirical support of the functional ability concept in the healthy ageing framework developed by the WHO in a sample of the Philippine older population. According to this framework, environmental factors may enhance or hinder functional ability, which is the person’s ability to do what they value, broadly represented by subjective well-being. Moreover, this network of relationships may be moderated by personal characteristics such as gender.

Design

Cross-sectional observational study.

Setting

Philippines, general population.

Participants

Respondents of the 2016 National Disability Prevalence Survey/Model Functioning Survey aged 50+ (N=2825).

Primary and secondary outcome measures

Latent (unobserved) measures of functional ability, environmental factors (physical environmental factors and social network and support) and subjective well-being (positive affect, negative affect and evaluative well-being) were obtained from different items from the survey questionnaire using a SEM framework.

Results

We found that the relationship between environmental factors and the three components of subjective well-being considered in this study was partially explained by differences in functional ability. The portion of those effects accounted for by functional ability was comparatively larger for the physical than for the social environmental factors. We found no evidences of gender differences in this network of relationships.

Conclusions

These findings suggest the relevance of functional ability at explaining the relationship between environmental factors and subjective well-being in older adults. Future studies may replicate these findings longitudinally and including other relevant measures as the person’s objective level of intrinsic capacity.
Infectious diseases experts as part of the antibiotic stewardship team in primary care: protocol for a cluster-randomised blinded study (IDASP)
Authors: Ronda Mar , Padullés Ariadna , Simonet Pere , Rodríguez Gemma , Estrada Cinta , Lérida Ana , Ferro Juan José , Cobo Sara , Tubau Fe , Gardeñes Lluïsa , Freixedas Rosa , López Montserrat , Carrera Elena , Pallarés Natàlia , Tebe Cristian , Carratala Jordi , Puig-Asensio Mireia , Shaw Evelyn
Published: October 2021

Introduction

Antibiotic overuse is directly related to antibiotic resistance, and primary care is one of the main reasons for this overuse. This study aims to demonstrate that including experts on infectious diseases (ID) within the antimicrobial stewardship (AMS) programme team in primary care settings achieves higher reductions in overall antibiotic consumption and increases the quality of prescription.

Methods and analysis

A multicentre, cluster-randomised, blinded clinical trial will be conducted between 2021 and 2023. Six primary care centres will be randomly assigned to an advanced or a standard AMS programme. The advanced AMS programme will consist of a standard AMS programme combined with the possibility that general practitioners (GP) will discuss patients’ therapies with ID experts telephonically during working days and biweekly meetings. The main endpoint will be overall antibiotic consumption, defined as daily defined dose per 1000 inhabitants per day (DHD). Secondary end-points will be: (1) unnecessary antibiotic prescriptions in patients diagnosed with upper respiratory tract or urinary tract infection, (2) adequacy of antibiotic prescription, (3) reattendance to GP or emergency room within 30 days after the initial GP visit and (4) hospital admissions for any reason within 30 days after the GP visit. Two secondary endpoints (unnecessary antibiotic therapy and adequacy of therapy) will be evaluated by blinded investigators.

We will select three clusters (centres) per arm (coverage of 147 644 inhabitants) which will allow the rejection of the null hypothesis of equal consumption with a power of 80%, assuming a moderate intracluster correlation of 0.2, an intracluster variance of 4 and a mean difference of 1 DHD. The type I error will be set at 5%.

Ethics and dissemination

The protocol was reviewed and approved by local ethics committees. The results of this study will be published in peer-reviewed journals and presented at medical conferences.

Trial registration number

NCT04848883
Socioeconomic variables and fracture risk in children and adolescents: a population-based study from northern Sweden
Authors: Hedström Erik , Crnalic Sead , Kullström Antonia , Waernbaum Ingeborg
Published: October 2021

Objectives

Previous studies have investigated the association between socioeconomic characteristics and fractures among children, producing different results. In a population-based study, we previously found an increased risk of fractures among children living in an urban municipality compared with rural municipalities. This study aimed to evaluate the importance of socioeconomic variables for the incidence of fractures among 0–17 year olds.

Setting, design and outcome measure

We present a longitudinal, observational study of a population 0–17 years of age. Data from an injury database were linked with additional socioeconomic data for the population at risk. These were 55 758 individuals residing within the primary catchment area of a regional hospital in northern Sweden. Using the number of fractures as the outcome, we fitted a generalised linear mixed model for a Poisson response with socioeconomic variables at the family level as independent variables while controlling for age, sex and place of residence.

Results

We found a significant association between higher levels of family income and the risk of fracture, rate ratio 1.40 (1.28–1.52) p<0.001 when comparing the highest income quintile to the lowest as well as the number of siblings and the risk of fracture. Children with one or two siblings had a rate ratio of 1.28 (1.19–1.38) p<0.001 when compared with children with no siblings. Parents’ educational level and having a single parent showed no significant association with fractures. The previously observed association between municipalities and fracture risk was less pronounced when taking family-level socioeconomic variables into account.

Conclusion

Our results indicate that children from families with higher income and with siblings are at greater risk of sustaining fractures.
Endoscopic ultrasound-guided neurolysis in advanced pancreatic cancer: current status
Authors: Hickman Katy , Godfrey Edmund , Ajithkumar Thankamma
Published: October 2021

Pancreatic cancer has a very poor prognosis with patients often presenting with locally advanced, inoperable or metastatic disease. A significant proportion of patients have visceral pain due to perineural infiltration or coeliac plexus involvement by the tumour. This pain is difficult to control and may become refractory to conventional pain management. Therefore, coeliac plexus neurolysis (CPN) has been proposed to ablate the neuronal transmission pathway of pain permanently. CPN is recommended for those who have uncontrolled pain, are experiencing unacceptable opioid adverse effects or are receiving escalating doses of analgesics. It is not known whether CPN performed at diagnosis as the first-line treatment (‘early’) would impact short-term and long-term pain control and quality of life. NICE has recommended (2018) a randomised trial comparing early endoscopic ultrasound-guided coeliac plexus neurolysis (EUS-CPN) with on-demand EUS-CPN in pancreatic cancer. In this context, we will review the current evidence on its clinical benefits.
Fibrotic interstitial lung disease - palliative care needs: a World-Café qualitative study
Authors: Cassidy Nicola , Fox Lynn , Love Maria , Byrne Irene , Doyle Anne Marie , Korn Bettina , Shanagher Deirdre , Shone Tony , Cullen Matt , Cullen Teresa , Mullaney Philo , O'Carroll Noreen , O'Dowd Gemma , O'Sullivan Tom , Russell Anne-Marie
Published: October 2021

Objectives

The importance of palliative care in those with advanced fibrotic interstitial lung diseases (F-ILD) is recognised, but the palliative care requirements of patients and caregivers affected by F-ILD regardless of disease course are not established. We set out to explore this and identify optimal solutions in meeting the needs of a F-ILD population in Ireland.

Methods

Implementing a World-Café qualitative research approach, we captured insights evolving, iteratively in interactive small group discussions in response to six predefined topics on palliative care and planning for the future. Thirty-nine stakeholders participated in the World-Café including 12 patients, 13 caregivers, 9 healthcare professionals, 4 industry representatives and 1 representative of the clergy.

Results

Palliative care emerged as fundamental to the care and treatment of F-ILDs, regardless of disease progression. Unmet palliative care needs were identified as psychological and social support, disease education, inclusion of caregivers and practical/legal advice for disease progression and end-of-life planning. Participants identified diagnosis as a particularly distressing time for patients and families. They called for the introduction of palliative care discussions at this early-stage alongside improvements in integrated care, specifically increasing the involvement of primary care practitioners in referrals to palliative services.

Conclusion

Patients and caregivers need discussions on palliative care associated with F-ILD to be included at the point of diagnosis. This approach may address persisting inadequacies in service provision previously identified over the course of the last decade in the UK, Ireland and European F-ILD patient charters.
Immune checkpoint inhibitors in patients with pre-existing psoriasis: safety and efficacy
Authors: Halle Briana Rose , Betof Warner Allison , Zaman Farzana Y , Haydon Andrew , Bhave Prachi , Dewan Anna K , Ye Fei , Irlmeier Rebecca , Mehta Paras , Kurtansky Nicholas R , Lacouture Mario E , Hassel Jessica C , Choi Jacob S , Sosman Jeffrey A , Chandra Sunandana , Otto Tracey S , Sullivan Ryan , Mooradian Meghan J , Chen Steven T , Dimitriou Florentia , Long Georgina , Carlino Matteo , Menzies Alexander , Johnson Douglas B , Rotemberg Veronica M
Published: October 2021

Background

Immune checkpoint inhibitors (ICIs) are approved to treat multiple cancers. Retrospective analyses demonstrate acceptable safety of ICIs in most patients with autoimmune disease, although disease exacerbation may occur. Psoriasis vulgaris is a common, immune-mediated disease, and outcomes of ICI treatment in patients with psoriasis are not well described. Thus we sought to define the safety profile and effectiveness of ICIs in patients with pre-existing psoriasis.

Methods

In this retrospective cohort study, patients from eight academic centers with pre-existing psoriasis who received ICI treatment for cancer were evaluated. Main safety outcomes were psoriasis exacerbation and immune-related adverse events (irAEs). We also assessed progression-free survival (PFS) and overall survival.

Results

Of 76 patients studied (50 (66%) male; median age 67 years; 62 (82%) with melanoma, 5 (7%) with lung cancer, 2 (3%) with head and neck cancer, and 7 (9%) with other cancers; median follow-up 25.1 months (range=0.2–99 months)), 51 (67%) received anti-PD-1 antibodies, 8 (11%) anti-CTLA-4, and 17 (22%) combination of anti-PD-1/CTLA-4. All patients had pre-existing psoriasis, most frequently plaque psoriasis (46 patients (61%)) and 15 (20%) with psoriatic arthritis. Forty-one patients (54%) had received any prior therapy for psoriasis although only two (3%) were on systemic immunosuppression at ICI initiation. With ICI treatment, 43 patients (57%) experienced a psoriasis flare of cutaneous and/or extracutaneous disease after a median of 44 days of receiving ICI. Of those who experienced a flare, 23 patients (53%) were managed with topical therapy only; 16 (21%) needed systemic therapy. Only five patients (7%) required immunotherapy discontinuation for psoriasis flare. Forty-five patients (59%) experienced other irAEs, 17 (22%) of which were grade 3/4. PFS with landmark analysis was significantly longer in patients with a psoriasis flare versus those without (39 vs 8.7 months, p=0.049).

Conclusions

In this multicenter study, ICI therapy was associated with frequent psoriasis exacerbation, although flares were manageable with standard psoriasis treatments and few required ICI discontinuation. Patients who experienced disease exacerbation performed at least as well as those who did not. Thus, pre-existing psoriasis should not prevent patients from receiving ICIs for treatment of malignancy.
Direct carotid artery access for neurointerventional procedures in infants
Authors: Requejo Flavio , Teplisky Darío Javier , Nguyen Thanh N , Abdalkader Mohamad
Published: October 2021

Background

Femoral access is the primary route for neurointerventional procedures in children. However, endovascular treatment may not always be possible through a femoral approach, necessitating conversion to alternative access routes.

Objective

To review the feasibility and safety of direct carotid puncture (DCP) in infants undergoing neuroendovascular interventions.

Methods

We conducted a retrospective review of all infants who underwent DCP as the access route to treat neuroendovascular pathologies between January 2011 and January 2021. Patients’ demographics, clinical presentation, imaging findings, and technical details were reviewed.

Results

Between January 2011 and January 2021, five infants aged between 28 and 150 days underwent DCP out of 1129 neuroendovascular interventions performed in our institution (0.4%). All five infants (100%) were diagnosed with intracranial fistulas and were found to have severe tortuosity of the cervical arteries. DCP was performed as the initial access route in 2/5 patients and as crossover after a failed femoral attempt in 3/5 patients. DCP was performed under ultrasound guidance in all patients. Closure was performed by manual compression, without complications. Ultrasound showed patent cervical vessels in all patients at 3 months’ follow-up.

Conclusion

Direct carotid access is a feasible and safe alternative route to treat neuroendovascular pathologies in infants and can be considered in cases of inaccessible or failed transfemoral access or in cases with severe arterial tortuosity in infants with intracranial fistulas.
Multistability and period-adding in a logarithmic Lorenz system
Authors: da Silva Angela , Pati N. C. , Rech Paulo C.
Published: October 2021

In this paper, we design and explore a novel 3D autonomous nonlinear system with logarithmic nonlinearity. It is framed from the Lorenz model by replacing the variable [Formula: see text] in the second equation by the nonlinear logarithmic term [Formula: see text]. The bi-parametric dynamics of the modeled system is presented. Studies reveal the emergence of shrimp-shaped periodic structures in chaotic regime with period-adding phenomenon, and coexisting periodic-chaotic attractors, which do not occur in the Lorenz model. The stability, bifurcation patterns, and chaotic behaviors of the system are explored with the aid of bifurcation diagrams, phase portraits and Lyapunov exponents. The complexity of the basin sets for the coexisting attractors is also studied.
An Improved GA with Matrix-Coding for Optimizing a Complex Disassembly Sequence Problem on ELV
Authors: Zhang Chunliang , Liu Can
Published: October 2021

Optimal disassembly sequencing is an NP-hard problem and has always been an ambition for industry production. In the context of increasing public concerns over environmental impacts, in addition to the feasibility of a disassembly sequence, dismantling enterprises have to consider the relationship between potential profits and the impacts. Thus, an ideal disassembly sequence should weight these three factors comprehensively. Up to now, an appropriate ELV disassembly sequence still mainly relies on people’s intuitive experience and seeking an optimal disassembly sequencing method assumes enormous importance. This paper aims to address the optimal disassembly sequencing problem of ELVs by means of an improved genetic algorithm, in which a matrix coding mechanism and an elite strategy are employed. The weight of different factors can be adjusted according to the actual conditions of factories. The paper gives a case and a series of Pareto fronts are obtained. The effects of population size and maximum evolutionary time on the Pareto solutions were investigated. Ultimately, the optimal Pareto disassembly sequence corresponding to balanced profit and environmental impact is achieved, thereby providing an appropriate disassembly depth defined by the aforementioned disassembly sequence. This can contribute to timely disassembly decisions for end-of-life vehicle (ELV) dismantling enterprises, achieving a cost-effective disassembly process for survival in the context of growing environmental concerns. This paper seeks to offer a viable decision-making approach prior to real disassembly of ELVs by detailing a Pareto disassembly depth and sequence.
Correlated transitions in fission mode and shell correction energy at zero excitation in actinides fission
Authors: Mehdipour Kaldiani Payam
Published: October 2021

In this paper, the transitions between symmetric and asymmetric modes are investigated for the fission of actinides within the scission point model. All effective energies in fission are investigated in detail, separately. This indicates that the interaction energy and the liquid-drop energy do not change much in the symmetric region, so they cannot play a major role in the transition of actinide fission modes. Additionally, the sum of shell correction of complementary fragments at zero excitation energy is plotted over the fission fragment mass numbers. Also, the mass distributions of actinides fission are calculated within the scission point model. There is a good agreement between the calculated mass distribution and the total shell correction distribution. This indicates that the minimum total shell correction energy at the excitation energy corresponds to the maximum mass distribution for actinides fission, especially for the fermium 258 fission. Therefore, the main reason for the formation of fission mode in the actinides fission is the total shell correction energy of the complementary fission fragments at the zero excitation energy.
MORPHOLOGICAL, MICRO-MECHANICAL, CORROSION AND IN VITRO BIOACTIVITY INVESTIGATION OF SUPERFICIAL LAYER FORMATION DURING WIRE ELECTRICAL DISCHARGE MACHINING OF Ti-6Al-4V ALLOY FOR BIOMEDICAL APPLICATION
Authors: MALIK SANDEEP , KUMAR VINEET
Published: October 2021

In this work, the experimental investigation of the surface integrity and biomechanical properties of the superficial layer obtained by wire electrical discharge machining (W-EDM) of Ti-6Al-4V alloy for biomedical application has been carried out. The surface morphology and elemental composition of the superficial layer have been investigated by field-emission scanning electron microscope (FE-SEM) and energy dispersive X-ray spectroscopy (EDS) techniques. The micro-mechanical behavior in terms of compressive strength and surface hardness was studied using the micro-pillar and nano-indentation technique. The corrosion resistance and in vitro bioactivity have been investigated using electrochemical and immersion test. Morphological analysis showed that surface morphology and superficial layer thickness were affected by peak current, pulse-duration and pulse-interval. The niobium (Nb)-rich layer was developed in superficial layer zone. The low peak current (3–6[Formula: see text]A), low pulse-duration (5–10[Formula: see text][Formula: see text]s) and high pulse-interval ([Formula: see text]s) have been recommended for better surface morphology and thin superficial layer (ranging from 4–6[Formula: see text][Formula: see text]m) free from surface defects. The micro-pillar and nano-indentation results showed that the superficial layer comprised of a brittle structure that improved the mechanical properties of the layer and the compressive strength was measured to be 1198 MPa. The corrosion resistance analysis revealed that the Nb-rich layer in the superficial layer improved the corrosion resistance and bioactivity. Excellent apatite growth has been found in the W-EDM-processed zone. The W-EDM can be used for the biomedical industry as a potential surface engineering technique.
Modeling of Wire Electro-Spark Machining of Inconel 690 Superalloy Using Support Vector Machine and Random Forest Regression Approaches
Authors: Raj Atul , Misra Joy Prakash , Khanduja Dinesh
Published: October 2021

Machine learning approaches are disseminating very rapidly in manufacturing industry. They emerge out as latent modeling approaches showing a great potential for solving manufacturing-related problems. This study aims to analyze and predict the micro-irregularities on the surface of Inconel 690 superalloy processed by wire electro-spark machining using machine learning approaches. Experimental runs are completed by using the box-Behnken design of response surface methodology. Spark-on time, spark-off time, current and voltage with varying constraints are used as the input process variables, whereas surface integrity is used as the output variable. Support vector machines with two different functions and random forest regression are exercised to predict the machining outcomes with the help of existing models and validate the experimental outcomes. Support vector machine with radial basis function emerged out as the best approach in predicting the process outcomes. It is also perceived that spark-on time is the most dominating input process variable.
A symmetry-inclusive algebraic approach to genome rearrangement
Authors: Terauds Venta , Stevenson Joshua , Sumner Jeremy
Published: October 2021

Of the many modern approaches to calculating evolutionary distance via models of genome rearrangement, most are tied to a particular set of genomic modeling assumptions and to a restricted class of allowed rearrangements. The “position paradigm”, in which genomes are represented as permutations signifying the position (and orientation) of each region, enables a refined model-based approach, where one can select biologically plausible rearrangements and assign to them relative probabilities/costs. Here, one must further incorporate any underlying structural symmetry of the genomes into the calculations and ensure that this symmetry is reflected in the model. In our recently-introduced framework of genome algebras, each genome corresponds to an element that simultaneously incorporates all of its inherent physical symmetries. The representation theory of these algebras then provides a natural model of evolution via rearrangement as a Markov chain. Whilst the implementation of this framework to calculate distances for genomes with “practical” numbers of regions is currently computationally infeasible, we consider it to be a significant theoretical advance: one can incorporate different genomic modeling assumptions, calculate various genomic distances, and compare the results under different rearrangement models. The aim of this paper is to demonstrate some of these features.
Spin frame transformations and Dirac equations
Authors: Noris Ruggero , Fatibene Lorenzo
Published: October 2021

In this paper, we define spin frames, with the aim of extending spin structures from the category of (pseudo-)Riemannian manifolds to the category of spin manifolds with a fixed signature on them, though with no selected metric structure. Due to these softer requirements, transformations allowed by spin frames are more general than usual spin transformations and they usually do not preserve the induced metric structures. We study how these new transformations affect connections both on the spin bundle and on the frame bundle and how this reflects on the Dirac equations.
Dirac’s analysis and Ostrogradskii’s theorem for a class of second-order degenerate Lagrangians
Authors: Gümral Hasan
Published: October 2021

This paper analyzes the constraint structure of a class of degenerate second-order particle Lagrangian that includes chiral oscillator, noncommutative oscillator, and two examples from reduced topologically massive gravity. For even-dimensional configuration spaces with maximal nondegeneracy, Dirac bracket is defined solely by coefficient field of highest derivative whereas for odd dimensions almost all fields may contribute. Ostrogradskii’s theorem on energy instability is discussed. Results of Dirac analysis are used to identify ghost degrees of freedom. Translational symmetries are used to construct first-order variational formalisms for oscillator examples, thereby making them ghost-free.
Using modeling and simulation and artificial intelligence to improve complex adaptive systems engineering
Authors: Tolk Andreas , Barry Philip , Doskey Steven C.
Published: October 2021

Systems engineering practices are evolving to address fast-changing needs in fielding complex systems. These needs create an environment in which system needs evolve or change too quickly to be tracked or managed by humans’ natural capabilities. We propose that systems engineering must aid systems engineering managers by providing architectural alternatives and design options. Further, as systems become more complex and dynamic, there is an increased need to identify hidden risks, model emergent behavior, and expose hidden patterns in the behavior of stakeholders. Systems engineering needs to evolve to build fast-fielded, resilient, and adaptive systems that leverage positive reinforcement feedback loops with multiple experimental and real-world information sources. The very basis of systems engineering must evolve from today’s development paradigms to a future that leverages modeling, simulation, and artificial intelligence to drastically improve the capability and agility for developing new systems. This paper proposes a common way forward to enable this new form of complex adaptive systems engineering.
Prediction of heart conditions by consensusK-nearest neighbor algorithm and convolution neural network
Authors: Waris Saiyed Faiayaz , Koteeswaran S.
Published: October 2021

In recent days, health problems are becoming more prevalent because of changes in lifestyles and inherited factors. Heart disease (HD), in particular, has become increasingly widespread in recent years, putting people’s lives in jeopardy. Blood pressure, cholesterol, and pulse rate are all varied for each person. Normal blood pressure should be 120/90, cholesterol should be 100–129[Formula: see text]mg/dL, pulse rate should be 72, fasting blood sugar level should be 100[Formula: see text]mg/dL, heart rate should be 60–100[Formula: see text]bpm, and ECG should be normal, according to medically established data. The aorta is 25[Formula: see text]mm (1 inch) wide, whereas capillaries are only 8[Formula: see text][Formula: see text]m wide, which signifies HD. This paper is based on a public health dataset that also contains a cardiac dataset. In our previous work, a new conventional neural network (CNN) architecture was used to extract and categorize histopathological images using the [Formula: see text]-means consensus clustering. We achieved good results with the cardiac dataset compared to the existing results. The outcome of the proposed work achieves a precision rate of 97%. In this paper, a novel conventional neural network (CNN) architecture was utilized to identify and characterize histopathology pictures with the help of using the consensus [Formula: see text]-nearest neighbor algorithm (CKNN). The usage of a deep neural network, as well as the selection and recovery of functionality, is an essential step until the dataset is classified. As a result, the training process has pre-formed the dataset. The system evaluates the person’s symptoms as input and provides the disease’s possibility as an output. The suggested approach is linked to temporal data modeling and makes use of a prior HD CNN prediction. In comparison to previous outcomes, we had good outcomes with the current cardiac dataset. The proposed model’s conclusion has brought out accuracy of 99.1%.
Performance and Economic Investigation of Solar Regenerated Liquid Desiccant Room Air Conditioning Systems using Eco-Friendly Desiccants
Authors: Paul Subhechchha , Seal Soumava , Lanjewar Siddhant , Saha Tathagata , Ganguly Aritra
Published: October 2021

Traditional air conditioning systems run on the vapor compression cycle, which utilizes electricity generated from fossil fuels, the reserves of which are fast depleting. Moreover, the refrigerants used in such systems have exacerbated ozone layer depletion and climate change. Liquid desiccant air conditioning (LDAC) systems appear as a favorable option in light of these drawbacks. This paper has developed the numerical model of an LDAC system using a dehumidifier that is internally cooled and has a finned coil. The study of this particular model has been limited in the past. The model has been validated against a reference study available in the literature. Moreover, the commonly used desiccant materials tend to be corrosive and detrimental to the air quality. Therefore, the feasibility of an ionic liquid (65% [Emim]OAc) and an organic salt solution (73% HCOOK) as desiccant materials has also been investigated in this paper. With the proposed scheme for room air conditioning, the air temperature and humidity levels within the range of comfort (21∘C, 53% R.H.) could be supplied to the conditioned space. Performance analysis revealed that the eco-friendly desiccants could achieve dehumidifier and regeneration effectiveness similar to that of the traditionally used corrosive salt solution of calcium chloride (CaCl2). Furthermore, the estimated dehumidifier efficiency of about 76% is found to be higher than that available in the previous studies. Economic analysis provides a comparison of total cost between the conventional and the novel desiccant air conditioning systems and also reveals HCOOK to be a more economical choice as desiccant material.
Machine-Learning-Based m5C Score for the Prognosis Diagnosis of Osteosarcoma
Authors: Zhang Haijie , Xu Peipei , Song Yichang
Published: October 2021

Background. Osteosarcoma is a common and highly metastatic malignant tumor, and m5C RNA methylation regulates various biological processes. The purpose of this study was to explore the prognostic role of m5C in osteosarcoma using machine learning. Methods. Osteosarcoma gene data and the corresponding clinical information were downloaded from the GEO database. Machine learning methods were used to screen m5C-related genes and construct m5C scores. In addition, the clusterProfiler package was used to predict the m5C-related functional pathways. xCell and CIBERSORT were used to calculate the immune microenvironment cells. GSVA was applied to analyze different categories of m5C genes, and the correlation between the GSVA and m5C scores was evaluated. Results. Twenty m5C genes were identified, and 54 related genes were screened. The m5C score was constructed based on the PCA score. With an increase in the m5C score, the expression of m5C genes and their related genes changed. Functional analysis indicated that the focal adhesion, cell-substrate adherens junction, cell adhesion molecule binding, and E2F targets might change with the m5C score. The naive B cells and CD4+ memory T cell also changed with the m5C score. The results of the correlation analysis showed that the m5C score was significantly correlated with the reader and eraser genes. Conclusion. The m5C score might be a prognostic index for osteosarcoma.
Primary Fallopian Tube Cancer in an 89-Year-Old Patient
Authors: Kontomanolis Emmanuel N. , Koutras Antonios , Ntounis Thomas , Diakosavvas Michail , Angelou Kyveli , Samara Athina A. , Grigoriadis Themistoklis , Kadari Pelagia , Tsirkas Ioannis , Theodora Marianna , Fasoulakis Zacharias
Published: October 2021

Fallopian tube cancer is an extremely rare gynecological condition, accounting for just 1 to 2% of all female tract malignancies. The mean age of diagnosis is similar to that of ovarian cancer, between 60 and 75 years, but it can affect a wide spectrum of ages. Advanced age and family history of ovarian and breast cancer are the main risk factors, since they are associated with increased incidence of this uncommon entity. In this study, we report a rare case of an elderly, 89-year-old patient that presented to our clinic due to vaginal bleeding.
Analysis of Nursing Effect and Impact of Narrative Nursing Model on Anxiety of Tumor Patients with PICC under Chemotherapy
Authors: Xu Huixia , Yang Wenying , Liu Ying , Mu Xuejing , Liu Yang , Hu Haiping
Published: October 2021

Objective. To explore the nursing effect of the narrative nursing model on tumor patients with PICC under chemotherapy and the impact on patients’ anxiety. Methods. 200 tumor patients with PICC under chemotherapy treated in our hospital from March 2019 to March 2021 were randomly selected and divided into the control group (routine nursing) and the experimental group (narrative nursing) by the draw method, with 100 cases each. All patients were investigated with the General Anxiety Disorder-7 (GAD-7) scale, and their anxiety scores were over 5 points. The GAD-7 anxiety scores, satisfaction scores, Self-Rating Anxiety Scale (SAS) scores, Self-Rating Depression Scale (SDS) scores, quality of life (QLI) scores, and Mental Status Scale in Non-Psychiatric Settings (MSSNS) scores before intubation (T0), 1 d after intubation (T1), 3 d after intubation (T2), and after extubation (T3) of patients in both groups were compared. The adverse reaction rate (ARR) during placement was assessed in both groups, and the effectiveness of patient care was evaluated after extubation. Results. Compared with the control group, the experimental group obtained significantly higher satisfaction scores and QLI scores at T0, T1, T2, and T3 and lower GAD-7 anxiety scores, SAS scores, SDS scores, and MSSNS scores at T0, T1, T2, and T3, which were statistically significant (

P
<
0.05

). The experimental group had a significantly higher efficiency of care than the control group and a significantly lower ARR during treatment (

P
<
0.05

). Conclusion. The narrative nursing model can remarkably improve the nursing effect, alleviate the anxiety, and provide a more quality nursing for tumor patients with PICC under chemotherapy.
Empirical Study of the Relationship between Financial Development and Economic Growth Based on Intelligent Algorithms Based on Wireless Network Communication
Authors: Xie Juan , Cao Yunfei
Published: October 2021

In order to discuss a series of issues surrounding financial development and economic growth, it makes it more meaningful to discuss regional financial development and economic growth. This article aims to study the empirical study of the relationship between financial development and economic growth based on intelligent algorithms based on wireless network communication. In this article, a two-side positioning model is established, and the optimal solution is found for the feasible region through the particle swarm optimization algorithm. After two anchor nodes are realized, the position of the unknown node can be calculated. In addition, this article uses the Shadowing model to calculate the distance between wireless network nodes. This model is composed of path loss and occlusion factors, which can fully consider the impact of environmental factors on the signal. Experimental research data show that the improved algorithm has a positioning coverage close to 100% when the anchor node density is 30%. The improved algorithm in this article speeds up the convergence speed than positioning algorithm 1 and reduces the time by about 35%. Although the running time of the algorithm in this article is longer than that of positioning algorithm 2, the overall positioning accuracy is higher than that of the positioning algorithm, which is about 20% higher.
An Artificial Neural Network Algorithm for the Evaluation of Postoperative Rehabilitation of Patients
Authors: Tang Kunhao , Luo Ruogu , Zhang Sanhua
Published: October 2021

In order to explore the application of artificial neural network in rehabilitation evaluation, a kind of ANN stable and reliable artificial intelligence algorithm is proposed. By learning the existing clinical gait data, this method extracted the gait characteristic parameters of patients with different ages, disease types and course of disease, and repeated data iteration and finally simulated the corresponding gait parameters of patients. Experiments showed that the trained ANN had the same score as the human for most of the data (82.2%, Cohen’s kappa = 0.743). There was a strong correlation between ANN and improved Ashworth scores as assessed by human raters (r = 0.825,

P
<
0.01

). As a stable and reliable artificial intelligence algorithm, ANN can provide new ideas and methods for clinical rehabilitation evaluation.
[Retracted] Audience Evaluation and Analysis of Symphony Performance Effects Based on the Genetic Neural Network Algorithm for the Multilayer Perceptron (GA‐MLP‐NN)
Authors: Yan Cong
Published: October 2021

Traditional symphony performances need to obtain a large amount of data in terms of effect evaluation to ensure the authenticity and stability of the data. In the process of processing the audience evaluation data, there are problems such as large calculation dimensions and low data relevance. Based on this, this article studies the audience evaluation model of teaching quality based on the multilayer perceptron genetic neural network algorithm for the data processing link in the evaluation of the symphony performance effect. Multilayer perceptrons are combined to collect data on the audience’s evaluation information; genetic neural network algorithm is used for comprehensive analysis to realize multivariate analysis and objective evaluation of all vocal data of the symphony performance process and effects according to different characteristics and expressions of the audience evaluation. Changes are analyzed and evaluated accurately. The experimental results show that the performance evaluation model of symphony performance based on the multilayer perceptron genetic neural network algorithm can be quantitatively evaluated in real time and is at least higher in accuracy than the results obtained by the mainstream evaluation method of data postprocessing with optimized iterative algorithms as the core 23.1%, its scope of application is also wider, and it has important practical significance in real‐time quantitative evaluation of the effect of symphony performance.
Comparison of Different Waves during the COVID-19 Pandemic: Retrospective Descriptive Study in Thailand
Authors: Kunno Jadsada , Supawattanabodee Busaba , Sumanasrethakul Chavanant , Wiriyasivaj Budsaba , Kuratong Sathit , Kaewchandee Chuthamat
Published: October 2021

Background. Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. An outbreak is called an epidemic when there is a sudden increase in cases. Many countries have experienced a two-wave pattern in the reported cases of COVID-19. The spread of COVID-19 in Thailand was a cluster event distributed over multiple locations. This study aims to compare the characteristics of different waves during the COVID-19 pandemic in Thailand. Methods. A retrospective cohort study was conducted from January 2020 to May 2021 (17 months) to determine the number of COVID-19 screenings and confirmed cases and deaths as well as sociodemographic characteristics such as gender, age, nationality, and source population at risk factors. The categorical data were compared using a chi-square test. Results. Three waves of the COVID-19 pandemic occurred within 17 months in Thailand, and the number of cases increased by over 100,000 due to source population at risk factors such as close contact with a previously confirmed patient, community risk, cluster communities, and active and community surveillance. The chi-square test revealed significant differences between the three waves (

p
<
0.01

). Conclusion. Significant differences between pandemic phases or waves may be due to weak social distancing policies and the lack of public health interventions. A COVID-19 vaccination plan is needed for people at risk of suffering severe symptoms and the general population in outbreak areas to increase immunity.
A Test Method for Creep Characteristics of Loess Based on the One‐Dimensional Consolidator
Authors: Huang Rongbin , Wang Shuangming , Gu Shuancheng , Mao Zhengjun
Published: October 2021

When the traditional one‐dimensional consolidator is used to study the creep characteristics of loess, due to the hoop effect of the ring cutter, only the attenuation creep stage and stable creep stage of loess can be studied, but the accelerated creep stage cannot be presented. In order to avoid the influence of drilling on the creep characteristics of loess, the paper improves the consolidation instrument by drilling holes along the diameter direction in the center of the sample to provide artificial space for soil failure. At the same time, the sample size is increased to ensure that the diameter of the sample is greater than five times of the diameter of the borehole, so as to avoid the influence of drilling on the creep characteristics of loess. The creep characteristics of loess are studied by step loading (vertical pressure at all levels is 125 kPa, 175 Pa, 225 kPa, and 275 kPa), and the whole creep process characteristic curves of loess under different stress conditions are obtained. An endoscope was placed in the hole to observe the deformation and failure characteristics of loess in different stages of creep. This method makes up for the defect that the traditional one‐dimensional consolidator cannot obtain the whole process characteristics of loess creep. At the same time, it has the advantages of simple operation, less external influence factors, stronger data reliability, and can directly observe the changes of loess creep soil. It has a beneficial role in promoting the experimental research of loess creep characteristics.
A General Method for Transferring Explicit Knowledge into Language Model Pretraining
Authors: Yan Ruiqing , Sun Lanchang , Wang Fang , Zhang Xiaoming
Published: October 2021

Recently, pretrained language models, such as Bert and XLNet, have rapidly advanced the state of the art on many NLP tasks. They can model implicit semantic information between words in the text. However, it is solely at the token level without considering the background knowledge. Intuitively, background knowledge influences the efficacy of text understanding. Inspired by this, we focus on improving model pretraining by leveraging external knowledge. Different from recent research that optimizes pretraining models by knowledge masking strategies, we propose a simple but general method to transfer explicit knowledge with pretraining. To be specific, we first match knowledge facts from a knowledge base (KB) and then add a knowledge injunction layer to a transformer directly without changing its architecture. This study seeks to find the direct impact of explicit knowledge on model pretraining. We conduct experiments on 7 datasets using 5 knowledge bases in different downstream tasks. Our investigation reveals promising results in all the tasks. The experiment also verifies that domain-specific knowledge is superior to open-domain knowledge in domain-specific task, and different knowledge bases have different performances in different tasks.
Challenging Diagnosis of Addison’s Disease Presenting with Adrenal Crisis
Authors: Wina Dharmesti Ni Wayan , Saraswati Made Ratna , Suastika Ketut , Gotera Wira , Dwipayana I Made Pande
Published: October 2021

Primary adrenal insufficiency, also known as Addison’s disease, is a rare but potentially fatal condition resulting from the failure of the adrenal cortex to produce glucocorticoid and/or mineralocorticoid hormones. Unfortunately, the clinical manifestation of primary adrenal insufficiency is not specific and often progresses insidiously, resulting in late diagnosis, or in severe cases, life-threatening circulatory collapse. Adrenal insufficiency should be considered in patients with unexplained vascular collapse. We report the case of a woman who presented to the emergency ward with unexplainable shock that was later diagnosed as adrenal crisis due to Addison’s disease. The presence of hyperpigmentation in patients with rapid progression of adrenal insufficiency suggests the diagnosis of Addison’s disease presenting with adrenal crisis.