bluuebunny/crossref_metadata_2025 huggingface dataset:
Domestic entities and access and benefit‐sharing: A legal critique of Divya Pharmacy v Union of India
Authors: Jolly Stellina
Published: July 2022

In the case of Divya Pharmacy v Union of India, the Uttarakhand High Court in India provided an innovative interpretation of the concept of access and benefit‐sharing by ruling that an Indian company, having no foreign participation, is mandated to undertake fair and equitable benefit‐sharing under the Biological Diversity Act 2002, India. The court employed a purposive interpretation, relying on the provisions of the Convention on Biological Diversity and its Nagoya Protocol. This article critically explores the Divya Pharmacy judgement, arguing that where a domestic statute makes a specific exemption in favour of domestic entities articulating a clear legislative intention, the judiciary should have engaged with constitutional provisions and environmental principles, which are part of domestic laws rather than relying exclusively on international treaty provisions to bring domestic entities under the purview of fair and equitable benefit‐sharing.
Caught in quicksand? Compliance and legitimacy challenges in using regulatory sandboxes to manage emerging technologies
Authors: Johnson Walter G.
Published: July 2022

Regulatory sandboxes have become the latest development in regulatory reform, starting first in financial regulation and now expanding to other sectors. While sandboxes offer notable potential benefits for managing emerging technologies, achieving desirable policy outcomes with this novel regulatory instrument also comes with technical and political challenges. This article offers a framework to characterize regulatory sandboxes in any sector, involving a blend of (1) approval regulation with broad‐based standards, (2) restricted discretion by the regulator for specific norms, (3) process‐oriented regulation, (4) an outcomes‐orientation, and (5) structured regulator–regulatee information sharing or dialogue. Using this model, the article outlines issues in compliance and legitimacy, including in trust and accountability, responsive enforcement, the politics of participation, and post‐sandbox oversight. The article concludes by calling for greater scrutiny when considering implementing a sandbox instrument, with attention to sector‐specific concerns, and offering directions for empirical evaluation of regulatory sandboxes.
Identifying supply and demand shocks in the South African Economy, 1960–2020
Authors: Fedderke Johannes W.
Published: July 2022

This paper addresses the identification of supply and demand shocks in the South African economy over the 1960–2020 period, the relative importance of the two types of shock to fluctuations of growth and inflation from their steady‐state values, as well as the potential impact of the two types of shocks on the steady‐state growth and inflation values. Crucially, the paper examines the significance of three alternative identification strategies on the nature of supply and demand shocks and their impact on the economy: zero shock covariance in the presence of long‐run demand neutrality; non‐zero shock covariance in the presence of long‐run demand neutrality and long‐run demand non‐neutrality with zero shock covariance. Interest lies in which of the identification strategies provides shock decompositions that are theoretically coherent and congruent with the empirics of South African growth and inflation. Results support non‐zero shock covariance in the presence of long‐run demand neutrality identification. The analysis suggests that growth shocks in South Africa are dominated by supply shocks, and inflation shocks by demand shocks. Further, negative supply shocks lower steady state growth and raise steady‐state inflation, while positive demand shocks only raise steady‐state inflation and are growth neutral. South Africa appears relatively isolated from international productivity shocks.
The use of medium cutoff dialyzers in patients with multiple myeloma and acute kidney injury requiring hemodialysis: A systematic review
Authors: Koniman Riece , Teo Su Hooi , Kaushik Manish , Nagarajan Chandramouli , Tan Melinda Si Yun , Tan Han Khim , Ramirez Maria Erika Gapas , Lim Cynthia Ciwei ,   S.I.N:G.A.P.O.R.E Initiative (Science In Nephrology: Growth And Progress Of Research & Education)
Published: July 2022

Background: Patients with multiple myeloma and high serum levels of circulating free light chains (FLC) have increased risk of acute kidney injury (AKI) secondary to cast nephropathy and is associated with poor survival. Despite removal of FLC by medium cutoff (MCO) dialyzer, the role of MCO hemodialysis (HD) in the treatment of cast nephropathy and its clinical benefits remain unknown. Methods: A systematic review was conducted to establish the effectiveness of MCO dialyzer and clinical outcomes, compared to other forms of dialyzers in the removal of FLC, in myeloma patients with AKI. The primary outcome was effectiveness of MCO‐HD in reducing serum FLC. The secondary outcomes were HD independence, estimated glomerular filtrate rate, mortality rates, length of hospitalization, rebound of serum FLC before the next dialysis, removal of other molecules during dialysis, and adverse events. Results: We identified three case series, with a total of 17 patients. There were no randomized controlled trials (RCTs) or cohort studies. These case series showed that MCO dialyzer was effective in the removal of FLC and led to a reduction in FLC concentration post‐dialysis. The majority of the case series did not have comparator arm and renal and/or other clinical outcomes. Conclusion: MCO dialyzer appeared to be effective in the removal of FLC based on the existing limited data. However, more data, particularly large‐scale RCTs, are needed to assess the use of MCO dialyzer in reducing serum FLC and its effect on clinical outcomes in patients with multiple myeloma and AKI.
Severe diabetic foot infections without systemic inflammatory response syndrome: Prospective validation of a new category
Authors: Aragón‐Sánchez Javier , Víquez‐Molina Gerardo , López‐Valverde María Eugenia , Rojas‐Bonilla José María
Published: July 2022

We aimed to validate the prognostic value of subclassifying moderate diabetic foot infections into two categories: moderate and moderate/severe. We conducted a prospective study of a cohort of 200 patients with moderate and severe infections. Moderate infections were subclassified after applying a previously published score. Variables associated with prognosis were: need for any amputation, major amputation, need for hospitalisation, length of hospitalisation, length of antibiotic therapy, reinfection rate and infection‐related mortality. Infections were moderate in 111 cases (55.5%) and severe in 89 (44.5%). Osteomyelitis (OM) was diagnosed in 114 cases (57%), 73 moderate (36.5%) and 41 severe (20.5%). Patients with severe OM had a higher rate of amputations, major amputations, hospitalisations and need for antibiotic therapy, and a longer duration of antibiotics when compared with moderate OM. After applying the score, moderate infections were subclassified into 73 moderate cases (65.7%) and 38 moderate/severe cases (34.3%). Moderate/severe had a higher rate of amputations, major amputations, hospitalisations and need for antibiotics than moderate ones. No differences regarding prognosis were found between moderate/severe and severe infections with systemic inflammatory response syndrome. Moderate/severe diabetic foot infections, which could also be known as severe infections without systemic inflammatory response syndrome, should be recognised as a new subgroup. We propose to merge severe diabetic foot infections with and without systemic inflammatory response syndrome into a unique category due to its prognostic value. Furthermore, OM should be added to both moderate and severe new categories of diabetic foot infections.
Evaluation of foot ulcer incidence in diabetic patients at a diabetic foot ulcer prevention clinic over a 10‐year period
Authors: Oe Makoto , Fukuda Mayu , Ohashi Yumiko , Shimojima Yuko , Tsuruoka Kahori , Qin Qi , Yamauchi Toshimasa , Sanada Hiromi
Published: July 2022

The present study aimed to evaluate diabetes patients over a 10‐year period that visited our outpatient clinic for prevention of diabetic foot ulcers and then investigate the incidence and aetiology of diabetic foot ulcers. The Department of Diabetes and Metabolic Diseases of a university hospital was in charge of the clinic that provided diabetes patients with individual education via the use of visualisation techniques. In this prospective cohort study, a total of 942 diabetes patients who visited the clinic were evaluated for neuropathy, angiopathy and medical history between November 2006 and March 2017. Using the patients' medical records, diabetic foot ulcer development was evaluated between the day of the first visit and December 31, 2018, with 20 out of 942 participants developing these ulcers. Over a period of 12, 60 and 120 months, the diabetic foot ulcer cumulative incidence was 0.2%, 2.4% and 5.8%, respectively. A history of diabetic foot ulcers and the male sex were shown by a Cox regression analysis to be correlated with diabetic foot ulcer development (Hazard Ratio [HR] 11.55, 95%CI 4.600–29.004,p < 0.001; and HR 3.55, 95%CI 1.031–12.196,p = 0.045, respectively). However, only five out of 20 participants with ulceration returned to the clinic for re‐examination. In conclusion, a 12‐month evaluation showed there was a low incidence of diabetic foot ulcers. These results might suggest that patients with a diabetic foot ulcer history need to undergo at least an annual follow‐up in order to further reduce diabetic foot ulcer incidence, although studies involving control groups needs to be conducted, in presenting these as evidence.
Comorbidity patterns, family history and breast cancer risk: a latent class analysis
Authors: Dalmartello Michela , Vermunt Jeroen , Parazzini Fabio , Serraino Diego , Giacosa Attilio , Crispo Anna , Negri Eva , Levi Fabio , Pelucchi Claudio , La Vecchia Carlo
Published: July 2022

Background

Limited evidence exists on how the presence of multiple conditions affects breast cancer (BC) risk.

Methods

We used data from a network hospital-based case–control study conducted in Italy and Switzerland, including 3034 BC cases and 3392 controls. Comorbidity patterns were identified using latent class analysis on a set of specific health conditions/diseases. A multiple logistic regression model was used to derive ORs and the corresponding 95% CIs for BC according to the patterns, adjusting for several covariates. A second model was fitted including an additional effect of FH on the comorbidity patterns.

Results

With respect to the ‘healthy’ pattern, the ‘metabolic disorders’ one reported an OR of 1.23 (95% CI 1.02 to 1.49) and the ‘breast diseases’ an OR of 1.86 (95% CI 1.23 to 2.83). The remaining two patterns reported an inverse association with BC, with ORs of 0.77, significant only for the ‘hysterectomy, uterine fibroids and bilateral ovariectomy’. In the second model, FH was associated with an increased risk of the ‘breast diseases’ pattern (OR=4.09, 95% CI 2.48 to 6.74). Non-significant increased risk of the other patterns according to FH emerged.

Conclusion

We identified mutually exclusive patterns of comorbidity, confirming the unfavourable role of those related to metabolic and breast disorders on the risk of BC, and the protective effect of those related to common surgical procedures. FH reported an incremented risk of all the comorbidity patterns.

Impact

Identifying clusters of comorbidity in patients with BC may help understand their effects and enable clinicians and policymakers to better organise patient and healthcare management.
Analysis of cervical HPV infections among unvaccinated young adult women to inform vaccine strategies in this age group: the Costa Rica HPV Vaccine Trial
Authors: Sierra Mónica S. , Tsang Sabrina H. , Porras Carolina , Herrero Rolando , Sampson Joshua N. , Cortes Bernal , Schussler John , Wagner Sarah , Carvajal Loretto , Quint Wim , Kreimer Aimée R. , Hu Shangying , Rodriguez Ana Cecilia , Romero Byron , Hildesheim Allan
Published: July 2022

Introduction

Human papillomavirus (HPV) vaccines protect against incident HPV infections, which cause cervical cancer.

Objectives

We estimated the prevalence and incidence of HPV infections in young adult women to understand the impact of an HPV vaccination programme in this population.

Methods

We collected cervical specimens from 6322 unvaccinated women, aged 18–37 years, who participated in the Costa Rica Vaccine Trial and its long-term follow-up. Women were followed for (median) 4.8 years and had (median) 4.0 study visits. Cervical specimens were tested for the presence/absence of 25 HPV genotypes. For each age band, we estimated the percentage of women with 1+ prevalent or 1+ incident HPV infections using generalised estimating equations. We also estimated the prevalence and incidence of HPV as a function of time since first sexual intercourse (FSI).

Results

The model estimated HPV incident infections peaked at 28.0% (95% CI 25.3% to 30.9%) at age 20 years then steadily declined to 11.8% (95% CI 7.6% to 17.8%) at age 37 years. Incident oncogenic HPV infections (HPV16/18/31/33/35/39/45/51/52/56/58/59) peaked and then declined from 20.3% (95% CI 17.9% to 22.9%) to 7.7% (95% CI 4.4% to 13.1%); HPV16/18 declined from 6.4% (95% CI 5.1% to 8.1%) to 1.1% (95% CI 0.33% to 3.6%) and HPV31/33/45/52/58 declined from 11.0% (95% CI 9.3% to 13.1%) to 4.5% (95% CI 2.2% to 8.9%) over the same ages. The percentage of women with 1+ incident HPV of any, oncogenic, non-oncogenic and vaccine-preventable (HPV16/18, HPV31/33/45, HPV31/33/45/52/58, and HPV6/11) types peaked <1 year after FSI and steadily declined with increasing time since FSI (p for trends <0.001). We observed similar patterns for model estimated HPV prevalences.

Conclusion

Young adult women may benefit from HPV vaccination if newly acquired vaccine-preventable oncogenic infections lead to cervical precancer and cancer. HPV vaccination targeting this population may provide additional opportunities for primary prevention.

Trial registration number

NCT00128661.
Type-specific concurrent anogenital HPV detection among young women and MSM attending Dutch sexual health clinics
Authors: Kusters Johannes MA , Heijne Janneke CM , van Benthem Birgit HB , King Audrey J , Schim van der Loeff Maarten F
Published: July 2022

Objectives

This study aimed to investigate type-specific concurrent anogenital human papillomavirus (HPV) detection and examine associations with concurrent detection.

Methods

Data from a Dutch repeated cross-sectional study among young sexual health clinic visitors (Papillomavirus Surveillance among STI clinic Youngsters in the Netherlands) between 2009 and 2019 were used. Cohen’s kappa was used to assess the degree of type-specific concordance of HPV detection between anal and genital sites for 25 HPV genotypes for women and men who have sex with men (MSM) separately. Associations with type-specific concurrent HPV were identified. Receptive anal intercourse (RAI) was forced into the model to investigate its influence.

Results

Among women (n=1492), type-specific concurrent anogenital detection was common; kappa was above 0.4 for 20 genotypes. Among MSM (n=614), kappa was <0.4 for all genotypes. The only significant association with type-specific concurrent anogenital detection among women was genital chlamydia (adjusted OR 1.5, 95% CI 1.1 to 2.2). RAI was not associated.

Conclusions

Type-specific concurrent anogenital HPV detection was common among young women, and uncommon among MSM. For women, concurrent HPV detection was associated with genital chlamydia. Our results are suggestive of autoinoculation of HPV among women.
An anisotropic extension of Heintzmann IIa solution with vanishing complexity factor
Authors: Andrade J.
Published: July 2022

This work is devoted to the construction of a new static and spherical solution for an anisotropic fluid distribution. The construction is based in the framework of gravitational decoupling through a particular case of the extended minimal geometric deformation called 2-steps GD. In this sense, the differential equations arising from gravitational decoupling are closed using the vanishing complexity factor. The Heintzmann IIa solution is used as seed solution. The solution fulfills the fundamental physical acceptability conditions for a restricted set of compactness parameters.
REGIONAL POVERTY PPPS IN CHINA: EXPERIMENTAL ESTIMATION AND APPLICATION
Authors: CHEN MENGGEN , RAO D. S. PRASADA
Published: July 2022

Accurate measurement of the incidence of poverty is essential for monitoring the performance of countries against poverty. In poverty measurement, the global poverty line (GPL) is usually converted to national equivalents in local currencies, with the available purchasing power parities (PPPs) from the World Bank’s International Comparison Program (ICP), instead of the exchange rate. This approach is often criticized for various limitations, and the poverty PPPs are recommended to be estimated from modifications of the ICP framework as a conversion factor of the GPL. This study employs a sample of price data in 2015 and the approximate expenditure budgets of poor households to estimate the regional poverty PPPs in China. The results show that the estimates of regional poverty PPPs with different aggregating methods are very similar, and the price levels for the poor in the more-developed regions are usually high, while those in the less-developed regions are relatively low. The urban poverty PPPs of four regions are greater than 1 (with Beijing = 1), while the rural poverty PPPs of seven regions are greater than 1. The series of regional poverty PPPs are obtained by extrapolation and reveal that there is a price convergence phenomenon among regions during the period. With the regional poverty PPPs, the urban and rural regional poverty lines (RPLs) across China are estimated, based on the World Bank’s GPL.
Inflation in f(R,T) gravity with double-well potential
Authors: Deb Biswajit , Deshamukhya Atri
Published: July 2022

In this work, we studied the inflation in the context of [Formula: see text] theory of gravity. We assumed the functional form of [Formula: see text] to be [Formula: see text], where R is the Ricci scalar, T is the trace of the energy–momentum tensor and [Formula: see text] is the model parameter. The cosmological observable parameters like scalar spectral index [Formula: see text] and tensor-to-scalar ratio [Formula: see text] are estimated for Double-Well potential. We found that for [Formula: see text], [Formula: see text] and [Formula: see text] are in good agreement with Planck 2018 data. Further, considering the vacuum expectation value in Double-Well potential to be Planckian, we observed the admissible range of model parameter to be [Formula: see text] for which this model remains consistent with Planck 2018 data.
Design and Implementation of Face Detection Architecture for Heterogeneous System-on-Chip
Authors: Panda Nidhi , Gupta Supratim
Published: July 2022

The seminal work of Viola and Jones for automatic face detection is widely used in many human–computer interaction and computer vision applications. On analyzing the existing face detection architectures, we observed that integral image calculation, feature computation in cascaded classifier, and recursive scanning of image with sliding window at multiple scales are the major reasons which increase the memory and time complexity of the algorithm. Therefore, in this paper, we have proposed a hardware–software co-design of Viola–Jones face detector for System-on-Chip (SoC). In the proposed architecture, integral image computation and cascaded classifier sub-modules are implemented on the hardware — Programmable Logic FPGA (PL-FPGA), while the image scaling and nonmaximum suppression sub-modules are implemented on the software — Processing System ARM (PS-ARM). Concepts of pipelining, folding, and parallel processing are effectively utilized to produce an optimum design architecture. The proposed architecture has been tested on PYNQ-Z1 board. The implementation results in a processing speed of [Formula: see text] fps with PL and PS clocks of [Formula: see text][Formula: see text]MHz and [Formula: see text][Formula: see text]MHz, respectively, for an image of QVGA resolution. Results analysis demonstrates that the proposed architecture has minimum resource requirement as compared to state-of-the-art implementations, which facilitates and promotes the usage of resource-constrained low-cost ZYNQ SoC for face detection.
A Compressed Model-Agnostic Meta-Learning Model Based on Pruning for Disease Diagnosis
Authors: Hu Xiangjun , Ding Xiuxiu , Bai Dongpeng , Zhang Qingchen
Published: July 2022

Meta-learning has been widely used in medical image analysis. However, it requires a large amount of storage space and computing resources to train and use neural networks, especially model-agnostic meta-learning (MAML) models, making networks difficult to deploy on embedded systems and low-power devices for smart healthcare. Aiming at this problem, we explore to compress a MAML model with pruning methods for disease diagnosis. First, for each task, we find unimportant and redundant connections in MAML for its classification, respectively. Next, we find common unimportant connections for most tasks with intersections. Finally, we prune the common unimportant connections of the initial network. We conduct some experiments to assess the proposed model by comparison with MAML on Omniglot dataset and MiniImagenet dataset. The results show that our method reduces 40% parameters of the raw models, without incurring accuracy loss, demonstrating the potential of the proposed method for disease diagnosis.
Clean and Learn: Improving Robustness to Spurious Solutions in API Question Answering
Authors: Yuan Shuai , Qin Haozhe , Gu Xiaodong , Shen Beijun
Published: July 2022

The development of a question answering (QA) system for application programming interface (API) documentation can greatly facilitate developers in API-related tasks. However, when applying deep learning technology, API QA systems suffer from the spurious solution problem. That is, the answer can literally appear in multiple positions (i.e. start-end indices) in the API documentation, though only one of them (called golden solution) correctly solves the question given its context. The other incorrect candidates (called spurious solutions) hinder the neural network model to learn reasonable solutions or correct answers. In this work, we propose Clean-and-Learn, an effective and robust method for API QA over documents. In order to reduce the spuriousness of candidate solutions used for training, we design several scoring functions to rank the candidate occurrences (clean). Only high-quality (top-[Formula: see text]) candidate solutions are involved in training. Then, we perform multi-task learning by weighing the losses computed from the top-k occurrences (learn). We evaluate our method on the constructed APIQASet dataset. The experiment results show that Clean-and-Learn achieves a ROUGE-L score of 75.8 and accuracy of 70.5% in API QA, which significantly outperforms state-of-the-art approaches.
THE ROLE OF SLEEP DISTURBANCE, SLEEPINESS, AND FATIGUE IN THE DEVELOPMENT OF ACUTE AND CHRONIC NECK PAIN
Authors: Aldabbas Mosab M. , Tanwar Tarushi , Ghrouz Amer , Iram Iram , Veqar Zubia
Published: July 2022

Background: Many physiological and psychological factors could play a significant role in acute and chronic neck pain, and they may delay the recovery process. Understanding the predictors for acute and chronic neck pain is essential to establishing effective management strategies for this population.

Aims: To identify the risk factors for acute and chronic neck pain, to compare the variables (sleep quality, daytime sleepiness, fatigue, depression, anxiety, and disability) between acute and chronic stage of neck pain, and to examine the gender differences between these variables.

Methods: Patients ([Formula: see text] = 436) with acute and chronic neck pain were included. They completed baseline questionnaires to report on the intensity of pain, sleep quality, sleepiness, fatigue, anxiety, depression, and disability.

Results: Data analysis was performed using a linear regression and multivariate analysis of covariance to evaluate the predictors of acute and chronic neck pain, and to compare the study variables between acute and chronic neck pain as well as to explore the presence of a gender bias. Poor sleep quality was the only predictor of acute neck pain. Poor sleep quality, sleepiness, and fatigue were significant predictors of chronic neck pain. Also, the score of these predictors was higher among chronic neck patients compared to acute conditions.

Conclusion: Sleep disturbances, sleepiness, and fatigue are important predictors of chronic neck pain. The findings highlight the importance of addressing these factors in the assessment and management of neck pain conditions.
CHANGES IN ANKLE PROPRIOCEPTION WITH SEVERITY OF OSTEOARTHRITIS OF KNEE
Authors: Shetty Samiksha , Eapen Charu , Prabhakar Ashish J
Published: July 2022

Background: Ankle proprioception may be affected in knee Osteoarthritis (OA), but there is a lack of evidence showing changes in ankle proprioception within the grades of severity of knee OA.

Objective: To assess ankle proprioception in patients with knee OA and find its change within the grades of severity of knee OA knee based on the Kellgren and Lawrence (KL) classification. A secondary aim was to see the association between ankle proprioception and functional status.

Methodology: It was a cross-sectional study. Sixty-three patients with knee OA were included in the study. X-rays of the patients were interpreted according to KL classification system to grade the severity of knee OA by an experienced orthopedic surgeon. Ankle joint reposition sense (reposition error) was measured using the active to active method with the Saunders digital inclinometer. The assessor was blinded to the grades of the knee OA. The functional status was evaluated using the WOMAC scale.

Results: The mean joint reposition error was 2.68 ± 1.80 (0.33-8.33), and WOMAC scores were 45.99 ± 11.67 (30.2–84.37). The WOMAC scores were significant ([Formula: see text] = 0.005) but not the joint reposition error ([Formula: see text] = 0.14) with the increasing severity of knee OA. When compared within the grades of severity, both were not significant. The correlation between WOMAC scores and joint reposition error scores was [Formula: see text] = 0.16 and [Formula: see text] = 0.22.

Conclusion: The joint reposition error did not vary with the severity of knee OA within the grades. It was also not found to be associated with the functional status of knee
Global Diversification and the Cost of Equity
Authors: Jiang Xiaowen , Lin Ling , Sen Pradyot K.
Published: July 2022

The conventional view in the standard finance textbooks is that organizational form does not matter for a firm’s cost of capital because firm diversification reduces only idiosyncratic risk and not systematic risk. In this study, we investigate the effect of global diversification on the ex-ante cost of equity implied by the residual income valuation model (Ohlson, Earnings, book value and dividends in security valuations. Contemporary Accounting Research, 11(2), 661–687, 1995), using a sample of US firms from 1997 to 2019. Employing the empirical approach developed in Easton et al. (Using forecasts of earnings to simultaneously estimate growth and the rate of return on equity investment. Journal of Accounting Research, 40(3), 657–676, 2002), our results suggest that global diversification reduces the cost of equity capital for both single-segment firms and multi-segment firms. Our results highlight the effect of global diversification on the equity risk reduction, which may explain the increasing proliferation of foreign operations among US firms — a trend that neither the cash flow effect nor the capital structure effect proposed in previous studies can explain.
DYNAMIC STABILITY DURING REPETITIVE AXIAL GLENOHUMERAL ROTATION USING CINE MRI IN HEALTHY ADULTS
Authors: MATSUI KAZUHISA , TACHIBANA TAKASHI , NOBUHARA KATSUYA , HASEGAWA TAKASHI , UCHIYAMA YASUSHI
Published: July 2022

Manual testing for dynamic shoulder instability includes noting and shifting of the humeral head, but the corresponding shift of the axis of rotation has been given little attention. The purpose of this study is to clarify translation of the humeral head during active glenohumeral rotation. Magnetic resonance images were taken at 2[Formula: see text]images/s on 22 shoulders of 11 healthy men. At [Formula: see text] shoulder elevation, the supine subject internally and externally rotated the humerus repeatedly over 20[Formula: see text]s. The location over the glenoid of the center of the humeral head (CENHED) projected was studied. During external rotation, projection of CENHED on the glenoid began posterior to the center of the glenoid and migrated to anterior. During internal rotation, this projection was initially positioned above the glenoid center and midway through the motion, shifted inferiorly to nearly the glenoid center. The projection of CENHED did not significantly differ in location over the glenoid at any position along the range of motion during shoulder rotation. Initial values are now available for judging excessive movements of the humeral head on the glenoid fossa during rotation at [Formula: see text] of abduction in the scapular plane. The method used in this study is amenable to clinical use.
ZnO:Fe3O4Nanoparticles Produced by Cold Plasma: Synthesis, Characterization and Anti-Microbial Activity
Authors: Mazhir Sabah N. , Ali Alyaa H. , Abdalameer Nisreen Kh. , Qasim Shaymaa A.
Published: July 2022

The cold atmospheric plasma in liquid (CAPL) technique was carried out in DI water as the solution to create Fe3O4-doped ZnO nanoparticles by adjusting the concentration (0.01, 0.02 and 0.03) M at ([Formula: see text][Formula: see text]kV, [Formula: see text][Formula: see text]mA and flow rate = 3[Formula: see text]L/min), while the exposure period was 3[Formula: see text]min. A UV-Vis. spectrophotometer, X-ray diffraction and field emission spectroscopy (FE-SEM) were used. The energy of the bandgap was discovered to be (2.95–2.85) eV. The form and dimensions obtained by FE-SEM have not changed much. All materials were tested against inactivated positive and negative gram bacteria (S. aureaus and E. coli) and showed promising antibacterial capabilities, especially Fe3O4-doped ZnO, which can inactivate bacteria under typical laboratory light.
Value Creation and Investment Projects: An Application of Fuzzy Sensitivity Analysis to Project Financing Transactions
Authors: Guerra Maria Letizia , Magni Carlo Alberto , Stefanini Luciano
Published: July 2022

This paper presents a methodology which blends sensitivity analysis (SA) and fuzzy arithmetic for managing uncertainty in project financing transactions. Specifically, we adopt the perspective of the equityholders and use the average return on equity (ROE) to measure shareholder value creation and, in particular, the financial efficiency of the equity investment. We cope with uncertainty via global and local SA and fuzzy arithmetic; we use the fuzzy version of the well-known (global) Gamma indicator and we introduce the fuzzy versions of two (local) importance measures, the differential importance measures (DIM). We then apply them to the pro forma financial statements drawn up by the analyst for measuring and ranking the impact of the key accounting parameters on the resulting values and we show how the uncertain accounting and financial magnitudes of the project company affect the financial efficiency. Among the advantages of this analysis, aimed to enhance the managerial insights generated by the financial model and to lead to appropriate managerial actions, we focus on the attractiveness of fuzzy calculus and possibility theory to represent and compute all relevant financial data that appear in project financing and budgeting, where available information is characterized by incompleteness or nonstatistical uncertainty. In this context, fuzzy computing and appropriate SA techniques, based on application of the extension principle, allow complete investigation of the project characteristics.
A New Method for Analysis of Customers’ Online Review in Medical Tourism Using Fuzzy Logic and Text Mining Approaches
Authors: Nilashi Mehrbakhsh , Samad Sarminah , Alghamdi Abdullah , Ismail Muhammed Yousoof , Alghamdi OA , Mehmood Syed Salman , Mohd Saidatulakmal , Zogaan Waleed Abdu , Alhargan Ashwaq
Published: July 2022

Mining medical tourists’ preferences and detecting their satisfaction level through Electronic Word of Mouth (eWOM) in medical tourism websites is an important task. Machine learning techniques have been very successful in developing recommendation agents through the analysis of eWOM in the e-commerce context. However, such methods are fairly unexplored in the medical tourism context through the analysis of user-generated content. This research is the first attempt to analyze eWOM in medical tourism websites for tourists’ preferences mining using machine learning techniques. The results of the eWOM analysis revealed that the learning techniques are able to effectively analyze online reviews and accurately predict their preferences for their decision-making process in medical tourism. Compared to the methods which rely solely on the supervised learning techniques, the method evaluation results demonstrated that the use of fuzzy clustering and text mining approaches can be an important stage of eWOM analysis in the prediction of medical tourists’ preferences.
Forecasting Foreign Visitors Arrivals Using Hybrid Model and Monte Carlo Simulation
Authors: Danbatta Salim Jibrin , Varol Asaf
Published: July 2022

The tourism industry is one of the important revenue sectors in today’s world. Millions of visits are made monthly to different countries across the planet. Some countries host more tourists than others, depending on the availability of factors that would fascinate visitors. Tourism demand can be affected by different factors, which may include government policies, insecurity, political motive, etc. Being an important sector, policymakers/governments are keen on models that would provide an insight into the inherent dynamics of tourism in their country. Especially in forecasting future tourist arrivals, as it will greatly assist in decision making. Several tourism demand models have been presented in the literature. The best practice is to have a model that would account for uncertainty in estimations. In this paper, an ANN-Polynomial-Fourier series model is implemented to capture and forecast tourist data for Turkey, Japan, Malaysia, and Singapore. The proposed model is a combination of the artificial neural network (ANN), polynomial fitting (poly), and Fourier series fitting (Fourier). The proposed model is designed to capture the data trend component using the polynomial fitting, the data seasonal component using the Fourier series fitting, and other data anomalies using the artificial neural network. Multistep ahead forecasting is made for each of the studied tourist data, and estimation uncertainties are covered by generating multiple forecast paths (Monte Carlo forecast). According to estimations, Turkey will expect a 10.22% increase in 2021 compared to the tourist arrivals it received in 2020. Japan is expected to have a 92.42% decrease in 2021 compared to the tourist arrivals it received in 2020. Malaysia is also expected to have a 54.81% decrease in 2021 when compared to the number of tourists it received in 2020. Finally, Singapore will expect a 70.55% decrease in 2021 compared to the number of tourists it received in 2020.
Toward a Maturity Model for Big Data Analytics: A Roadmap for Complex Data Processing
Authors: Pour Mona Jami , Abbasi Fatemeh , Sohrabi Babak
Published: July 2022

In the current data-driven digital economy, organizations attempt to harness big data power to make their decisions better. The big data analytics assist them not only to identify new opportunities but extract knowledge and obtain better performance. Despite a huge investment in big data analytics initiatives, the majority of organizations have failed to successfully exploit their power. Although big data analytics have received considerable research attention, a little has been done on how organizations implement strategies in order to integrate the different dimensions of big data analytics; hence, a roadmap is required to navigate these technological initiatives. This paper is also an attempt to overcome this challenge by developing a comprehensive big data analytics maturity model to help managers evaluate their existing capabilities and formulate an appropriate strategy for further progress. A mixed-method was applied in this research using a qualitative meta-synthesis approach. For this purpose, first, a systematic literature review was conducted to identify the capabilities and practices of big data analytics maturity. Then the proposed key capabilities and practices were assessed and prioritized based on the opinions of experts using the quantitative survey method. Finally, considering the architecture of the big data analytics maturity model, the capabilities were assigned to maturity levels according to their priority of implementation using a focus group. The proposed model is comprised of four main capabilities, nine key dimensions (KDs) and five maturity levels based on the capability maturity model integration (CMMI) architecture. A questionnaire and a focus group were used to present the big data maturity model. The capabilities and KDs, as well as their implementation order and weight in the proposed maturity model are presented as a roadmap for implementing big data analytics effectively. The proposed model enables organizations to assess their current big data analytics capabilities and navigate them to select appropriate strategies for their improvement. Due to its nature, it allows managers to find their strong and weak points and identify investment priorities. This study provides a comprehensive maturity model using a meta-synthesis which has not been used in this field so far. The proposed model is both descriptive and prescriptive and has a significant theoretical contribution to big data researches. The paper provides a mechanism to benchmark big data analytics projects and develop an appropriate strategy in terms of progress.
Assimilation of Pair-Wise Comparison Method to Decide Weights of Features Based on the Content of Image
Authors: Rout Narendra Kumar , Atulkar Mithilesh , Ahirwal Mitul Kumar
Published: July 2022

Computer-based image recognition systems rely on training with an initial training set to recognize similar images. However, when such training set is not available, individual features within a given image can be used to identify and compare with congruent features in database to find similarity among images. An experiment is implemented for extracting similar images using this technique of computer-based image recognition. For this study multiple features color, shape and texture have been extracted from Corel 10k database images. After manual selection of individual feature weightage, all features with equal weightage have been used to identify similar images from database. After observing class wise average precision and average recall of Corel 10k database images, it has been found that equal weightage approach yields satisfactory results and also better as compared with individual feature approach in maximum number of classes. In some of the classes, results are not satisfactory with equal weightage approach. In these classes, results vary with weights of feature according to nature of image. The average precision and recall of entire classes are 96.62% based on all feature equal weight. Now, the problem is to decide weights of features. For this, this study proposes the automatic determination of the weightage for features using pair-wise comparison method. The problem is formulated as multiple criteria decision-making (MCMD) problem and solved through analytic hierarchical process (AHP). Graphical user interface (GUI) is also designed. The proposed approach determines color dominant, shape dominant and texture dominant based on importance on respective features. The average precision and recall of 95 classes are 100% in all dominant features. The average precision and recall of remaining five classes are 59%, 53% and 46% in color dominant, shape dominant and texture dominant, respectively. Performance measure shows that the proposed method archives better results as compared to manual assignment of weights of features.
A Health Evaluation Method of Complex Systems Based on Evidential Reasoning Rule Considering Perturbations
Authors: Tang Shuaiwen , Zhou Zhijie , Cao You , Ning Pengyun , Zhang Peng , Zhao Dao , Chen Leiyu
Published: July 2022

The complex system has been widely applied in aerospace, chemical industry, manufacturing, military equipment and other fields. To ensure its safe and reliable operation, it is necessary for technicians to grasp the health state of the system effectively. However, if there are perturbations in the observation data, the evaluation result may be inaccurate. Besides, the effectiveness of evaluation result can be affected by perturbation, which means that the threshold of perturbation intensity should be determined. To solve these problems, in this paper, a new health evaluation method of complex systems is proposed based on the evidential reasoning (ER) rule by considering perturbations. First, the structure of the evaluation model is constructed. Second, an ER rule-based health evaluation model is proposed, and the idea of perturbation analysis is introduced for the robustness analysis of the model. Third, a parameter optimization model is established, and the upper bound of perturbation intensity is estimated accurately. The threshold can measure the effectiveness of the evaluation result and the anti-perturbation ability of the system in engineering practice. Finally, a case study of the WD615 model diesel engine is conducted to validate the effectiveness of the proposed method.
Effects of Cover Depth and Rock Type on Dynamic Response of Road Tunnels Against Internal Explosions
Authors: Cheng Ruishan , Chen Wensu , Li Jingde , Hao Hong
Published: July 2022

Dynamic response of road tunnels against internal explosions can vary depending on the types and cover depths of surrounding rock mass. However, the influences of cover depth and rock type on dynamic response of road tunnels under internal explosions are very less investigated. Based on the calibrated numerical model of road tunnel, the present study investigates the dynamic response of an arched road tunnel subjected to an internal Boiling Liquid Expansion Vapour Explosion (BLEVE) and its equivalent TNT explosion under varied cover depths and different rock types. The results indicate that the increment of the cover depth can reduce the lining response (e.g., strain energy and damage) against the internal BLEVE. However, beyond a certain cover depth, the TNT explosion-induced lining response (e.g., strain energy) escalates with the increased cover depth due to the enlarged rebound deformations of the lining with the increased in-situ stress. In addition, the rock mass with better mechanical properties is beneficial to reduce the tunnel response under the internal BLEVE but leads to more severe tunnel response under the internal TNT explosion. Using equivalent TNT explosion loads may not give reliable predictions of tunnel responses subjected to BLEVE loads.
Structural and Electronic Properties of ZnO Bilayer and Twist Bilayer: A First-Principles Study
Authors: Yu Wen , Wang Xiao , Li Chuanguo
Published: July 2022

By using the first principles calculations, we study the structural and electronic properties of zinc oxide (ZnO) bilayers. Initial ZnO bilayer has a planar structure, which is different from bulk ZnO. Another kind of twist ZnO bilayer is designed by rotating 60° on the basis of ZnO bilayer structure with a Zn/O atom as the axis. Both the bilayers have stable structure and high symmetry. As the interlayer distance increases, the interaction of the upper and the lower layers will weaken in both the bilayers. It is Zn atom but not O atom that plays a key role in the interlayer interaction, which has been confirmed by Mulliken charge and density of states results. The band gap of the bilayers can be tuned by translation motion, and ZnO twist bilayer shows a better performance than the initial bilayer in this study. Combining the two factors (interlayer distance and twist angle), ZnO bilayers are very hopeful to be utilized in 3D joints of nanoelectronic devices. Our results provide a detailed understanding of the structural and electronic properties of ZnO bilayers and help to predict the performance of ZnO-based two-dimensional nanoelectronics and nanocomposites.
On Hermite–Hadamard–Fejér-type inequalities for co-ordinated trigonometrically ρ-convex functions
Authors: Kara Hasan , Budak Hüseyin , Ki̇ri̇ş Mehmet Eyüp
Published: July 2022

In this paper, we first obtain Hermite–Hadamard–Fejér inequalities for co-ordinated trigonometrically [Formula: see text]-convex functions. By using these obtained inequalities, we give some inequalities involving Riemann–Liouville fractional integrals. The inequalities presented in this study provide generalizations of some results given in earlier works.
On left φ-essential Connes-amenability of Banach algebras
Authors: Shariati Gazgazareh Nasrin , Naseri Saber , Ghaderi Eghbal , Shariati Seyedeh Fatemeh
Published: July 2022

In this paper, we introduce and study the notion of left [Formula: see text]-essential Connes amenable for dual Banach algebras. We investigate the hereditary properties of this new concept and we give some results for [Formula: see text]-Lau product and module extension. For unital dual Banach algebras, we show that left [Formula: see text]-essential Connes-amenability and left [Formula: see text]-Connes amenability are equivalent. Finally, with various examples, we examined this concept for upper triangular matrix algebras and [Formula: see text]-direct sum of Banach algebras.
A novel high-performance cathode for rechargeable aqueous zinc-ion battery: transformed ZnMnO3nanosheets from rhodochrosite MnCO3cubes
Authors: Wang Ning , Ni Kefan , Liu Hao , Cui Rukun , Gu Jianmin , Fan Xiaoyong , Wang Desong
Published: July 2022

Rechargeable aqueous zinc-ion battery (RAZIB) shows great practical value as energy storage system owing to the high safety, low cost, non-polluting, high energy and high power density. However, it still faces a series of scientific and technical problems, such as the undesirable cycling stability and high-rate capability. Herein, we synthesized micro-sized MnCO3cubes as a novel cathode for aqueous zinc-ion battery, where the cathode materials has the phase transition from rhodochrosite MnCO3to layered-type ZnMnO3induced by the continuous uptake/removal of zinc ions during electrochemical cycling. The RAZIB has a specific capacity of 97.6 mA h g[Formula: see text]and distinguished cycling stability up to 5000 cycles with 79.1% retention at 1.8 A g[Formula: see text]. This work benefits for the electrochemical performance of aqueous zinc-ion battery, and clarifies the understanding of its electrochemical mechanism.