Miracle-dz/UniFAR-FTUs huggingface dataset:
Genicular Nerve Radiofrequency Ablation and Dual Subsartorial Block for Chronic Knee Pain Post Total Knee Replacement: A Case Report

Introduction. Chronic pain defines as pain persisting for three months or longer, chronic post-surgical pain can affect all dimensions of health-related quality of life, and is associated with functional limitations. treatment of chronic pain after total knee replacement is challenging, and evaluation of combined treatments and individually targeted treatments matched to patient characteristic. Genicular nerve block radiofrequency ablation is a safe and effective therapeutic procedure for pain associated with chronic pain due to knee osteoarthritis, and the evolution of newer regional analgesia techniques aids in reducing postoperative pain Dual Subsartorial Block (DSB) as a procedure specific, post total knee replacemet. historically there has been a reliance on using a pain-spesific assessment tools Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Case Presentation. A 55-year old woman admitted she had pain on bilateral knee, the knee pain had affected her daily living, she was diagnosed with chronic knee pain post TKR because of osteoarthritis genu bilateral, the patient was planning genicular nerve radiofrequency ablation and dual subsartorial block, from the examination we found that numeric rating scale was 6 (moderate pain) with WOMAC score 76, before the procedure the patients are examined through radiology for any deformity in the knee. The genicular nerve radiofrequency ablation under ultrasound guidance on bonylandmark, resulting anesthesia of the anterior compartment of the knee, and dual subsartorial block that cover almost all the innervations of pain generating component of the anterior and posterior knee joint involved in TKR surgery. After the procedure we reevaluated the pain score using NRS was 2 (mild pain), and with WOMAC Score 19. Conclusion. Treatment of chronic pain post total knee replacemet was challenging, targeted treatment may ameliorate the pain and prevent long term disability.
Exploring the Barriers and Driving Factors in Implementing Building Information Modelling (BIM) in the Malaysian Construction Industry: A Preliminary Study

In Malaysia, Building Information Modelling (BIM) has recently gained attraction from construction players and some of them have applied it to several projects. By utilising the BIM process, the construction players have the opportunity to plan, coordinate and design in an integrated approach. This is one of the many benefits that they could gain and resulting in increased productivity. Despite these benefits, the implementation of BIM in the Malaysian construction industry is still lagging behind Singapore, for instance. Thus, it warrants a study such as the present to determine what are the actual barriers that hamper its implementation and what are the driving factors that could enhance its pace of implementation in the Malaysian construction industry. In this study, a questionnaire survey based on Convenience Sampling Method was carried out to gather the possible barriers and driving factors for BIM implementation among the Malaysian construction players. Additionally, Relative Importance Indices (RII) were used to analyse the data obtained and to identify those barriers and driving factors for the implementation of BIM in this country. Consequently, results of this study revealed that the main barriers for implementing the BIM are: 1) Lack of knowledge about BIM, 2) Reluctance and/or no insistence shown by the Malaysian construction industry players (Clients, Contractors and Consultants alike) on the use or implementation of BIM. The driving factors, on the other hand, that could lead to the speeding up of the implementation of BIM are: 1) Support and enforcing the implementation of BIM by the Government, 2) promote BIM training program and 3) Initiatives of senior management of the related industry players. In conclusion, for successful wide spread application of BIM in Malaysia, a good push from the government alone is far from enough. All other construction industry players mentioned must assume their roles well in promoting the use of BIM in their construction projects.
Modeling consumers’ trust in mobile food delivery apps: perspectives of technology acceptance model, mobile service quality and personalization-privacy theory

ABSTRACT Considering the importance of customer trust in the m-commerce domain, this study aims to examine the role of technology acceptance model (TAM) factors, mobile service quality (M-SERQUAL) factors, and personalization and privacy in promoting customers’ trust and in turn their loyalty towards mobile food delivery apps (MFDAs). Four hundred ninety-four valid responses were collected from the online Facebook groups of MFDA review and analyzed through Partial Least Squares-based SEM approach. Our findings demonstrated that TAM factors (perceived ease of use and perceived usefulness), M-SERQUAL factors (interface quality, interaction quality, and information quality), and personalization were positively associated with customer trust in MFDAs, which was in turn positively related to customer loyalty towards MFDAs. Customer trust was observed as a mediator for the effects of TAM factors, M-SERQUAL factors, and personalization on customer loyalty. Nonetheless, privacy was not significantly associated with customer trust, which did not mediate the association between privacy and customer loyalty.
Decisions and coordination of retailer-led fresh produce supply chain under two-period dynamic pricing and portfolio contracts

Fresh agricultural produce is almost the staple food and necessity of people's daily diet all over the world. However, natural perishability and freshness affect the demand for fresh agricultural produce. Due to the change of freshness, the retailer has to adopt a multi-period dynamic pricing strategy to deal with unsold products. The research object of this paper is the retailer's two-echelon supply chain of fresh agricultural produce, and the aim is to achieve the optimal two-period coordination and ordering through options and wholesale contracts in the supply chain. In the case of two-period pricing, we find that the optimal wholesale order quantity increases with the decline of the price in the first period and tends to be stable with the decline of the price in the second period. In contrast, the price change in the first period has a greater impact on the retailer's optimal order quantity. The profits of both the retailer and the supplier increase significantly with the increase of the price in the first period, while the impact of the change of the price in the second period is not obvious. Meanwhile, decentralized decision-making can only be coordinated in the supply chain through the original option contract at the first-period price. In the second period, the cost-sharing contract is introduced to coordinate the supply chain, increase orders, and increase the profits of both the retailer and the supplier. These findings are of great significance for both the retailer and the supplier in the multi-period dynamic pricing of fresh produce under the option contract.
Digital Transformation and Ecosystem of Smart Pillows

This paper discusses how smart pillows relate to and benefit from digital platforms and ecosystems. With increasing demand for products that improve quality of life, many firms are focusing on products that improve the quality of our sleep. Modern digital technologies make it possible to expand the functionalities of sleep products and offer new smart features that can help people sleep better. These new digital features are possible because of two advances driven by modern digital technologies. The first is about tapping new kinds of data through technologies like sensors. And the second concerns digital ecosystems, or networks of data generators and recipients possible because of the exponential rise of the Internet of Things (IoT). This paper highlights how these advances apply to the specific case of smart pillows.
Lift Force of Airfoil (NACA 0012, NACA 4612, NACA 6612) With Variation of Angle of Attack and Camber: Computational Fluid Dynamics Study

Airfoil is a cross section from air plane wings can affect aerodynamic performance to lift force (FL). The lift force generated by airfoil has different values due to several external and internal factors, including angle of attack, flow rate and camber. To find the lift force of airfoils with different cambers and variations angle of attack and then flow rate can use computational fluid dynamics simulation. Computational fluid dynamics is simulation on a computer that can complete systems for fluid, heat transfer and other physical processes. This research using computational fluid dynamics simulation performed by SolidWorks, with NACA airfoil type which has different camber NACA 0012, NACA 4612 and NACA 6612. The angle of attack used in research was 0o, 4o, 8o, 12o, 16o and 20o. Flow rate used in research was 20m/s, 40 m/s, 60 m/s, 80 m/s and 100 m/s. From this research will be the bigger camber can produce a greater force lift. In addition, the greater airfoil flow rate can produce a greater force lift. This research also that the connection between force lift with coefficient lift (CL) is nonlinear quadratic form.
STUDY OF MRI MORPHOLOGY OF SPINAL TUBERCULOSIS

OBJECTIVE: To study the morphology of tuberculosis of spine on MRI. METHODS AND MATERIALS: A retrospective study was done in the department of Radiodiagnosis, PESIMSR, Kuppam.This study includes 37 patients with suspected Spinal Tuberculosis, who were referred to the department of Radiodiagnosis between 2019 Jan to 2021 July. Informed consent was taken from all the patients. This study was done on GE Signa Explorer 1.5 Tesla. RESULTS: A total of 37 cases were included in the study. Of these 37 cases, 31 were males and 6 were females. The most common age group involved was between 20-40 years, seen in 15 cases followed by 41-60 yrs seen in 14 cases and 61-90 yrs seen in 8 cases. Lumbar vertebrae were commonly affected accounting for 86% of total cases (32cases) followed by dorsal and cervical vertebrae accounting for 8% and 5 % respectively (3 and 2 cases respectively). Intervertebral disc involvement (Discitis) was most commonly seen in 32 cases followed by vertebral endplate involvement (27 cases) in our study. Prevertebral & paravertebral involvement were found in 20 and 23 cases respectively . In our study,19 cases had shown the involvement of posterior elements . Epidural soft tissue component was seen in 22 cases. Psoas abscess and paraspinal involvement were seen in 9 and 8 cases respectively. CONCLUSION: MRI helps in the early assessment of the extent and severity of disease compared to X-ray and CT scan. It is valuable in detecting early marrow changes, intervertebral disc involvement, extradural abscess and cord compression.
Impact of Dependency Ratio on Economic Growth among Most Populated Asian Countries

1. Assistant Professor, Department of Management Sciences, COMSATS University Islamabad, Vehari Campus, Punjab, Pakistan 2. Assistant Professor, School of Economics, Bahauddin Zakariya University Multan, Punjab, Pakistan PAPER INFO ABSTRACT Received: August 27, 2021 Accepted: December 17, 2021 Online: December 19, 2021 Demographic transition through different channels significantly influences economic growth. Malthusian view postulated as dependency ratio adversely affects economic growth while Julian Simon's view is quite different, highlighted the long-run benefits of the population in the range of 5 to15 years on economic growth. This study can be a valuable addition in research to analyzing the association of dependency ratio and economic growth of the five most populated Asian countries (Bangladesh, China, Indonesia, India, and Pakistan). Empirical findings of the study indicated that a total dependency and younger dependency ratio has a positive and significant influence on economic growth in both short-run and longrun scenarios while the old dependency ratio shows a negative influence on economic growth in the long run while short-run results are unpredictable. There is a need for state-based proper policy measures in focusing the higher financing in human capital development specifically in education and health.
Optical Fiber pH Sensor

Optocliemical sensor has been stressed domestically and internationally in recent 10 years. The real-time test and control to pH values is very significant to biochemistry, biomedicine and environment protection. The writers of this paper has finished 2 research projects such as basic features of optical pH sensor and sample of pH meter. It can be applied to test of ferment industry and realizes computer real-time supervision.
The Progress on Real Options for Company Valuation

Nowadays, real options derived from financial options are increasingly used in asset pricing. However, with different business models varied by companies, the existing real option pricing models are unable to be generally adopted. This paper addresses the problem of asset pricing under the impact of potential factors and discusses the path to carry out fair asset pricing with various business models. For the purpose of exploring the pricing method of using real options for asset pricing in practice, the article researches and sorts out the existing literature based on information retrieval. The applicability of real options, real options pricing models, parameter estimations, and the difficulties and problems during the application are systematically analyzed. Subsequently, the future research outlook and guideline are proposed. These results shed light for a more accurate and practical company valuation provided by real option pricing methodology compared with the DCF method
Data-driven modeling of ultimate load capacity of closed- and open-ended piles using machine learning

ABSTRACT Field pile load tests are fairly expensive experiments that can be applied to certain pile types required to be installed in full scale. Hence, it is neither practical nor efficient to perform a load test for every installed pile. While there exist many empirical relations for predicting pile capacities, such methods typically suffer from accuracy and generality. Therefore, current geotechnical practice still looks for methods to accommodate full-scale pile load testing to serve as accurate and practical tools. In this study, load bearing capacities of closed- and open-ended piles in cohesive and cohesionless soils are predicted using machine learning. Nine such methods are utilized in the analyses where Cone Penetration Test (CPT) and pile data are considered as the learning features necessary to teach those methods the database gathered via a comprehensive search. Then, machine learning models are developed, and the databases are separated into five-folds according to the cross-validation-principle, which are used for both training and testing of the machine learning methods. Model predictions are validated with classical CPT-based equations. Results indicate that Relevance Vector Regression and the Random Forest methods typically generate considerably better predictions than the other methods and empirical equations. Thus, machine learning methods are found as reliable tools to predict the pile load capacities of both open-ended and closed-ended pile provided that there is a large enough database and that an appropriate method is used.
Updated Perspectives on the Challenges of Managing Multiple Sclerosis During Pregnancy

Abstract Multiple sclerosis (MS) is a chronic immune-mediated, inflammatory, and degenerative disease that is up to three times more frequent in young women. MS does not alter fertility and has no impact on fetal development, the course of pregnancy, or childbirth. The Pregnancy in Multiple Sclerosis Study in 1998 showed that pregnancy, mostly in untreated women, did not adversely affect MS, as disease activity decreased during pregnancy (although it significantly increased in the first trimester postpartum). These findings, together with the limited information available on the potential risks of fetal exposure to disease modifying treatments (DMTs), meant that women were advised to delay the onset of DMTs, stop them prior to conception, or, in case of unplanned pregnancy, discontinue them when pregnancy was confirmed. Now, many women with MS receive DMTs before pregnancy and, despite being considered a period of MS stability, up to 30% of patients could relapse in the first trimester postpartum. Factors associated with an increased risk of relapse and disability during pregnancy and postpartum include relapses before and during pregnancy, a greater disability at the time of conception, the occurrence of relapses after DMT cessation before conception, and the use of high-efficacy DMTs before conception, especially natalizumab or fingolimod. Strategies to prevent postpartum activity are needed in some patients, but consensus is lacking regarding the therapeutic strategies for women with MS of a fertile age. This, along with the increasing number of DMTs, means that the decision-making processes in aspects related to family planning and therapeutic strategies before, during, and after pregnancy are increasingly more complex. The purpose of this review is to provide an update on pregnancy-related issues in women with MS, including recommendations for counseling, general management, use of DMTs in pre-pregnancy, pregnancy, and postpartum periods, and breastfeeding-related aspects of DMTs.
Sequence-assignment validation in cryo-EM models with checkMySequence

The availability of new AI-based protein structure prediction tools radically changed the way cryo-EM maps are interpreted, but it has not eliminated the challenges of map interpretation faced by a microscopist. Models will continue to be locally rebuilt and refined using interactive tools. This inevitably results in occasional errors, among which register-shifts remain one of the most difficult to identify and correct. Here we introduce checkMySequence; a fast, fully automated and parameter-free method for detecting register-shifts in protein models built into cryo-EM maps. We show that the method can assist model building in cases where poorer map resolution hinders visual interpretation. We also show that checkMySequence could have helped avoid a widely discussed sequence register error in a model of SARS-CoV-2 RNA-dependent RNA polymerase that was originally detected thanks to a visual residue-by-residue inspection by members of the structural biology community. Synopsis We present a new method, checkMySequence, for fast and automated detection of register errors in protein models built into cryo-EM reconstructions.
Molecular Dynamics Free Energy Simulation study to Investigate Binding Pattern of Isoliquiritigenin as PPAR𝛾 Agonist

Phytochemicals are rich source of bioactive constituents and can be used as another alternative to currently used drugs for diseases like Diabetes mellitus. The potential of Isoliquiritigenin (a constituent of Pterocarpus marsupium) as PPAR𝛾 agonist was evaluated by in silico technique. Autodock results showed that Tyr327, and Tyr473 of the PPARγ forms H-bonds with Isoliquiritigenin (binding energy of -7.46 kcal/mol) and Troglitazone (known drug) showed H bond with Tyr327, Ser289, with binding energy of -11.01 kcal/mol. Isoliquiritigenin, binding energy in Extra precision (XP) was -6.74 kcal/mol while Troglitazone docking, gave binding energy in XP mode as -9.59 kcal/mol. The best Induced fit docking (IFD) score of the optimised PPARγ- Isoliquiritigenin complexes was -9.39 Kcal/mol. The important residues in IFD forming H bond were Cys 285, Arg 288, Tyr 327 and Leu 340. The post docking MM/GBSA free energy for PPARγ with Isoliquiritigenin and Troglitazone was -49.29 and -71.48 Kcal/mol respectively. Binding interaction in MD simulation and Principal Component Analysis studies revealed stable binding throughout 100 ns simulation. Post Simulation MM/PBSA free energy was calculated. The results indicated that compound possessed a negative binding free energy with -114.37KJ/mol. It was observed that van der Waals, electrostatic interactions and non-polar solvation energy negatively contributed to the total interaction energy while only polar solvation energy positively contributed to total free binding energy. The Isoliquiritigenin fulfils the criteria of drug-likeness property. Thus, study presents a systematic analysis on molecular mechanism of action of Isoliquiritigenin as PPARγ agonist in controlling Diabetes mellitus.
Constrained Clustering for the Capacitated Vehicle Routing Problem (CC-CVRP)

ABSTRACT eCommerce, postal and logistics’ planners require to solve large-scale capacitated vehicle routing problems (CVRPs) on a daily basis. CVRP problems are NP-Hard and cannot be easily solved for large problem instances. Given their complexity, we propose a methodology to reduce the size of CVRP problems that can be later solved with state-of-the-art optimization solvers. Our method is an efficient version of clustering that considers the constraints of the original problem to transform it into a more tractable version. We call this approach Constrained Clustering Capacitated Vehicle Routing Solver (CC-CVRS) because it produces a soft-clustered vehicle routing problem with reduced decision variables. We demonstrate how this method reduces the computational complexity associated with the solution of the original CVRP and how the computed solution can be transformed back into the original space. Extensive numerical experiments show that our method allows to solve very large CVRP instances within seconds with optimality gaps of less than 16%. Therefore, our method has the following benefits: it can compute improved solutions with small optimality gaps in near real-time, and it can be used as a warm-up solver to compute an improved solution that can be used as an initial solution guess by an exact solver.
Efficacy and Safety of Radiofrequency Ablation for the Treatment of Autonomously Functioning Thyroid Nodules: A Long-Term Prospective Study

Objective This study aims to evaluate the efficacy and safety of RFA in the AFTN treatment after 2 years of follow-up and to find the factors related to treatment responses through TSH level and VRR. Materials and Methods This long-term prospective study was conducted from September 2017 to April 2021 on 17 AFTNs treated with RFA. Clinical evaluations, thyroid function tests, thyroid scintigraphy, and ultrasonography examinations were performed at 1 month, 3 months, 6 months, and 24 months after ablation. The primary endpoint was the success rate of RFA in restoring the euthyroidism stage after 24 months of follow-ups; secondary outcomes were VRR and improvements of US parameters, clinical examinations, and complications. The Spearman rank correlation test was used to determine related factors with treatment response variables. Results At the 24 months after the procedure, symptom score, cosmetic score, vascularity grade, and nodule volume significantly decreased. The VRR reduced approximately 42.77%, 63.13%, 78.3%, and 95.65% after 1 month, 3 months, 6 months, and 24 months follow-up. All 17 patients were restored euthyroid state without taking ATDs. No major complications were collected. The last TSH level was significantly correlated with the age of patients (Spearman rho = −0.637, p = 0.008). The VRR was significantly correlated with age of patients (Spearman rho = 0.566, p = 0.018) and initial TSH (Spearman rho = 0.485, p = 0.048). Conclusion RFA was demonstrated as a safe and effective option for AFTN treatment in long-term follow-up. It can be used as an alternative treatment with encouraging results.