bluuebunny/crossref_metadata_2025 huggingface dataset:
Functional Epiphora – An under-reported entity
Authors: Usmani Eiman , Shapira Yinon , Selva Dinesh
Published: November 2022

Purpose To determine the etiology of epiphora in a tertiary Australian lacrimal clinic and highlight the high proportion of ‘functional’ cases Methods Single-center retrospective review. Records of adult patients presenting to a tertiary lacrimal clinic from January 2011 to February 2021 with epiphora were reviewed. Patients underwent testing with syringing/probing and lacrimal imaging to reach a diagnosis of functional epiphora. Functional epiphora was diagnosed based on the exclusion of alternate causes of epiphora on clinical examination, patent lacrimal syringing, normal dacryocystography, and delay on dacryoscintigraphy Results 576 symptomatic eyes of 372 adult patients (mean 66.2 ± 15.5years, 63.4% females) with epiphora were evaluated for causes. Post-sac obstruction (stenosis/complete obstruction) and functional epiphora (non-anatomical delay) were the most common causes of presentations to the lacrimal clinic (26% each). Functional epiphora with post-sac delay was substantially more common than functional epiphora with pre-sac delay (89% versus 11%). In 16% of the cases, no cause for the epiphora was found while more than one cause (multifactorial) was present 11% of the time. Conclusion Functional epiphora was found to be as common as a nasolacrimal anatomical obstruction when lacrimal imaging is utilized.
Prevalence and associated factors of alcohol consumption among pregnant women attending antenatal care in a Rural District in Tete, Mozambique
Authors: Xavier Sancho Pedro , José Jorge Manuel , Cote Nelson Domingos , Xavi Ramim , Victor Audêncio
Published: November 2022

Background: Alcohol consumption during pregnancy is a significant public health and pregnancy-related problem, such as spontaneous abortion, stillbirth or low birth weight. According to the WHO, there is no safe amount of alcohol consumption during pregnancy. Studies show high rates of alcohol consumption during pregnancy in sub-Saharan African countries with a prevalence range (2.2-87%). This research aimed to determine the prevalence and associated factors of alcohol consumption among pregnant women attending antenatal care in a rural district of Tete, Mozambique.
Methods: A cross sectional survey was conducted between May and June 2022. The non-probability convenience method was applied for sample selection. Prevalence was determined using a 95% CI. binary logistic Regression was used to determine the factors associated with alcohol consumption. Data were analysed using statistical SPPS v26 and Stata.
Results: The prevalence of alcohol consumption during pregnancy was 85.9% (152/177; 95% CI: 80.7-91.0), which was associated with increasing age (OR= 8.86; 95% CI: 2.646-29.687; p-value = 0.000 and OR= 9.81; 95% CI: 2.262-42.576; p-value = 0.002) respectively. In addition, another associated factor was following some religion (OR= 0.07; 95% CI: 0.020-0.246; p-value = 0.000).
Conclusion: The survey significantly reveals a high prevalence of alcohol consumption among pregnant women attended in a antenatal care in Chitima. Maternal age and religion were the variables that have some significant association with alcohol consumption during pregnancy. Therefore, interventions for behavioural change to reduce alcohol consumption during pregnancy are needed, especially in all age groups.
Clinical Outcomes of Patients with Metastatic Breast Cancer treated with Hypo-Fractionated Liver Radiotherapy
Authors: MUSHONGA Melinda , Helou Joelle , Weiss Jessica , Dawson Laura , Lukovic Jelena , Wong Rebecca , ABDALATY ALI HOSNI , Kim John , Koch Anne C , Lindsay Patricia , Stanescu Teodor , Alrabiah Khalid , Barry Aisling
Published: November 2022

IntroductionGrowing data support the safe and efficacious use of ablative radiotherapy in the setting of liver metastases, with some studies suggesting that patients with metastatic breast cancer (MBCa) do better than patients with metastases from other cancers. This study aims to retrospectively review clinical outcomes of patients with MBCa following liver radiotherapy (RT).Materials and MethodsPatients with MBCa who received liver hypo fractionated ablative RT between 2004 – 2020 were classified according to metastatic classification and treatment intent (i.e., oligo-metastatic (OM) or oligo-progressive (OP)). Demographics, disease characteristics and treatment characteristics were collated. Primary outcome was local control (LC) of treated metastases. Secondary outcomes included overall survival (OS), progression-free survival (PFS), and time to next line systemic therapy (ST), analyzed by univariate (UVA) and multi-variable analysis (MVA).ResultsThirty MBCa patients with 50 liver metastases treated with 5 – 10 fraction ablative intent RT were identified for analysis. Median follow-up was 14.6 months (range 0.9 - 156.2 months). Mean age was 55.6 years (range 32.1 - 79.3 years); 53% were ER+/HER2-ve and 33% HER2+ve. Class of metastatic disease was described as – induced (12 patients, 40%), repeat (15 patients, 50%) and de novo (3 patients, 10%) (1 synchronous, 2 metachronous). Indication of treatment was OP (73%) and OM (27%). Median size of treated liver metastases (LM) was 3.1 cm (range 1cm – 8.8 cm) and the median dose delivered was 40Gy (range 30Gy-60Gy). 1 and 3-year LC rates were 100%. Median OS was 57.7-months with size of treated liver metastases predictive of overall survival (HR 1.35, p=0.023) on UVA. Median time to progression post treatment was 4.8 months (0.8 – 114.7). Patients with induced OMD had a significantly higher rate of progression (HR 4.77, p=0.01) on UVA compared to others, which trended to significance on MVA (HR 3.23, p=0.051).ConclusionHypo-fractionated ablative liver RT in patients with MBCa provides safe, tolerable treatment with excellent LC. Further studies assessing the impact, ideal sequencing, and indications of RT in each metastatic class in MBCa are required.
Resveratrol improves the progression of osteoarthritis by regulating cholesterol metabolism
Authors: Liang ChuanCai , Xing Hengte , Wang ChenYu , Xu XiongFeng , Hao Yarong , Qiu Bo
Published: November 2022

Osteoarthritis (OA) is considered a metabolic disorder.This study investigated the effect of resveratrol (RES) on cholesterol accumulation in osteoarthritic articular cartilage via the SIRT1/FoxO1 pathway. Interleukin (IL)-1β-treated chondrocytes that mimic OA chondrocytes were used in in vitro experiments. The optimal RES concentration was selected based on the results of chondrocyte proliferation in the Cell Counting Kit-8 assay. Western blotting, immunofluorescence, and reverse transcription-quantitative polymerase chain reaction were performed. For the animal experiments, mice were randomly divided into the RES group (n = 15), medial meniscus destabilization group (n = 15), and Sham group (n = 15), and each group received the same dose of RES or saline. Articular cartilage tissue was obtained eight weeks after surgery for relevant histological analysis. Clinical tissue test results suggest that downregulation of the SIRT1/FoxO1 pathway is associated with cholesterol buildup in OA chondrocytes. For the in vitro studies, RES increased SIRT1expression and FoxO1 phosphorylation in IL-1β-treated chondrocytes, promoted the expression of cholesterol efflux factors (LXRα, ABCA1, and ApoA1), and inhibited the expression of cholesterol synthesis-related factors (SREBP-2and HMGCR). This reduced IL-1β-induced chondrocytes cholesterol accumulation. SIRT1 inhibition prevented the RES-mediated reduction in cholesterol buildup. Inhibiting FoxO1but not SIRT1reduced FoxO1phosphorylation and increased cholesterol buildup in cultured chondrocytes. Additionally, in vivo experiments have shown that RES can alleviate cholesterol buildup and pathological changes in OA cartilage. Our findings suggest that RES regulates cholesterol buildup in osteoarthritic articular cartilage via the SIRT1/FoxO1 pathway, thereby improving the progression of OA.
Evaluation Of The Effectiveness Of Intravitreal Anti-VEGF Injection With Intravitreal Dexamethasone Implant In Patients With Treatment-Resistant Diabetic Macular Edema
Authors: Hakan Koc , Atilla Alpay , Hayri Ugurbas Suat
Published: November 2022

Purpose: To assess the effectiveness of monthly anti-VEGF therapy with an intravitreal dexamethasone (DEX) implant in patients with diabetic macular edema (DME) whose macular edema persists despite anti-VEGF therapy.
Materials and methods: This study included 94 eyes of 94 patients whose diabetic macular edema (Central Macular Thickness (CMT) >300 µm) persisted despite previous injections of 3 doses of anti-VEGF. The patients were followed up at the first, second, third, and six month after intravitreal injection. Best corrected visual acuity (BCVA), central macular thickness (CMT) and intraocular pressure (IOP) change parameters were evaluated.
Results: In terms of age, proliferation, and lens status, there was no statistically significant difference between the groups. When CMT, BCVA, and IOP were assessed among the 4 groups at the end of the sixth month, no statistical difference between the groups was found. There was no need for medical intervention despite the statistically significant increase in IOP at the end of the sixth month compared to the third month in the dexamethasone implanted groups. In contrast to the decrease in CMT, which was statistically significant in all 4 groups at the end of the 6th month compared to the 3rd month, the increase in BCVA was not statistically significant in any of the 4 groups at the end of the 6th month.
Conclusion: According to the results of our study, there is no superiority between continuing with existing anti-VEGF or switching to dexamethasone implant after 3 doses of anti-VEGF.
SLAMF8, a potential novel immune checkpoint molecule, is associated with the prognosis of colorectal cancer
Authors: Zhang Yaping , Zhang Qun , Han Xingzhi , Han Lu , Wang Ting , Hu Jing , Li Li , Ding Zhou , Shi Xiao , Qian Xiaoping
Published: November 2022

Recently, immune checkpoint inhibitors (ICIs) represented by programmed cell death 1(PD-1) monoclonal antibody (mAb) have revolutionized the treatment mode of malignant tumors, and have achieved long-lasting antitumor effects in a variety of solid tumors. However, this antitumor effect is limited to a small subset of specific colorectal cancer (CRC). Therefore, screening and identifying new immune checkpoint molecules are key points and hotspots in the research field of anti-tumor immunotherapy. The signaling lymphocytic activation molecule (SLAM) family is mainly expressed by and regulates the functions of immune cells. Recent studies have shown that several SLAM family members are involved in the regulation of the tumor immune microenvironment, which are promising targets for anti-tumor immunotherapy. The signaling lymphocytic activation molecule family member 8 (SLAMF8) (B-lymphocyte activator macrophage expressed/CD353) is a type I cell surface glycoprotein and clusters on chromosome 1q21. Our previous studies have shown that SLAMF8 is a potential marker for predicting the efficacy of anti-PD1 immunotherapy in gastrointestinal tumors. To further illustrate the clinical value of SLAMF8 in CRC, we retrospectively analyzed the relationship between SLAMF8 expression and prognosis of CRC patients (CRCs), the associations of the expression levels of SLAMF8 and SLAM family other members and other classical immune checkpoint molecules, using The Cancer Genome Atlas (TCGA) dataset, RNA sequencing dataset, tissue immunohistochemical staining, and systematic follow-up. In the present study, high SLAMF8 expression is associated with poor OS in CRCs. and the mRNA expression of SLAMF8 was positively correlated with the expression of multiple classical immune checkpoints (PDL1 PDL2, CTLA4, and LILRB4) and other SLAM family members. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested that high SLAMF8 expression CRC tissues were significantly enriched in signaling pathways related to tumor and immune signal regulation
Risk factors associated with complications and 30-day readmission in endoscopic endonasal transsphenoidal surgery: a single-institution retrospective analysis
Authors: Mezzacappa Frank M. , Wang Alan , Opperman Patrick J. , Shearin Alexander E. , Rezaii Elhaum G. , Samson Kaeli , Drincic Andjela , Coughlin Andrew , Barnes Christie , Pate Samuel , Gard Andrew , Aizenberg Michele , Thorell William , Surdell Daniel
Published: November 2022

Purpose: There is a recent trend towards rapid discharge after endoscopic endonasal transsphenoidal surgery (EETS). We aimed to identify factors related to in-hospital complications and 30-day readmissions to help inform postoperative care practices.
Methods: This is a retrospective analysis of patients that underwent EETS for resection of a tumor. Primary outcomes included complications and 30-day readmission.
Results: Transient diabetes insipidus occurred in 37% of patients with a complication. Complication was associated with bedrest, occurring in 15.4% of patients without no bedrest, in 24.5% of patients with bedrest of 2-3 days, and in 54.6% of patients with >3 days of bedrest (p=0.02). The median length of stay was 6 days and 4 days in patients with and without a complication, respectively (p<0.0001). Readmission within 30 days occurred in 9.5% of cases, most commonly due to hyponatremia. 30-day readmission was associated with American Society of Anesthesiologists (ASA) class, where 12.5%, 5.9%, and 37.5% patients with ASA class 2, 3, and 4 were readmitted in 30 days, respectively (p=0.02). A maximum tumor diameter (TDmax) of 20-29 mm was associated with readmission, occurring in 20.9% of those patients (p=0.01). EOR was not associated with postoperative complication or with 30-day readmission.
Conclusion: In-hospital complication was associated with increased duration of postoperative bedrest, although no causative relationship can be established based on this data. Preoperative anticoagulation usage, increasing ASA class, and TDmax 20-29 mm may help predict 30-day readmission after EETS. EOR was not associated with complications or 30-day readmission.
Measurement of amplitude and medium of light waves
Authors: Tian Yunchuan
Published: November 2022

Amplitude and medium are important issues of light waves and have not been discussed in the past.We measured them with three optics experiments.The first experiment shows that the polarization direction of small angle reflected light on metal remains unchanged.Liquid refractive index data prove that the light wave is a transverse wave on a one-dimensional string and the medium of the light wave is present.The second experiment measures the selection effect of the surface electrons on the amplitudeof light.The amplitude of light is obtained from the new refractive index formula.The third experimenton interference shows that solids can reduce the speed of light outside the surface. All three experiments demonstrate that the Substance density distribution of the electron is accurate.
A Low cost and high throughput spectroscopic method for quantification of seed coat colour differences in plain seeded bean (Phaseolus vulgaris L.) germplasm from Western Himalayan Kashmir
Authors: Sofi Parvaze Ahmad , Khalid Ramsha , Shafi Sadiah , Zaffar Aaqif , Zargar Sajad Majeed
Published: November 2022

Seed phenotyping is routinely done using visual assessment that suffers from subjectivity. In the present study we phenotyped 278 Western Himalayan bean accessions using a low cost spectroscopic method based on quantification of seed colour in terms of L*,a*,b* and δ E. There was substantial variation for L*, a*, b* and δ E parameters for all seven colour classes. The mean value for L* was lowest for red (31.31) and highest for white (78.17) and reverse in case of a*. Similarly, mean value for b* was lowest for black (-0.29) and highest for yellow (40.86). In terms of deviations from standard colours depicted by δ E, highest mean value was observed in red colour (6012.16) and lowest was recorded for green (18.36) with a mean of 2525.72 across all colours. The first two principal components accounted for 86.74% of variation. contributed by colour and L* in PC1 and b*, L* and a* in PC2. In the present study, based on the factor loading graph, colour is strongly correlated with L* as is evident from its significant contribution in both PC1 and PC2. The multivariate analysis clearly delineates the diversity panel of 278 genotypes into distinct colour groups as shown by concentration of genotypes of similar colour class into specific regions of four coordinates of biplot based on L*, a* and b* values and their observed relationship with colour scores. The method removes the subjectivity in visual colour specifications, is quantitative and can help in exact quantification of varietal differences.
Dynamic and thermodynamic impact of L94A, W100A, and W100L mutations on the D2 dopamine receptor bound to risperidone
Authors: Bello Martiniano , Azam Faizul
Published: November 2022

DRD2 is an important receptor in the mediation of antipsychotic drugs but also in Parkinson medication, hyperprolactinemia, nausea and vomiting. Recently, crystallographic studies of the DRD2-risperidone complex have provided important information about risperidone recognition in wild-type and different stabilizing DRD2-risperidone residues. Using the crystallographic structure of the DRD2-risperidone complex as a starting point, we undertook molecular dynamics (MD) simulations to investigate the structural and thermodynamic basis of molecular recognition by risperidone at the ligand-binding sites of wild-type and mutant DRD2. A solvated phospholipid bilayer was used to construct DRD2-risperidone complexes, which were then subjected to several microsecond (µs) MD simulations in order to obtain realistic receptor–ligand conformations under the equilibrated simulation time. Risperidone had a higher affinity for wild-type and L94A mutant DRD2 than the W100L and W100A mutants, according to binding free energy calculations using the Molecular Mechanics Generalized-Born Surface Area (MMGBSA) method, explaining the experimental differences in ligand residence times. Principal component analysis revealed important conformational mobility upon molecular recognition of risperidone for the L94A mutant compared to the wild type, indicating an unfavorable entropic component that may contribute to improving risperidone affinity in the L94A DRD2 mutant.
Prediction of watershed processes based on morphometric features using feature selection, SOM, and GMDH algorithms
Authors: Mokarram Marzieh , Pourghasemi Hamid Reza , Tiefenbacher John P.
Published: November 2022

Alluvial fans of 4 watersheds in Iran were extracted semi-automatically using GIS and digital elevation model (DEM) analysis. The relationships between 25 morphometric features of these watersheds, the amounts of erosion, and formation material were investigated using the self-organizing map (SOM) method. A feature-selection algorithm was used to select the most important parameters affecting erosion and formation material. The group method of data handling (GMDH) algorithm was employed to predict erosion and formation material based on morphometrics. The results indicated that the semi-automatic method in GIS was able to detect alluvial fans. The SOM algorithm determined that the morphometric factors affecting the formation material were fan length, minimum height of fan, and minimum fan slope. The main factors affecting the erosion were fan area and minimum fan height. The feature selection algorithm identified minimum fan height, maximum fan height, minimum fan slope, and fan length to be the morphometrics most important for determining formation material, and basin area, fan area, maximum fan height and C irb were the most important characteristics for determining erosion rates. The GMDH algorithm predicted the fan formation materials and rates of erosion with high accuracy (R 2 = 0.94, R 2 = 0.87).
A proposal of a supply risk classification method based on the combination of fuzzy and consensus reaching techniques
Authors: Arantes Rafael Ferro Munhoz , Carpinetti Luiz Cesar Ribeiro
Published: November 2022

One of the challenges of supply chain management is to properly react to supply interruptions due to disruption risks or poor performance. In this context, supply risk assessment and mitigation based on judgments of severity and occurrence is a common approach to establish risk factor mitigation priorities. This is a decision process that entails imprecise judgments by a group of decision makers, which may be better dealt with by applying computing with words combined with soft consensus techniques. Therefore, taking into account limitations of previous studies, this paper proposes a group decision making model to classify supply risk factors using the possibility distribution-based hesitant fuzzy linguistic term set as inputs to a fuzzy rule base classification system using a non-compensatory rule base. Also, the study includes computational modeling and a pilot application of the proposed decision model in a manufacturing company. The results of the pilot application were coherent with the experts´ evaluations. Using hesitant fuzzy linguistic term sets enabled the experts to express their uncertainty about judgments in a better way. Also, the fuzzy rule base classification system is better to classify risk factors than the Mamdani FIS, which is more adequate to simply order risk factors.
Construction of a Clustered Intelligent Piano Performance Multimedia System from Neural Networks to Group Optimization
Authors: Wang Qi
Published: November 2022

Piano plays an irreplaceable role in Western musical instruments. Since the advent and development of piano, it has a history of more than 500 years. In the different stages of its development, the structure of piano has also changed a series. "Smart piano" as a new instrument for piano learning, its broad market development prospects have been valued. It is characterized by the comprehensive application of modern science and technology on the basis of maintaining the musical characteristics of traditional piano, and the transformation and expansion of its product structure and use function. "Smart piano" connects interactive computer with piano and forms human-computer interaction. The computer leads the performer to play, taking the screen as the display window, and displaying the music score or music related content. In the process of practical application, we often encounter some special situations, such as the small scale of data set, the lack of sample data and data instability. In order to achieve satisfactory classification ability, neural network must first learn from the training sample data. For small-scale data sets, there is a lack of samples for neural network learning, so the learning effect can not meet the requirements. Based on the above analysis, this paper constructs an intelligent piano performance system based on neural network and cluster optimization.
Determination of Best Possible Parameter in Soft Set
Authors: Demirtaş Naime , DALKILIÇ ORHAN
Published: November 2022

Decision making problem in an uncertain environment is found prime importance in current periods of time. An innovative methods based on soft set theory with applications in many fields of daily life of uncertain environment have already been developed and proposed. In this paper, We find out the best possible parameter from the given fixed set of parameters in any soft sets over the universe U, which is given for the solution of an uncertainty problem. Moreover, we construct an algorithm, which proceed towards an application for a type of uncertainty problem. The paragon outcome is achieved in a scope of group work to compute the success value of the group. We hope that this research for the selection of best possible parameter of universal set in any soft set will be worthwhile to researchers working on problems having uncertainty in many features for further studies in this field.
Mathematics Subject Classification (2010). 03E75, 90B50, 91B06
Research on Policy Diffusion Mechanism of Government Procurement of Public Services Based on MFCM
Authors: Zhang Yuting , Xu Lan , Lu Zhengnan
Published: November 2022

Research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation. In view of four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy. Research results show that, compared with monolayer Fuzzy Cognitive Map, MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned.
Adaptive Whale Optimization Algorithm with simulated annealing strategy and Its Application in Magnetic Target Location
Authors: Gao Yuanyuan , You Haidong , Xu Jun
Published: November 2022

Aiming at the problem that the detection of underground magnetic targets is greatly affected by the measurement accuracy and the recognition effect is not ideal, this paper proposes a magnetic target positioning method based on an adaptive whale optimization algorithm. As the whale optimization algorithm has problems such as easy to fall into local optima and slow convergence speed, this paper introduces two strategy improvements, simulated annealing (SA) and adaptive weighting (AW). Through 16 standard test functions, the improved whale optimization algorithm in this paper is compared with the standard whale optimization algorithm (WOA), particle swarm optimization algorithm (PSO), and cuckoo algorithm (CS). The results show that the improved whale optimization algorithm proposed in this paper It has higher optimization precision and faster convergence speed. Finally, the optimization algorithm in this paper is applied to the research of magnetic target positioning, and the effectiveness of the algorithm is verified through simulation experiments, and the accuracy of positioning the target is optimized.
A Preference Algorithm Based on Objective Proportion for Evolutionary Multiobjective Optimization
Authors: Zheng Jinhua , Liu Sisi , Zou Juan , Yang Shengxiang , Hu Yaru
Published: November 2022

Traditional multiobjective optimization evolutionary algorithms (MOEAs) with a limited population have difficulty solving multiobjective optimization problems (MOPs), especially when the number of objectives is larger than three. In real-world applications, the decision maker (DM) may only prefer a partial region of the Pareto front (PF), named the region of interest (ROI). With the preference information from the DM, the complexity of solving MOPs can be greatly reduced since only solutions inside the ROI need to remain. This paper develops an approach of establishing preference model through the preference information —— the proportion of each objective. The approach can control the spread of the preferred solutions accommodating the DM's expectation of the extent of the ROI without the size of the ROI. Meanwhile, we incorporate the preference model into decomposition-based evolutionary multiobjective optimization methods, which means it is able to lead the search process toward the ROI. Extensive experiments show that our proposed method has effectiveness and competitiveness for approaching the preferred solutions in the ROI compared with four other preference-based algorithms.
Improved Particle Swarm Optimization on based Quantum Behaved Framework for Big Data Optimization
Authors: Baş Emine
Published: November 2022

In recent years, Big data has become an important issue with the rapid increase of digitalization. The problems that find solutions to the problems of finding and evaluating the features of big data are called optimization problems. In this paper, data sets containing EEG signals have been studied. The core of the problem is to identify true EEG signals and minimize the extra brain activity signals in the captured data, thus providing more reliable interpretation accuracy. In this study, a new algorithm based on swarm intelligence is proposed to solve Big Data optimization problems (BigOpt). An Improved PSO-Q was proposed by updating the random walking phase of the Particle Swarm Optimization on based quantum behaved algorithm (PSO-Q) for BigOpt problems. PSO-Q's local search capability has been improved. The success of PSO-Q and IPSO-Q has been thoroughly tested in various cycles (maximum iterations) (300, 400, 500, and 1000) and population sizes (10, 25, and 50) on six data sets. PSO-Q and IPSO-Q results were statistically evaluated with the Wilcoxon Signed-Rank Test. PSO-Q and IPSO-Q have been compared with newly developed swarm-based algorithms (BA, TSA, Jaya, AOA, etc.) in the literature in recent years. The success of IPSO-Q has been shown by evaluating the results obtained. The results showed that IPSO-Q can be used as an alternative algorithm in BigOpt problems.
SMART CONTRACT IN BANKING FOR UKRAINE’S ECONOMY DIGITALIZATION
Authors: Yatsenko V. , Kovalov B. , Kubatko O. , Kharchenko M. , Mazin Yu. , Piven V.
Published: November 2022

Smart contracts are one of the digital technologies that have the potential to significantly alter the way market participants interact. It is emphasized in the research that a smart contract is a specialized computer protocol that allows negotiating parties to exchange assets between themselves: stocks, money, or property without involving a third party as an intermediary. It should be noted that smart contracts also have a wide area for use not only in the financial sector, but also in other sectors of the economy, and the global trend towards digitalization is one of the fundamental drivers of the development of this tool. The most recognizable technology for the operation of smart contracts today is blockchain. It is mentioned that blockchain guarantees the reliability and security of the concluded contracts in terms of their confidentiality, immutability, and permanence. Four basic stages of a blockchain-based smart contract were revealed. It is stated in the article that one of the most promising applications for smart contracts is the automation of the provision of banking services, such as supply chain financing, mortgage lending and small business lending. The automatic implementation of the full lending process, from application to credit risk assessment, mortgage renewals, title transfer, and mortgage servicing and securitization, can be facilitated by sharing borrower information and digital versions of multiple registries and title documents.It is emphasized that smart contracts have a number of advantages over traditional paper-based contracts. It's important to remember that no matter how advanced technology gets, there's always the risk of IT-system vulnerabilities. The future of smart contracts in banking was forecasted. Many banking processes and legal agreements will be substituted by blockchain-based finance solutions in the future; however the shift will be slow. Incumbent banking institutions are unlikely to completely relinquish control of their databases from unknown third parties. Most likely, groups of banking institutions will use authorized blockchains, and customers will only interact with trusted nodes, and not directly with the ledger.
MODELING THE INFLUENCE SHADOW ECONOMY ON THE MACROECONOMIC INDICATORS UKRAINE
Authors: Kashcha M. , Revenko A.
Published: November 2022

The presented work summarizes the arguments and counter-arguments within the scientific discussion on the construction of models of the impact of the shadow economy on the macroeconomic indicators of the country. The level of the shadow economy has a negative impact on Ukraine's macroeconomic indicators. The shadow economy is a covert and / or non-covert economic activity whose purpose is to intentionally or forcibly generate excess profits due to uncontrolled socio-economic relations. The main purpose of the study is to identify the impact of the shadow economy on the macroeconomic indicators of the country. The systematization of literature sources and approaches to solving the problem of finding a connection between the level of the shadow economy and macroeconomic indicators has shown that this problem is quite relevant among scientists around the world. The research was carried out in the following logical sequence: 1) acquaintance with the basic concepts of research and analysis of literature sources; 2) formation of the input data set for further research; 3) verification of data for anomalies; 4) calculation of the integrated indicator; 5) verification of data on stationarity; 6) check for multicollinearity; 7) correlation-regression analysis. The methodological tools of the conducted research were the methods of correlation-regression analysis, the application of the Irwin criterion to detect abnormal levels, the Foster-Student method to investigate the stationarity of time series, and the Ferrar-Glober algorithm to detect multicollinearity in the input array. The study period is 2010-2021. Ukraine was chosen as the object of research. The scientific work presents the results of an empirical analysis of models of the impact of macroeconomic indicators on the level of the shadow economy of Ukraine, which showed that this impact exists and is quite strong. Based on the results of the research, conclusions were formulated about the strong influence of macroeconomic indicators on the level of the shadow economy of Ukraine, it was theoretically proven that the level of the shadow economy of Ukraine is more than 90% described by the selected set of macroeconomic indicators.
ANALYSIS OF MATHEMATICAL MODELS FOR COUNTERING CYBER FRAUD IN BANKS
Authors: Kuzmenko O. , Yarovenko H. , Skrynka L.
Published: November 2022

The article is devoted to the current topic of analysis of mathematical models for countering cyber fraud in banks. This problem is due to the security risks growth in the banking system, which are formed by fraudsters' cyberattacks and cybercrimes implementation. Therefore, the priority task for cyberbanking security is the application of modern mathematical methods to analyse the sources of cyber attacks, identify threats and losses in the banking services market, identify cyber-attacks and assess the scenario of potential cyber risk, etc. The article analyses the most widespread types of cyber fraud: social engineering, phishing, stalking, farming, DoS attacks, online fraud, potentially unwanted programs, etc. The study also considered a model of cognitive computing and detection of suspicious transactions in banking cyber-physical systems based on quantum computing in BCPS for the post-quantum era. The advantages, disadvantages and results of the model are defined. Predictive modelling is proposed to detect fraud in real-time by analysing incoming bank transactions with payment cards. Within the framework of this method, such models are used for the classification of fraud detection as logistic regression, a decision tree, and a narrower technique - a random forest decision tree. The study also considered using the harmonic search algorithm in neural networks to improve fraud detection in the banking system. It is found that although this model has the advantage of learning ability based on past behaviour, there are difficulties in the long-term processing of many neural networks. The stages of model implementation are also given. In addition, the modelling of credit card fraud detection is based on using two types of models: supervised and unsupervised. Supervised models include logistic regression, K-nearest neighbours, and extreme gradient boosting. The one-class support vector model, restricted Boltzmann model, and generative-competitive network are considered among uncontrolled generative models.
EDUCATIONAL SERVICES MARKET RESEARCH
Authors: Nekhoroshkova Yu.
Published: November 2022

The problem of the connection between the amount of training of specialists and their employment in the field of economic activity at the current stage of economic development is becoming quite necessary for research. The education system must adjust its activities according to the needs of the labor market, and it, in turn, must provide information for education in a timely manner. This connection is fundamental and will help to ensure the perfect functioning of the markets under study. However, unfortunately, today the connection between the labor market and the market of educational services functions only conditionally.
The main subjects of the educational services market are: applicants, parents, schools, employers, recruitment agencies, state institutions, other universities. Each of these subjects realizes certain economic interests. And only thanks to the functioning of the "win-win" system, maintaining the balance becomes possible.
The researched interrelationships between the main subjects of the market of educational services indicate the imperfect functioning of the system today. By comparing the number of submitted applications for bachelor's degrees by field with the volume of their government orders, it became clear about the existing imbalance in the market. State-priority technical specialties are in minimal demand among applicants, who, instead, choose "fashionable" specialties. In turn, the university focuses on the demand of applicants, and this leads to an increase in the level of unemployment and oversaturation of the labor market with specialists in social sciences and the service sector.
Another problem in maintaining the balance between education and the labor market is the passivity of employers. They do not provide timely information about existing problems and are not involved in forecasting the necessary specialists on the labor market. If, for example, the employer would involve students in solving existing problems, then everyone would be equally "winners". After all, students would have the opportunity to solve practical problems, and the company would receive new innovative solutions from students. By correcting this shortcoming, the functioning of the educational services market would improve significantly.
Features of retrochoir hematomas and their effect on the course of pregnancy
Authors: Koshova Ilona , Lubkovska Oleksandra
Published: November 2022

The aim. Study of the features of retrochoir hematomas (RHG) and their influence on the formation of the placenta, the course of pregnancy, as well as the occurrence of premature birth.

Materials and methods. 2 groups of pregnant women were selected depending on the frequency of RHG formation: 1 group – 60 pregnant women with recurrent RHG, group 2 – 50 pregnant women with RHG, which was detected only in the early stages of pregnancy. extragenital and genital pathology did not differ reliably. All the women studied were anamnesis, examined, and ultrasound and dopplerometry were performed.

Statistical methods included an assessment of statistical significance using Student's t-criterion and criterion X2 and were considered significant at p<0.05.

Results. Supracervical localization of hematomas prevailed in the studied pregnant women, namely: in group 1 – 51.7 % (in 31 pregnant women) and 68 % (in 34 women) in group 2. The same pattern was observed regarding the involution of hematomas.

Changes in the yolk sac were found in both groups with RHG (in 6.7 % of women (i.e., in 4 pregnant women) of group 1 and 4 % (in 2 pregnant women) of group 1.

Mean values of the pulsation index (PI) of blood flow velocity curves in the uterine arteries (UA) and umbilical cord artery (UCA) in pregnant women with RHG were higher than the standard average for gestational age.

In pregnant RHGs, a history of various types of fetal growth retardation (FGR) is detected. The number of early forms of URP was higher in group 1 (16.7 %, i.e. in 10 pregnant women) as opposed to group 2 (2.0 %, i.e. 1 case). The late form was approximately the same amount in both groups. Also, group 1 was characterized by a significantly larger number of FGR of 2-3 centuries.

In addition, in both groups with RHG, such pathological conditions were identified during pregnancy as the threat of premature birth, premature placental maturation, placental hypoplasia, oligohydramnios, and hydramnios.

Conclusions. Pregnant women with recurrent RHG compared to pregnant women with sporadic RHGs have a greater number of complications during pregnancy, including the threat of preterm labour, premature placental maturation, placental hypoplasia, oligohydramnios, hydramnios, FGR, impaired uterine-placental and placental-fetal blood flow.
Dari Pelayanan Kesurupan Menuju Pelayanan yang Holistik
Authors: Lienardy Timotius
Published: November 2022

AbstractNot a few exorcism services carried out by the church did not produce results. Because of that, the question arises, is it still necessary for the church to carry out the ministry of exorcism? In modern times like now, isn’t it enough if a psychiatrist or a doctor only does it? Does Jesus’ exorcism ministry in the Gospel accounts still have any relevance today? This study tries to look at explanations from various disciplines about possessed people. Is it all because of evil spirits, or are there other factors? This study also tries to dig up the method that Jesus usedin casting out demons to see its relevance in today’s church services. This study departs from anxiety as a church servant, but hopefully, the results can also be helpful for the church’s pastoral ministry and other professionals. 

AbstrakTidak sedikit pelayanan pengusiran yang dilakukan gereja tidak membuahkan hasil. Karena itu muncul pertanyaan, masih perlukah gereja melakukan pelayanan pengusiran roh jahat? Di jaman modern seperti sekarang, tidak cukupkah bila hal itu dilakukan oleh ahli jiwa atau dokter saja? Apakah pelayanan pengusiran roh jahat yang dilakukan Yesus dalam cerita Injil masih memiliki relevansi pada masa sekarang? Studi ini mencoba melihat penjelasan-penjelasan dari berbagai disiplin ilmu tentang orang yang kesurupan. Benarkah semua itu karena roh jahat atau ada faktor-faktor lain. Studi ini juga mencoba menggali kembali cara yang Yesus pakai dalam mengusir setan untuk melihat relevansinya pada layanan gereja jaman sekarang. Studi ini berangkat dari keresahan sebagai pelayan gereja namun semoga hasilnya dapat juga bermanfaat bagi pelayanan pastoral gereja dan profesional lainnya.
Measuring efficiency of banks in Saudi Arabia: A data envelopment analysis approach
Authors: Rahman Shaik Abdul
Published: November 2022

The current study investigates the efficiency of banks in Saudi Arabia in terms of technical change and change in total productivity. The study considers ten banks listed on Tadawul as a sample from 2016 to 2021. The Malmquist Data Envelopment Analysis (Malmquist DEA) model is employed to measure banks’ efficiency. Customer deposits and balances with other banks and financial institutions are inputs, while the operating profit and net income are outputs to measure efficiency. The results of efficiency report that most of the Saudi Arabian banks are considerably efficient, while some are marginally efficient. The technical change report results show that Saudi Arabia’s banks are enthusiastic about adopting new technologies that lead to their growth. Further, the results of the change in total productivity show great dynamism among the Saudi Arabian banks to become more productive, which ultimately leads to a more remarkable performance. The study results demonstrate the good performance of Saudi Arabian banks; however, very few banks are marginally efficient in terms of efficiency change. Therefore, the study supports the established hypothesis that there is a significant change in the technical efficiency and total productivity of Saudi Arabian banks. AcknowledgmentThe author(s) acknowledge that the Deanship of Scientific Research supports the current project at Prince Sattam Bin Abdulaziz University under research project number 2022/02/20810.
A 4-Term Exponential-Quadratic Approximation for Gaussian Q or Error Functions Accurate to $1.65\times 10^{-4}$
Authors: Pulford Graham
Published: November 2022

Integrals on [0, ∞) where the integrand is of the form Qn(a√x) p(x), where Q is the Gaussian Q function, p(·) a Gamma PDF, n a positive integer and a > 0; or of the form erfn(ax + b) xr exp(-c2x2 + 2dx), where erf(x) is the error function, with integers r ≥ 0, n > 0, arise in performance modelling of communication and machine learning systems. Such integrals cannot be evaluated analytically in general, but they are reducible to a set of key integrals whose integrand is erfn(ax + b) N(x; m, s) where N() is a Gaussian PDF with mean m and variance s. Seeking an efficient and accurate evaluation method, we develop a new 4-term exponential quadratic approximator (EQA) for the error function that includes both linear and quadratic terms in its exponents. The EQA minimises a sum-of-squares cost function with two “spline-type” constraints, i.e., constraints on the function value and its first derivative. This constrained optimisation problem is reduced to an unconstrained one by inverting a 4-D linear system, then solved by gradient descent. The resulting approximator has a maximum absolute error of 1.65 × 10-4 on the real line, and outperforms many other exponential sum approximators for erf(x) on x ∈ [0, 1.5] and for Q(x) on x ∈ [0, 2]. Moreover, due to its functional form, the EQA leads to an analytical formula for the set of key integrals, which, in the n = 1 case, is accurate to 3 to 4 significant figures while being orders of magnitude more efficient than Monte Carlo integration. The EQA can equally be used to obtain closed forms for the average symbol error probability of various modulation schemes on Rayleigh fading channels.