Normal Criteria Research Articles

Relationship Marketing and Customer Loyalty among Deposit-Taking SACCOS in Western Kenya

Deposit-taking Savings and Credit Cooperative Societies (SACCOS) in Kenya have faced significant challenges due to intense competition and declining customer numbers, which underscores the need for further investigation into relationship marketing strategies. A key research gap is the role of digital platforms in moderating the effectiveness of these strategies and their impact on customer loyalty. This study aimed to evaluate how digital platforms influence the relationship between relationship marketing (RM) and customer loyalty among SACCOs in Western Kenya. Using Relationship Commitment, Social Exchange, and Commitment Trust theories, the research focused on 23 SACCOs with 37,137 customers and surveyed 396 respondents, including prior pilot study. Descriptive and correlational research designs were used, with data collected via self-administered questionnaires and systematic sampling. Analysis with SPSS assessed validity and reliability, employing descriptive statistics and inferential methods such as Pearson’s Correlation, Simple Linear Regression, and Hierarchical Regression Analysis. Assumption tests confirmed that the research data met normality, linearity, homoscedasticity, and multicollinearity criteria, with a response rate of 87.63% and significant correlations (p<0.05) among variables. Digital Platforms were found to contribute significant moderating role on the link between Relationship Management and Customer Loyalty (p<0.05), emphasizing features like interactivity, personalization, and trustworthiness. The results suggest that in order to enhance customer experience, SACCOs should allocate resources towards the development of user-friendly digital platforms, utilize data analytics in targeted marketing efforts, so as to enhance engagement with the community via online channels. Moreover, it is crucial for SACCOs to prioritize personalized service, establish trust, and strive for continuous improvement, while taking into account regulatory revisions, in order to maximize the effectiveness of digital platforms within the financial sector.

Pain neuroscience education and therapeutic exercise for the treatment of sequelae in breast cancer survivors living with chronic pain: A pilot study

BackgroundBreast cancer represents the most common type of malignant neoplasm worldwide. Advances in diagnosis and treatment have increased the life expectancy of patients. However, the sequelae associated with the treatment of the disease such as chronic pain, kinesiophobia and loss of physical function in breast cancer survivors (BCS) are a long-term health problem. Therapeutic strategies are required for the treatment of chronic sequelae in this population. ObjectivesTo evaluate the effectiveness of a pain neuroscience education (PNE) and therapeutic exercise (TE) for the treatment of chronic sequelae in BCS. MethodsQuasi-experimental repeated measures study. The intervention lasted 9 weeks, with 3 educational and 24 exercise sessions. Pain frequency and intensity (VAS scale), neuropathic pain (DN4), kinesiophobia level (TSK-11V), central sensitization (CSI-Sp), functionality of the affected arm (ULFI-Sp) and active joint range (ROM) with goniometry were measured at baseline, 3rd, 6th and 9th week. Statistical analysis included Friedman's test and ANOVA according to normality criteria. ResultsA total sample of 26 BCS participate in the study. Significant statistical changes were found from the 3rd week of treatment in the frequency and intensity of pain, kinesiophobia and neuropathic pain (p < 0.05). All variables had significant changes at the 9th week (p = 0.001). ConclusionThe results of the present investigation suggest that the combination of PNE and TE are effective in treating sequelae at short term in BCS with chronic pain.

Detection of uniformity and spatial correlation of subgrade compaction quality based on intelligent compaction technology

Intelligent compaction uniformity and spatial correlation detection of subgrade is an important part of intelligent compaction technology. In this paper, a subgrade compaction uniformity detection method is established based on the univariate statistical normal distribution 3σ criterion, and further a subgrade compaction quality spatial correlation detection method is established by the multivariate statistical spatial semi-variance function, and finally the established subgrade compaction uniformity and spatial correlation methods are verified by field tests. The subgrade compaction uniformity and spatial correlation are detected based on field tests. The results obtained in this paper show that the 3σ criterion based on normal distribution can be used for the detection of intelligent compaction uniformity of subgrade, and the field test results are verified by this method, and all the intelligent compaction uniformity of subgrade meets the requirements; considering the construction efficiency and the influence between rollers, it is recommended that the rolling speed should be in the interval range of 2–3 m/s, and the construction spacing of rollers is maintained at 10 m and above.

Barriers to Early Progress in Adult Cochlear Implant Outcomes.

Adult cochlear implant (CI) recipients obtain varying levels of speech perception from their device. Adult CI users adapt quickly to their CI if they have no peripheral "bottom-up" or neurocognitive "top-down" limiting factors. Our objective here was to understand the influence of limiting factors on the progression of sentence understanding in quiet and in noise, initially and over time. We hypothesized that the presence of limiting factors, detected using a short test battery, would predictably influence sentence recognition with practical consequences. We aimed to validate the test battery by comparing the presence of limiting factors and the success criteria of >90% sentence understanding in quiet 1 month after activation. The study was a single-clinic, cross-sectional, retrospective design incorporating 32 adult unilateral Nucleus CI users aged 27 to 90 years (mean = 70, SD = 13.5). Postoperative outcome was assessed through sentence recognition scores in quiet and in varying signal to noise ratios at 1 day, 1 to 2 months, and up to 2 years. Our clinic's standard test battery comprises physiological and neurocognitive measures. Physiological measures included electrically evoked compound action potentials for recovery function, spread of excitation, and polarity effect. To evaluate general cognitive function, inhibition, and phonological awareness, the Montreal Cognitive Assessment screening test, the Stroop Color-Word Test, and tests 3 and 4 of the French Assessment of Reading Skills in Adults over 16 years of age, respectively were performed. Physiological scores were considered abnormal, and therefore limiting, when total neural recovery periods and polarity effects, for both apical and basal electrode positions, were >1.65 SDs from the population mean. A spread of excitation of >6 electrode units was also considered limiting. For the neurocognitive tests, scores poorer than 1.65 SDs from published normal population means were considered limiting. At 1 month, 13 out of 32 CI users scored ≥90% sentence recognition in quiet with no significant dependence on age. Subjects with no limiting peripheral or neurocognitive factors were 8.5 times more likely to achieve ≥90% score in quiet at 1 month after CI switch-on (p = 0.010). In our sample, we detected 4 out of 32 cases with peripheral limiting factors that related to neural health or poor electrode-neural interface at both apical and basal positions. In contrast, neurocognitive limiting factors were identified in 14 out of 32 subjects. Early sentence recognition scores were predictive of long-term sentence recognition thresholds in noise such that limiting factors appeared to be of continuous influence. Both peripheral and neurocognitive processing factors affect early sentence recognition after CI activation. Peripheral limiting factors may have been detected less often than neurocognitive limiting factors because they were defined using sample-based criteria versus normal population-based criteria. Early performance was generally predictive of long-term performance. Understanding the measurable covariables that limit CI performance may inform follow-up and improve counseling. A score of ≥90% for sentence recognition in quiet at 1 month may be used to define successful progress; whereas, lower scores indicate the need for diagnostic testing and ongoing rehabilitation. Our findings suggest that sentence test scores as early as 1 day after activation can provide vital information for the new CI user and indicate the need for rehabilitation follow-up.

Outcome of intraoperative brachytherapy as asalvage treatment for locally recurrent rectal cancer.

Locally advanced recurrent rectal cancer (RRC) requires amultimodal approach. Intraoperative high-dose-rate brachytherapy (HDR-BT) may reduce the risk of local recurrence. However, the optimal therapeutic regimen remains unclear. The aim of this retrospective monocentric study was to evaluate the toxicity of HDR-BT after resection of RRC. Between 2018 and 2022, 17patients with RRC received resection and HDR-BT. HDR-BT was delivered alone or as an anticipated boost with amedian dose of 13 Gy (range 10-13 Gy) using an 192iridium microSelectron HDR remote afterloader (Elekta AB, Stockholm, Sweden). All participants were followed for assessment of acute and late adverse events using the Common Terminology Criteria for Adverse Events version5.0 and the modified Late Effects in Normal Tissues criteria (subjective, objective, management, and analytic; LENT-SOMA) at 3‑ to 6‑month intervals. Atotal of 17patients were treated by HDR-BT with median dose of 13 Gy (range 10-13 Gy). Most patients (47%) had an RRC tumor stage of cT3‑4 N0. At the time of RRC diagnosis, 7patients (41.2%) had visceral metastases (hepatic, pulmonary, or peritoneal) in the sense of oligometastatic disease. The median interval between primary tumor resection and diagnosis of RRC was 17months (range 1-65months). In addition to HDR-BT, 2patients received long-course chemoradiotherapy (CRT; up to 50.4 Gy in 1.8-Gy fractions) and 2patients received short-course CRT up to 36 Gy in 2‑Gy fractions. For concomitant CRT, all patients received 5‑fluorouracil (5-FU) or capecitabine. Median follow-up was 13months (range 1-54). The most common acute grade1-2 toxicities were pain in 7patients (41.2%), wound healing disorder in 3patients (17.6%), and lymphedema in 2patients (11.8%). Chronic toxicities were similar: grade1-2 pain in 7patients (41.2%), wound healing disorder in 3patients (17.6%), and incontinence in 2patients (11.8%). No patient experienced agrade ≥3 event. Reirradiation using HDR-BT is well tolerated with low toxicity. An individualized multimodality approach using HDR-BT in the oligometastatic setting should be evaluated in prospective multi-institutional studies.

Bicomplex analogues of some normality criteria

Bicomplex analogues of some normality criteria

FORECASTING INFLATION IN INDONESIA USING THE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE METHOD

Indonesia faces significant economic challenges, particularly inflation, which affects the economic, social, and cultural sectors. High inflation can exacerbate poverty, alter consumption patterns, and contribute to social injustice, whereas low inflation can enhance national income and stimulate economic activities. Given its fluctuating nature, inflation in Indonesia requires accurate forecasting to inform policy-making and economic decisions. This study aims to forecast inflation in Indonesia for the next eight months using the Autoregressive Integrated Moving Average (ARIMA) method. Monthly inflation data from January 2020 to April 2024 obtained from Bank Indonesia were analyzed. The ARIMA model, suitable for short-term forecasting, was selected due to its ability to handle data trends, non-stationarity, and noise filtering. The Augmented Dickey-Fuller (ADF) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests to ensure stationarity. Initial ADF tests showed the presence of a unit root in the original data and the first differencing data, but data became stationary after the second differencing. The KPSS test confirmed a unit root in the original data and trend stationarity after the second and third differencing. Ordinary Least Squares (OLS) regression on the original data revealed a significant time trend, indicating deterministic trends. The optimal model identified was ARIMA(0,2,1) with AIC=51.81, as it met the criteria for normality, independence, and zero mean of residuals. This model effectively forecasts inflation from May to December 2024, which showed an increase with inflation values ​​of 3.02, 3.05, 3.07, 3.10, 3.12, 3.14, 3.17, and 3.19.

Effect of normalization techniques and criteria weight calculation methodologies on nontraditional machining process rank for m-polar fuzzy set ELECTRE-I algorithm

Effect of normalization techniques and criteria weight calculation methodologies on nontraditional machining process rank for m-polar fuzzy set ELECTRE-I algorithm

How well do ridge parameter estimators proposed so far perform in terms of normality, outlier detection, and MSE criteria?

Ridge regression is a commonly used prediction method in cases of multicollinearity among regressors in multiple linear regression model. In this study, the performances of 366 different estimators proposed in the literature for ridge parameter estimation were evaluated. The criteria of estimators’ ratio of generating outliers and the proportion of normality besides the Mean Square Error (MSE) criterion were used for diagnosing ridge parameter estimators. Besides, the effect of outliers and deviations from normality generated by the ridge parameter estimators on the MSE was revealed by Spearman’s Rho correlation analysis. To do so, a Monte Carlo simulation was designed for 2420 different cases, considering the simulation parameters comprehensively in terms of the number of regressors, sample size, collinearity level and error variances. The results revealed that some ridge parameter estimators recommended according to MSE criterion, do not perform well in terms of outlier generation and normality criteria. Significant inter-linear correlations were also found among the ridge parameter estimators’ MSE performance criterion, ratios of outlier generation criterion and normality criterion. Thus, it is suggested that an effective ridge parameter estimator should perform well in terms of outlier generation and normality criteria, as well as having small MSE value.

Linked Data Generation Methodology and the Geospatial Cross-Sectional Buildings Energy Benchmarking Use Case

Cross-sectional energy benchmarking in the building domain has become crucial for policymakers, energy managers and property owners as they can compare an immovable property performance against its closest peers. For this, Key Performance Indicators (KPIs) are formulated, often relying on multiple and heterogeneous data sources which, combined, can be used to set benchmarks following normalization criteria. Geographically delimited parameters are important among these criteria because they enclose entities sharing key common characteristics the geometrical boundaries represent. Linking georeferenced heterogeneous data is not trivial, for it requires geographical aggregation, which is often taken for granted or hidden within a pre-processing activity in most energy benchmarking studies. In this article, a novel approach for Linked Data (LD) generation is presented as a methodological solution for data integration together with its application in the energy benchmarking use case. The methodology consists of eight phases that follow the best principles and recommend standards including the well-known GeoSPARQL Open Geospatial Consortium (OGC) for leveraging the geographical aggregation. Its feasibility is demonstrated by the integrated exploitation of INSPIRE-formatted cadastral data and the Buildings Performance Certifications (BPCs) available for the Catalonia region in Spain. The outcomes of this research support the adoption of the proposed methodology and provide the means for generating cross-sectional building energy benchmarking histograms from any-scale geographical aggregations on the fly.

An entire function and its k-th derivatives satisfying normality criterion sharing a set of four elements

An entire function and its k-th derivatives satisfying normality criterion sharing a set of four elements

Changes in microstructure, magnetocaloric effect and critical behavior of La0.8Sr0.2MnO3 manganites by K/Co doping

We prepared La0.8-xKxSr0.2Mn0.95Co0.05O3 (0 ⩽ x ⩽ 0.1) (LKSMCO) through the modified sol-gel method (S-G) and its structure. Then, the magnetic, magnetocaloric, and critical behavior were analyzed. LKSMCO was confirmed to be the rhombohedral structure within the R-3c space group (No.167) using transmission electron microscopy and X-ray diffraction. For validating the chemical composition of LKSMCO, X-ray photoelectron spectroscopy and EDS were applied, showing that K+ was successfully doped. Phase transition of LKSMCO from paramagnetic to ferromagnetic phase near Curie temperature (Tc) was confirmed with a Magnetic Property Measurement System (MPMS). Using normalization and Banerjee's criterion, LKSMCO was demonstrated to be the second-order magnetic phase transition (SOMPT). As shown from the applied magnetic field, the maximal magnetic entropy (−ΔSMmax) of LKSMCO near Tc was 3.87 J/(kg K) (x= 0.00), 4.28 J/(kg K) (x= 0.05) and 4.44 J/(kg K) (x= 0.10). We employed the Kouvel-Fisher approach (KF) and modified Arrott plots to confirm the values of γ, δ, and β. This indicates that critical exponents of LKSMCO were consistent with the Mean-filed model.

FUZZY APPLICATION (MAMDANI METHOD) IN DECISION-MAKING ON LED TV SELECTION

Science is now developing very quickly. Information technology has been used in various places. Using computers in business, government, and personal activities shows how important science and technology are in helping human activities. One method used to solve various problems is fuzzy logic. Several types of Fuzzy are classified as Fuzzy Inference Systems (FIS), namely Tsukamoto, Mamdani, and Sugeno. The application of vague logic in making decisions about choosing an LED TV is to make it easier to select electronic media. This research aims to help people who need clarification on the many LED TV choices currently available. So, we need a decision-making method to help people choose an LED TV that suits their needs and budget. One of the methods used in this research is the Mamdani method. There were 50 LED TV brands in this research, and the criteria used in selecting LED TVs were based on size, resolution, and price. An LED TV that meets the medium size, high resolution, and normal price criteria will be purchased. The LED TV data that meets the medium size, high resolution, and normal price criteria is the Samsung UA43AU7000KXXD brand LED TV. However, the actual decision remains based on the buyer's decision.

Development and Validation of a Scoring System to Predict Response to Obeticholic Acid in Primary Biliary Cholangitis

Background & AimsObeticholic acid (OCA) is the only licensed second-line therapy for primary biliary cholangitis (PBC). With novel therapeutics in advanced development, clinical tools are needed to tailor the treatment algorithm. We aimed to derive and externally validate the OCA response score (ORS) for predicting the response probability of individuals with PBC to OCA. MethodsWe used data from the Italian RECAPITULATE (N 441) and the IBER-PBC (N 244) OCA real-world prospective cohorts to derive/validate a score including widely available variables obtained either pre-treatment (ORS), or also after 6 months of treatment (ORS+). Multivariable Cox’s regressions with backward selection were applied to obtain parsimonious predictive models. The predicted outcomes were biochemical response according to POISE (ALP/ULN<1.67 with a reduction of at least 15%, and normal bilirubin), or ALP/ULN<1.67, or NORMAL RANGE criteria (NR: normal ALP, ALT and bilirubin) up to 24 months. ResultsDepending on the response criteria, ORS included age, pruritus, cirrhosis, ALP/ULN, ALT/ULN, GGT/ULN and bilirubin. ORS+ also included ALP/ULN and bilirubin after 6 months of OCA therapy. Internally validated c-statistics for ORS were of 0.75, 0.78 and 0.72 for POISE, ALP/ULN<1.67 and NR response, which raised to 0.83, 0.88, 0.81 with ORS+, respectively. The respective performances in validation were of 0.70, 0.72 and 0.71 for ORS, and 0.80, 0.84, 0.78 for ORS+. Results were consistent across groups with mild/severe disease. ConclusionsWe developed and externally validated a scoring system capable to predict OCA response according to different criteria. This tool will enhance a stratified second-line therapy model to streamline standard care and trial delivery in PBC.

Classification of Embryos Using Microscopic Pictures

Abstract: This study focuses on classifying the microscopic images of embryo by using DL neural networks including Mobilenet that captures the crucial patterns in the images and classify whether the Embryo is Good or Bad for In-Vitro Fertilization (IVF). The paper introduces an enhanced DL-based approach for recognizing patterns within images and adjusting each input image to meet specified normalization criteria, as normalization plays a crucial role in ensuring consistency, comparability across data sets. The dataset consists of 1079 embryos from which 239 microscopy images were utilized to validate the proposed method.

Normal Order Non-Classical Criteria In Non-Degenerate Four-Wave Mixing Process: Quantum Entanglement, Squeezing And Anti-Bunching

Normal Order Non-Classical Criteria In Non-Degenerate Four-Wave Mixing Process: Quantum Entanglement, Squeezing And Anti-Bunching

The Distribution of Risk Across Healthcare Providers and Reducing Misclassification

Four linear multilevel mixed-risk models were compared using model assumption tests and predictions. Models varied by the number of random intercepts from 1 to 4, producing 2-level through 5-level models of the same measure, operative time. Normality of the dependent variable and residuals, variance homoscedasticity, level-1, and level-2 exogeneity were tested using the robust test of the level-1 residuals variance by surgeon, estimates of density, skew, and the Hausman test. Measure (operative time by hospital and surgeon) aberrancy and risk classification were evaluated using traditional methods and used to assess distribution measures. The dependent variable and the level-1 residuals required transformation for linearity and variance stabilization, respectively. Normality criteria were met for both level-1 and level-2 residuals and standardized residuals. The likelihood ratio comparing the four models was significantly larger for the 5-level (1016.1; P&amp;lt;0.00005) model than the likelihood ratio for the four-level and other models. Shrinkage was greatest for the 2-level model (0.039; P&amp;lt;0.00005) and least for the 5-level model (0.028; P&amp;lt;0.00005). Level-1 variance homoscedasticity was confirmed by the robust variance test across all models (P&amp;gt;F=1). Aberrant value detection did not require the exclusion of any observations, while prediction intervals revealed low or high risk for 54.2% of surgeons for the 2-level model and 8.6% for the 5-level model. The traditional (c2 = -11.01; P=1) and instrumental variable (c2 = 21.06; P=1) Hausman tests show that the null hypothesis cannot be rejected for level-1 or level-2 exogeneity. Once level-1 and level-2 exogeneity was confirmed, and since deconfounding was a model consideration, causal inferential capacity was assumed. The likelihood ratio, residual variance, shrinkage, and predictions show that the 5-level model is preferred to the other models.

The status and influencing factors of lung ventilation function in employees exposed to dust in enterprises of the XPCC, China.

Occupational health is closely related to harmful factors in the workplace. Dust is the primary contributing factor causing impaired lung ventilation function among employees with dust exposure, and their lung ventilation function may also be influenced by other factors. We aimed at assessing the status and influencing factors of lung ventilation function among employees exposed to dust in the enterprises of the Eighth Division located in the Xinjiang Production and Construction Corps (XPCC), China. Employees exposed to dust in enterprises of the Eighth Division located in the XPCC in 2023 were selected as the subjects of this cross-sectional study. Their lung ventilation function indicators were extracted from health examination records, and an on-site electronic questionnaire survey was conducted among them. Binary logistic regression analyses were conducted to evaluate the factors influencing lung ventilation function. According to the fixed value criteria, the abnormal rates of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and FEV1/FVC were 31.6, 1.4, and 0.4%, respectively. The lower limit of normal (LLN) criteria could overestimate the rate of abnormal lung ventilation function. Several factors were related to impaired lung ventilation function, including gender, age, education level, marital status, body mass index (BMI), smoking status, physical activity, the type of dust, industry, enterprise scale, occupation, length of service, working shift, monthly income, and respiratory protection. A relatively low abnormal rate of lung ventilation function was observed among employees exposed to dust in enterprises of the Eighth Division, XPCC, and their lung ventilation function was associated with various factors. Effective measures should be taken urgently to reduce the effects of adverse factors on lung ventilation function, thereby further protecting the health of the occupational population.

Resilience Scale (RS-14): Psychometric Study in a Population of Young People from Lima and Callao

The Resilience Scale (RS-14) instrument assesses an individual's level of resilience when facing adverse life situations. This study aimed to examine the psychometric properties of the RS-14 in a sample of young adults from Lima and Callao, aged 18 to 29 years old. Initially, a statistical analysis of the items was conducted, revealing satisfactory normality criteria and discriminative capacity. Subsequently, validity evidence was obtained through Confirmatory Factor Analysis (CFA), demonstrating a good fit (χ²/df = 1.47, CFI = .94, TLI = .92, SRMR = .04, and RMSEA = .04). Finally, reliability was assessed using both Alpha and Omega coefficients, yielding values of α = .91 and ω = .92, respectively, considered acceptable. In conclusion, the RS-14 is considered a valid and reliable scale for future research endeavors in this domain.

Normality Criterion Concerning Total Derivatives of Holomorphic Functions in $$ {\mathbb {C}}^n $$

Normality Criterion Concerning Total Derivatives of Holomorphic Functions in $$ {\mathbb {C}}^n $$