Simple Linear Regression Model Research Articles

Influence of Economic Dimension Strategy on Organizational Image of Kisumu Heart Hospital

Corporate Social responsibility (CSR) is becoming an increasingly significant component of many firms’ strategic planning decisions. Statistics shows that more than 80% of health sector organizations in Kenya don’t seem to realize the importance of Corporate Social Responsibility. Among the approximately 20% that do understand the significance of corporate social responsibility, only 2% strive to implement it owing to a number of reasons. This has left a negative perception and bad image to the organizational stakeholders involving the patients, shareholders and the staff, sometimes leading to low profitability. This is evident despite the fact that success of a company is measured by its contribution to society. Most studies have shown both positive and negative relationship or failed to clarify impacts of corporate social responsibility of organizational corporate social responsibility on its image. None of the studies has also specifically shown how adoption of economic, environmental and social dimension strategies have impacted on organizational image of Kisumu heart Hospital. The main objective of this study was therefore to investigate the influence of economic dimension strategy on organizational image of Kisumu heart hospital. Study was anchored stakeholder theory. The study adopted correlational research design. The population of the study comprised of a total of 400 outpatients, inpatient and employees. The study adopted stratified random sampling and the sample size was 196 respondents. Primary data was used which was collected through questionnaire. Data was analysed using both descriptive and correlation statistics specifically Pearson Product Moment Correlation and Simple linear regression Model. The findings revealed that Economic dimension strategy has a positive and significant effect on corporate image (B=.132, p<.05. It was concluded that corporate social responsibility has a positive and significant effect on corporate image of Kisumu heart hospital. The study however recommended improving both economic dimension strategy The study may also inform the stakeholders in the health sector on the importance of CSR on the organizational image and growth.

Towards Contrastive and Data Driven Cloud Data Center Energy Prediction using Regression Analysis

Abstract: Data centers are the backbone of todays Internet and cloud computing systems. Due to the increasing demand for electrical energy by data centers, it is necessary to account for the vast amount of energy they consume. Energy modeling and prediction of data centers plays a pivotal role in this context. In this study, we address the challenge of predicting energy consumption in cloud data centers, crucial for managing their significant electricity demand. Despite numerous existing methods, there remains a lack of robust methodologies. To fill this gap, we propose a novel approach that incorporates aleatoric uncertainty estimation. Our method utilizes regression distributions to model this uncertainty, with parameters derived from regressive techniques. This yields energy consumption predictions as random variables drawn from these distributions. Additionally, we illustrate how these random variables can be aggregated to form probabilistic forecasts for diverse data center portfolios. Our methodology achieves three key advancements: 1) introducing a simple multiple linear regression model for fundamental series; 2) devising a unique method that combines quantile regression and empirical copulas to estimate joint distribution; 3) enhancing prediction accuracy through a weighted correction technique based on constrained quantile regression.

Going a Step Deeper Down the Rabbit Hole: Deep Learning Model to Measure the Size of the Unregistered Economy Activity

AbstractAccurately estimating the size of unregistered economies is crucial for informed policymaking and economic analysis. However, many studies seem to overfit partial data as these use simple linear regression models. Recent studies adopted a more advanced approach, using non-linear models obtained using machine learning techniques. In this study, we take a step forward on the road of data-driven models for the unregistered economy activity’s (UEA) size prediction using a novel deep-learning approach. The proposed two-phase deep learning model combines an AutoEncoder for feature representation and a Long Short-Term Memory (LSTM) for time-series prediction. We show it outperforms traditional linear regression models and current state-of-the-art machine learning-based models, offering a more accurate and reliable estimation. Moreover, we show that the proposed model is better in generalizing UEA’s dynamics across countries and timeframes, providing policymakers with a more profound group to design socio-economic policies to tackle UEA.

Tractable Bayesian Inference For An Unidentified Simple Linear Regression Model

In this article, I propose a tractable approach to Bayesian inference in a simple linear regression model for which the standard exogeneity assumption does not hold. By specifying a beta prior for the squared correlation between an error term and regressor, I demonstrate that the implied prior for a bias parameter is t-distributed. If the posterior distribution for the identified regression coefficient is normal, this implies that the posterior distribution for the unidentified treatment effect is the convolution of a normal distribution and a t-distribution. This result is closely related to the literatures on unidentified regression models, imperfect instrumental variables, and sensitivity analysis.

Impact of Crime and Insecurity on Citizen Trust in Public Institutions: Evidence from Bangladesh

The paper aims to explore how crime and insecurity influence citizen trust in public institutions. The study takes Bangladesh as a case study to analyze individual-level data from 1200 respondents obtained from Wave 7 of the World Values Survey (WVS) conducted following a representative sampling. Employing simple linear and multiple regression models, the results demonstrate that the relationships between citizen trust and the four variables of crime and insecurity are significantly negative. The findings indicate that crime incidence in neighborhoods, victimization, fear of crime, and worrying about life detrimentally affect or erode citizen trust and confidence in public institutions. Therefore, the study concludes that combating crime, protecting public security, and maintaining law and order are crucial to restoring citizen trust in public institutions and improving government performance.

Quantitative identification and sensor sensitivity analysis in detection of odor volatile compounds emitted by scaly grain mites, Suidasia pontifica Oudemans.

In Thailand, the scaly grain mite, Suidasia pontifica Oudemans, impacts the feed industry by emitting a lemongrass-like odor in contaminated feed, reducing its palatability. This study focused on identifying volatile organic compounds (VOCs) associated with this odor in contaminated chicken feeds and ground maize, as well as individual mites using gas chromatography-mass spectrometry (GC-MS). We explored the relationship between VOC concentration and mite population size in chicken feed cultures, aiming to detect minimal mite presence through regression models. Additionally, we tested the sensitivity of nine electronic odor sensors in detecting these VOCs. Our results showed Z-citral and E-citral present in mite-contaminated ground maize, chicken feeds, but absent in uncontaminated samples. Mite populations in chicken feed followed a normal distribution, increasing rapidly, peaking, and then declining, a pattern mirrored in the concentrations of Z-citral and E-citral. Simple linear regression models confirmed a positive correlation between mite density and citral concentrations. Polynomial regression models indicated Z-citral is detectable at mite densities over 67 individuals per gram and E-citral over 3.89 individuals per gram. Odor sensors showed varying readings across different citral concentrations, uncontaminated, and mite-infested chicken feeds. Our study confirms that S. pontifica are responsible for the lemongrass-like odor in infested samples, due to Z-citral and E-citral. The citral concentrations increase with mite population growth and are detectable at low mite densities, suggesting their effectiveness as biomarkers for early mite infestation detection. Additionally, MQ series odor sensors detected these VOCs, indicating their potential for monitoring mite infestations in storage environments. This article is protected by copyright. All rights reserved.

Quality of Life and Its Association With Time in Range Among People With Type 2 Diabetes Mellitus Following Different Dietary Interventions: A Crossover Clinical Trial.

Background Quality of Life (QoL) is an essential consideration in healthcare. Numerous studies have examined QoL in India; however, data on QoL following different dietary interventions are lacking. Similarly, the use of technology such as continuous glucose monitoring (CGM) for diabetes care has independently demonstrated improvements in glycemic control; however, its association with QoL remains limited. Purpose The purpose was to study the role of different dietary interventions on QoL and its association with Time in Range (TIR), Time Above Range (TAR), and Time Below Range (TBR) among the Type 2 Diabetes Mellitus (T2DM) population. Methodology A crossover interventional clinical trial (CTRI/2022/07/044356) was conducted among participants with T2DM of less than 5 years' duration, aged between 25 and 55 years, with an HbA1c level of less than 8%, and who were on Metformin only. Their QoL was assessed after following two diet patterns: the Continuous Calorie Restricted Diet (CCRD) - calorie reduction with small frequent meals, and Time Restricted Intermittent Fasting (TRIF) - calorie reduction with only two meals a day, using the Modified QoL (MDQOL-17) questionnaire. The association between post-dietary interventions QoL and TIR was studied using a 14-day CGM device. Results The overall QoL of 51 participants at the end of the dietary interventions was significantly better compared to their QoL before any dietary intervention (85.6±19.0% and 63.1±13.0%, respectively, p = 0.000). Decreased TIR correlated with increased role limitations due to physical functioning (p = 0.002) and decreased energy levels (p = 0.00). As TBR increased, role limitation due to emotional well-being increased, and energy levels decreased significantly (p = 0.01). As TAR increased, energy levels decreased (p = 0.01). A simple linear regression model was statistically significant for role limitations due to physical functioning (p = 0.003) and energy fatigue (p = 0.000), suggesting that higher TIR is associated with higher scores in these domains. Conclusion Dietary interventions that improve the TIR and reduce the TAR and TBR can enhance the QoL of individuals with T2DM.

The economic burden of hemodialysis and associated factors of among patients in private and public health facilities: a cross-sectional study in Addis Ababa, Ethiopia

IntroductionThe treatment of kidney disease, including hemodialysis, poses challenges in healthcare and finances. Despite limited data on hemodialysis costs and determinants in Ethiopia, existing literature indicates a paucity of evidence regarding the economic burden of hemodialysis. This study aims to evaluate the direct and indirect costs of hemodialysis among end-stage renal disease (ESRD) patients, alongside associated factors, among selected governmental and private institutions in Addis Ababa, Ethiopia.MethodsAn institutional-based cross-sectional study using a simple random sampling technique was conducted from September 10 to November 1, 2021. One hundred twenty-eight patients participated in the study. Data was collected using an interviewer-administered questionnaire. The analysis used proportion and frequency measures of central tendency and linear regression measures. Both simple and multiple linear regression models were used to assess associated factors. The final model used a P value < 0.05 at 95% confidence interval (CI) was used to determine significance.ResultThe mean cost of hemodialysis in a representative sample of selected hospitals in Addis Ababa was 7,739.17 $ ±2,833.51 $, with direct medical cost contributing 72.9% of the total cost. Furthermore, the institution type (private or public) and duration on hemodialysis were associated with an increased cost of hemodialysis.ConclusionOur findings underline the necessity for policymakers, program administrators, and healthcare institution executives to prioritize this group, recognizing the substantial load they bear and extending these services in government facilities to a broader patient population.

Deterioration Models and Service Life Prediction of Vertical Assets of Urban Water Systems

AbstractThis study proposes a methodology for developing deterioration models and predicting the service lives of vertical assets of urban water systems (i.e., water storage tanks and pumping stations) using regression analysis. The main factors contributing to the deterioration of these assets are analyzed. Simple and multiple linear regression models of average and maximum deterioration are calculated for 22 water storage tanks and 17 wastewater pumping stations. Data on a set of four water storage tanks are used to validate the developed deterioration models. Service life prediction is carried out using the developed models and considering two maximum deterioration levels: the maximum recommended and admissible deterioration levels. Two water storage tanks are further studied to illustrate and discuss the effect of maintenance and rehabilitation interventions on asset service life by comparing the asset deterioration before and after the interventions. Results include simple linear regression models of average and maximum deterioration indices as a function of asset age and multiple linear regression models that incorporate other physical, operational and environmental factors. The results show that simple linear regression models of asset deterioration show a better predictive power than multiple regression models. Despite the higher data variability of multiple regression models, these models allow to include the random process of asset deterioration, through the calculation of the standard deviation. This study also shows that periodic interventions are a preferable maintenance and rehabilitation strategy over major sporadic rehabilitation interventions since it allows to maintain assets in good condition and to extend their service life almost indefinitely.

Preoperative Degenerative Changes at the Medial Sesamoid-Metatarsal Joint Is Associated with Postoperative Patient-Reported Outcomes in Hallux Valgus

Introduction/Purpose: While hallux valgus (HV) is understood to be a triplanar deformity of the first metatarsal, less is known about the contribution of the sesamoid-metatarsal joint (SMJ) to pain and function. Osteoarthritis of the SMJ is frequently present in HV feet, with an incidence rate ranging from 32% to 81%. Following surgical correction, approximately 10% of HV patients remain dissatisfied, but factors affecting postoperative outcomes are poorly understood. The primary aim of our study was to describe the relationship between degenerative changes at the SMJ as measured on weightbearing CT (WBCT) scans and 1-year patient-reported outcome scores following a modified Lapidus procedure for correction of HV. We hypothesized that decreased joint space at the SMJ would affect postoperative patient-reported outcomes. Methods: This study included 48 consecutive patients who underwent a modified Lapidus procedure for HV, had preoperative and at least 5-month postoperative WBCT scans, and had preoperative PROMIS scores and at least 1-year postoperative PROMIS Physical Function (PF), Pain Interference, and Pain Intensity scores. For each patient, the first metatarsal and sesamoids on pre- and postoperative WBCT scans were segmented using Disior Bonelogic software and uploaded to Geomagic Design X to perform distancing mapping. The minimum and average distances between the first metatarsal head and medial sesamoid (medial-SMJ) for each patient pre- and postoperatively were calculated. Sesamoid subluxation was measured on WBCT scans using the grading system from 0 to 3 (Yildirim et al.). A simple linear regression model was used to investigate the correlations between minimum preoperative and postoperative medial-SMJ distances and 1-year postoperative PROMIS scores in patients with postoperative reduction of the sesamoids (grade 0). Results: Preoperatively, the mean minimum and average medial-SMJ distances were 0.76 ± 0.37 mm and 1.54 ± 0.33 mm, respectively. Postoperatively, the mean minimum and average medial-SMJ distances were 1.08 ± 0.25 mm and 1.73 ± 0.24 mm, respectively. Thirty-five of 48 patients had a complete reduction of the sesamoids. Lower preoperative minimum distances at the medial-SMJ were significantly correlated with worse 1-year PROMIS PF scores (r=0.405, P=0.016) (Figure 1). Similarly, lower preoperative minimum distances at the medial-SMJ were significantly correlated with worse 1-year PROMIS Pain Intensity scores (r=-0.350, P=0.039) but did not reach significance for 1-year PROMIS Pain Interference scores (r=-0.286, P=0.095). The postoperative minimum medial-SMJ distance was not correlated with 1-year PROMIS PF, Pain Interference, and Pain Intensity scores. Conclusion: In HV patients undergoing a modified Lapidus procedure with postoperatively reduced sesamoids, decreased joint space at the medial sesamoid-metatarsal head articulation was associated with worse 1-year postoperative function as measured by PROMIS PF scores and worse 1-year postoperative pain as measured by PROMIS Pain Intensity scores. In contrast, postoperative degenerative changes at the SMJ were not found to be associated with patient-reported outcomes. Our results suggest that pre-existing SMJ arthritic changes may affect postoperative outcomes and may be a source of dissatisfaction following HV surgery despite appropriate correction of the deformity. Figure 1. Preoperative medial sesamoid to the first metatarsal head minimum distance relative to 1-year PROMIS Physical Function, Pain Intensity, and Pain Interference scores. A simple linear regression demonstrates a significant association between preoperative medial sesamoid –metatarsal head minimum joint distance and 1-year PROMIS Physical Function (r=0.405, P=0.016) and Pain Intensity (r=‒0.305, P=0.039) scores.

The Predictive Power of Monetary Policy on International Stock Market Returns—Evidence From TV-ARMAX Model

In this paper, we apply the time-varying ARMA model with exogenous variable (TV-ARMAX) to examine the predictive power of monetary policy on international stock returns. This method allows time-varying coefficient estimates and uses time-dependent cumulated variation penalty to filter noisy outlier data points. Based on a wide range of 31 countries, our method robustly outperforms other popular methods including the simple linear-regression model (SLM), the vector autoregression and its variants (VAR, TV-VAR, and VARX) and the ARMA model with exogenous variable (ARMAX).

Development of novel resistivity-chargeability statistical relationships for subsurface characterization at Langkawi, Kedah.

The significance of resistivity-chargeability relationships has been acknowledged and applied in various geologic terrains and different environmental conditions. However, there remains an underexplored opportunity to fully utilize these methods in complex geological terrains with a mixture of granitic and sedimentary rocks where empirical relationships have not been established. Such discoveries are crucial for accurately delineating petrophysical and geomechanical properties, which are essential in addressing urgent environmental concerns like landslides, foundation collapse, groundwater shortages, and pollution. To address this research gap, a novel approach was employed: resistivity-chargeability data with simple linear regression modeling. The study focused on developing resistivity-chargeability relationships specifically tailored for tropical granitic environments, using a typical example from Kedah Langkawi, Malaysia. The regions are characterized by complex geological features, ruggedness, and irregular progressive weathering and fracturing of subsurface strata, making the task challenging. Despite these complexities, the study successfully derived an efficient resistivity-chargeability empirical relation that correlates resistivity and chargeability. The derived empirical relationship exhibited high accuracy, surpassing 87%, in predicting chargeability from resistivity datasets or vice versa. This achievement holds great promise in promptly and accurately addressing environmental issues specific to the target region under study. By utilizing this novel resistivity-chargeability relationship, geoscientists, engineers, and environmental practitioners can make informed decisions and effectively manage environmental challenges in these regions, especially during the pre-development stage.

Development of an integrated milestone assessment tool across multiple early-adopter programs for breaking bad news: a pilot project

BackgroundThe transition of the Accreditation Council for Graduate Medical Education (ACGME) to milestone assessment creates opportunities for collaboration and shared assessments across graduate medical programs. Breaking bad news is an essential communication skill that is a common milestone across almost every medical specialty. The purpose of this study was to develop and pilot an integrated milestone assessment (IMA) tool for breaking bad news using ACGME milestone criteria and to compare the IMA tool with the existing SPIKES protocol.MethodsThe IMA tool was created using sub-anchors in professionalism and interpersonal communication skills that are applicable to every specialty and to the ability to break bad news. Two cases of breaking bad news, designed to be “easy” and “intermediate” in difficulty, were used to assess basic skills in breaking bad news in first-year medical residents from six residency specialties. Eight standardized patients were trained to portray the cases in sessions held in November 2013 and May 2014. Standardized patients completed an assessment checklist to evaluate each resident’s performance in breaking bad news based on their use of the SPIKES protocol and IMA tool. Residents answered post-encounter questions about their training and comfort in breaking bad news. The association between SPIKES and IMA scores was investigated by simple linear regression models and Spearman rank correlations.ResultsThere were 136 eligible medical residents: 108 (79.4%) participated in the first session and 97 (71.3%) participated in the second session, with 96 (70.6%) residents participating in both sessions. Overall, we were able to identify residents that performed at both extremes of the assessment criteria using the integrated milestone assessment (IMA) and the SPIKES protocol. Interestingly, residents rated themselves below “comfortable” on average.ConclusionWe developed an integrated milestone assessment (IMA) that was better than the SPIKES protocol at assessing the skill of breaking bad news. This collaborative assessment tool can be used as supplement tool in the era of milestone transformation. We aim assess our tool in other specialties and institutions, as well as assess other shared milestones across specialties.

Strategic audit and its role in the performance of non-profit units

The research aims to demonstrate the importance of strategic auditing in economic units as it is considered one of the tools used to increase confirmation of the information provided by the administration in how it exploits the resources available to the economic unit، which leads to reducing risks and increasing opportunities for management to benefit from the resources available to it. One of the important reasons that necessitated choosing this title is to spread the culture of strategic auditing among the control and internal audit departments in the economic units، as well as benefiting from the development occurring in the field of internal auditing in the economic units in the rest of the institutions operating in developed countries. The descriptive and analytical system was adopted، and the statistical methods that were used in the analysis depended on the Cronbachalpa equation to measure the extent of consistency in performance to measure and ensure the internal consistency of the questions included in the questionnaire form، the use of descriptive statistics، and the use of independent sample tests. T-Test). Using a simple linear regression model to measure the effect of hypotheses. The research reached a set of conclusions and recommendations، and one of the most important of these conclusions was that strategic audit is considered a type of audit based on examining and evaluating strategic performance to ensure that operations are conducted according to sound principles to ensure planned results. Likewise، strategic audit represents a comprehensive system for various strategic levels ( Pre-or preventive audit، simultaneous audit - inspection - and post-audit - feedback -). The most important recommendations recommended by the research are to intensify training courses for the auditor in order to increase experience، as well as greater attention to the aspect of strategic auditing because of its great importance in determining the course of the economic unit.

Exploring the relationship between mothers' competence and comfort in sexual and reproductive health discourse with adolescent girls and its related factors.

The mothers-adolescent discussion regarding sexual and reproductive health (SHR) issues plays an important role in preventing negative outcome associated with sexual risk behaviors. The present study aimed to explore the relationship between mothers' competence and comfort in SHR discourse with adolescent girls and its related factors. A cross-sectional study was conducted involving 160 mothers from July to September 2020. Data were collected through questionnaires covering demographic characteristics, Mother's Comfort in Sexual Discourse (MCSD), Mother's Interest in Sexual Discourse (MISD), and Parenting Sense of Competence (PSOC). The collected data were analyzed using simple and multiple linear regression models. The mean scores for MCSD, MISD, and PSOC were 45.49±16.15 (13-78), 7.9±4.2 (0-13), and 64.07±9.44 (45-94), respectively. The primary topics of mother-adolescent discourse on SRH were menstruation (5.61±0.98) and the delivery process (4.55±1.57). The mean age for "sex talks" and age-appropriate "sex talks" with daughters was 11.76±1.85 (range: 6-15) and 17.05±1.86 (range: 14-23) years, respectively. Significant associations were found between MCSD and MISD (β=0.482, p<0.0001), PSOC (β=0.223, p<0.005), self-efficacy (β=0.202, p<0.011), mother's job (β=0.185, p<0.019), mother's education (β=0.173, p<0.029), and father's age (β=0.161, p<0.042). After adjusting for other variables, major influencing factors on MCSD included MISD (β=0.487, p<0.0001), self-efficacy (β=0.143, p<0.039), satisfaction (β=0.169, p<0.015), daughter number (β=-0.235, p<0.014), son number (β=-0.219, p<0.024), birth rank (β=0.263, p<0.008), and residency (β=0.172, p<0.014). MISD, PSOC, and certain demographic characteristics emerge as significant factors influencing MCSD in mother-daughter sexual discourse. As such, it is imperative to consider these determinants when devising strategies to maintain and enhance the sexual health of teenage girls.

Incomplete recording of race/colour in health information systems in Brazil: time trend, 2009-2018.

This ecological study of time trends and multiple groups evaluated incompleteness in the race/colour field of Brazilian health information system records and the related time trend, 2009-2018, for the diseases and disorders most prevalent in the black population. The Romero and Cunha (2006) classification was applied in order to examine incompleteness using secondary data from Brazil's National Notifiable Diseases System, Hospital Information System and Mortality Information System, by administrative regions of Brazil, while percentage underreporting and time trend were calculated using simple linear regression models with Prais-Winsten correction (p-value<0.05). All records scored poorly except those for mortality from external causes (excellent), tuberculosis (good) and infant mortality (fair). An overall downward trend was observed in percentage incompleteness. Analysis by region found highest mean incompleteness in the North (30.5%), Northeast (33.3%) and Midwest (33.0%) regions. The Southeast and Northeast regions showed the strongest downward trends. The findings intended to increase visibility on the implications of the race/color field for health equity.

Health Disparities in Young Adults: A Direct Comparison of Distress and Unmet Needs Across Cancer Centers.

Information on concerns that young adults (YAs) with cancer face when receiving care outside of specialized treatment centers is needed to increase equitable care to YAs at greater risk of marginalization by the health care system. The current study compared distress and unmet needs at the time of clinic visit between YAs receiving care from three different cancer clinics: (1) a National Cancer Institute-designated center, (2) a community-based clinic, and (3) a county hospital outpatient clinic. The Adolescent and Young Adult Psycho-Oncology Screening Tool (AYA-POST) was administered to measure distress and cancer-related concerns of YAs in active treatment. A one-way analysis of variance (ANOVA) compared distress scores by treatment site. A Fisher's exact test compared the number of participants endorsing each item on the Needs Assessment Checklist from each site. A simple linear regression determined the association between distress and number of items endorsed on the Needs Assessment Checklist. Ninety-seven participants completed the AYA-POST, endorsing, on average, 11 concerns. Fisher's exact test showed significant differences between sites in the proportion of participants endorsing eight items: boredom (P < .001), eating/appetite (P < .001), nausea/vomiting (P < .001), financial concern (P = .002), hopelessness/helplessness (P = .03), confidentiality (P = .04), sibling concern (P = .04), and insurance (P = .05). The simple linear regression model was significant (F(1, 94) = 39.772, P < .001, R2 = 0.297), indicating the number of unmet needs accounted for almost 30% of the variance in distress. The one-way ANOVA was not significant (F(2, 93) = 1.34, P = .267). Social determinants of health can influence the number and type of unmet needs experienced, affecting distress and other outcomes and underscoring the importance of timely, effective, age-appropriate screening and intervention for distress and unmet needs in YAs with cancer.

Multilayer perceptron and support vector regression models for feline parturition date prediction

A crucial challenge in feline obstetric care is the accurate prediction of the parturition date during late pregnancy. The classic simple linear regression (SLR) model, which employed the fetal biparietal diameter (BPD) as the single input feature, was frequently applied for such prediction with limited accuracy. Since Multilayer Perceptron (MLP) and Support Vector Regression (SVR) are now two of the most potent scientific regression models, this study, for the first time, introduced such models as the new promising tools for feline parturition date prediction. The following features were candidate inputs for our models: biparietal diameter (BPD), litter size, and maternal weight. We observed and compared the performance results for each model. As the best-performed model, MLP delivered the highest coefficient score (0.972 ± 0.006), lowest mean absolute error score (1.110 ± 0.060), and lowest mean squared error score (1.540 ± 0.141), respectively. For the first time in this study, BPD, litter size, and maternal weight were considered the essential features for the innovative MLP and SVR modeling. With the optimized model parameters and the described analytical platform, further verification of these advanced models in feline obstetric practices is feasible.

Potential of ground-penetrating radar to calibrate electromagnetic induction for shallow soil water content estimation

Ground-penetrating radar (GPR) and electromagnetic induction (EMI) are used to determine and map soil water content (SWC) in the agricultural landscape. While GPR provides a straightforward estimation of SWC, EMI requires site-specific calibrations mainly based on point-scale measurements such as time domain reflectometry (TDR). However, there is a significant difference in the measurement volumes between EMI and point-scale TDR measurements. This study aimed to enhance the calibration of EMI for estimating SWC in the agricultural landscape by leveraging the larger sampling volumes provided by GPR. Apparent electrical conductivity (ECa) from a multi-coil EMI sensor and dielectric constant from GPR with two center frequencies (500 MHz and 250 MHz) were collected as soil proxies along with TDR measurements. Calibration models were developed under irrigated conditions and the model evaluation was conducted under natural moisture conditions. Correlations were assessed between the proxies from GPR and EMI with TDR-derived SWCs. Simple linear regression (SLR) models were developed between EMI and GPR data to predict SWC. Strong positive correlations (r ≥ 0.80) were observed between the proxies (GPR and the shorter inter-coil spacing (0.32 m) of EMI) and TDR-measured SWC. ECa data from vertical and horizontal coil orientations of the shorter inter-coil spacings were selected to develop SLR models with GPR. The SLR models with the GPR 500 MHz frequency showed a higher coefficient of determination (R2 > 0.70) for both coil orientations of EMI. Results showed the potential of using GPR to calibrate EMI for shallow SWC estimation (below 0.5 m). Nevertheless, the EMI estimated SWCs were not effectively verified with GPR-estimated SWCs, which could be attributed to specific site conditions in the study area. Further research must focus on improving the calibration and model evaluation by incorporating the variability of other soil parameters (soil porosity, pore-water conductivity, and soil salinity) that may affect the SWC–ECa relationship.

Local anesthetics as a tool for Staphylococcus spp. control: a systematic review.

The objective of this work was to carry out a systematic review on the effectiveness of local anesthetics as antimicrobial agents against Staphylococcus spp. Searches were performed in the PubMed, Web of science, Scopus, Embase and Lilacs databases. As inclusion criteria, complete original articles, with in vitro experimental tests with the application of selected anesthetics and bacteria of the genus Staphylococcus spp. This review followed the methodological checklist for writing papers reporting systematic reviews by the PRISMA statement. The risk of bias was assessed according to the JBI critical appraisal checklist. Analysis was performed using an anesthetic-moderated simple linear regression model. This systematic review was registered by the Open Science Framework-OSF ( https://doi.org/10.17605/OSF.IO/C5JM7 ). Initially, 1141 articles were found, of which, after careful selection, 52 articles were analyzed. Lidocaine was the most commonly used anesthetic, being evaluated in 35 of the articles. S. aureus ATCC 25923 was the standard microorganism in 17 articles. The impact of the anesthetic concentration in relation to the antimicrobial effect was evaluated and the results showed that there was no statistically significant difference. (F [5, 12] = 0.688 p = 0.642), even when taking into account the moderator effect of anesthetics individually. Therefore, although the antimicrobial effect of local anesthetics was demonstrated in 82.7% of the studies evaluated, great heterogeneity of the results was found, which made it impossible to carry out a meta-analysis and make recommendations based on the evidence.