ANOVA Method Research Articles

Real versus virtual celebrity endorsement: presentation of online product information and consumer attitudes toward digital products

PurposeThis paper aims to reveal the influence of the presentation of online product information (POPI) on consumer attitudes in the context of online buying digital products.Design/methodology/approachTwo main experimental designs are used to collect data. The ANOVA, t-test and Bootstrap methods are applied to check hypotheses.FindingsFindings of Study 1 indicate that if the POPI is combined with different types of celebrity endorsement (CE) (real vs virtual), the self-brand connection will be changed and further influence consumer attitudes toward digital products. Study 2 verifies the diverse moderating effects of the type of virtual CE. The CRP (central-route presentation) online product information with SVCE (super-realistic-digital virtual CE) can decrease consumer attitudes, while the PRP (peripheral-route presentation) online product information with AVCE (anthropomorphic virtual CE) can enhance consumer attitudes.Practical implicationsE-commerce enterprises should optimize the current layout of POPI by considering diverse matchings between POPI and CE to increase consumer attitudes. Moreover, marketers could make various schemes of POPI considering (virtual) CE and self-brand connection.Originality/valueFindings contribute to understanding the relationship between POPI and consumer attitudes considering the mediation of self-brand connection and the mediations of virtual/real CE. Additionally, this study bridges the gap between research on virtual CE and business practices.

Antimicrobial Activity Screening of Bacteria Isolated from Tasik Cermin

Introduction: With the emergence of the multi-drug resistant bacteria that threaten the human health, novel antimicrobial compounds from natural environment have been increasingly explored. Tasik Cermin is a lake completely covered by karst towers and hills and lacks any inflow or outflow of water making it an oligotrophic environment with limited nutrient availability. Increased competition among microorganisms leads to production of antimicrobial compounds that can inhibit the growth of its competitor. Thus, the aim of this study is to assess antimicrobial activity of bacterial isolates from Tasik Cermin and identify the most resistant isolate. Methods: The isolates were tested against five test bacteria: Staphylococcus aureus, Bacillus subtilis, Streptococcus pneumoniae, Escherichia coli, and Proteus vulgaris by primary screening through perpendicular streak method, secondary screening followed by MIC and MBC and the most resistant bacteria was identified by molecular identification. Results: The result indicates that only one isolate (Isolate TC1A) was able to show potential antimicrobial activity against P. vulgaris and S. pneumoniae. This isolate was further tested by secondary screening through agar well diffusion method and inhibition zone were observed on P. vulgaris (14.97 ± 0.05), E. coli (9.23 ± 0.25) and S. pneumoniae (14.93 ± 0.12). Statistical analysis by One-Way ANOVA and Tukey test method indicates that inhibition zone of E. coli is significantly different as compared to S. pneumoniae and P. vulgaris. Molecular identification revealed that the isolate TC1A was identified as Achromobacter sp. with 97.68% similarity percentage. Conclusion: This finding shows that bacterial isolates from under-explored areas have the potential of producing novel antimicrobial compounds.

Application of Dimension Reduction Methods for Stress Detection

Effective detection of stress situations plays an important role in combating it. This is the main source of motivation for research to identify and evaluate different psychological conditions. Different monitor signals are used to identify individuals' stress situations in daily life. Electroencephalogram (EEG) signals are the main component used to detect stress and depression. The long-term acquisition of this signals partially interrupts daily life and negatively affects it. Researchers are trying to develop wearable technologies that can eliminate this disadvantage. In this study, stress situations are detected utilizing different sensors without EEG signals. The achievements of three different classification methods for different dimensional feature spaces have been compared. The effects of the feature selection and dimension reduction methods on the system performance have been analyzed. During the dimension reduction process, Minimum Redundancy Maximum Relevance (MRMR), Anova, Chi-2, Relieff, Kruskal Wallis (KW) and Principal Component Analysis (PCA) methods are implemented. Support Vector Machines (SVM), Linear Discriminant Analysis (LDA) and k-Nearest Neighbor (k-NN) methods are used as classifiers. The best performance is achieved with 96.2 % accuracy in 15-dimensional by using LDA and PCA methods together.

Biological variation of inflammatory and iron metabolism markers in high-endurance recreational athletes; are these markers useful for athlete monitoring?

To deliver biological variation (BV) data for serum hepcidin, soluble transferrin receptor (sTfR), erythropoietin (EPO) and interleukin 6 (IL-6) in a population of well-characterized high-endurance athletes, and to evaluate the potential influence of exercise and health-related factors on the BV. Thirty triathletes (15 females) were sampled monthly (11months). All samples were analyzed in duplicate and BV estimates were delivered by Bayesian and ANOVA methods. A linear mixed model was applied to study the effect of factors related to exercise, health, and sampling intervals on the BV estimates. Within-subject BV estimates (CVI) were for hepcidin 51.9 % (95 % credibility interval 46.9-58.1), sTfR 10.3 % (8.8-12) and EPO 27.3 % (24.8-30.3). The mean concentrations were significantly different between sex, but CVI estimates were similar and not influenced by exercise, health-related factors, or sampling intervals. The data were homogeneously distributed for EPO but not for hepcidin or sTfR. IL-6 results were mostly below the limit of detection. Factors related to exercise, health, and sampling intervals did not influence the BV estimates. This study provides, for the first time, BV data for EPO, derived from a cohort of well-characterized endurance athletes and indicates that EPO is a good candidate for athlete follow-up. The application of the Bayesian method to deliver BV data illustrates that for hepcidin and sTfR, BV data are heterogeneously distributed and using a mean BV estimate may not be appropriate when using BV data for laboratory and clinical applications.

Environmental issues, governmental policies, and accountability on the public communication agenda. Statistical results from Central and Eastern European countries

This paper highlights the importance of environmental policies in a social and economic context characterized by multiple structural crises. The beginning of the XXI-st century proposes a new perspective, based on the transition from industrial to clean energy and green economies. In this context, environmental preservation should be seen as a main goal for decision-makers and the civic community. The paper aims to identify several relevant predictors that are involved in the further dynamics of the Environmental Performance Index. In order to argue the role played by economic factors in preserving the environment, the paper used quantitative and multivariate statistics, being based on linear, nonlinear, and multiple equations of regression. Using one-way ANOVA and nearest neighbourhood methods, the paper highlights the fact that environmental performance is strongly related to economic welfare, governmental coordination of climate policies, the level of sustainable development, and civic accountability.

Antibacterial activity of gel hand sanitizer from seaweed extract (Kappaphycus alvarezii)

Seaweed extract (Kappaphycus alvarezii) contains flavonoids, triterpenoids, steroids, and alkaloids which have antibacterial activity. The purpose of this study was to determine the potential of seaweed extract (K. alvarezii) as a hand sanitizer product and to determine the antibacterial activity of hand sanitizer gel from seaweed extract (K. alvarezii) against S. aureus and E. coli bacteria. This research was conducted by experimental methods Inhibitory Zone Test, Homogeneity Test, Viscosity Test, pH Test, Spreadability Diameter Test, Organoleptic Test and Skin Irritation Test. This study used a completely randomized design (CRD). The data obtained were then analyzed using the ANOVA method and if there was a difference, then the significant difference test was continued using the Duncan Multiple Range Test (DMRT) at a significance level of 5% (α=0.05). The results of this study showed that the seaweed extract of K. alvarezii gave good results. The appearance of the hand sanitizer gel in each treatment is homogeneous. The value of gel viscosity is close to standard. The hand sanitizer gel has a pH of 5. The diameter of the spread has a result of 5-6. Does not cause irritation to the skin. Has a zone of inhibition that is classified as strong-very strong.

Abstract C023: Variations in clinical presentation and outcomes of rare ovarian cancers by race and nativity

Abstract Introduction: Disparities in the prevalence of disease, medical access, and survival rates have been well documented in women with epithelial ovarian cancer. Black women tend to develop more aggressive tumors and have worse overall survival. Aside from race, however, nativity (region of birth) has been associated with variations in treatment outcomes. There is a paucity of research specifically about rare ovarian cancer subtypes, including germ cell (GC) and stromal cell (SC) tumors. Our study aims to provide a comparative analysis of clinical presentation and outcomes among women of Caribbean and US origin with GC and SC tumors, stratified by race. Methods: Analyses were conducted using the Florida Cancer Data Service (FCDS), the statewide cancer registry. Women who were diagnosed with GC and SC ovarian cancer subtypes from 1987 to 2017 were identified, and categorized as either US-born (USB) White, USB Black, Caribbean-born (CB)White, or CB Black. Abstracted data included patient-level demographic data, treatment histories, and all-cause overall survival. Statistical analyses were performed using chi-square, ANOVA, log-rank test, and Kaplan-Meier method, with the threshold for statistical significance set at p < 0.05. Results: 691 women with GC and SC were identified. There was a significant difference in mean age at diagnosis by race and nativity. USB Black women were diagnosed at the youngest mean age (34.4 yr, SD 20.62), followed by USB White (38.6 yr, SD 20.97), CB Black (43.9 yr, SD 20.79), and CB White (45.9 yr, SD 18.66)(p=0.002). CB White patients had the highest utilization of Medicaid (23.5%), while CB Black had the highest proportion of uninsured patients (22.2%)(p<0.001). There were no differences in stage, tumor characteristics (grade, histology, lymph vascular invasion) or treatments (surgery, chemotherapy, radiation) administered among the groups. CB Black women had a much lower prevalence of smoking (2.8%) compared to the other subgroups (CB White 23.5%5; USB White 28.1%; USB Black 16.9%, p=0.003). There were no significant differences in median OS by race and nativity (USB White 184 months; USB Black USB 244 months; CB White 270 months; CB Black CB 204 months; log-rank p=0.8). Conclusion: Despite a younger age of diagnosis in USB versus CB women, and Black women vs White women, there were no differences in survival outcomes in women with GC and SC ovarian cancers, even when considering variations in insurance coverage and smoking histories. While the long survival is likely due to the natural history of these tumors, the variation in age at diagnosis suggests variable susceptibility to tumor initiation by race and place of birth. Citation Format: Maurice J. Chery, Alex P. Sanchez-Covarrubias, Sophia H.L. George, Matthew P. Schlumbrecht. Variations in clinical presentation and outcomes of rare ovarian cancers by race and nativity [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C023.

Tribological Behavior of Polytetrafluoroethylene and Its Composites Using the Taguchi Method

The frictional and wear characteristics of polymer materials and their composites, particularly bearing materials, are studied in this paper. The study was achieved by inspecting a wide range of process parameters such as load, sliding distance, and sliding velocity. Optimization of experimentation was done using the Taguchi approach. The experimentation work was carried out on a Pin-on-disc machine. The ANOVA method was used to analyze the experimental results, which were then represented using tables and graphs. The wear analysis of the composite PTFE was studied with the help of Signal-to-Noise ratio and multiple regression analysis, which strongly indicates that the wear of a polymer material is greatly influenced by blending filler materials.

Sleep Treatment Education Program for Young Adult Cancer Survivors (STEP-YA): Protocol for an Efficacy Trial.

Young adult cancer survivors (YACS) are at elevated risk for chronic insomnia, even years after completing treatment. In addition to potential health consequences, insomnia can interrupt social, educational, and vocational development just as they are trying to "make up" for time lost to cancer. Cognitive behavioral therapy for insomnia (CBTI) is recommended as first-line treatment for insomnia but remains largely unavailable to YACS due to several barriers (ie, shortage of trained providers, geographic limitations, financial limitations). Traditional CBTI has not been adapted to meet YACS' unique developmental and circadian challenges. To improve availability of effective behavioral insomnia treatment for this population, we developed the Sleep Treatment Education Program for Young Adult Cancer Survivors (STEP-YA), a low-intensity educational intervention delivered virtually online. In this phase 2 "proof of concept" trial, primary aims are to test the efficacy of STEP-YA to improve insomnia symptoms and mood in YACS and assess the utility of individualized coaching to improve treatment effects. A secondary aim will explore participant variables associated with clinically significant response to STEP-YA. This 2-arm randomized prospective trial will enroll 74 off-treatment YACS aged 20 years to 39 years with clinically significant insomnia. Each participant completes the STEP-YA intervention in a 1-on-1 synchronous online session led by a trained interventionist following a structured outline. The 90-minute intervention presents educational information on the development of insomnia after cancer and offers specific suggestions for improving insomnia symptoms. During the session, participants review the suggestions and develop a personalized sleep action plan for implementing them. After the session, participants are randomized to either the coaching condition, in which they receive 2 telephone coaching sessions, or the no-coaching condition, which offers no subsequent coaching. The Insomnia Severity Index (ISI) and the Profile of Mood States: Short Form (POMS-SF) are assessed at baseline and 4 and 8 weeks postintervention. Enrollment began in November 2022, with 28 participants currently enrolled. We anticipate recruitment will be completed in 2024. The primary endpoint is a change in ISI score from baseline to 8 weeks postintervention. The secondary endpoint is change in mood symptoms (POMS-SF) from baseline to 8 weeks postintervention. Change scores will be treated as continuous variables. Primary analyses will use ANOVA methods. A within-subjects analysis will examine if the STEP-YA intervention is associated with significant changes in insomnia and mood over time. A 2-way ANOVA will be used to evaluate the utility of coaching sessions to improve treatment effects. Chronic insomnia has significant negative effects on YACS' medical, educational, and psychological functioning. STEP-YA aims to address their needs; study results will determine if the intervention warrants future effectiveness and dissemination studies and if individualized coaching is necessary for adequate treatment response. ClinicalTrials.gov NCT05358951: https://clinicaltrials.gov/study/NCT05358951. DERR1-10.2196/52315.

The Effect of Interval Training 1:2 and 1:3 on Increasing the Speed of the Sickle Kick in Terms of Leg Muscle Power

The speed of the sickle kick is an important component in martial arts, which plays an important role in defensive and ffensive techniques on athletes. This study aims to find out: (1) the difference in the effect between 1:2 and 1:3 training on sickle kick speed; (2) the difference in the effect between athletes who have high and low leg power on the speed of the sickle kick; (3) The interaction between 1:2 and 1:3 interval training and high and low leg power on the speed of the sickle kick in IPSI athletes in Kendari City. This type of research is experimental research using a 2x2 factorial design. The population in this study was IPSI athletes in Kendari City which amounted to 38 people. The sample in this study amounted to 20 people who were then carried out ordinally paired and had been divided by 37% of the total population. A tool used to measure the speed of the sickle kick using the target speed and leg strength with a vertical jump. Data analysis was carried out using the two-way ANOVA method using SPSS software version 20.0, with a significance level of 5% or 0.05. The results showed that: (1) there was a significant difference in the effect between interval training of 1:2 and 1:3 on the speed of the sickle kick, as evidenced by a value of 6.283 with a significance value of 0.023 sig < 0.05. (2) There is a significant difference in the influence on the power ability of the limb on the sickle kick speed component, with a significance value of 0.001. (3) There was a significant interaction between 1:2 and 1:3 interval training on sickle kick speed in athletes, with a significance value of 0.042 sig < 0.05. So the conclusion of this study is that training with a ratio of 1: 2 and 1: 3, the level of leg power, and the interaction between the two significantly affect the speed of the sickle kick in IPSI athletes in Kendari City. These factors need to be considered in the planning and execution of training programs to improve the performance of athletes in terms of sickle kick speed.

Identification of Anti-Cancer Compounds in Medicinal Plants Using Metabolomic Approaches: A Review

The modern lifestyle despite its comfort has made cancer a second leading public health problem, following cardiovascular disease. As chemotherapeutic has many side effects including resistance, recent attention has focused on plants which may provide a good opportunity for complementary cancer treatment. Several studies have begun to focus on metabolomic research in order to discover the mechanisms of action of diverse medicinal plants, investigate biomarkers, and comprehend cancer progression at metabolic rates. This study aims to analyze and highlight related metabolomic investigations in medicinal plants that demonstrate the potential of biomarker compounds and their processes in cancer disease. The research methodology uses a literature review that is compiled from many connected journals. According to the findings, bioactive substances present in medicinal plants can be used as biomarkers to disrupt the metabolism of enzymes, transporters, and signaling pathways in cancer cells. Utilized analytical platforms include HPLC, GC-MS, FTIR and NMR. Statistical analysis employs the Anova, PCA, and OPLS-DA methods. Finally, we reviewed biomarkers of medicinal plants and metabolomic pathways, with the result that anticancer compounds may exert their activity by various methods affecting DNA replication, cell cycle, migration and apoptosis.The modern lifestyle despite its comfort has made cancer a second leading public health problem, following cardiovascular disease. As chemotherapeutic has many side effects including resistance, recent attention has focused on plants which may provide a good opportunity for complementary cancer treatment. Several studies have begun to focus on metabolomic research in order to discover the mechanisms of action of diverse medicinal plants, investigate biomarkers, and comprehend cancer progression at metabolic rates. This study aims to analyze and highlight related metabolomic investigations in medicinal plants that demonstrate the potential of biomarker compounds and their processes in cancer disease. The research methodology uses a literature review that is compiled from many connected journals. According to the findings, bioactive substances present in medicinal plants can be used as biomarkers to disrupt the metabolism of enzymes, transporters, and signaling pathways in cancer cells. Utilized analytical platforms include HPLC, GC-MS, FTIR and NMR. Statistical analysis employs the Anova, PCA, and OPLS-DA methods. Finally, we reviewed biomarkers of medicinal plants and metabolomic pathways, with the result that anticancer compounds may exert their activity by various methods affecting DNA replication, cell cycle, migration and apoptosis.

The Role of Educational Games in Increasing Student Motivation and Engagement

Education is the learning of knowledge, skills, and habits of a group of people passed down from one generation to the next through teaching, research, and training, therefore an education must require a forum to achieve these goals. One example of a place to develop student education is a school, in a school there is a person who acts as a teacher or educator whose job is to develop the potential of students so that they can become an intelligent person. The purpose of this research is to find out a more in-depth discussion about the role of educational games in increasing student motivation and involvement in the learning process. This research was conducted to understand the role of the game given by an educator to students, whether the game in learning motivates students or not. The method used in this study uses a quantitative method that aims to examine the role of educational games through statistical techniques by collecting research variables using google form media and then imported and processed into the SPSS application and tested using the One Way Anova method. Based on the data obtained, it shows that the role of educational games in increasing student motivation and involvement is very influential, which is a good learning strategy that can have an effect in the teaching and learning process so that the role of the game can foster enthusiasm or motivation and student involvement in learning so that students become excited about learning and are not easily bored. The conclusion in this study explains that applying educational games as a learning medium is very important in the world of education, where the use of educational games in increasing student motivation and involvement can help increase student knowledge. So it can be concluded that games in education are very useful for students in the teaching and learning process to eliminate boredom and to motivate students in learning.

Visualisasi Data Malnutrisi Anak Di Asia Menggunakan Looker Studio Serta Analisis Data Dengan Metode ANOVA

Child malnutrition is a serious problem involving complex factors in various countries. The level of the economy in a country is one of the factors that influences the occurrence of this problem. Using data obtained from the data UNICEF site on Child Malnutrition, this study involved processing the data to create a data visualization in the form of a dashboard. This dashboard is able to provide information on the prevalence of child malnutrition and its geographic distribution patterns in the Asian region by utilizing the Looker Studio platform. In addition, this study was also conducted to analyze the effect of state income classification on the percentage of child malnutrition that occurs. The use of the ANOVA analysis method in this study is the basis for answering research questions related to analysis. The stages carried out in this study were Data Collection, Data Preprocessing, data analysis using the ANOVA method, and data visualization. The result of this study is a data visualization in the form of an informative dashboard, as well as the results of the analysis showing that there is a significant effect of the classification of state income on the percentage of child malnutrition in that country. This study provides important insights into the problem of child malnutrition in Asia in a visual form and provides results of statistical significance, indicating that there is a significant relationship or influence between the classification of national income and the percentage of child malnutrition that occurs in that country, not just a coincidence.

Design Parameters Optimization in CNC Machining Based on Taguchi, ANOVA, and Screening Method

Design Parameters Optimization in CNC Machining Based on Taguchi, ANOVA, and Screening Method

Comprehensive analysis of the heterogeneous computing performance of DNNs under typical frameworks on cloud and edge computing platforms

In this paper, nearly 40 commonly used deep neural network(DNN) models are selected, and their cross-platform and cross-inference frameworks are deeply analysed. The main metrics of accuracy, the total number of model parameters, the computational complexity, the accuracy density, the inference time, the memory consumption and other related parameters are used to measure their performance. The heterogeneous computing experiment is implemented on both the Google Colab cloud computing platform and the Jetson Nano embedded edge computing platform. The obtained performance is compared with that of two previous computing platforms: a workstation equipped with an NVIDIA Titan X Pascal and an embedded system based on an NVIDIA Jetson TX1 board. In addition, on the Jetson Nano embedded edge computing platform, different inference frameworks are investigated to evaluate the inference efficiency of the DNN models. Regression models are established to characterize the variation in the computing performance of different DNN classification algorithms so that the inference results of unknown models can be estimated. ANOVA methods are proposed to quantify the differences between models. The experimental results have important guiding significance for the better selection, deployment and application of DNN models in practice. Codes are available at this https URL https://github.com/Foreverzfy/Model-Test.

Room factors that affect the physical and non-physical quality of working space at home during the pandemic era: workers’ perceptions

During the pandemic, the trend of working from home is changing the pattern of working space at home. Undesign working space will affect the performance of workers. Knowledge about the ideal working space at home is required. To answer this, it is necessary to know the room factors that affect the physical and non-physical quality of the working space at home. This study will examine the workers’ perception of the working space at home quality. The purpose of this study is to analyze the room factors that affect the physical and nonphysical quality of working space at home based on workers’ perceptions. Questionnaires have been distributed and get 206 respondents. 200 data that can be processed, will be analyzed using the ANOVA method. The results of the study found that the room factors that affect the physical and non-physical quality of the working space at home are the opening position, natural air availability, and the scenery category with moderate influence. Based on the results of the study, designing a working space at home, the important thing that must be considered is a good view that can prevent boredom when doing activities at home. To support the physical and non-physical qualities in a comfortable working space at home, a room with side openings, conditionable air ventilation, and a view of a well-maintained garden is needed.

Optimization of resistance spot welding with surface roughness dissimilar mild steel with stainless steel

Resistance spot welding plays a critical role in the manufacture dissimilar material industry. However, there are differences in mechanical properties between mild steel and satinless steel so as to reduce the quality of welded joints. In order for differences in mechanical properties to be corrected, surface roughness was treated. The aim of this study was to optimize the welding parameters of DRSW with surface roughness by analysis using the Taguchi and Anova Methods. In this study discusses about investigates the Resistance spot welding parameters on weld geometry, mechanical properties, and SEM EDS on dissimilar materials of mild steel and stainless steel. The material thickness of the mild steel and stainless steel are 1 mm, respectively. The process parameters of the resistance spot welding joint used, example; surface roughness, current, welding time, and electrode force. Quality welding joint test results include weld geometry, mechanical properties, and SEM EDS. Weld geometry testing to determine the weld nugget profile. The mechanical properties test was shear tensile test, while the SEM EDS included macrostruture and microstructure observations. The results showed the highest nugget diameter 6.65 mm highest shear tensile strength 7.66 kN. The most influential parameter is current by 75.08 %, then surface roughness by 12.35 %. The highest tensile strength has fewer defects. Surface roughness treatment before welding is very good to make welding quality joints between mild steel and quality stainless steel increase. Surface roughness treatment was very good to be included when making welding procedures for welding engineers for welding processes resistance spot welding dissimilar mild steel with stainless steel.

Action Strategies of Start-ups

There are quite a lot of opinions and little knowledge about the strategies of start-ups. The notions on this topic are inconsistent and with little agreement. Hypothetical works predominate and, although logically consistent, there is no empirical research that would provide verified scientific knowledge. Business strategies of start-ups should be a systematic object of research because start-ups have to compensate for a number of their natural limitations (weaknesses) with practical conduct that has the nature of an action strategy. The goal of the research is to identify a typology of start-up strategies that would clarify and specify the strategizing of start-ups based on their actual action. The research was conducted on a sample of 147 start-ups. Methods of descriptive statistics, factor analysis, hierarchical clustering, and ANOVA were used to analyse the research sample. The criteria describing the action of start-ups were divided (reduced) into two strategic dimensions using factor analysis, the combination of which, using clustering by the Ward method, there were identified four types of action strategies of start-ups: proactive leader, waiting leader, proactive follower, waiting follower. The main knowledge contribution of the research lies in the fact that the seemingly disorganized, spontaneous, and even chaotic action got clear contours that will allow a better understanding of the behaviour of start-ups. The research also included an assessment of the performance of the identified types of strategies.

Aktivitas Antibakteri Kombinasi Ekstrak Biji Manjakani (Quercus infectoria) Dan Daun Sirih Merah (Piper crocatum) Terhadap Pertumbuhan Bakteri Klebsiella pneumoniae

Potential plants found in Indonesia that can be used for the treatment of urinary tract infections include: Manjakani seeds (Quercus infectoria) and red betel leaves (Piper crocatum). Manjakani seeds are pharmacologically claimed to have biological activities such as anti-inflammatory, antibacterial and antifungal. Red betel leaf has the potential as an antibacterial in the treatment of infectious diseases. The purpose of this study was to determine the antibacterial activity of the combination of manjakani seed extract and red betel leaf in inhibiting the growth of Klebsiella pneumoniae bacteria. The type of research used istrue experiment study with a completely randomized design (CRD) with three factors, namely the type of solvent n-hexane, ethyl acetate, ethanol 96%, ratio (1:1,1:2,2:1) and concentration (75%,100%) with each treatment being repeated twice. This research was conducted in the microbiology laboratory, Labkes, East Kalimantan. The population in this study is the manjakani plant and red betel plant and tested using the agar diffusion technique method Kirby Bauer with positive control (Ciprofloxacin) and negative control (aquadest). Data analysis used is One Way ANOVA and advanced test methods Duncan with a significance level of 0,05. The results obtained showed that there was an effect of antibacterial activity of Manjakani seed extract and red betel leaf on growth K. pneumoniae. The most effective concentration was found in ethanol 96% extract, (2:1 combination of 100% concentration) of 13,97 mm and an effectiveness of 55,74% with a positive control ciprofloxacin 5µg of 25,06 mm. It can be concluded that the combined extract of manjakani seeds and red betel leaves has antibacterial activity against bacteria Klebsiella pneumoniae,but the potential is still low of ciprofloxacin.

Profitability and financial performance of Italian real estate companies: quantitative profiles

PurposeThis study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.Design/methodology/approachThe analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.FindingsThe study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.Research limitations/implicationsIn the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.Practical implicationsPublic policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.Social implicationsThe research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.Originality/valueThe study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.