Coefficient Correlation Research Articles

A Nexus between Project Management Lifecycle and Performance of Slums Upgrading Projects in Nairobi City County, Kenya

The alarming rate of urban sprawl poses a social menace for city planners and governments worldwide and Nairobi city of Kenya is not an exception. Challenges of access to appropriate and affordable housing has forced majority of city residents to occupy shanties with deplorable living conditions thus, the need to improve the infrastructure in the slums. In Kenya, the government has initiated various projects in a bid to carry out a facelift of slums countrywide. Although, involvement of key stakeholders in each of the phases of project management lifecycle (PMLC) that is, project initiation, planning, implementation, Monitoring & evaluation and closure remains a critical factor to the realization of slum upgrading infrastructure development, the affected communities are not fully engaged thus thwarting effective implementation of the planned activities. In this regard, the aim of the study was to examine the influence of PMLC on performance of slums upgrading projects (PSUP). A descriptive survey research design and a correlational research design were utilized whereby data was analysed and interpreted using means, standard deviations, correlation of coefficient and correlation of determination. A sample of 266 was drawn from a target population of 794, of which 208 responded to a 5-point Likert Scale questionnaire. Qualitative data collected was presented in narrative form. Results obtained indicated a linearly positive and a very strong significant relationship between PMLC and PSUP. When all phases were combined PMLC explained 62.9% of the overall variation in PSUP. The findings indicate that a unit increase in initiation and planning stages result to an increase in PSUP by 7.77% and 1.97% respectively whereas for a unit decrease in project implementation and project M&E, PSUP decreases by 2.07% and 1.72% respectively. It was thus concluded that PMLC significantly influences Performance of Slum Upgrading Projects. The recommendation of the study was that activities pertaining to project planning, M&E and project closure phases be efficiently executed for optimum performance of the projects.

Coupled analysis of arable land input intensity and output intensity based on sliding windows

Sustainable intensification (SI) of agriculture can produce more food to meet the demand of a growing population while considering ecosystem health. The current SI estimation framework ignores the complex coupling between input and output intensity of arable land. A method for coupled analysis of arable land input intensity and output intensity based on sliding windows is proposed. By calculating the correlation coefficient and partial correlation coefficient between input intensity and output intensity in different value ranges as the order parameter, the phase transition and the influence process of input intensity on output intensity can be explained. Meanwhile, a python-based framework is developed.An application of the method was made to reveal the interaction process between annual provincial input intensity and output intensity in mainland China. Researchers in many fields may benefit from the method by obtaining a fast way to analysis the coupling relationship between driving and dependent variables in complex systems.•New method for SI estimation is presented.•The order parameter of the coupling relationship between input and output intensity is calculated based on sliding windows.•Analysis of coupling relationships between driving and dependent variables in complex systems.

Reliability of dynamic and isometric upper muscle strength testing in breast cancer survivors.

Breast cancer is the most common cancer in women worldwide, and its treatment usually involves a combination of many medical procedures, including surgery, chemotherapy, radiotherapy, and hormonal therapy. One of the detrimental effects on physical function is reduced upper limb muscle strength. This study aimed to evaluate upper body strength intra-day and inter-day (test-retest) reliability using the handgrip strength test (HGS) and the bilateral isometric bench press (BIBP) and the test-retest reliability of the one repetition maximum on the bench press (BP-1RM) in breast cancer survivors (BCS). Thirty-two (52.94 ± 8.99 yrs) BCS participated in this study. The muscle strength tests were performed in two different moments, three to seven days apart. Intraclass coefficient correlation (ICC) and coefficient of variation (CV) were used to assess the reliability. Standard error of measurement (SEM), typical error of measurement (TEM), and minimally detectable change (MDC) analyses were performed. The Bland-Altman analysis was used to assess the agreement between test-retest. We found a reliability that can be described as "high" to "very high" (ICC ≥ 0.88; CV ≤ 10%) for intra-day and test-retest. SEM% and MDC% were lower than 5% and 11%, respectively, for all intra-day testing. SEM% and TEM% ranged from 3% to 11%, and MDC% ranged from 9% to 23% in the test-retest reliability. The agreement demonstrated a systematic bias ranging from 2.3% to 6.0% for all testing, and a lower systematic bias may be presented in the non-treated side assessed by HGS and BIBP. HGS, BIBP, and BP-1RM assessments are reliable for measuring upper-body muscle strength in BCS.

A METHODOLOGY TO COMPARE REFRIGERANTS BASED ON THEIR THERMOPHYSICAL PROPERTIES

To compare different refrigerants in a fair way has been always a matter of discusión. There are some properties like Isoentropic COP, volumetric capacities, pressure ratio that can be compared easily and supply some relevant information. However, how they are translated into real systems is not so direct. For instance, isentropic COP is obtained under the assumption that all the refrigerants are able to work in the same condensing and evaporating temperatures, but these variables depend on the temperature lift of the secondary fluid and in real systems, they will not be the same. The size of the heat exchangers and, hence, the cost depend on heat transfer coefficients and pressure drop, and extrapolating this data in a straightforward way is not easy; even the required refrigerant charge is not easy to determine. In this work, the authors propose a methodology to compare different refrigerants based on the external operating conditions, the approach compares the system performance not only in terms of efficiency parameters but also in term of operation map, size and cost of the system and refrigerant charge. To do that, a basic modelling approach has been developed based on quite extended correlations for heat transfer coefficient, pressure drop and void fraction in the heat exchangers. The developed methodology does not pretend to be an exact design guide but a guide that researchers and students can use to estimate qualitatively the differences among refrigerants

Characterisation of a plate heat exchanger working as condenser. Comparative analysis

This paper presents a method to evaluate the heating capacity of a plate heat exchanger working as condenser. As in previous works with phe evaporators and single phase heat exchangers, the proposed methodology relays on a discretisation of the heat exchanger in cells, in such a way that the outlet temperature is assumed and the heat transferred is calculated by integrating along the heat exchanger by means of a 1D approach which allows us to determine the outlet variables iteratively based on a heat transfer area calculation.The input variables of the model are pressure, enthalpy, and flow rate of both fluids at the inlet of the heat exchanger .The study presents the method, pays attention the heat transfer coefficient correlations utilised, and is used to comparatively determine the heat transferred by the refrigerant to the secondary fluid. Experimental results are used for validation and to analyse the goodness of the different correlations tested. Some conclusions are finally drawn.

Hybridized deep learning goniometry for improved precision in Ehlers-Danlos Syndrome (EDS) evaluation

BackgroundGeneralized Joint Hyper-mobility (GJH) can aid in the diagnosis of Ehlers-Danlos Syndrome (EDS), a complex genetic connective tissue disorder with clinical features that can mimic other disease processes. Our study focuses on developing a unique image-based goniometry system, the HybridPoseNet, which utilizes a hybrid deep learning model.ObjectiveThe proposed model is designed to provide the most accurate joint angle measurements in EDS appraisals. Using a hybrid of CNNs and HyperLSTMs in the pose estimation module of HybridPoseNet offers superior generalization and time consistency properties, setting it apart from existing complex libraries.MethodologyHybridPoseNet integrates the spatial pattern recognition prowess of MobileNet-V2 with the sequential data processing capability of HyperLSTM units. The system captures the dynamic nature of joint motion by creating a model that learns from individual frames and the sequence of movements. The CNN module of HybridPoseNet was trained on a large and diverse data set before the fine-tuning of video data involving 50 individuals visiting the EDS clinic, focusing on joints that can hyperextend. HyperLSTMs have been incorporated in video frames to avoid any time breakage in joint angle estimation in consecutive frames. The model performance was evaluated using Spearman’s coefficient correlation versus manual goniometry measurements, as well as by the human labeling of joint position, the second validation step.OutcomePreliminary findings demonstrate HybridPoseNet achieving a remarkable correlation with manual Goniometric measurements: thumb (rho = 0.847), elbows (rho = 0.822), knees (rho = 0.839), and fifth fingers (rho = 0.896), indicating that the newest model is considerably better. The model manifested a consistent performance in all joint assessments, hence not requiring selecting a variety of pose-measuring libraries for every joint. The presentation of HybridPoseNet contributes to achieving a combined and normalized approach to reviewing the mobility of joints, which has an overall enhancement of approximately 20% in accuracy compared to the regular pose estimation libraries. This innovation is very valuable to the field of medical diagnostics of connective tissue diseases and a vast improvement to its understanding.

Automated segmentation of MRI white matter hyperintensities in 8,421 patients with acute ischemic stroke.

To date, only a few small studies have attempted deep learning-based automatic segmentation of white matter hyperintensity (WMH) lesions in patients with cerebral infarction, which is complicated because stroke-related lesions can obscure WMH borders. We developed and validated deep learning algorithms to segment WMH lesions accurately in patients with cerebral infarction, using multisite datasets involving 8,421 patients with acute ischemic stroke. We included 8,421 stroke patients from 9 centers in Korea. 2D UNet and SE-Unet models were trained using 2,408 FLAIR MRI from 3 hospitals and validated using 6,013 FLAIR MRIs from 6 hospitals. WMH segmentation performance was assessed by calculating DSC, correlation coefficient, and concordance correlation coefficient compared to a human-segmented gold standard. In addition, we obtained an uncertainty index that represents overall ambiguity in the voxel classification for WMH segmentation in each patient based on the Kullback-Leibler divergence. In the training dataset, the mean age was 67.4±13.0 years and 60.4% were men. The mean (95% CI) DSCs for Unet in internal testing and external validation were respectively 0.659 (0.649-0.669) and 0.710 (0.707-0.714), which were slightly lower than the reliability between humans (DSC=0.744; 95% CI=0.738-0.751; P=.031). Compared with the Unet, the SE-Unet demonstrated better performance, achieving a mean DSC of 0.675 (0.666-0.685; P<.001) in the internal testing and 0.722 (0.719-0.726; P<.001) in the external validation; moreover, it achieved high DSC values (ranging from 0.672 to 0.744) across multiple validation datasets. We observed a significant correlation between WMH volumes that were segmented automatically and manually for the Unet (r=0.917, P<.0001) and even stronger for the SE-Unet (r=0.933, P<.0001). The SE-Unet also attained a high concordance correlation coefficient (ranging from 0.841 to 0.956) in external test datasets. In addition, the uncertainty indices in the majority of patients (86%) in the external datasets were below 0.35, with an average DSC of 0.744 in these patients. We developed and validated deep learning algorithms to segment WMH in patients with acute cerebral infarction using the largest-ever MRI datasets. In addition, we showed that the uncertainty index can be used to identify cases where automatic WMH segmentation is less accurate and requires human review. WMH = white matter hyperintensity; CNN = convolutional neural networks; SE = squeeze-and-excitation; KL = Kullback-Leibler; ReLU = rectified linear unit; LKW = last known well; mRS = modified Rankin Scale; NIHSS = National Institute of Health Stroke Scale; LAA = large artery atherosclerosis; SVO = small vessel occlusion; CE = cardioembolism.

Effects of the COVID-19 Pandemic and to Develop Strategies for Resistance on the Farming Practices in Ganjam District-An Analysis

The present study entitled “Scientific study on the farming practices in ganjam district to comprehend the effects of the COVID-19 pandemic and to develop strategies for resistance” was undertaken with a view to evaluate COVID-19's effects on farmers of Ganjam District of Odisha and to suggest them how to overcome such pandemic situation. The study followed purposive and random sampling techniques that were found appropriate and taken to undergo the analysis. The study was conducted in the Department of Agricultural Extension and Communication, Institute of Agricultural Sciences (IAS), Siksha ‘O’ Anusandhan University Bhubaneswar, between December 2020 and August 2022. For the selection of District, Blocks and Villages covering 120 respondents, information was collected through structured interview schedule and focus group discussion. Suitable tools and techniques used during the analysis to suffice the study need are frequency, percentage, mean score, standard deviation, Person’s coefficient Correlation, T- test, multiple regression was employed for analyzing collected data. The study revealed that majority of the respondents (85%) belong to middle and older group, having the sex ratio of 3:2 male and female. The study revealed that the education of children adversely affected with mean score of 2.625, further it has been observed that the farmers couldn’t ensure expenses on purchase of household materials. The study depicted that quality food consumption, expenditure habit and farming in general have been adversely affected. The banking activities as regard to getting loan, taking banking transactions have also been adversely affected. Several farmers have faced physical, socio-economic, technological and production constraints. In this study, particularly problem in sound sleep, depression, feeling of insecurity, slowdown of supply chain and non-availability of quality inputs for cultivation are the main focus constraints encountered by agriculture. It was also found that to mitigate such situation farmers had opined that the vaccine should be taken regularly and farmer should develop the saving habit for future use.

Evaluating neurocognitive outcomes in out-of-hospital cardiac arrest survivors: A comparative study of performance-based and reported measures

AimsTo (1) describe the prevalence of cognitive dysfunctions using performance-based and reported measures, and (2) explore the correlations between selected performance-based, patient-reported, and observer-reported neurocognitive outcome measures three months after hospital discharge in a population of out-of-hospital cardiac arrest (OHCA) survivors. MethodsData from 193 OHCA survivors was derived from the Danish multicenter REVIVAL cohort study. At three months, four subtests of the performance-based Delis-Kaplan Executive Function System (D-KEFS) (Trail making, Color-word interference, Verbal fluency, and Figure design), the patient-reported Behavior Rating Inventory of Executive Function − Adult (BRIEF-A), and the observer-reported 16-item Short Form (SF) Informant Questionnaire on Cognitive Decline after Cardiac Arrest (SF-16 IQCODE-CA) were collected. Spearman’s rank coefficient correlation analysis was performed to examine correlations between D-KEFS, BRIEF-A, and SF-16 IQCODE-CA. ResultsOverall, 21% of survivors exhibited impairment in executive functioning using the D-KEFS subtest Color-word interference, while only 9% self-reported executive impairment (BRIEF-A) and 7% of relatives reported cognitive decline (SF-16 IQCODE-CA) in survivors at three months post-arrest. All correlations between D-KEFS, BRIEF-A and SF-16 IQCODE-CA were negligible to low. ConclusionThe results of this REVIVAL substudy suggest that although the performance-based and reported measures did not correlate, dual neurocognitive screening tools containing both a self-reported and an informant-reported version may have the potential to detect executive discrepancies in the return to everyday life and guide targeted neurorehabilitation after OHCA.

Immunohistochemical characterization of inflammatory infiltrates in unstable vitiligo

Objectives: Disease instability in vitiligo is a prominent step during the development or extension of disease. The presence of marked inflammatory infiltrate may be considered a diagnostic clue for disease instability. However, there is a paucity of literature regarding this. Therefore, the present study was carried out to characterize the nature of inflammatory infiltration in cases of unstable vitiligo. Materials and Methods: Thirty patients of unstable vitiligo diagnosed clinically were enrolled and two biopsies: Lesional and perilesional obtained. Histopathological examination with respect to five parameters, i.e., spongiosis, epidermal lymphocytes, basal cell vacuolation, dermal lymphocytes, and melanophages was done including histological scoring. Immunohistochemical characterization was done for T lymphocytes, Langerhans cells (LCs), macrophages, and B cells by studying their number and distribution. Statistical analysis: Statistical analysis was done using Spearman’s rank coefficient correlation test. Results: Mean T-lymphocytes, macrophages, and LC count were significantly higher in lesional skin. The three parameters correlated with vitiligo histological score. T cells were present more frequently in the dermis and stratum basale. Macrophages were found more in the dermis whereas LC was mainly located in the epidermis. Conclusions: An increase in the population of inflammatory cells, especially T lymphocytes and LC, may serve as an indicator of unstable vitiligo. The relative distribution of these cells points toward signaling between them and their role in the destruction of melanocytes and keratinocytes. A better understanding of the underlying mechanisms may lead to the development of novel targeted therapies.

Infodemiology and Infoveillance of the Four Most Widespread Arbovirus Diseases in Italy.

The purpose of this observational study was to evaluate the potential epidemiological trend of arboviral diseases most reported in Italy by the dedicated national surveillance system (ISS data) compared to searches on the internet, assessing whether a correlation/association between users' searches in Google and Wikipedia and real cases exists. The study considers a time interval from June 2012 to December 2023. We used the following Italian search terms: "Virus Toscana", "Virus del Nilo occidentale" (West Nile Virus in English), "Encefalite trasmessa da zecche" (Tick Borne encephalitis in English), and "Dengue". We overlapped Google Trends and Wikipedia data to perform a linear regression and correlation analysis. Statistical analyses were performed using Pearson's correlation coefficient (r) or Spearman's rank correlation coefficient (rho) as appropriate. All the correlations between the ISS data and Wikipedia or GT exhibited statistical significance. The correlations were strong for Dengue GT and ISS (rho = 0.71) and TBE GT and ISS (rho = 0.71), while the remaining correlations had values of r and rho between 0.32 and 0.67, showing a moderate temporal correlation. The observed correlations and regression models provide a foundation for future research, encouraging a more nuanced exploration of the dynamics between digital information-seeking behavior and disease prevalence.

The Correlation of Heat Tolerance Coefficient (HTC) and Temperature Humidity Index (THI) with Milk Production of Dairy Cows in Bangun Lestari Farm, Tulungagung

Determining the relationship between environmental adaptability and milk production across various parities using HTC and THI values was the aim of this study. Purposive sampling was employed to choose thirty dairy cows of parity 1 and 2, for the study. For this investigation, a case study was employed. The temperatures and humidity of the barn environment were used to measure the THI value, which was determined by the HTC value, the milk production of mothers with varying parities, and the rectal temperature and respiratory frequency. Research results demonstrated a negative connection between the two independent variables—the THI and HTC values—and milk production at parities 1 and 2. This suggests that either environmental stressors or higher HTC or THI values resulted in lower milk production. At parity 1, there was a poor correlation, and at parity 2, a moderate correlation between the HTC value and milk production. The correlation coefficients for parity 1 and parity 2 were, respectively, r = 0.410, R2 = 0.168, and r = 0.370, R2 = 0.137. There was just a slight association observed between the THI value and milk production at parities 1 and 2. The correlation coefficient for parity 1 was (r = 0.220; R2 = 0.049), but the correlation coefficient for parity 2 was (r = 0.227; R2 = 0.51). According to the study's findings, milk production in parities 1 and 2 is only marginally correlated with HTC and THI values.

Retinal Blood Vessels Segmentation With Improved SE‐UNet Model

ABSTRACTAccurate segmentation of retinal vessels is crucial for the early diagnosis and treatment of eye diseases, for example, diabetic retinopathy, glaucoma, and macular degeneration. Due to the intricate structure of retinal vessels, it is essential to extract their features with precision for the semantic segmentation of medical images. In this study, an improved deep learning neural network was developed with a focus on feature extraction based on the U‐Net structure. The enhanced U‐Net combines the architecture of convolutional neural networks (CNNs) with SE blocks (squeeze‐and‐excitation blocks) to adaptively extract image features after each U‐Net encoder's convolution. This approach aids in suppressing nonvascular regions and highlighting features for specific segmentation tasks. The proposed method was trained and tested on the DRIVECHASE_DB1 and STARE datasets. As a result, the proposed model had an algorithmic accuracy, sensitivity, specificity, Dice coefficient (Dc), and Matthews correlation coefficient (MCC) of 95.62/0.9853/0.9652, 0.7751/0.7976/0.7773, 0.9832/0.8567/0.9865, 82.53/87.23/83.42, and 0.7823/0.7987/0.8345, respectively, outperforming previous methods, including UNet++, attention U‐Net, and ResUNet. The experimental results demonstrated that the proposed method improved the retinal vessel segmentation performance.

Multi-exposure fused light field image quality assessment for dynamic scenes: Benchmark dataset and objective metric

The luminance dynamic range in natural scenes is exceedingly wide. However, capturing the wide dynamic range information of natural scenes through a single exposure is challenging for commercial light field cameras. One solution to expand the luminance dynamic range of captured light field images is to employ multi-exposure imaging techniques. Nevertheless, this approach may introduce various distortions during the image fusion procedure, especially for dynamic scenes. To evaluate the visual quality of multi-exposure fused light field images (MEFLFIs) and compare the performance of different multi-exposure light field fusion methods, we initially conduct a subjective quality assessment on MEFLFIs for dynamic scenes and establish the first MEFLFI benchmark dataset, which comprises 480 fused light field images generated by eleven state-of-the-art multi-exposure fusion algorithms and two tone-mapping algorithms, along with their corresponding subjective scores. Subsequently, a novel specially designed objective quality assessment metric for MEFLFIs is developed, which incorporates both local–global joint features and angular quality-aware features. The key contribution of this work lies in establishing a pioneering benchmark dataset for MEFLFIs along with a novel tailored objective quality metric. Experimental results conducted over our established MEFLFI database demonstrate that the proposed metric achieves superior performance, with Pearson linear correlation coefficient (PLCC) and Spearman rank correlation coefficient (SROCC) values of 0.8895 and 0.8658 respectively, representing a significant improvement of approximately 5.7 % and 4.9 % compared to the second-best specifically-designed LFI quality metric available. Furthermore, ablation experiments have confirmed that the integration of local–global joint features and angular features significantly enhances the performance of our objective metric, resulting in a better alignment with human visual perception.

Development and Validation of a Micronutrients Knowledge, Attitudes, and Practices Questionnaire for Adolescents Using Psychometric Analysis.

Introduction The development of a questionnaire that measures knowledge, attitude, and practices towards micronutrients will help to develop nutrition intervention programs. The present study aimed to develop and assess the validity and reliability of a questionnaire on knowledge, attitude, and practices (KAP) on micronutrients in adolescents in India. Methods A total of 150 adolescent girls participated in the study. The literature was reviewed to formulate an initial draft of a questionnaire (122 items). Face and content validity were measured by participants and subject experts, respectively, and the content validity index was calculated. Construct validity was assessed using the principal component method of exploratory factor analysis.Internal consistency and test-retest reliability were determined by Cronbach's α value and interclass correlation coefficient correlations, respectively. Results The content validity index for all items except eight items from thepractice subscalewas satisfactory. Face validity results showed that participants understood all items. Exploratory factor analysis suggested a four-factor construct (perceived susceptibility and severity, perceived benefits, readiness to change, and perceived barrier) in the attitude subscale. Internal consistency for knowledge, attitude, and practice items were 0.980, 0.840, and 0.930, respectively. For knowledge and attitude items, interclass correlation coefficient correlation estimates ranged between 0.705 to 0.987 and 0.775 to 0.997, respectively, whereas for practice items, it ranged from 0.701 to 0.945. In the final questionnaire, 134 items consisting of 33 knowledge, 21 attitudes, and 80 practices (55 dietary practices and 25 other practices related to micronutrients) were included. Conclusion The results provided evidence of the validity and reliability of the questionnaire on micronutrients and that can be used to assess the knowledge, attitude, and practices on micronutrients in adolescents.Further studies in different diverse settings are recommended.

Mental health and academic achievement of secondary students in west Bengal

A condition of mental health is characterized by an individual's self-awareness, ability to manage everyday stressors, productivity at work, and capacity to give back to the community. One of the most researched social effects of mental health issues is academic achievement. The purposes of this study how mental health related with academic achievement. In this study the researcher used descriptive type survey method and used mixed sampling method for data collection. Uses analysis by ‘t’ test and ‘co-efficient correlation’. 600 sample were selected for this study. Researcher developed the tool of mental health scale. The finding of this study is · there is mean difference between Academic Achievement and Mental Health among secondary level students. · Finding of the present study reveals that there is no mean difference between Male and Female Secondary Students in Mental Health · In the present study, the researcher found mean difference between Rural and Urban Secondary Students in Mental Health. · There is positive relationship between Academic Achievement and Mental Health among secondary level students.

The study of solid particles effect on the gas bubble dispersion dynamics of complex gas-liquid mixtures at the intake screen of submersible pump

The study of gas phase dispersion at the intake of submersible pumping equipment is an actual issue, since changes in gas phase dispersion can lead to changes in natural separation. At the same time, the gas separation efficiency can be affected by the presence of solid phase in the well products, which would change the structure of gas-liquid mixture and operation mode of electric submersible pump. The results of the research are novel, which takes into account the influence of the properties of multi-component gas-liquid mixture on the character of operation of ESP well. The new dependences of gas bubble diameter at the submersible equipment intake on gas content for four model gas-liquid mixtures: «water – air», «water – surfactants – air», «water – air – solids» and «water – surfactants – air – solids» with the concentration of suspended particles in the flow of 1.0 g/l have been experimentally obtained in conditions of gauge pressure at the intake 0.04 - 0.05 MPa, gas content of mixture was increased up to 71%, liquid flow rate was changed in the range of values from 13 to 68 m3/day. High-speed video recording with fixing the structure of gas-liquid mixture in the near-intake space of the ESP was carried out during the tests. Visualization allows us to clarify the boundary of the flow regime transition from «bubble» to «slug/churn» compared to the Caetano method. There were developed new correlations of natural gas separation coefficient taking into account the influence of solid phase at different operating modes of ESP well. Keywords: gas-liquid mixture (GLM); gas bubble; natural gas separation; solid particles; surfactants.

Islamic Leadership Style and its Relation to the Academic Leaders’ Work Performance in Southern Universities of Khyber Pakhtunkhwa

This descriptive study was conducted with the aims to investigate the academic leaders’ practice of Islamic leadership style in southern universities of Khyber Pakhtunkhwa, to find out the level of work performance of the academic leaders perceived by their teaching faculty, and to find out the correlation between academic leaders’ Islamic leadership style with their work performance. Data were collected from teaching faculty working in different departments of four universities located in southern Pakhtunkhwa. Mean, SD, and Pearson Coefficient Correlation were applied as statistical tests for data analysis. The study’s results showed that academic leaders of different departments in southern universities of Khyber Pakhtunkhwa, sometimes use Islamic leadership style, and their work performance is average, as perceived by their teaching faculty, Islamic Leadership style has strong correlation with academic leader’ work performance. Researchers recommended that academic leaders should practice Islamic leadership style as it ensures the exemplary performance of the leaders and organization as well.

The effect of climate change on the radial growth of Pinus sylvestris l. and Quercus robur l. in the stands of Kharkiv green zone

Purpose. To identify the characteristics of the reaction of the radial growth of Scots pine (Pinus Sylvestris L.) and Scots oak (Quercus robur L.) to climate change in the forest-steppe zone of Ukraine. Methods. Dendrochronological, dendroclimatological, and statistical methods are applied. COFECHA and ARSTAN programs were used. Results. The study was conducted in 100-year-old stands of English oak and Scots pine in the Southern Forestry (Left-bank Forest-steppe). The reaction of the radial growth of trees to climate changes was compared for 1960-1987 and 1988-2016. For the dendroclimatic analysis, the de Martonne hydrothermal indices, the Selyaninov hydrothermal coefficient, the forest aridity index, and the O1 hydrothermal coefficient were used. Relative humidity indicators, which are derived from temperature and precipitation, were also used. It was found that in the second period, the sensitivity of the reaction of the radial growth of trees to climate variations increased, which indicates a certain weakening of the stands due to the increase in temperature. Dendroclimatic analysis of Pinus sylvestris L. and Quercus robur L. showed that when comparing the response of the radial growth of trees to climate variations in 1960-1987 and 1988-2016, the condition of both pine and oak weakened, as evidenced by an increase in significant coefficients correlations between growth indices and climatic factors. Conclusions. Pine was found to be more sensitive to climate change compared to oak. At the same time, these species of these trees at this stage were able to adapt to climate change, as evidenced by tree-ring chronologies, which show stable growth during 2010-2016.

Flow boiling pressure drop and heat transfer at high mass fluxes for R514a in a single microchannel

This paper presents pioneer experimental data about flow boiling heat transfer coefficient and pressure drop for R514a, which is a new environmentally friendly HFO refrigerant substitute for the HCFC R123. Data was collected in a single 1.1 mm internal diameter microchannel with high mass velocity conditions, ranging from 1500 to 7000 kg/m2s, allowing measurements of very high heat transfer coefficients, above 50 kW/m2K. In addition, saturation temperatures up to 92 °C were tested, which has an important application in evaporators of organic Rankine cycles. Comparisons were made between the experimental results of R514a and R123. R514a showed a general trend of a higher heat transfer coefficient and pressure drop (up to 20% higher) relative to R123. Frictional pressure drop literature correlations could predict the R514a data with a mean absolute error below 20% and heat transfer coefficient correlations with mean absolute error below 25%.