Frequency Distribution Research Articles

Investigating academic researchers' perceptions of a recommender system for mentor-to-mentee matching

The importance of mentoring among researchers cannot be overemphasized, and to this effect, several recommender systems have been presented in the literature to find experts for collaborations. However, matching researchers as mentors to their respective mentees has not been looked into. Earlier works suggest that expert-finding recommender systems primarily use metadata from experts' publications for making recommendations. Meanwhile, when matching for mentorship, more emphasis should be placed on the areas and major areas of both the mentors and mentees as intended in our proposed system. It is observed that many authors co-author in some areas in which they are not major, which may not certify them as experts in such areas. This research attempts to investigate the views of researchers about mentoring and also to determine the perceptions of the researchers on the need to develop a recommender system that can match researchers for mentorship. The study was conducted in two universities in south-western Nigeria, namely; Federal University of Technology, Akure, and Federal University, Oye-Ekiti. Data were collected with the aid of structured questionnaires using both online and paper surveys. The collected data were analyzed using frequency tables and charts. The results show that 99% strongly agreed and 1% agreed that mentorship is essential among researchers in academia. 98% strongly agreed and 2% agreed that there is need for tools that can help users get personalized items in all areas of life. 56% strongly agreed, 42% agreed, and 2% were indifferent that building a recommender system for matching researchers for mentorship is important. As can be seen from the results, the majority of the respondents acknowledged the importance of mentorship among academic researchers and the need to develop a recommender system to match these researchers for mentorship.

Phase tracking using a Kalman filter based on probability density distribution in frequency-scanning interferometry

Frequency-scanning interferometry (FSI) utilizing external cavity diode lasers (ECDL) stands out as a potent technique for absolute distance measurement. Nevertheless, the inherent scanning nonlinearity of ECDL and phase noise pose a challenge, as it can compromise the accuracy of phase extraction from interference signals, thereby reducing the measurement accuracy of FSI. In this study, we propose a composite algorithm aimed at mitigating non-orthogonal errors by integrating the least-squares and Heydemann correction technique. Furthermore, we employ Kalman filtering for precise phase tracking. We introduce a parameter selection strategy based on the statistical distribution of instantaneous frequency to achieve the fusion estimation of phase observation values and theoretical models, which starts a new perspective for the application of multi-dimensional data fusion in FSI measurement. Through simulation and experimental validation, the efficacy of this approach is confirmed. The experimental results show promising outcomes: with an average phase error of 0.12%, a standard deviation of less than 1.7 µm in absolute distance measurement, and an average positioning accuracy error of 0.29 µm.

Time distribution of stimulated transition probabilities

In recent years, an increasing number of experimental results have been published for a wide variety of systems in which high-precision, ultra-fast, and ultra-short laser pulses techniques have been used to study time-resolved dynamical processes. In the absence of a theoretical prediction of the time distribution of the transition probabilities, the lifetimes τ are generally extracted by fitting the decay time with an exponential, bi-exponential or three-exponential function. In fitting the data, the short-time behavior is generally neglected. The purpose of this study is to show that an explicit formula for the time distribution of the transition probability can be determined rigorously using time-dependent perturbation theory. A formula that perfectly fits an important subset of the experimental results from t = 0 to t=∞ . We show that by following a route different from the usual procedure for deriving transition amplitudes and Einstein coefficients in time-dependent perturbation theory, one ends up with a time-dependent factor, that is, a temporal distribution function of the transition probabilities, and for the Einstein coefficients. The time distribution reported here looks in the time domain similar to the Planck distribution in the frequency domain. In fact, the behavior of the time distribution, with a maximum at 2τln⁡2 , and with τ playing the role of temperature, resembles the behavior of the Planck frequency distribution. We present several examples to demonstrate that the theoretical formula allows for easier fitting of the experimental results reported in the literature. We also show that the time distribution explains the difference in resonance heights between the experimental and theoretical blue laser spectra.

Impact of wave action on the entrainment rate and droplet size of oil

Oil dispersed on the water surface undergoes fragmentation into droplets, subsequently entering the water column under wave action. The oil entrainment rate and the droplet size distribution (DSD) significantly influence the subsequent migration and transformation of oil in the water column. A wave tank system was employed to investigate the impact of wave action on oil entrainment rate and DSD. The experimental results revealed that increased wave height and wave frequency facilitated the entry of oil into the water column and fragmented it into dispersed droplets. Relationships between oil entrainment rate and energy dissipation, as well as DSD, were established and supported by mathematical regression analyses. Non-linear regression analysis indicated that the cumulative frequency distribution of DSD adhered to the Log-Normal and Rosin-Rammler distributions. These findings contribute to a comprehensive understanding of natural oil dispersion and subsea transport, valuable for estimating the origin of oil spills.

Neuregulin 2 Is a Candidate Gene for Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with heterogeneous and complex genetic underpinnings. Our previous microarray gene expression profiling identified significantly different neuregulin-2 gene (NRG2) expression between ASD patients and controls. Thus, we aimed to clarify whether NRG2 is a candidate gene associated with ASD. The study consisted of two stages. First, we used real-time quantitative PCR in 20 ASDs and 20 controls to confirm the microarray gene expression profiling results. The average NRG2 gene expression level in patients with ASD (3.23 ± 2.80) was significantly lower than that in the controls (9.27 ± 4.78, p < 0.001). Next, we conducted resequencing of all the exons of NRG2 in a sample of 349 individuals with ASD, aiming to identify variants of the NRG2 associated with ASD. We identified three variants, including two single nucleotide variants (SNVs), IVS3 + 13A > G (rs889022) and IVS10 + 32T > A (rs182642591), and one small deletion at exon 11 of NRG2 (delGCCCGG, rs933769137). Using data from the Taiwan Biobank as the controls, we found no significant differences in allele frequencies of rs889022 and rs182642591 between two groups. However, there is a significant difference in the genotype and allele frequency distribution of rs933769137 between ASDs and controls (p < 0.0001). The small deletion is located in the EGF-like domain at the C-terminal of the NRG2 precursor protein. Our findings suggest that NRG2 might be a susceptibility gene for ASD.

Conditions Underlying the Appearance of Spontaneous Otoacoustic Emissions in Mammals.

Across the wide range of land vertebrate species, spontaneous otoacoustic emissions (SOAE) are common, but not always found. The reasons for the differences between species of the various groups in their emission patterns are often not well understood, particularly within mammals. This review examines the question as to what determines in mammals whether SOAE are emitted or not, and suggests that the coupling between hair-cell regions diminishes when the space constant of frequency distribution becomes larger. The reduced coupling is assumed to result in a greater likelihood of SOAE being emitted.

Free electron emission in vacuum assisted by photonic time crystals

The Cerenkov radiation and Smith–Purcell (SP) effect state that free electron emission occurs exclusively in dielectrics when the velocity of the particles exceeds the speed of light in the medium or in the vicinity of periodic gratings close to each other within a vacuum. We demonstrate that free electrons in a vacuum can also emit highly directional monochromatic waves when they are in close proximity to a medium that is periodically modulated temporally, suggesting the existence of the temporal SP effect. The momentum band gaps of time-varying media, such as photonic time crystals (PTCs), create new pathways for the injection of external energy, allowing the frequency, intensity, and spatial distribution of electromagnetic fields to be controlled. Moreover, the PTC substrate enables the conversion of localized evanescent fields into amplified, highly directional propagating plane waves that are only sensitive to the velocity of particles and the modulation frequency, which allows us to observe and utilize Cerenkov-like radiation in free space. Our work presents significant opportunities for the utilization of time-varying structures in various fields, including particle identification, ultraweak signal detection, and improved radiation source design.

Crater Detection and Population Statistics in Tianwen-1 Landing Area Based on Segment Anything Model (SAM)

Crater detection is useful for research into dating a planetary surface’s age and geological mapping. The high-resolution imaging camera (HiRIC) carried by the Tianwen-1 rover provides digital image model (DIM) datasets with a resolution of 0.7 m/pixel, which are suitable for detecting meter-scale craters. The existing deep-learning-based automatic crater detection algorithms require a large number of crater annotation datasets for training. However, there is currently a lack of datasets of optical images of small-sized craters. In this study, we propose a model based on the Segment Anything Model (SAM) to detect craters in Tianwen-1’s landing area and perform statistical analysis. The SAM network was used to obtain a segmentation mask of the craters from the DIM images. Then non-circular filtering was used to filter out irregular craters. Finally, deduplication and removal of false positives were performed to obtain accurate circular craters, and their center’s position and diameter were obtained through circular fitting analysis. We extracted 841,727 craters in total, with diameters ranging from 1.57 m to 7910.47 m. These data are useful for further Martian crater catalogs and crater datasets. Additionally, the crater size–frequency distribution (CSFD) was also analyzed, indicating that the surface ages of the Tianwen-1 landing area are ~3.25 billion years, with subsequent surface resurfacing events occurring ~1.67 billion years ago.

Aggregating inconclusive data sets

An administrator is provided with data collected by several practitioners. These data may include inconclusive observations. The administrator is required to form a frequency distribution on the states of nature that would be approved by external auditors as long as it is compatible with the available information. We state a novel result on the compatibility of a probability with a finite set of capacities. We use this result to provide necessary and sufficient conditions for the compatibility of the administrator's frequency distribution with the data collected by the practitioners, according to two auditing criteria.

The Contribution of Subsistence Agriculture to the Livelihoods of the Smallholder Farmers in South Kivu Province, Democratic Republic of Congo

Subsistence agriculture in most cases is practiced on a limited space of land by farmers and it is dependent on human power that results into production of food consumed at household level, with little or no surplus for sale. A study about the contribution of subsistence agriculture to the livelihoods of the smallholder farmers in south Kivu province was carried out. A total of 303 smallholder farmers were randomly selected and interviewed to examine the effects of practicing subsistence agriculture on the socioeconomic status of the farmers. How the socioeconomic status attained by the farmers influenced their sustainable livelihoods was also assessed. Data were analyzed using means, frequency distribution, correlation, ANOVA and Chi square test. Thematic analysis was done on qualitative data. The farmers practiced shifting and primitive agriculture, intensive subsistence, and nomadic herding. There was a significant difference in the yields of crops grown (F = 0.0088; P = 0.05), while education and income status significantly affected the farmer’s socioeconomic status by practicing subsistence agriculture (P < 0.05). An average mean value of 3.12 for the components of the farmers’ livelihoods were exhibited, with the human capital mean value being highest (4.16) compared to natural, social and financial capital. The socioeconomic status attained had a significant effect on sustainable livelihoods of the farmers at P < 0.05. This implies that the smallholder farmers need to be trained by the agricultural extension workers better and sustainable methods of farming for higher crop yields. In addition, the Central Government though the Ministry of Agriculture, should avail improved seed inputs to the local community for better crop yields. All these will enable the smallholder farmers improve their socioeconomic status and at the same time attain higher sustainable livelihoods.

Current Assessment of Dietary Habits, Physical Activity, and Related BMI among Students of People’s University of Medical & Health Sciences for Women, Nawabshah (SBA)

Background: Eating habits and adequate physical activity play significant roles in enhancing growth, development, health, and physical and mental fitness of individuals. University students, especially those in medical fields, often face demanding schedules and rigorous studies that can lead to altered dietary habits and lifestyles. Assessing these patterns is crucial for identifying potential nutritional or eating disorders and understanding their impact on students' health. Objective: The study aimed to assess dietary habits, physical activity levels, and related BMI among female students of People’s University of Medical & Health Sciences for Women, Nawabshah (PUMHSW). Methods: This cross-sectional study was conducted over one and a half months within the premises of PUMHSW. A total of 331 female students from MBBS and Allied Sciences programs were selected using convenient sampling. Inclusion criteria included students aged 18-25 years enrolled in any year of their respective programs, while exclusion criteria excluded those below 18 or above 25 years old and postgraduate students. Data were collected through a structured English-language questionnaire administered via face-to-face interviews. The questionnaire covered variables such as income, education, parental occupation, dietary habits, physical activity, and BMI. Verbal consent was obtained from all participants, ensuring confidentiality. Ethical approval was obtained in accordance with the Declaration of Helsinki. Data analysis was performed using SPSS version 25, with descriptive statistics including percentages, means, and standard deviations. Results were presented using frequency tables, charts, and graphs. Results: The majority of students were aged 21-23 years (61.6%), with most having a normal BMI (59.5%). Among the participants, 23.0% were underweight, 13.6% were overweight, and 3.9% were obese. Regular sleep patterns were reported by 68.9% of students, while 31.1% had irregular sleep patterns. A significant proportion (76.7%) did not engage in regular physical activity. The distribution of BMI classifications showed that 23.0% were underweight, 59.5% had normal BMI, 13.6% were overweight, and 3.9% were obese. A higher frequency of normal BMI was observed among MBBS students compared to Allied Sciences students. Conclusion: The study concluded that while most students had a normal BMI, a notable proportion were underweight, overweight, or obese. These findings underscore the need for targeted interventions to promote healthier lifestyles among university students, focusing on dietary habits, physical activity, and sleep patterns to prevent future health issues.

Long-term stellar activity of M dwarfs. A combined K2 and TESS study of two early M-type stars

Studies of the rotation and activity of M type stars are essential in order to enhance our understanding of stellar dynamos and angular momentum evolution. Using the outstanding photometric capabilities of space telescopes, even those rotation signals with low amplitudes can now be investigated in previously unrivaled detail. By combining data of K2 and the TESS prime mission, the star spot activity of M dwarfs can be monitored over a timescale of half a decade. In the framework of our study on the rotation--activity relation for bright and nearby M dwarfs, we also aim to investigate their long-term activity. While K2 was observing fields distributed around the ecliptic plane, the TESS prime mission was oriented along a line of ecliptic longitude, with one camera centered on an ecliptic pole. Due to these different observing strategies, the overlap between K2 and the TESS prime mission is marginal. However, 45 stars from our sample were observed with both missions, and of these, two early M-type stars that fulfill our selection criteria, EPIC\,202059229 and EPIC\,245919787, were analyzed in more detail. We find that, for both stars, the rotation period did not change, while the rotational phase did change for EPIC\,245919787 by sim 0.2. The amplitude of the spot-induced variability changed for both stars but more significantly for EPIC\,245919787. By comparing the cumulative flare frequency distributions, we find that the flare activity for EPIC\,202059229 is unchanged, while it slightly changes for EPIC\,245919787 between the K2 and TESS epochs. Using a combination of light curves from K2 and TESS that span a baseline of up to 4.5 years, we are able to measure significant differential rotation for EPIC\,245919787. Furthermore, we show that combining missions like K2 and TESS is a promising method for detecting stellar activity cycles.

Generalizability of a Musculoskeletal Therapist Electronic Health Record for Modelling Outcomes to Work-Related Musculoskeletal Disorders.

Electronic Health Records (EHRs) can contain vast amounts of clinical information that could be reused in modelling outcomes of work-related musculoskeletal disorders (WMSDs). Determining the generalizability of an EHR dataset is an important step in determining the appropriateness of its reuse. The study aims to describe the EHR dataset used by occupational musculoskeletal therapists and determine whether the EHR dataset is generalizable to the Australian workers' population and injury characteristics seen in workers' compensation claims. Variables were considered if they were associated with outcomes of WMSDs and variables data were available. Completeness and external validity assessment analysed frequency distributions, percentage of records and confidence intervals. There were 48,434 patient care plans across 10 industries from 2014 to 2021. The EHR collects information related to clinical interventions, health and psychosocial factors, job demands, work accommodations as well as workplace culture, which have all been shown to be valuable variables in determining outcomes to WMSDs. Distributions of age, duration of employment, gender and region of birth were mostly similar to the Australian workforce. Upper limb WMSDs were higher in the EHR compared to workers' compensation claims and diagnoses were similar. The study shows the EHR has strong potential to be used for further research into WMSDs as it has a similar population to the Australian workforce, manufacturing industry and workers' compensation claims. It contains many variables that may be relevant in modelling outcomes to WMSDs that are not typically available in existing datasets.

Examining Color Recognition in the Kurdish Language: A Sociolinguistic Perspective

This study employs a cross-sectional research design to explore color recognition among Kurdish participants, encompassing individuals from various age and education groups. The research aims to investigate patterns of color perception across demographic segments within the Kurdish population. Participants were selected from four distinct groups: elementary school graduates (elderly), high school students, university students, and university graduates. The study involved presenting participants with a list of color names in Kurdish and recording their responses to assess color recognition. Descriptive statistics, including frequency distributions and percentages, were utilized to analyze the data and identify trends in color perception. The total number of participants in the study was 274. Findings indicate a high level of familiarity with basic colors such as black, white, red, green, yellow, and blue across all participant groups, with recognition rates ranging from 85% to 96%. However, less common colors, including gray, orange, pink, and purple, showed varying levels of recognition among different participant groups. Gray was relatively better recognized compared to other less common colors, with recognition rates ranging from 8.93% to 15%, suggesting potential differences in exposure to color terminology among different age and education groups.

Financial Accounting Controls and Financial Reporting Quality: An Empirical Analysis of Public Educational Agencies in Nigeria

This study examined financial accounting controls and financial reporting quality: an empirical analysis of public educational agencies in Nigeria. This study adopted a cross-sectional descriptive survey design because it provides a clear outcome and the characteristics associated with it at a specific point in time. The target population for this study constituted the total number of employees in the accounting/finance, administration, and operations departments in the four educational examination agencies. The number of staff in the accounts/finance, administration, and operations departments in the four regulatory agencies totaled one hundred and thirty-seven (137). The sample size derived with the Cochran sample size derivation statistic yielded one hundred and one (101). For this study, primary data was employed. The data were collected with the aid of a questionnaire that was properly drafted using the 5-point Likert scale for the questionnaire. The study adopted the use of frequency tables and percentages to analyze the questions and employed linear regression with the application of the ordinary least squares to test the hypotheses of the study. The major findings that were extracted from the analysis reveal that detective accounting controls have a significant effect on the financial reporting quality of selected educational regulatory agencies in Nigeria and preventive accounting controls have no significant effect on the financial reporting quality of selected educational regulatory agencies in Nigeria. It is therefore the recommendation of the study that regulatory agencies should sustain the use of detective accounting control systems through proper optimization and regulatory agencies should ensure they make consistent periodic financial reconciliations as a complement to preventive accounting control.

Random and time-persistent depositional processes in turbidite successions: an example from the marine deep-water Aoshima Formation (Neogene, Kyushu Island, southwest Japan)

ABSTRACT The deposits of flood- and earthquake-derived subaqueous sediment gravity flows represent a significant fraction of lacustrine and deep-sea sedimentary successions, thus providing a valuable record of such natural disasters. The magnitude of these events and the thickness of the associated deposits are considered to follow a lognormal or power-law frequency distribution, whilst that of time intervals between subsequent events appear to be best approximated by a Poisson model, indicative of a random, time-independent phenomenon. However, the debate on whether the sedimentary record of these natural disasters is governed by randomness alone or whether there is some underlying stratigraphic ordering is still unsettled and requires detailed time-series analysis. This study consists of a time-series analysis of mudstone- and sandstone-dominated turbidite successions offshore a fan-delta system in the Neogene Aoshima Formation that belongs to the sedimentary fill of the forearc basin of southwest Japan. The formation consists of a monotonous alternation of very fine- to medium-grained sandstones capped by hemipelagic mudstones and, more rarely, by turbidite mudstones. The results show that the autocorrelation function of the time series suggests quasi-periodic variability in the upper sandstone-dominated part, whereas the lower mudstone-dominated part shows a white-noise-like pattern. Rescaled range analysis shows that the number of events per unit time in the lower part is characterized by a random time series, such as Brownian noise with a Hurst exponent of 0.5. In contrast, the thickness of event beds of the lower part and the thickness and the number of events of the upper part are persistent time series with a Hurst exponent > 0.5. These results suggest that the number of turbidite depositional events in the mudstone-dominated part indicates random timing, whereas its thickness time series and the sandstone-dominant part are not governed by simple stochastic processes but are affected by sea-level changes, sediment transport dynamics, and other factors such as, for example, seafloor topography.

Program VUE: analysing distributions of cryo-EM projections using uniform spherical grids

Three-dimensional cryo electron microscopy reconstructions are obtained by extracting information from a large number of projections of the object. These projections correspond to different `views' or `orientations', i.e. directions in which these projections show the reconstructed object. Uneven distribution of these views and the presence of dominating preferred orientations may distort the reconstructed spatial images. This work describes the program VUE (views on uniform grids for cryo electron microscopy), designed to study such distributions. Its algorithms, based on uniform virtual grids on a sphere, allow an easy calculation and accurate quantitative analysis of the frequency distribution of the views. The key computational element is the Lambert azimuthal equal-area projection of a spherical uniform grid onto a disc. This projection keeps the surface area constant and represents the frequency distribution with no visual bias. Since it has multiple tunable parameters, the program is easily adaptable to individual needs, and to the features of a particular project or of the figure to be produced. It can help identify problems related to an uneven distribution of views. Optionally, it can modify the list of projections, distributing the views more uniformly. The program can also be used as a teaching tool.

Harnessing Text and Web Analytics to Enhance Decision-Making in Job Opportunity Categorization

Text analytics is defined as a method of analyzing compilations of structured text such as dates, times, locations, semi structured text, such as HTML and JSON as well as unstructured text, such as word documents, videos, and images, to extract and discover trends and relationships without requiring the exact words or terms to convey those concepts. Web analytics on the other hand is the technology that collects, measures, analyses, and provides reports of data on how users use websites and web applications. It is used to track a number of aspects of direct user-website interactions, such as the number of visits, time spent on the site, and click pathway. It also aids in the identification of user interest areas and the enhancement of web application features. We used clustering techniques to categorize the job opportunities that are available for the job seekers. By implementing text analytics, text data may be grouped with the goal of providing outcomes in the form of word frequency distribution, pattern identification, and predictive analytics. Text analytics may create one-of-a-kind values to use in the improvement of decision-making and business processes, as well as the development of new business models.

Managing the E-commerce Data Deluge through Text Analytics and Web Management (Overview of Amazon.com)

Today, more than 80% of the big data handled in the e-commerce industry is text and unstructured data. Text analytics is an automated process for analyzing text and extracting useful information from it. It can discover trends and relationships in data. Web analytics is the collection, processing, and analysis of data in order to draw conclusions to optimize usability on a website. Web analytics can be used to improve the usability of a site by analyzing user behavior patterns such as time spent on the site, abandonment rates, most frequently accessed products, click-through rates, etc. It can also help analyze the interests of different user demographics, as it tracks granular details such as user demographics, age and gender, geography, and devices used as data. In order to obtain UpToDate information, the business can utilize business intelligence for real-time data processing, then they can practice stream analysis to analyse continuous flow of data. For instance, the business can collect instant information in Twitter or other social media and analyse it by using social media analysis. For website management, business can practice web analysis to analyse the customer’s behaviours. Tracking the customer’s activity, page view and conversion rate is important for business to analyse how to improve the website performance. Text analytics of comments received on Amazon can be used to group text data and produce results in terms of word frequency distribution and sentiment analysis. Text analytics could be used for decision making, improving service quality, and developing new business models.

Tuberculosis in Wild Pigs from Argentina.

Mycobacterium bovis, a member of the Mycobacterium tuberculosis complex (MTC) and non-tuberculous Mycobacteria (NTM), may infect wild and domestic mammals, including humans. Although cattle are the main hosts and spreaders of M. bovis, many wildlife hosts play an important role worldwide. In Argentina, wild boar and domestic pigs are considered important links in mammalian tuberculosis (mTB) transmission. The aim of this work was to investigate the presence of M. bovis in wild pigs from different regions of Argentina, to characterize isolates of M. bovis obtained, and to compare those with other previously found in vertebrate hosts. A total of 311 samples from wild pigs were obtained, and bacteriological culture, molecular identification and genotyping were performed, obtaining 63 isolates (34 MTC and 29 NTM). Twelve M. bovis spoligotypes were detected. Our findings suggest that wild pigs have a prominent role as reservoirs of mTB in Argentina, based on an estimated prevalence of 11.2 ± 1.8% (95% CI 8.0-14.8) for MTC and the frequency distribution of spoligotypes shared by cattle (75%), domestic pigs (58%) and wildlife (50%). Argentina has a typical scenario where cattle and pigs are farm-raised extensively, sharing the environment with wildlife, creating conditions for effective transmission of mTB in the wildlife-livestock-human interface.