Miracle-dz/UniFAR-FTUs huggingface dataset:
Consequences of Choosing Different Settings When Processing Hip-Based Accelerometry Data From Older Adults: A Practical Approach Using Baseline Data From the SITLESS Study

Accurately measuring older adults’ physical activity (PA) and sedentary behavior (SB) using accelerometers is essential, as both are important markers of health. This study aimed to highlight how steps taken during data processing may affect key hip-based accelerometry outcomes in older adults, using a selection of baseline accelerometry data (n = 658) from the SITLESS study. Different analytical parameters tested included wear-time algorithms, use of low-frequency extension (LFE) filter, epoch length, and minimum and maximum daily wear-time thresholds. These were compared against vertical axis counts per minute (CPM), vector magnitude (VM) CPM, SB, light PA, moderate-to-vigorous PA, step counts, and wear-time percentage. Differences in settings across the analytical parameters were assessed using paired sample t-tests and repeated measures ANOVAs using Bonferroni correction. Using the “Choi” versus “Troiano” wear-time algorithm resulted in a higher percentage wear-time. Most SB and PA outcomes were significantly different across wear-time algorithms (p < .001). This was similar when using the LFE filter versus normal filter (p < .001). Using 10-second epoch length increased daily SB time (between +75.7 and +79.2 minutes) compared to 60-second. Most SB and PA outcomes significantly changed comparing minimum-wear-time thresholds of 360, 480, 600, and 720 minutes per day (p < .001). Applying a log-diary with a ≥1140-minute threshold had a significant impact on vertical axis CPM, VM CPM, SB, and light PA outcomes (p < .001). This study demonstrates the potential variability in the number of participants being included in studies and reported SB and PA levels when processing older adults’ accelerometry data dependent on the analytical procedures utilized.
A Miniaturized Chemical Vapor Detector Using MEMS Flexible Platform

According to the Canadian Cancer Society, lung cancer is the one of the leading causes of cancer death. It has been shown that cancer survival chance depends on factors including the availability of early detection and diagnostic tools such as miniaturized and sensitive gas sensor. This can detect the released volatiles in addition to be implementable in portable electronics, which decisively improves the patient’s survival rate. Therefore, in this thesis and in an effort to develop high-sensitive and miniaturized gas sensor, a microelectromechanical systems (MEMS) platform is utilized. In this work, a sensitive gas sensor is proposed by employing capacitive micromachined ultrasonic transducer (CMUT) configuration due to its high sensitivity, low LOD and reversibility. The comprehensive analytical model is proposed for this circular bilayer CMUT-based gas sensor for the first time, which includes all the known critical design parameters of the sensor. The model also includes effects of membrane softening and residual stress of the top membrane and the sensing component. The model is further followed by conducting FEA simulations, to investigate effect of critical parameters on center resonant frequency of the device. The achieved results for FEA simulations are compared with the proposed model, which shows less than 5% average variation. Both model and simulations verify that maximum sensitivity occurs at smaller radius, thinner membrane and structural material with lower density. The simulations results are utilized to maximize the sensitivity of the gas sensor in a sample frequency range of 5MHz and 25MHz. The proposed device has a 500nm functionalized polysilicon membrane with 300nm polyisobutylene (PIB) while the cavity height is 500nm and 30V DC bias voltage is applied. The proposed and designed CMUT-based gas sensor offers a 222Hz/zg sensitivity (∆ f /∆m) in the aforementioned frequency range.
Long-Term Trends in Adult Socio-Economic Resemblance between Former Schoolmates and Neighbouring Children

Schools and residential neighbourhoods constitute key contexts of development beyond the family of origin. Yet, few prior studies address whether the overall impact of these childhood contexts on adult life chances has changed over time. In this article, we investigate changes in socio-economic resemblance between former schoolmates and neighbouring children using Norwegian administrative data covering three decades. We use cross-classified multilevel models to decompose the variance in children’s educational attainment and adult earnings into the contributions found within and between their school and neighbourhood contexts in adolescence. We find that unadjusted school and neighbourhood correlations in educational attainment are relatively modest and declining over time. These trends largely reflect declining socio-economic segregation between schools and neighbourhoods over time. After adjusting for sorting by family background, schools account for 2 per cent or less of the total variation in completed years of education in the more recent cohorts and neighbourhoods even less. For adult earnings, the adjusted school correlations are very low, accounting for around 1 per cent of the total variance, while the contribution of neighbourhoods is close to zero. Our findings suggest that adolescent school and neighbourhood contexts are not major determinants of children’s later-life socio-economic attainments in the Norwegian welfare state setting.
Non-destructive detection of kiwifruit soluble solid content based on hyperspectral and fluorescence spectral imaging

The soluble solid content (SSC) is one of the important parameters depicting the quality, maturity and taste of fruits. This study explored hyperspectral imaging (HSI) and fluorescence spectral imaging (FSI) techniques, as well as suitable chemometric techniques to predict the SSC in kiwifruit. 90 kiwifruit samples were divided into 70 calibration sets and 20 prediction sets. The hyperspectral images of samples in the spectral range of 387 nm~1034 nm and the fluorescence spectral images in the spectral range of 400 nm~1000 nm were collected, and their regions of interest were extracted. Six spectral pre-processing techniques were used to pre-process the two spectral data, and the best pre-processing method was selected after comparing it with the predicted results. Then, five primary and three secondary feature extraction algorithms were used to extract feature variables from the pre-processed spectral data. Subsequently, three regression prediction models, i.e., the extreme learning machines (ELM), the partial least squares regression (PLSR) and the particle swarm optimization - least square support vector machine (PSO-LSSVM), were established. The prediction results were analyzed and compared further. MASS-Boss-ELM, based on fluorescence spectral imaging technique, exhibited the best prediction performance for the kiwifruit SSC, with the R p 2 , R c 2 and RPD of 0.8894, 0.9429 and 2.88, respectively. MASS-Boss-PLSR based on the hyperspectral imaging technique showed a slightly lower prediction performance, with the R p 2 , R c 2 , and RPD of 0.8717, 0.8747, and 2.89, respectively. The outcome presents that the two spectral imaging techniques are suitable for the non-destructive prediction of fruit quality. Among them, the FSI technology illustrates better prediction, providing technical support for the non-destructive detection of intrinsic fruit quality.
Identifikasi moral remaja di era informasi post-truth: perspektif psikologi sosial gestalt

Dalam kurun waktu 5 tahun terakhir istilah post-truth sangat banyak digunakan dan dipraktikkan meski individu dan kelompok itu tidak semua menyadari hal itu sesuatu yang buruk, baik berupa perilaku maupun pemikirannya. Hal ini memiliki efek pada pola persepsi kognitif, perilaku dalam pendidikan, sosial budaya individu dan kelompok. Ditemukan maraknya informasi hoax, media sosial yang menyampaikan informasi yang mengakibatkan stigmatisasi persepsi akan suatu hal, sehingga berimbas pada perilaku perundungan sehingga tidak jelas mana yang baik dan buruk, mana yang benar dan salah. Kajian ini dilakukan secara kualitatif dan kuantitatif berdasarkan data survey observasi, wawancara dan angket pada sampel 100 remaja di kota Padang. Tujuan penelitian awal ini untuk mengidentifikasi nilai moral remaja dari segi persepsi kognitif moral dan perilaku sosial moral di era informasi post-truth , serta menganalisisnya dalam perspektif psikologi sosial gestalt. Hal ini penting sebagai temuan awal, bahwa era post-truth bisa mengakibatkan perubahan tata pikir, dan budaya generasi manusia masa depan dengan era revolusi sosial 5.0 ini. Abstract In the last 5 years, term “post-truth” is very widely used and practiced by individual and groups. This has an effect on individual and group’s cognitive perception and behavior in education, social and cultural. The fact found that lot of hoax information, social media that convey an information that result to stigmatize of cognitive perceptions, thus impacting abuse behavior so it is not clear which are good or bad, which are right or wrong. This study was conducted qualitative and quantitative based on observational data, interview and questionnaire with a sample of 100 teenagers in the city of Padang. The purpose of this preliminary research is to identification of the moral values of adolescents in terms of moral’s cognitive perception and moral’s social behavior in the era information of post-truth, and analyze it with gestalt social psychology perspective. This is important as a preliminary finding, that in the era of post-truth can lead to change in a mindset and social culture in the future generation of human with the era of social revolution 5.0.
Anti-inflammatory effects of Urtica pilulifera l. seeds extracts in the rat

Urtica pilulifera l. seeds extracts (Decocted and Methanolic extracts) have anti-inflammatory effects. In an experimental-interventional study, Anti-inflammatory effects of Urtica pilulifera l. (UPL), a Traditional Iranian Medicine (TIM) plant, were examined with formalin-induced hind paw edema model in the rat. Sodium salicylate (S.S) injection (300 mg/kg; IP) was used as a positive control group and was put to comparison with methanolic extract of UPL (20 mg/kg; IP), three doses of decocted extract of UPL (20, 40 and 80 mg/kg; IP) and a group of distilled water (6 ml/kg; IP). The differences were estimated by means of one-way ANOVA followed by LSD test for acute anti-inflammatory studies (One hour after formalin injection), and by means of Student's unpaired t-test for the chronic studies (Day one to day seven edema surveys). In Acute anti-inflammatory studies, two doses of decocted UPL extract (40 mg/kg and 80 mg/kg) and S.S group had anti-inflammatory effects (p-value
Constructing the social network prediction model based on data mining and link prediction analysis

The purpose of this paper is to apply link prediction to community mining and to clarify the role of link prediction in improving the performance of social network analysis. ,In this study, the 2009 version of Enron e-mail data set provided by Carnegie Mellon University was selected as the research object first, and bibliometric analysis method and citation analysis method were adopted to compare the differences between various studies. Second, based on the impact of various interpersonal relationships, the link model was adopted to analyze the relationship among people. Finally, the factorization of the matrix was further adopted to obtain the characteristics of the research object, so as to predict the unknown relationship. ,The experimental results show that the prediction results obtained by considering multiple relationships are more accurate than those obtained by considering only one relationship. ,Due to the limited number of objects in the data set, the link prediction method has not been tested on the large-scale data set, and the validity and correctness of the method need to be further verified with larger data. In addition, the research on algorithm complexity and algorithm optimization, including the storage of sparse matrix, also need to be further studied. At the same time, in the case of extremely sparse data, the accuracy of the link prediction method will decline a lot, and further research and discussion should be carried out on the sparse data. ,The focus of this research is on link prediction in social network analysis. The traditional prediction model is based on a certain relationship between the objects to predict and analyze, but in real life, the relationship between people is diverse, and different relationships are interactive. Therefore, in this study, the graph model is used to express different kinds of relations, and the influence between different kinds of relations is considered in the actual prediction process. Finally, experiments on real data sets prove the effectiveness and accuracy of this method. In addition, link prediction, as an important part of social network analysis, is also of great significance for other applications of social network analysis. This study attempts to prove that link prediction is helpful to the improvement of performance analysis of social network by applying link prediction to community mining. ,This study adopts a variety of methods, such as link prediction, data mining, literature analysis and citation analysis. The research direction is relatively new, and the experimental results obtained have a certain degree of credibility, which is of certain reference value for the following related research.
Academic support for students with developmental disabilities in elementary schools: the roles and experiences of Chinese classroom teachers

Objectives: The aim of the study was to explore the perspectives of elementary classroom teachers in relation to the academic support that is provided to students with developmental disabilities (DDs) in China. Method: A qualitative research design, using focus groups, individual interviews and document analysis, was adopted to explore classroom teachers’ perspectives on their roles and experiences in providing academic support to students with developmental disabilities. In this study, three focus groups consisting of 19 classroom teachers were solicited from 16 regular elementary schools across three districts in Shanghai, China. Ten of these teachers agreed to take part in subsequent individual interviews, and eight of these ten participants provided their Individualized Education Programs (IEPs) for analysis. Results: The transcripts of focus groups, interviews and the IEPs were analyzed to generate themes and subthemes related to the classroom teachers’ roles and practices in supporting students with DDs in learning activities, the barriers to practice, and support needs. Conclusion: The findings of this study offer empirical insights into the issues surrounding academic support from teachers for students with DDs and the needs and challenges faced by these teachers.
Hooke and Jeeves Pattern Search Method and Global Optimal Solution

In Data Science, it is imperative to build a model that learns the parameters from the data itself to solve either predictive or prescriptive problems while ensuring improved fidelity of the solution. In this article, we propose to model the non-stationary present in the data in terms of spatial anisotropic interpolation which encapsulates the trend as polynomial regression and characterizes the associated error field as a Gaussian noise process. The fundamental emphasis of the paper lies in the minimization of anisotropic error by learning the model parameters using Hooke and Jeeve’s pattern search algorithm, a gradient-free pattern search algorithm and works even in missing value scenarios. The Design and Analysis of the Computer Experiments (DACE) based metaphor are developed and the quality of results are demonstrated on benchmark functions. The proposed implementation essentially has a wide range of applications in Computer Vision, weather prediction, Ore mining, etc.
Assessment of the relationship between serum vitamin (A, B 12 , C, D, folate) and zinc levels and polycystic ovary syndrome

Introduction: There is increasing evidence that vitamin D affects insulin and glucose metabolism, and a low vitamin D status is suspected to be a risk factor for impaired glucose tolerance, insulin resistance and so polycystic ovary syndrome (PCOS), but there is no evidence to suggest that there is a relationship between vitamin A, vitamin B12, vitamin C, folate, zinc (Zn) and PCOS in the literature. We aimed to investigate the levels of vitamins A, B12, C and D and zinc and the association between vitamins A, B12, C and D, folate and zinc level and hormonal-biochemical parameters in PCOS. Material and methods: We recruited 65 women with PCOS and 67 healthy individuals. Correlations between clinical and metabolic parameters and vitamins A, B12, C and D and zinc status were analyzed separately in patients and controls. Results: Women with PCOS showed a decreased serum level of vitamin A compared with the control group (p < 0.05), but they showed no differences in the levels of vitamin D, vitamin B12, vitamin C, folate or Zn (p > 0.05). Conclusions: Our study found no differences in the absolute levels of serum vitamins B12, C, D, folate or Zn between PCOS patients and matched controls, but the vitamin A level was lower in PCOS patients. Prevalence of vitamins A, B12, C and D and Zn insufficiency was equally common among both patients and controls.
PNEUMATIC SYSTEMS FOR AUTOMATIC SORTING EQUIPMENT

The aim of the research work was focused on a research of manipulators design using suction grippers. The results of the research can be applied in the design of jigs - manipulators for handling thin sheets. The FME analysis was used in the investigation to show the course of elastic deformations and stresses in stressed areas. An experimental observation of the change in the free deflection of the workpiece from the positioning of the suction cups under gravity load by means of a laser 3D scanner was carried out for the FEM deflection detection method.
The mechanical characteristics of single-leg squat exercise with emphasis on pelvic elevation

Movement control and muscle function for pelvic movement in the frontal plane (pelvic elevation) are important for various single-leg sports activities. We aimed to clarify mechanical characteristics of pelvic squat (P-Sq: single-leg squat exercise with emphasis on pelvic elevation, developed by our research group) compared with the double-leg squat (D-Sq) and single-leg squat (S-Sq). Twelve male track and field athletes performed D-Sq, S-Sq, and P-Sq exercises at various loads (90%, 75%, and 60% of 1-repetition maximum [1RM]), using maximum effort. Kinematic and kinetic data were calculated using data recorded with a motion capture system and force platforms. We observed the highest values with P-Sq, followed by S-Sq and D-Sq under all load conditions as follows: peak vertical ground reaction force and rate of force development (RFD), range of pelvic elevation, peak pelvic elevation velocity, peak powers associated with hip abduction torque and trunk lateral flexion torque. In P-Sq, RFD at 90% 1RM was smaller than under the other load conditions, whereas peak vertical ground reaction force at 90% 1RM was larger than under the other load conditions. There were no differences among load conditions with regard to hip abduction and trunk lateral flexion torques and powers. Therefore, characteristics of P-Sq compared to those of D-Sq and S-Sq are 1) larger and faster pelvic elevation, using related muscles (hip abductors and trunk lateral flexors) under all load conditions, 2) larger peak ground reaction force with pelvic elevation under large load conditions, and larger RFD in pelvic elevation under low load conditions. Jpn J Phys Fitness Sports Med, 67(2): 187-197 (2018)
For the greater good? Patient and public attitudes to use of medical free text data in research

Objectives: Electronic health records (EHRs) contain rich information for understanding health conditions and their treatment. A large proportion of clinical information in EHRs is stored in narrative free text. This text is currently under-utilised due to privacy concerns, as it is harder to remove patient identifiers from text than from structured data. Automated de-identification of clinical text is now possible using heuristic or machine-learning-based systems. We conducted a review of the literature on patient and public understanding and attitudes towards the use of patients’ medical data for research, particularly seeking views on free text. The aim was to inform and develop a governance framework for the de-identification and use of medical free text for research, and to instigate a wider discussion on the topic. Approach: We undertook a systematic search in Web of Science and ScienceDirect with terms such as “public attitudes” and “electronic health records”. 3480 results were sifted by title, abstract and full text. Forty-two articles were retained for review, these reported on studies of patient and public perceptions, understanding and attitudes towards the use of patients’ medical data in research. Results: Research participants were positively inclined towards information in records being used in research “for the greater good”. However, no clear patterns by age, ethnicity, education level or SES emerged as to who was more favourable to data use. Participants generally trusted health care professionals and public sector researchers with de-identified medical data, whereas government health agencies and commercial entities were not trusted. No explicitly feared harms associated with data use were articulated. However the general objections appeared to be a dislike of personal data being exploited for commercial gain, and a dislike of personal data being moved around and used without personal knowledge or consent. Notably the use of EHR medical text for research did not emerge as a specific patient/public concern. De-identification was important to participants but text was not identified as a distinct privacy risk. Conclusion: This review demonstrates that transparency about data usage, and working “for the greater good” rather than financial gain, appear to be the most important public concerns to be addressed when using patients’ medical data. Governance frameworks for using EHRs must now be enhanced to provide for the use of medical text. This will involve informing both regulators and the public about the current capabilities of automated de-identification, and developing other assurances to safeguard patients’ privacy.