Data mining tool for academic data exploitation: selection of most suitable algorithms

SPEET project is aimed at exploiting the potential synergy among the huge amount of academic data actually existing at universities and the maturity of data science in order to provide tools to extract information from students’ data. A rich picture can be extracted from this data if conveniently processed. The purpose of this project is to apply data mining algorithms to process this data in order to extract information about and to identify student profiles. In this document, the results obtained at SPEET project under the development of the data mining tools are presented. More specifically, two mechanisms have been developed: a clustering/classification scheme of students in terms of academic performance and a drop-out prediction system. The document starts by addressing the motivation of the development of data mining tools along with the considerations taken into account for academic data gathering. These considerations include the proposed unified dataset format and some details about confidentiality issues. Next, the students’ clustering and classification schemes are presented in detail. More specifically, a description of the considered machine learning algorithms can be found. Besides, a discussion of obtained results when considering data belonging to the different SPEET project’s partners is addressed. Results show how groups of clusters can be automatically identified and how new students can be classified into existing groups with a high accuracy. Finally, the implemented drop-out prediction system is considered by presenting several algorithms alternatives. In this case, the evaluation of the dropout mechanism is focused on one institution, showing a prediction accuracy around 91 %. Algorithms presented at this document are available at repositories or inline code format, as accordingly indicated.info:eu-repo/semantics/publishedVersio

Mixed matrix membranes based on MIL-101 metal–organic frameworks in polymer of intrinsic microporosity PIM-1

This work presents a study on mixed matrix membranes (MMMs) of the polymer of intrinsic microporosity PIM-1, embedding the crystalline Cr-terephthalate metal-organic framework (MOF), known as MIL-101. Different kinds of MIL-101 were used: MIL-101 with an average particle size of ca. 0.2 µm, NanoMIL-101 (ca. 50 nm), ED-MIL-101 (MIL-101 functionalized with ethylene diamine) and NH2-MIL-101 (MIL-101 synthesized using 2-aminoterephthalic acid instead of terephthalic acid). Permeability, diffusion and solubility coefficients and their corresponding ideal selectivities were determined for the gases He, H2, O2, N2, CH4 and CO2 on the “as-cast” samples and after alcohol treatment. The performance of the MMMs was evaluated in relation to the Maxwell model. The addition of NH2-MIL-101 and ED-MIL-101 does not increase the membrane performance for the CO2/N2 and CO2/CH4 separation because of an initial decrease in selectivity at low MOF content, whereas the O2 and N2 permeability both increase for NH2-MIL-101. In contrast, MIL-101 and NanoMIL-101 cause a strong shift to higher permeability in the Robeson diagrams for all gas pairs, especially for CO2, without significant change in selectivity. Unprecedented CO2 permeabilities up to 35,600 Barrer were achieved, which are among the highest values reached with PIM-1 based mixed matrix membranes. For various gas pairs, the permeability and selectivity were far above the Robeson upper bound after alcohol treatment. Short to medium time aging shows that alcohol treated samples with MIL-101 maintain a systematically higher permeability in time. Mixed gas permeation experiments on an aged as-cast sample with 47 vol% MIL-101 reveal that the MMM sample maintains an excellent combination of permeability and selectivity, far above the Robeson upper bound (CO2 = 3500–3800 Barrer, CO2/N2 = 25–27; CO2/CH4 = 21–24). This suggests good perspectives for these materials in thin film composite membranes for real applications.</p

Smart garment for trunk posture monitoring: A preliminary study

© 2008 Wong and Wong; licensee BioMed Central Ltd

A novel method of using accelerometry for upper limb FES control.

This paper reports on a novel approach to using a 3-axis accelerometer to capture body segment angle for upper limb functional electrical stimulation (FES) control. The approach calculates the angle between the accelerometer x -axis and the gravity vector, while avoiding poor sensitivity at certain angles and minimizing errors when true acceleration is relatively large in comparison to gravity. This approach was incorporated into a state-machine controller which is used for the real-time control of FES during up- per limb functional task performance. An experimental approach was used to validate the new method. Two participants with different upper limb impairments resulting from a stroke carried out four different FES-assisted tasks. Comparisons were made between angle calculated from arm-mounted accelerometer data using our algorithm and angle calculated from limb-mounted reflective marker data. After removal of coordinate misalignment error, mean error across tasks and subjects ranged between 1.4 and 2.9 °. The approach shows promise for use in the control of upper limb FES and other human movement applications where true acceleration is relatively small in comparison with gravity

Mixed matrix membranes based on MIL-101 metal–organic frameworks in polymer of intrinsic microporosity PIM-1

This work presents a study on mixed matrix membranes (MMMs) of the polymer of intrinsic microporosity PIM-1, embedding the crystalline Cr-terephthalate metal-organic framework (MOF), known as MIL-101. Different kinds of MIL-101 were used: MIL-101 with an average particle size of ca. 0.2 µm, NanoMIL-101 (ca. 50 nm), ED-MIL-101 (MIL-101 functionalized with ethylene diamine) and NH2-MIL-101 (MIL-101 synthesized using 2-aminoterephthalic acid instead of terephthalic acid). Permeability, diffusion and solubility coefficients and their corresponding ideal selectivities were determined for the gases He, H2, O2, N2, CH4 and CO2 on the “as-cast” samples and after alcohol treatment. The performance of the MMMs was evaluated in relation to the Maxwell model. The addition of NH2-MIL-101 and ED-MIL-101 does not increase the membrane performance for the CO2/N2 and CO2/CH4 separation because of an initial decrease in selectivity at low MOF content, whereas the O2 and N2 permeability both increase for NH2-MIL-101. In contrast, MIL-101 and NanoMIL-101 cause a strong shift to higher permeability in the Robeson diagrams for all gas pairs, especially for CO2, without significant change in selectivity. Unprecedented CO2 permeabilities up to 35,600 Barrer were achieved, which are among the highest values reached with PIM-1 based mixed matrix membranes. For various gas pairs, the permeability and selectivity were far above the Robeson upper bound after alcohol treatment. Short to medium time aging shows that alcohol treated samples with MIL-101 maintain a systematically higher permeability in time. Mixed gas permeation experiments on an aged as-cast sample with 47 vol% MIL-101 reveal that the MMM sample maintains an excellent combination of permeability and selectivity, far above the Robeson upper bound (CO2 = 3500–3800 Barrer, CO2/N2 = 25–27; CO2/CH4 = 21–24). This suggests good perspectives for these materials in thin film composite membranes for real applications.</p

Phototoxicity induced in living HeLa cells by focused femtosecond laser pulses: a data-driven approach

Nonlinear optical microscopy is a powerful label-free imaging technology, providing biochemical and structural information in living cells and tissues. A possible drawback is photodamage induced by high-power ultrashort laser pulses. Here we present an experimental study on thousands of HeLa cells, to characterize the damage induced by focused femtosecond near-infrared laser pulses as a function of laser power, scanning speed and exposure time, in both wide-field and point-scanning illumination configurations. Our data-driven approach offers an interpretation of the underlying damage mechanisms and provides a predictive model that estimates its probability and extension and a safety limit for the working conditions in nonlinear optical microscopy. In particular, we demonstrate that cells can withstand high temperatures for a short amount of time, while they die if exposed for longer times to mild temperatures. It is thus better to illuminate the samples with high irradiances: thanks to the nonlinear imaging mechanism, much stronger signals will be generated, enabling fast imaging and thus avoiding sample photodamage

Differences in Preoperative Health-Related Quality of Life between Women Receiving Mastectomy or Breast Conserving Surgery in a Prospectively Recruited Cohort of Breast Cancer Patients

As rates of total mastectomy rise, the relationships between surgery modality with domains of health-related quality of life is not well understood. This study reports differences in depression, anxiety, pain, and health status among a cohort of women scheduled to receive total mastectomy or breast-conserving surgery. Patient-reported outcomes measured preoperative differences between patients receiving total mastectomy or breast-conserving surgery in a cross-sectional design. Regression analyses was used to model health outcomes and adjust for patient demographics on patient measures. Participants scheduled for total mastectomy were more likely to report more severe symptoms of depression and anxiety. This association was non-significant after adjusting for demographic differences. Younger participants were more likely to be scheduled for total mastectomy. Age was negatively associated with symptoms of depression and anxiety. Screening patients for mental health symptoms may be particularly important among younger patients who were more likely to report depression and anxiety before their surgery and were more likely to receive total mastectomy

Trunk posture monitoring with inertial sensors

Measurement of human posture and movement is an important area of research in the bioengineering and rehabilitation fields. Various attempts have been initiated for different clinical application goals, such as diagnosis of pathological posture and movements, assessment of pre- and post-treatment efficacy and comparison of different treatment protocols. Image-based methods for measurements of human posture and movements have been developed, such as the radiography, photogrammetry, optoelectric technique and video analysis. However, it is found that these methods are complicated to set up, time-consuming to operate and could only be applied in laboratory environments. This study introduced a method of using a posture monitoring system in estimating the spinal curvature changes during trunk movements on the sagittal and coronal planes and providing trunk posture monitoring during daily activities. The system consisted of three sensor modules, each with one tri-axial accelerometer and three uni-axial gyroscopes orthogonally aligned, and a digital data acquisition and feedback system. The accuracy of this system was tested with a motion analysis system (Vicon 370) in calibration with experimental setup and in trunk posture measurement with nine human subjects, and the performance of the posture monitoring system during daily activities with two human subjects was reported. The averaged root mean squared differences between the measurements of the system and motion analysis system were found to be <1.5° in dynamic calibration, and <3.1° for the sagittal plane and ≤2.1° for the coronal plane in estimation of the trunk posture change during trunk movements. The measurements of the system and the motion analysis system was highly correlated (>0.999 for dynamic calibration and >0.829 for estimation of spinal curvature change in domain planes of movement during flexion and lateral bending). With the sensing modules located on the upper trunk, mid-trunk and the pelvic levels, the inclination of trunk segment and the change of spinal curvature in trunk movements could be estimated. The posture information of five subjects was recorded at 30 s intervals during daily activity over a period of 3 days and 2 h a day. The preliminary results demonstrated that the subjects could improve their posture when feedback signals were provided. The posture monitoring system could be used for the purpose of posture monitoring during daily activity