Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Head Motion on the Evaluation of Age-related Brain Network Changes Using Resting State Functional MRI

Purpose: The estimation of functional connectivity (FC) measures using resting state functional MRI (fMRI) is often affected by head motion during functional imaging scans. Head motion is more common in the elderly than in young participants and could therefore affect the evaluation of age-related changes in brain networks. Thus, this study aimed to investigate the influence of head motion in FC estimation when evaluating age-related changes in brain networks. Methods: This study involved 132 healthy volunteers divided into 3 groups: elderly participants with high motion (OldHM, mean age (±SD) = 69.6 (±5.31), N = 44), elderly participants with low motion (OldLM, mean age (±SD) = 68.7 (±4.59), N = 43), and young adult participants with low motion (YugLM, mean age (±SD) = 27.6 (±5.26), N = 45). Head motion was quantified using the mean of the framewise displacement of resting state fMRI data. After preprocessing all resting state fMRI datasets, several resting state networks (RSNs) were extracted using independent component analysis (ICA). In addition, several network metrics were also calculated using network analysis. These FC measures were then compared among the 3 groups. Results: In ICA, the number of voxels with significant differences in RSNs was higher in YugLM vs. OldLM comparison than in YugLM vs. OldHM. In network analysis, all network metrics showed significant (P < 0.05) differences in comparisons involving low vs. high motion groups (OldHM vs. OldLM and OldHM vs. YugLM). However, there was no significant (P > 0.05) difference in the comparison involving the low motion groups (OldLM vs. YugLM). Conclusion: Our findings showed that head motion during functional imaging could significantly affect the evaluation of age-related brain network changes using resting state fMRI data.
The Spanish Family Quality of Life Scales under and over 18 Years Old: Psychometric Properties and Families’ Perceptions

Background: Family quality of life (FQoL), just like individual quality of life, has become a priority outcome in the policies and services received by persons with intellectual and developmental disabilities (IDD) and their families. Conceptualizing, measuring, and theorizing FQoL has been the object of investigation in recent decades. The goal of this paper is to present a revision of the Spanish Family Quality of Life Scales, the CdVF-E < 18 and the CdVF-E >18, and describe the FQoL of Spanish families with a member with IDD. Methods: The sample included a total of 548 families with a member under 18 years old and 657 families with a member over 18. Based on an Exploratory Factor Analysis (EFA) firstly and a Confirmatory Factor Analysis (CFA) secondly, the two scales’ psychometric properties were explored. Results: The CdVF-ER < 18 and the CdVF-ER > 18 comprise 5 dimensions, containing 35 and 32 items, respectively, and they show good validity and reliability. The families obtained a high FQoL score, although some differences exist between the dimensions on which families with children under and over 18 score highest and lowest. Conclusion: The characteristics of the revised scales facilitate their use by professionals, administrations, and services.
An Optimal Time for Treatment—Predicting Circadian Time by Machine Learning and Mathematical Modelling

Simple Summary Personalized cancer treatments show decreased side-effects and improved treatment success. One aspect of individualized treatment is the timing of medicine intake, which may be optimized based on the biological diurnal rhythm of the patient. The personal biological time can be assessed by a variety of tools not yet commonly included in diagnostics. We review these tools with a focus on their applicability in a clinical context. Using biological samples from the patient, most tools predict individual time using machine learning methodologies, often supported by rhythmicity analysis and mathematical core-clock models. We compare different approaches and discuss possible promising future directions. Abstract Tailoring medical interventions to a particular patient and pathology has been termed personalized medicine. The outcome of cancer treatments is improved when the intervention is timed in accordance with the patient’s internal time. Yet, one challenge of personalized medicine is how to consider the biological time of the patient. Prerequisite for this so-called chronotherapy is an accurate characterization of the internal circadian time of the patient. As an alternative to time-consuming measurements in a sleep-laboratory, recent studies in chronobiology predict circadian time by applying machine learning approaches and mathematical modelling to easier accessible observables such as gene expression. Embedding these results into the mathematical dynamics between clock and cancer in mammals, we review the precision of predictions and the potential usage with respect to cancer treatment and discuss whether the patient’s internal time and circadian observables, may provide an additional indication for individualized treatment timing. Besides the health improvement, timing treatment may imply financial advantages, by ameliorating side effects of treatments, thus reducing costs. Summarizing the advances of recent years, this review brings together the current clinical standard for measuring biological time, the general assessment of circadian rhythmicity, the usage of rhythmic variables to predict biological time and models of circadian rhythmicity.
Modelling the Directional Response of Fabry-Pérot Ultrasound Sensors

Fabry-Perot ultrasound sensors offer an alternative to traditional piezoelectric sensors for clinical and metrological applications, for example, measuring high intensity focused-ultrasound (HIFU) fields. In this thesis, a model of the frequency dependent directional response was developed based on the partial-wave method, treating the sensor as a multi-layered elastic structure. An open-source MATLAB toolbox called ElasticMatrix was developed to model acoustic and elastic-wave propagation in multi-layered structures with anisotropic material properties. The toolbox uses an object-oriented framework, giving it a simple scripting interface and allowing it to be expanded easily. The toolbox is capable of calculating and plotting reflection and transmission coefficients, slowness profiles, dispersion curves and displacement and stress fields. An additional MATLAB class is included to model the frequency-dependent directional response of Fabry-Perot ultrasound sensors. The model was validated, tested and compared with directional response measurements made on two glass-etalon sensors: an air-backed cover-slip sensor with well-known acoustic properties, and an all-hard-dielectric sensor. Features of the directional response were investigated and attributed to the critical angles of the substrate backing, and Lamb- and Rayleigh-modes propagating in the sensor. The directional response of two sensors with Parylene C (a commonly used soft-polymer) were also investigated: a sensor with a Parylene C spacer, and a glass-etalon sensor with a thick Parylene C coating. X-ray diffraction and transmission electron microscope measurements indicated Parylene has a crystal structure and impedance measurements indicated that Parylene is acoustically anisotropic. Using the measured impedance values, the modelled and measured directivity had improved agreement compared with isotropic values based on the phase-speeds of guided modes. The developed modelling tools allow detailed analysis of the physical mechanisms affecting the frequency-dependent directional response of planar Fabry-Perot sensors. This knowledge can be used to inform future sensor design, to aid with material selection, and for deconvolution of the sensor response from acoustic measurements.
Toxicity Evaluation of Nanostructured Silica Orally Administered to Rats: Influence on Immune System Function

The experimental data on the oral toxicity of nanostructured amorphous silica (SiO2), widely used in food supplements, pharmaceuticals, and cosmetics, in terms of its in vivo effect on the immune system, are contradictory. Therefore, this study aimed to assess the rat’s immune function after SiO2 oral administration. In the first experiment, SiO2 was daily orally administered to Wistar rats for 92 days in doses of 0.1, 1.0, 10, and 100 mg/kg of body weight (bw). In the second 28-day experiment, SiO2 in a dose of 100 mg/kg bw was daily orally administered to rats parenterally immunized with the food allergen ovalbumin (OVA) for the reproduction of systemic anaphylaxis reaction. Together with integral indices, we assessed intestinal permeability to protein macromolecules; hematology; CD45RA+, CD3+, CD4+, CD8+, and CD161a+ cells; cytokines TNF-α, IL-6, and IL-10; and IgG to OVA. The results obtained showed that SiO2 has no effect on the severity of the anaphylactic reaction, but is capable inducing a toxic effect on the T-cell immune systems of rats. Estimated no observed adverse effect level NOAEL for SiO2 ranges up to 100 mg/kg bw in terms of its daily consumption for 1–3 months. Using SiO2 as a food additive should be the subject of regulation.
Towards sustainable energy materials : broadening life cycle assessment for emerging technology development and resource-effective choices

Energy materials are particularly important from a sustainability perspective for advancing renewable energy systems, including energy production and storage. Their appropriate use and development require quantitative assessment methods. Life Cycle Assessment (LCA) is a method to support sustainable development that can be used to identify environmental hotspots and compare different technologies. The purpose of this research is to support development of several energy materials and make LCA a more relevant tool for sustainability assessment by extending its use in two emerging directions: assessment of technologies at the early stage of development, and by supporting more resource-effective choices for a circular economy.The research objectives focus on informing the development of technologies and identifying methodological challenges and opportunities by applying LCA to three energy-technology case studies, each at a different technological maturity level. In the first case study, alkaline batteries, currently at a high maturity level (incumbent products), are evaluated using LCA in combination with a circular economy indicator, the Material Circularity Indicator (MCI). The aim was to investigate opportunities to combine the two methods, while considering trade-offs between indicators for different strategies for battery design and management. In the second case study, nickel-cobalt hydroxide charge storage electrodes, currently at a low maturity level (laboratory-scale), are evaluated to investigate environmental hotspots and preferred synthesis route. In the third case study, organic photovoltaic portable chargers for small electronics, currently at a medium maturity level (pilot-scale), are evaluated for replacing conventional electricity grid for charging a mobile phone.
Characteristics and Performances of a Nanostructured Material for Passive Samplers of Gaseous Hg

Passive air samplers (PASs) have been used for mapping gaseous mercury concentration in extensive areas. In this work, an easy-to-use and -prepare gold nanoparticle (NP)-based PAS has been investigated. The PAS is constituted of a microfibrous quartz disk filter impregnated of gold NP photo-growth on TiO2 NPs (Au@TiO2) and used as gaseous mercury adsorbing material. The disk was housed in a cylinder glass container and subjected to an axial diffusive sampling. The adsorbed mercury was measured by thermal desorption using a Tekran® instrument. Different amounts of Au@TiO2 (ranging between 4.0 and 4.0 × 10−3 mg) were deposited by drop-casting onto the fibrous substrate and assessed for about 1 year of deployment in outdoor environment with a mercury concentration mean of about 1.24 ± 0.32 ng/m3 in order to optimize the adsorbing layer. PASs showed a linear relation of the adsorbed mercury as a function of time with a rate of 18.5 ± 0.4 pg/day (≈1.5% of the gaseous concentration per day). However, only the PAS with 4 mg of Au@TiO2, provided with a surface density of about 3.26 × 10−2 mg/mm2 and 50 μm thick inside the fibrous quartz, kept stability in working, with a constant sampling rate (SR) (0.0138 ± 0.0005 m3/day) over an outdoor monitoring experimental campaign of about 1 year. On the other hand, higher sampling rates have been found when PASs were deployed for a few days, making these tools also effective for one-day monitoring. Furthermore, these PASs were used and re-used after each thermal desorption to confirm the chance to reuse such structured layers within their samplers, thus supporting the purpose to design inexpensive, compact and portable air pollutant sampling devices, ideal for assessing both personal and environmental exposures. During the whole deployment, PASs were aided by simultaneous Tekran® measurements.
Spatio-temporal diversity of the mosquito fauna (Diptera: Culicidae) in Switzerland

The spatio-temporal diversity of the Swiss mosquito fauna was investigated at eight locations distributed throughout the country (altitude between 198 and 1,255 meters above sea level) by five samplings over two years (July 2011 to September 2012). At each location at two sites (nature zone, suburban zone), mosquito immature stages were collected in 15-30 larval habitats (LH), and adults were trapped with CO 2 -baited traps. Mosquitoes were morphologically identified to species or sister taxa / species complex level. Mosquitoes were found at all sites. Among the 1,362 LHs inspections, 36.7% revealed the presence of mosquito immature stages, and around 9,000 specimens were identified. Adult trapping yielded around 2,000 mosquitoes. Fifteen mosquito species, 3 sibling species (of which all 6 species were confirmed) and the Anopheles maculipennis complex were collected. The nature zones showed the higher diversity (all species observed) but a lower relative abundance as compared to the suburban zones (overall 11 species and 2 sibling species identified). The most abundant species was Culex. pipiens / torrentium (61.2% of all specimens collected) occurring at all except two sites. Six species were frequently observed ( Cx. hortensis , Aedes japonicus , An. maculipennis complex members, Ae. vexans , Ae. cinereus / geminus , and Ae. sticticus , accounting for 8.5% to 3.9%, respectively, of the individuals). Six of these seven most abundant species have a potential to act as vector. The highest relative abundances of the mosquito fauna, all species, were observed in June and July, for both nature and suburban zones, with peak abundances of different species varying from June to September. The experimental approach (repeated larval sampling and CO 2 -baited trapping) looks reliable for collecting most of the mosquito species. From the 36 mosquito species known to Switzerland, only 13 were not detected during the study: Ae. albopictus which is present in southern Ticino outside the study area only; 12 other species which are known to be rare or to occur at high altitudes. In addition to Ae. albopictus , the other invasive species Ae. japonicus shows a remarkable distribution,
Mapping Utility Poles in Aerial Orthoimages Using ATSS Deep Learning Method

Mapping utility poles using side-view images acquired with car-mounted cameras is a time-consuming task, mainly in larger areas due to the need for street-by-street surveying. Aerial images cover larger areas and can be feasible alternatives although the detection and mapping of the utility poles in urban environments using top-view images is challenging. Thus, we propose the use of Adaptive Training Sample Selection (ATSS) for detecting utility poles in urban areas since it is a novel method and has not yet investigated in remote sensing applications. Here, we compared ATSS with Faster Region-based Convolutional Neural Networks (Faster R-CNN) and Focal Loss for Dense Object Detection (RetinaNet ), currently used in remote sensing applications, to assess the performance of the proposed methodology. We used 99,473 patches of 256 × 256 pixels with ground sample distance (GSD) of 10 cm. The patches were divided into training, validation and test datasets in approximate proportions of 60%, 20% and 20%, respectively. As the utility pole labels are point coordinates and the object detection methods require a bounding box, we assessed the influence of the bounding box size on the ATSS method by varying the dimensions from 30×30 to 70×70 pixels. For the proposal task, our findings show that ATSS is, on average, 5% more accurate than Faster R-CNN and RetinaNet. For a bounding box size of 40×40, we achieved Average Precision with intersection over union of 50% (AP50) of 0.913 for ATSS, 0.875 for Faster R-CNN and 0.874 for RetinaNet. Regarding the influence of the bounding box size on ATSS, our results indicate that the AP50 is about 6.5% higher for 60×60 compared to 30×30. For AP75, this margin reaches 23.1% in favor of the 60×60 bounding box size. In terms of computational costs, all the methods tested remain at the same level, with an average processing time around of 0.048 s per patch. Our findings show that ATSS outperforms other methodologies and is suitable for developing operation tools that can automatically detect and map utility poles.
Personalization of Aspirin Therapy Ex Vivo in Patients with Atherosclerosis Using Light Transmission Aggregometry

Acetylsalicylic acid (ASA), also known as aspirin, appears to be ineffective in inhibiting platelet aggregation in 20–30% of patients. Light transmission aggregometry (LTA) is a gold standard platelet function assay. In this pilot study, we used LTA to personalize ASA therapy ex vivo in atherosclerotic patients. Patients were recruited who were on 81 mg ASA, presenting to ambulatory clinics at St. Michael’s Hospital (n = 64), with evidence of atherosclerotic disease defined as clinical symptoms and diagnostic findings indicative of symptomatic peripheral arterial disease (PAD), with an ankle brachial index (ABI) of <0.9 (n = 52) or had diagnostic features of asymptomatic carotid arterial stenosis (CAS), with >50% stenosis of internal carotid artery on duplex ultrasound (n = 12). ASA compliance was assessed via multisegmented injection-capillary electrophoresis-mass spectrometry based on measuring the predominant urinary ASA metabolite, salicyluric acid. LTA with arachidonic acid was used to test for ASA sensitivity. Escalating ASA dosages of 162 mg and 325 mg were investigated ex vivo for ASA dose personalization. Of the 64 atherosclerotic patients recruited, 8 patients (13%) were non-compliant with ASA. Of ASA compliant patients (n = 56), 9 patients (14%) were non-sensitive to their 81 mg ASA dosage. Personalizing ASA therapy in 81 mg ASA non-sensitive patients with escalating dosages of ASA demonstrated that 6 patients became sensitive to a dosage equivalent to 162 mg ASA and 3 patients became sensitive to a dosage equivalent to 325 mg ASA. We were able to personalize ASA dosage ex vivo in all ASA non-sensitive patients with escalating dosages of ASA within 1 h of testing.
Glaucoma as a prognostic factor of central retinal vein occlusion: visual and anatomical outcomes and occurrence of ischaemic central retinal vein occlusion

To compare the functional and anatomical outcomes of central retinal vein occlusion (CRVO) according to the presence of glaucoma before the onset of CRVO, and to assess whether pre‐existing glaucoma affects the prognosis of CRVO in terms of development and conversion to ischaemic CRVO.
The impact of Israeli Geopolitical Risks on the Lebanese Financial Market: A Destabilizer Multiplier

This paper is the first econometric study that investigates empirically the impact of Israeli Geopolitical Risks on the Lebanese financial market. We run Vector Autoregression model, Granger causality tests, generalized impulse response functions and Variance Decomposition Analysis, to assess the impacts of Israeli Geopolitical Risks (GPRs) on the Lebanese financial stability, on the foreign reserves’ depletion and the economic activity. To measure the Lebanese financial stability, we consider the Lebanese financial stress index that was initially calculated by Ishrakieh et al. (2019, 2020). The geopolitical risks index is measured by taking the continuous variable calculated on a monthly basis to best suit time series analyses, calculated by Dario Caldara & Matteo Iacoviello in 2018. This paper illustrates many novelties such as incorporating the Lebanese financial stress index for the first time in an empirical-econometric study. Also, the adequate level of foreign reserves (also known as international reserves) is taken by calculating the ratio of international reserves to foreign currency deposits as a more appropriate measurement for a dollarized country. Similarly, to measure the economic activity and the business cycle on a monthly basis, we consider the employment in private sector as a better proxy than traditional variables considered in previous studies. Results show that if any financial crisis occurs in Lebanon, an economic recession is more likely to follow within six months. Also, we find that foreign reserves ‘shocks may cause a financial crisis thus economic recession. Finally, we conclude that Israeli GPRs are somehow a destabilizer multiplier: they trigger financial instability and economic recession in Lebanon. They cause international reserves’ depletion, threaten the Lebanese financial market and provoke economic recession. To sustain financial market stability, policy makers should not only accumulate sufficient level of foreign reserves, but also, they have to avoid Israeli-Hezbollah tensions.
Photosynthetic Responses of Canola to Exogenous Application or Endogenous Overproduction of 5-Aminolevulinic Acid (ALA) under Various Nitrogen Levels

Limited data are available on the effects of 5-aminolevulinic acid (ALA) on plant photosynthesis in relation to the nitrogen (N) level. In this study, we investigate photosynthetic responses to ALA in canola plants (Brassica napus L.). We used wild-type plants without ALA addition (controls), wild-type plants with exogenous ALA application, and transgenic plants that endogenously overproduced ALA. The plants were grown hydroponically in nutrient solutions with low, middle, and high concentrations of N. Our results indicate that plants in both treatment groups had higher chlorophyll contents and net photosynthetic rates and lower intracellular CO2 concentrations in the leaves, as compared to controls. Furthermore, simultaneous measurement of prompt chlorophyll fluorescence and modulated 820-nm reflections showed that the active photosystem II (PS II) reaction centers, electron transfer capacity, and photosystem I (PS I) activity were all higher in treated plants than controls at all N levels; however, the responses of some photochemical processes to ALA were significantly affected by the N level. For example, under low N conditions only, a negative ΔK peak appeared in the prompt chlorophyll fluorescence curve, indicating a protective effect of ALA on electron donation via activation of the oxygen-evolving complex. Taken together, our findings suggest that ALA contributes to the promotion of photosynthesis by regulating photosynthetic electron transport under various N levels. These findings may provide a new strategy for improving photosynthesis in crops grown in N-poor conditions or reduced N-fertilization requirements.