Hirschsheridan1636

The purpose of this study was to carry out a literature review on the effectiveness of the validation method (VM) in job satisfaction and motivation of care professionals working with older people in nursing homes. The review was carried out in specialised databases Scopus, PsychINFO, PubMed, Web of Science (WOS), Google Scholar, Scielo, and Cochrane Database of Systematic Reviews. 9046 results were obtained, out of which a total of 14 studies met the inclusion criteria five quantitative, four qualitative, one single case series, two quasi-experimental and two mixed methods studies. The results of the analysed studies report that the VM can be an effective tool that facilitates communication and interaction in care, reducing levels of stress and job dissatisfaction among care professionals. The VM facilitates communication between professionals and older people with dementia, and improves the management of complex situations that may arise in care, directly influencing a reduction in work stress and increasing job satisfaction.With the increasing aging population in modern society, falls as well as fall-induced injuries in elderly people become one of the major public health problems. This study proposes a classification framework that uses floor vibrations to detect fall events as well as distinguish different fall postures. A scaled 3D-printed model with twelve fully adjustable joints that can simulate human body movement was built to generate human fall data. The mass proportion of a human body takes was carefully studied and was reflected in the model. Object drops, human falling tests were carried out and the vibration signature generated in the floor was recorded for analyses. Machine learning algorithms including K-means algorithm and K nearest neighbor algorithm were introduced in the classification process. Three classifiers (human walking versus human fall, human fall versus object drop, human falls from different postures) were developed in this study. Results showed that the three proposed classifiers can achieve the accuracy of 100, 85, and 91%. This paper developed a framework of using floor vibration to build the pattern recognition system in detecting human falls based on a machine learning approach.Carcinogenicity is a crucial endpoint for the safety assessment of chemicals and products. During the last few decades, the development of quantitative structure-activity relationship ((Q)SAR) models has gained importance for regulatory use, in combination with in vitro testing or expert-based reasoning. Several classification models can now predict both human and rat carcinogenicity, but there are few models to quantitatively assess carcinogenicity in humans. To our knowledge, slope factor (SF), a parameter describing carcinogenicity potential used especially for human risk assessment of contaminated sites, has never been modeled for both inhalation and oral exposures. In this study, we developed classification and regression models for inhalation and oral SFs using data from the Risk Assessment Information System (RAIS) and different machine learning approaches. The models performed well in classification, with accuracies for the external set of 0.76 and 0.74 for oral and inhalation exposure, respectively, and r2 values of 0.57 and 0.65 in the regression models for oral and inhalation SFs in external validation. These models might therefore support regulators in (de)prioritizing substances for regulatory action and in weighing evidence in the context of chemical safety assessments. Moreover, these models are implemented on the VEGA platform and are now freely downloadable online.Conformational transitions in multidomain proteins are essential for biological functions. The Apo conformations are typically open and flexible, while the Holo states form more compact conformations stabilized by protein-ligand interactions. Unfortunately, the atomically detailed mechanisms for such open-closed conformational changes are difficult to be accessed experimentally as well as computationally. To simulate the transitions using atomistic molecular dynamics (MD) simulations, efficient conformational sampling algorithms are required. In this work, we propose a new approach based on generalized replica-exchange with solute tempering (gREST) for exploring the open-closed conformational changes in multidomain proteins. Wherein, selected surface charged residues in a target protein are defined as the solute region in gREST simulation and the solute temperatures are different in replicas and exchanged between them to enhance the domain motions. This approach is called gREST selected surface charged residues (gREST_SSCR) and is applied to the Apo and Holo states of ribose binding protein (RBP) in solution. The conformational spaces sampled with gREST_SSCR are much wider than those with the conventional MD, sampling open-closed conformational changes while maintaining RBP domains' stability. The free-energy landscapes of RBP in the Apo and Holo states are drawn along with twist and hinge angles of the two moving domains. The inter-domain salt-bridges that are not observed in the experimental structures are also important in the intermediate states during the conformational changes.The heating of a biologic solution is a crucial part in an amplification process such as the catalytic detection of a biological target. However, in many situations, heating must be limited in microfluidic devices, as high temperatures can cause the denaturation of the chip components. Local heating through magnetic hyperthermia on magnetic nano-objects has opened the doors to numerous improvements, such as for oncology where a reduced heating allows the synergy of chemotherapy and thermotherapy. Here we report on the design and implementation of a lab on chip without global heating of samples. It takes advantage of the extreme efficiency of DNA-modified superparamagnetic core-shell nanoparticles to capture complementary sequences (microRNA-target), uses magnetic hyperthermia to locally release these targets, and detects them through electrochemical techniques using ultra-sensitive channel DNA-modified ultramicroelectrodes. The combination of magnetic hyperthermia and microfluidics coupled with on-chip electrochemistry opens the way to a drastic reduction in the time devoted to the steps of extraction, amplification and nucleic acids detection. The originality comes from the design and microfabrication of the microfluidic chip suitable to its insertion in the millimetric gap of toric inductance with a ferrite core.We formulate and analyze a generic coverage optimization problem arising in wireless sensor networks with sensors of limited mobility. Given a set of targets to be covered and a set of mobile sensors, we seek a sensor dispatch algorithm maximizing the covered targets under the constraint that the maximal moving distance for each sensor is upper-bounded by a given threshold. We prove that the problem is NP-hard. Given its hardness, we devise four algorithms to solve it heuristically or approximately. Among the approximate algorithms, we first develop randomized (1-1/e)-optimal algorithm. We then employ a derandomization technique to devise a deterministic (1-1/e)-approximation algorithm. We also design a deterministic approximation algorithm with nearly ▵-1 approximation ratio by using a colouring technique, where denotes the maximal number of subsets covering the same target. Experiments are also conducted to validate the effectiveness of the algorithms in a variety of parameter settings.Staphylococcus aureus is a bacterium which people have been in contact with for thousands of years. Its presence often leads to severe disorders of the respiratory and circulatory systems. The authors of this article present a prototype of a textronic sensor enabling the detection of this bacterium. This sensor was created using a process of physical vacuum deposition on a flexible textile substrate which can be implemented on clothing. With increasing numbers of bacterial colonies, changes in the sensor's electrical parameters were observed. The sensor's resistance reduced by 50% and the capacitance more than doubled within the first two days of starting bacterial cultures. Extensive changes in electrical parameters were observed at 100 Hz and 120 Hz of the measurement signal.As the outermost barrier of the body, skin is a major target of oxidative stress. read more In the brain, estrogen has been reported synthesized locally and protects neurons from oxidative stress. Here, we explored whether estrogen is also locally synthesized in the skin to protect from oxidative stress and whether aberrant local estrogen synthesis is involved in skin disorders. Enzymes and estrogen receptor expression in skin cells were examined first by quantitative real-time PCR and Western blot analyses. Interestingly, the estrogen synthesis enzyme was mainly localized in epidermal keratinocytes and estrogen receptors were mainly expressed in melanocytes among 13 kinds of cultured human skin cells. The most abundant estrogen synthesis enzyme expressed in the epidermis was 17β-hydroxysteroid dehydrogenase 1 (HSD17β1) localized in keratinocytes, and the most dominant estrogen receptor expressed in the epidermis was G protein-coupled estrogen receptor 1 (GPER1) in melanocytes. To investigate whether keratinocyte-derived estradiol could protect melanocytes from oxidative stress, cultured human primary epidermal melanocytes (HEMn-MPs) were treated with H2O2 in the presence or absence of 17β estradiol or co-cultured with HSD17β1 siRNA-transfected keratinocytes. Keratinocyte-derived estradiol exhibited protective effects against H2O2-induced cell death. Further, reduced expression of HSD17β1 in the epidermis of skin from vitiligo patients was observed compared to the skin from healthy donors or in the normal portions of the skin in vitiligo patients. Our results suggest a possible new target for interventions that may be used in combination with current therapies for patients with vitiligo.In recent research activities, shake-table tests were revealed to be useful to investigate the seismic behavior of cold-formed steel (CFS) buildings. However, testing full-scale buildings or reduced-scale prototypes is not always possible; indeed, predicting tools and numerical models could help designers to evaluate earthquake response. For this reason, numerical modelling of two strap-braced prototype buildings, recently tested on shake-table at University of Naples Federico II in cooperation with Lamieredil S.p.A. company, was developed. The models were validated trough the comparison between experimental and numerical results, in term of dynamic properties (fundamental period of vibration and modal shapes), peak roof drift ratios and peak inter-story drift ratios. Although dynamic properties of mock-ups were captured with accuracy by the developed models, the comparison highlighted the need to consider accumulation of damage and rocking phenomenon in the modelling to capture with good accuracy the seismic behavior of CFS strap-braced building, subjected to high intensity records.Polylactic acid (PLA) films containing 1 wt % and 3 wt % of lignin nanoparticles (pristine (LNP), chemically modified with citric acid (caLNP) and acetylated (aLNP)) were prepared by extrusion and characterized in terms of their overall performance as food packaging materials. Morphological, mechanical, thermal, UV-Vis barrier, antioxidant and antibacterial properties were assayed; appropriate migration values in food simulants and disintegration in simulated composting conditions were also verified. The results obtained indicated that all lignin nanoparticles succeeded in conferring UV-blocking, antioxidant and antibacterial properties to the PLA films, especially at the higher filler loadings assayed. Chemical modification of the fillers partially reduced the UV protection and the antioxidant properties of the resulting composites, but it induced better nanoparticles dispersion, reduced aggregates size, enhanced ductility and improved aesthetic quality of the films through reduction of the characteristic dark color of lignin.