Tracing the refinement of policy tools for disability rights: a content analysis of how the granting process of state-funded personal assistance in Sweden is aligned with the LSS Act.

PURPOSE: According to the Swedish Act concerning Support and Service for Persons with Certain Functional Impairments (The LSS Act), personal assistance (PA) aims to enhance good living conditions for people with disability. The Act is operationalised by a policy tool, an instruction developed and refined by the Swedish Social Insurance Agency (SSIA) to grant PA. The study explores how this instruction is aligned with the LSS rationale and goals. MATERIAL AND METHOD: Qualitative content analysis was applied on the material i.e., a government bill preceding the LSS Act and the policy tool, i.e., the SSIA instruction, versions 1994 and 2019. RESULTS: The result shows that the instruction has deviated from the LSS Act over time, by decreasing users' access to community life, a shift towards health care activities, lack of support for the PA user, increased control and service-granting criteria. CONCLUSION: This paper emphasises that the selection of policy tools goes beyond mere pragmatism, as they are subject to refinement procedures that have significant impacts over time. The deviations observed in fulfilling the objectives of the LSS Act highlights the importance of ongoing adjustments to policy tools to align with the original policy goals in order to promote disability rights.

The study explored how policy tools, which serve as compulsory guidance by outlining the personal assistance granting process for local caseworkers, align with the rationale and policy goals of the Swedish Disability Act and policy goals, aiming to enhance good living conditions for people with disabilities.The designs of policy tools are frequently revised and adjusted and consequently influence policy outcome over time.Since policy tools are important for the implementation of government policy they need to be reviewed and monitored in order to secure original policy goals with the ultimate aim of enhancing good living conditions and advancing disability rights.

Effects of temporary access to environmental enrichment on measures of laboratory mouse welfare.

Laboratory mice are typically housed in "shoebox" cages with limited opportunities to engage in natural behaviour. Temporary access to environments with increased space and complexity (playpens) may improve mouse welfare. Previous work by our group has shown that mice are motivated to access and use these environments, but it is unknown how other aspects of welfare are impacted. Female C57BL/6J, BALB/cJ, and DBA/2J mice (n = 21; 7 mice per strain) were housed in mixed-strain trios and given temporary access to a large playpen with their cage mates three times per week. Control mice (n = 21; 7 mice per strain) remained in their home cages. Home cage behaviour (development of stereotypic behaviour over time, aggression following cage-changing) and anxiety tests were used to assess how playpen access impacted welfare. Contrary to our predictions, we found increased time spent performing stereotypies in playpen mice; this difference may be related to negative emotional states, increased motivation to escape the home cage, or active coping strategies. Playpen access resulted in strain-dependent improvements in aggression and some measures of anxiety. Aggression was lower for C57BL/6J mice in the playpen treatment following cage changing than it was for C57BL/6J control mice, while playpen mice, and particularly the C57BL/6J strain, spent more time in the center of the open field test and produced fewer fecal boli during anxiety testing, supporting other research showing that strain differences play an important role in behaviour and stress resiliency.

In some cases more complicated approaches to refinement of macromolecular structures are not necessary.

The manuscript `Modeling a unit cell: crystallographic refinement procedure using the biomolecular MD simulation platform Amber' presents a novel protein structure refinement method claimed to offer improvements over traditional techniques like Refmac5 and Phenix. Our re-evaluation suggests that while the new method provides improvements, traditional methods achieve comparable results with less computational effort.

Evaluating the efficacy and suggesting technical optimizations for endoscopic lumbar interbody fusion across different lumbar spondylolisthesis types.

Purpose: To evaluate the efficacy of the endoscopic lumbar interbody fusion technique across different types of lumbar spondylolisthesis, specifically Grade I and Grade II, and suggest technical optimizations based on therapeutic outcomes, complications, and patient satisfaction for both grades. Methods: We analyzed data from 57 L4 to 5 spondylolisthesis patients, all categorized as either Grade I or Grade II, comprising 31 males and 26 females. Of these, 36 were diagnosed with Grade I and 21 with Grade II. All subjects underwent the endoscopic lumbar interbody fusion procedure. Primary evaluation metrics included pre and post-operative Vasual Analogue Scale（VAS） pain scores, Osewewtry Disability Index（ODI） functional scores, surgical duration, intraoperative blood loss, degree of spondylolisthesis correction, complications, and patient satisfaction levels. Results: At a minimum of 6 months post-operation, the VAS score for the Grade I cohort reduced from an initial 7.30 ± 0.69 to 2.97 ± 0.47, while the Grade II cohort saw a decrease from 7.53 ± 0.56 to 3.37 ± 0.62 (P = 0.0194). The ODI score in the Grade I group declined from 66.88 ± 5.15 % pre-operation to 29.88 ± 6.36 % post-operation, and in the Grade II group, it decreased from 69.33 ± 5.27 % to 34.66 ± 6.01 % (P = 0.0092). The average surgical duration for the Grade I group stood at 155.72 ± 17.75 min, compared to 180.38 ± 14.72 min for the Grade II group (P < 0.001). The mean intraoperative blood loss for the Grade I group was 144.58 ± 28.61 ml, whereas the Grade II group registered 188.23 ± 9.41 ml (P < 0.001). Post-surgery, 83 % of the Grade I patients achieved a correction degree exceeding 80 %, and 61 % of the Grade II patients surpassed 50 % (P = 0.0055). Complication rates were recorded at 8 % for Grade I and 16 % for Grade II. Patient satisfaction reached 94 % in the Grade I cohort and 90 % in the Grade II cohort. Conclusion: Endoscopic lumbar interbody fusion showcases promising therapeutic outcomes for both Grade I and Grade II lumbar spondylolisthesis. However, surgeries for Grade II spondylolisthesis tend to be lengthier, more challenging, involve greater blood loss, and have a heightened complication risk. Tailored technical adjustments and enhancements are essential for addressing the distinct spondylolisthesis types.

Circadian variations influence anxiety-related behaviour, olfaction, and hedonic response in male Sprague-Dawley rats.

INTRODUCTION: Despite the acknowledged impact of circadian rhythms on various aspects of life, behavioural tests with laboratory animals often overlook alignment with their natural activity patterns. This study aims to evaluate the influence of circadian variations on the results, validity, and reliability of different behavioural tests in rats. METHODS: Three behavioural tests, the Light-Dark Box Test (LDB), assessing anxiety-related behaviour and locomotor activity; the Buried Pellet Test (BPT), revealing olfactory abilities and motivation issues; and the Sucrose Preference Test (SPT), studying the anhedonic response, were employed to encompass multiple daytime-dependent behavioural aspects in male Sprague-Dawley rats. RESULTS: Our findings underscore distinct circadian effects on locomotor activity, exploratory behaviour, olfactory acuity, motivation, and hedonic response. Notably, anxious behaviour remained unaffected by daytime conditions. Furthermore, decreased data variance was found to be correlated with conducting behavioural tests during the subjects' active phase. DISCUSSION: This study demonstrates extensive circadian influences on nearly all parameters investigated, coupled with a significant reduction in data variability during the active phase. Emphasising the importance of aligning experimental timing with rats' natural activity patterns, our results suggest that conducting tests during the active phase of the animals not only refines test sensitivity , reduces stress, and provides more representative data, but also contributes to ethical animal research (3 R) and improves test relevance. This, in turn, enhances the reliability and validity of experimental outcomes in behavioural research and promotes animal welfare.

Refinement of Docked Protein-Protein Complexes Using Repulsive Scaling Replica Exchange Simulations.

Accurate prediction and evaluation of protein-protein complex structures is of major importance to understand the cellular interactome. Predicted complex structures based on deep learning approaches or traditional docking methods require often structural refinement and rescoring for realistic evaluation. Standard molecular dynamics (MD) simulations are time-consuming and often do not structurally improve docking solutions. Better refinement can be achieved with our recently developed replica-exchange-based scheme employing different levels of repulsive biasing between proteins in each replica simulation (RS-REMD). The bias acts specifically on the intermolecular interactions based on an increase in effective pairwise van der Waals radii without changing interactions within each protein or with the solvent. It allows for an improvement of the predicted protein-protein complex structure and simultaneous realistic free energy scoring of protein-protein complexes. The setup of RS-REMD simulations is described in detail including the application on two examples (all necessary scripts and input files can be obtained from https://gitlab.com/TillCyrill/mmib ).

LBRT: Local-Information-Refined Transformer for Image Copy-Move Forgery Detection.

The current deep learning methods for copy-move forgery detection (CMFD) are mostly based on deep convolutional neural networks, which frequently discard a large amount of detail information throughout convolutional feature extraction and have poor long-range information extraction capabilities. The Transformer structure is adept at modeling global context information, but the patch-wise self-attention calculation still neglects the extraction of details in local regions that have been tampered with. A local-information-refined dual-branch network, LBRT (Local Branch Refinement Transformer), is designed in this study. It performs Transformer encoding on the global patches segmented from the image and local patches re-segmented from the global patches using a global modeling branch and a local refinement branch, respectively. The self-attention features from both branches are precisely fused, and the fused feature map is then up-sampled and decoded. Therefore, LBRT considers both global semantic information modeling and local detail information refinement. The experimental results show that LBRT outperforms several state-of-the-art CMFD methods on the USCISI dataset, CASIA CMFD dataset, and DEFACTO CMFD dataset.

Hot Deformation Constitutive Analysis and Processing Maps of Ultrasonic Melt Treated A5052 Alloy.

Hot deformation constitutive analysis and processing maps of ultrasonic melt treated (UST) A5052 alloy were carried out based on a hot torsion test in this study. The addition of the Al-Ti master alloy as a grain refiner with no UST produced a finer grain size than the UST and pure Ti sonotrode. The Al3Ti phase particles in the case of the Al-10Ti master alloy acted as a nucleus for grain refinement, while the Ti atoms dissolved in the melt from the sonotrode were considered to have less of a grain refinement effect, even under UST conditions, than the Al3Ti phase particles in the Al-Ti master alloy. The constitutive equations for each experimental condition by torsion test were derived. In the processing maps examined in this study, the flow instability region was not present under UST in the as-cast condition, but it existed under the no UST condition. The effects of UST examined in this study are considered as (i) the uniform distribution of Ti solutes from the sonotrode and (ii) the reduction of pores by the degassing effect. After the homogenization heat treatment, most instability regions disappeared because the microstructures became uniform following the decomposition of intermetallic compounds and distribution of solute elements.

Effect of Glycerol and Sisal Nanofiber Content on the Tensile Properties of Corn Starch/Sisal Nanofiber Films.

Currently, petroleum-derived plastics are widely used despite the disadvantage of their long degradation time. Natural polymers, however, can be used as alternatives to overcome this obstacle, particularly cornstarch. The tensile properties of cornstarch films can be improved by adding plant-derived nanofibers. Sisal (Agave sisalana), a very common low-cost species in Brazil, can be used to obtain plant nanofibers. The goal of this study was to obtain sisal nanofibers using low concentrations of sulfuric acid to produce thermoplastic starch nanocomposite films. The films were produced by a casting technique using commercial corn starch, glycerol, and sisal nanofibers, accomplished by acid hydrolysis. The effects of glycerol and sisal nanofiber content on the tensile mechanical properties of the nanocomposites were investigated. Transmission electron microscopy findings demonstrated that the lowest concentration of sulfuric acid produced fibers with nanometric dimensions related to the concentrations used. X-ray diffraction revealed that the untreated fibers and fibers subjected to acid hydrolysis exhibited a crystallinity index of 61.06 and 84.44%, respectively. When the glycerol and nanofiber contents were 28 and 1%, respectively, the tensile stress and elongation were 8.02 MPa and 3.4%. In general, nanocomposites reinforced with sisal nanofibers showed lower tensile stress and higher elongation than matrices without nanofibers did. These results were attributed to the inefficient dispersion of the nanofibers in the polymer matrix. Our findings demonstrate the potential of corn starch nanocomposite films in the packaging industry.

HRGCNLDA: Forecasting of lncRNA-disease association based on hierarchical refinement graph convolutional neural network.

Long non-coding RNA (lncRNA) is considered to be a crucial regulator involved in various human biological processes, including the regulation of tumor immune checkpoint proteins. It has great potential as both a cancer biomolecular biomarker and therapeutic target. Nevertheless, conventional biological experimental techniques are both resource-intensive and laborious, making it essential to develop an accurate and efficient computational method to facilitate the discovery of potential links between lncRNAs and diseases. In this study, we proposed HRGCNLDA, a computational approach utilizing hierarchical refinement of graph convolutional neural networks for forecasting lncRNA-disease potential associations. This approach effectively addresses the over-smoothing problem that arises from stacking multiple layers of graph convolutional neural networks. Specifically, HRGCNLDA enhances the layer representation during message propagation and node updates, thereby amplifying the contribution of hidden layers that resemble the ego layer while reducing discrepancies. The results of the experiments showed that HRGCNLDA achieved the highest AUC-ROC (area under the receiver operating characteristic curve, AUC for short) and AUC-PR (area under the precision versus recall curve, AUPR for short) values compared to other methods. Finally, to further demonstrate the reliability and efficacy of our approach, we performed case studies on the case of three prevalent human diseases, namely, breast cancer, lung cancer and gastric cancer.

RDLR: A Robust Deep Learning-Based Image Registration Method for Pediatric Retinal Images.

Retinal diseases stand as a primary cause of childhood blindness. Analyzing the progression of these diseases requires close attention to lesion morphology and spatial information. Standard image registration methods fail to accurately reconstruct pediatric fundus images containing significant distortion and blurring. To address this challenge, we proposed a robust deep learning-based image registration method (RDLR). The method consisted of two modules: registration module (RM) and panoramic view module (PVM). RM effectively integrated global and local feature information and learned prior information related to the orientation of images. PVM was capable of reconstructing spatial information in panoramic images. Furthermore, as the registration model was trained on over 280,000 pediatric fundus images, we introduced a registration annotation automatic generation process coupled with a quality control module to ensure the reliability of training data. We compared the performance of RDLR to the other methods, including conventional registration pipeline (CRP), voxel morph (WM), generalizable image matcher (GIM), and self-supervised techniques (SS). RDLR achieved significantly higher registration accuracy (average Dice score of 0.948) than the other methods (ranging from 0.491 to 0.802). The resulting panoramic retinal maps reconstructed by RDLR also demonstrated substantially higher fidelity (average Dice score of 0.960) compared to the other methods (ranging from 0.720 to 0.783). Overall, the proposed method addressed key challenges in pediatric retinal imaging, providing an effective solution to enhance disease diagnosis. Our source code is available at https://github.com/wuwusky/RobustDeepLeraningRegistration .

Efficient Refinement of Complex Structures of Flexible Histone Peptides Using Post-Docking Molecular Dynamics Protocols.

Histones are keys to many epigenetic events and their complexes have therapeutic and diagnostic importance. The determination of the structures of histone complexes is fundamental in the design of new drugs. Computational molecular docking is widely used for the prediction of target-ligand complexes. Large, linear peptides like the tail regions of histones are challenging ligands for docking due to their large conformational flexibility, extensive hydration, and weak interactions with the shallow binding pockets of their reader proteins. Thus, fast docking methods often fail to produce complex structures of such peptide ligands at a level appropriate for drug design. To address this challenge, and improve the structural quality of the docked complexes, post-docking refinement has been applied using various molecular dynamics (MD) approaches. However, a final consensus has not been reached on the desired MD refinement protocol. In this present study, MD refinement strategies were systematically explored on a set of problematic complexes of histone peptide ligands with relatively large errors in their docked geometries. Six protocols were compared that differ in their MD simulation parameters. In all cases, pre-MD hydration of the complex interface regions was applied to avoid the unwanted presence of empty cavities. The best-performing protocol achieved a median of 32% improvement over the docked structures in terms of the change in root mean squared deviations from the experimental references. The influence of structural factors and explicit hydration on the performance of post-docking MD refinements are also discussed to help with their implementation in future methods and applications.

Structural Refinement and Optoelectrical Properties of Nd2Ru2O7 and Gd2Ru2O7 Pyrochlore Oxides for Photovoltaic Applications.

High-performance photovoltaic devices require active photoanodes with superior optoelectric properties. In this study, we synthesized neodymium ruthenate, Nd2Ru2O7 (NRO), and gadolinium ruthenate pyrochlore oxides, Gd2Ru2O7 (GRO), via the solid-state reaction technique, showcasing their potential as promising candidates for photoanode absorbers to enhance the efficiency of dye-sensitized solar cells. A structural analysis revealed predominantly cubic symmetry phases for both materials within the Fd-3m space group, along with residual orthorhombic symmetry phases (Nd3RuO7 and Gd3RuO7, respectively) refined in the Pnma space group. Raman spectroscopy further confirmed these phases, identifying distinct active modes of vibration in the predominant pyrochlore oxides. Additionally, a scanning electron microscopy (SEM) analysis coupled with energy-dispersive X-ray spectroscopy (EDX) elucidated the morphology and chemical composition of the compounds. The average grain size was determined to be approximately 0.5 µm for GRO and 1 µm for NRO. Electrical characterization via I-V measurements revealed that these pyrochlore oxides exhibit n-type semiconductor behavior, with conductivity estimated at 1.5 (Ohm·cm)-1 for GRO and 4.5 (Ohm·cm)-1 for NRO. Collectively, these findings position these metallic oxides as promising absorber materials for solar panels.

Corrosion Activity of Ultrafine-Grained Pure Magnesium and ZK60 Magnesium Alloy in Phosphate Buffered Saline Solution.

The magnesium alloy ZK60 is a promising candidate as a material for biodegradable implants. One of the most important factors for biodegradable implants is the modification of their corrosion behavior to match the requirements for the healing bone or tissue. The corrosion behavior can be influenced by different factors, among them the grain size, which can be changed by severe plastic deformation processes such as High Pressure Torsion Extrusion (HPTE). This study focuses on the corrosion behavior of samples of pure magnesium and ZK60 before and after HPTE, and the influence of the microstructure on the corrosion activity. The samples are subjected to immersion tests in phosphate buffered saline solution (PBS). The corrosion activity is defined by the emerging hydrogen volume from the corrosion process which is collected and by subsequently observing the resulting sample surfaces. The findings of this study suggest that pure magnesium shows lower corrosion activities than ZK60 and that HPTE processing leads to higher corrosion activities in PBS.

Study of Quenching and Partitioning (Q&P) and Ultrasonic Surface Rolling (USR) Process on Microstructure and Mechanical Property of a High-Strength Martensitic Steel.

Steel with a combination of strength and plasticity is prevalently demanded for lightweight design and emission reductions in manufacturing. In this study, a high-strength Cr-Ni-Mo martensitic steel treated by quenching and partitioning (Q&P) and ultrasonic surface rolling (USR) processes was studied for both strength and plasticity enhancement. Specimens were austenitized at 850 °C and then quenched to 240 °C via cooling by water, oil, and normalization in quenching. This was followed by partitioning, in which two groups of specimens were heated to 370 °C and 350 °C for 45 min, respectively. At last, all the specimens were quenched to room temperature with the same methods of quenching. The highest tensile strength increased from 681.73 MPa to 1389.76 MPa when compared to as-received (AR) steel after the Q&P process. The USR process with a static force of 800 N further improved the tensile strength of specimens with high tensile strength after the Q&P process, which improved from 1389.76 MPa to 1586.62 MPa and the product's strength and elongation (PSE) increased from 15.76 GPa% to 15.9 GPa%, while the total elongation showed a mitigatory decrease from 11.34% to 10.02%. Tensile fractures were also studied and verified using a combination of strength and plasticity after a combined process of Q&P and USR.

Exploring Red Wine Aging: Comparative Analysis of Cellar and Sea Underwater Aging on Chemical Composition and Quality.

The aging process of wine is influenced by various factors, including the presence of oxygen, the temperature, and the storage conditions. While oxygen can have both positive and negative effects on wine quality, temperature fluctuations during storage can impact its chemical composition. This study has investigated the aging of Merlot and Sangiovese wines under traditional cellar conditions and underwater, exploring the influence of storage parameters on their chemical evolution. Analyzing parameters such as temperature, pressure, and chemical composition, the research revealed subtle but significant changes in the wines over time. Both wines showed a gradual reduction in total phenols, anthocyanins, non-flavonoid compounds, and total sulfur dioxide, irrespective of the storage conditions. Preliminary findings suggested that aging wine underwater does not induce significant alterations in its fundamental characteristics compared to traditional cellar aging. These results contribute to a deeper understanding of wine aging processes and highlight the importance of storage conditions in preserving wine quality. Further research is needed to fully elucidate the complexities of underwater aging and its broader implications for wine production.

Corrosion Behavior of CMT Cladding Layer of AZ91 Magnesium Alloy Subjected to Friction Stir Processing.

Friction stir processing (FSP) was performed on an AZ91 magnesium alloy cladding layer fabricated by a cold metal transfer (CMT) technique. Electrochemical properties and immersion corrosion behavior of the cladding layer before and after FSP in 3.5 wt.% NaCl solution were investigated. After applying the FSP, the corrosion potential and corrosion current density of the cladding layer increased from -1.455 V to -1.397 V and decreased from 4.135 µA/cm2 to 1.275 µA/cm2, respectively. The results of OM and SEM displayed the refinement of grains and the dispersion of ß-Mg17Al12 second phase in the friction stir processed (FSPed) cladding layer and more severe corrosion of the unprocessed sample. The corrosion rate of the FSPed cladding layer was lower, and a more compact corrosion product film was formed on the surface of the FSPed cladding layer. EDS results and XRD patterns showed that the corrosion products was mainly composed of Mg(OH)2. The increase in Al content in the α-Mg matrix, grain refinement, and fragmentation and dispersion of the ß-Mg17Al12 second phase induced by FSP were the main factors that led to the improvement in corrosion resistance of the cladding layer of the AZ91 magnesium alloy fabricated by CMT.

Fast and Accurate EEG/MEG BEM-Based Forward Problem Solution for High-Resolution Head Models.

A BEM (boundary element method) based approach is developed to accurately solve an EEG/MEG forward problem for a modern high-resolution head model in approximately 60 seconds using a common workstation. The method utilizes a charge-based BEM with fast multipole acceleration (BEM-FMM) and a "smart" mesh pre-refinement (called b-refinement) close to the singular source(s). No costly matrix-filling or direct solution steps typical for the standard BEM are required; the method generates on-skin voltages as well as MEG magnetic fields for high-resolution head models in approximately 60 seconds after initial model assembly. The method is verified both theoretically and experimentally.