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People with visual impairment have reduced access to participate in exercise due to factors related to their impaired vision. Individuals with visual impairment in Taiwan similarly have lower participation rates in exercise than those without visual impairment. Consequently, people with visual impairment in Taiwan are at increased risk of poorer health. In recent years, some social welfare organisations that provide services to people with visual impairment have become aware of this issue, and have commenced provision of exercise programs within their service. However, little is known about the impact these exercise programs have for people with visual impairment in Taiwan. The consideration of applicability, suitability, and the occupational meaning of exercise programs for people with visual impairment are also limited. This research will investigate the influence of a purposely-designed exercise program for people with visual impairment in Taiwan.

Supplementary Material 1

Reconstructing interactions from observational data is a critical need for investigating natural biological networks, wherein network dimensionality (i.e. number of interacting components) is usually high and interactions are time-varying. These pose a challenge to existing methods that can quantify only small interaction networks or assume static interactions under steady state. Here, we proposed a novel approach to reconstruct high-dimensional, time-varying interaction networks using empirical time series. This method, named "multiview distance regularized S-map", generalized the state space reconstruction to accommodate high dimensionality and overcome difficulties in quantifying massive interactions with limited data. When we evaluated this method using the time series generated from a large theoretical model involving hundreds of interacting species, estimated interaction strengths were in good agreement with theoretical expectations. As a result, reconstructed networks preserved important topological properties, such as centrality, strength distribution and derived stability measures. Moreover, our method effectively forecasted the dynamic behavior of network nodes. Applying this method to a natural bacterial community helped identify keystone species from the interaction network and revealed the mechanisms governing the dynamical stability of bacterial community. Our method overcame the challenge of high dimensionality and disentangled complex time-varying interactions in large natural dynamical systems., The first 28 pages are the main text (including four figures and one table) and followed by SI Texts, including Fig. S1-S12 and Table S1-S2

Additional file 1: Supplementary Figure 1. Flow of study selection. NS indicates nephrotic syndrome; IS, ischemic stroke; ICH, intracranial hemorrhage. Supplementary Table 1. The numbers of missing laboratory data. Supplementary Table 2. Demographic features of nephrotic syndrome patients with stroke (additional data). Supplementary Table 3. Demographic features and clinical courses of nephrotic syndrome patients with ischemic stroke (additional data). Supplementary Table 4. Demographic features and clinical courses of nephrotic syndrome patients with intracranial hemorrhage (additional data). Supplementary Table 5. Cox regression analysis of patient survival during the 30-day period, intracranial hemorrhage vs. ischemic stroke (detailed items). Supplementary Table 6. Cox regression analysis of patient survival during the 30-day period in nephrotic syndrome patients with ischemic stroke (detailed items). Supplementary Table 7. Cox regression analysis of patient survival during the 30-day period in nephrotic syndrome patients with intracranial hemorrhage (detailed items).

It has been estimated that more than 48% of global methane emissions from lakes and reservoirs occur at low latitudes (

Mesial temporal lobe epilepsy (MTLE) is a common epilepsy syndrome often refractory to antiepileptic drug (AED) treatment. The purpose of this study was to evaluate the effectiveness and tolerability of perampanel (PER) as add-on treatment for patients of MTLE. We pooled retrospective data from adult patients with MTLE, from a tertiary center in Taiwan, who were prescribed PER between March 2016 and December 2016. The retention, responder, and seizure-free rate as well as the treatment emergent adverse events were assessed after 6 months of PER adjunctive treatment in this single-center postmarketing study. Review of medical records revealed that adequate data were available for 44 patients who were being administered PER (mean age: 42.0 ± 13.3 years, 24 females; baseline mean seizure frequency: 5.4 per 28 days). Twelve patients exhibited hippocampal sclerosis (HS). Open-label PER was added to ongoing medications. Twelve patients withdrew because of ineffectiveness (n = 6) or adverse effects (n = 6). The retention rate was 72.7% at 6 months. On final evaluation, with a mean PER dose of 5.7 mg/day for 6 months, a ≥50% reduction in seizure frequency was observed in 46.9% of the patients, and 5 patients became seizure-free. The effectiveness was similar for patients with or without HS. Twenty-three patients (52.3%) experienced adverse effects. The most common adverse effects were dizziness, ataxia, and irritability. Our results suggest that PER, at doses of 2 to 12 mg/day, reduces seizure frequency effectively with acceptable safety profiles for adults with MTLE.

The human lifestyle can be foreseen to have a tremendous change once the automation of transportation has been fully realised. The majority of current researches merely focus on improving the efficiency performance of autonomous vehicles(e.g. the energy management system, the handling, etc.)instead of putting the human acceptance and preference into consideration, leaving the knowledge gap of achieving the personalised automation. The primary objective of this research is to develop a novel human-like trajectory planning algorithm that is able to mimic the performance of human drivers and generate a feasible trajectory for an autonomous vehicle to complete a motorway lane change, which is the most representative and commonest manoeuvre on the motorway. This thesis can be divided into four main sections. Starting with the part of literature review, which summarises the existing techniques and the associated knowledges that can be taken the advantage of; including the trajectory planning, the driving styles, the lane change manoeuvre and the Model Predictive Control (MPC). An appropriate-designed experiment is then introduced and implemented, with the purpose of constructing a precise and reliable human driving database. This database contains 551 lane changes on the motorway from 12 different male drivers. Through applying data statistics methods, the human characteristics can be mined from the experimental data, showing that the vehicle velocity 𝒗, the hand steering wheel angle 𝜹 𝒉𝒂𝒏𝒅𝒓𝒆𝒂𝒍, the longitudinal acceleration a𝒙, the rate of hand steering 𝜸 𝒉𝒂𝒏𝒅𝒔𝒕𝒆𝒆𝒓 and the rate of longitudinal accelerating 𝜸 𝒍𝒐𝒏𝒈𝑨𝒄𝒄 are the essential features for the motorway lane change manoeuvre. An off-line constraint table for the three nominated driving styles can be therefore constructed based on these features. Finally, the obtained human information is then fused with the traditional MPC planning technique so as to achieve the proposed human-like trajectory planning algorithm. The main contribution of this study is proposing a novel approach of combining the real human driving data and the traditional planning technique(i.e. MPC) to achieve human-like lane change trajectory planning for autonomous vehicles. An integrated human driving database which contains both the video footages and the vehicle-dynamic-based signals from 12 different participants is built. Moreover, the draft marginal values of the essential parameters for the driving styles while performing a right lane change on the motorway are also presented. Both the collected driving database and the driving styles’ constraint table can be seen as distinctive achievements, providing resourceful materials for future researches. PhD in Transport Systems

Statistical averaging and asynchronous population dynamics as portfolio mechanisms are considered as the most important processes with which biodiversity contributes to ecosystem stability. However, portfolio theories usually regard biodiversity as a fixed property, but overlook the dynamics of biodiversity altered by other ecosystem components. Here, we proposed a new mechanistic food chain model with nutrient-diversity feedback to investigate how dynamics of phytoplankton species diversity determines ecosystem stability. Our model focuses on nutrient, community biomass of phytoplankton and zooplankton, and phytoplankton species richness. The model assumes diversity effects of phytoplankton on trophic interaction strength along plankton food chain: phytoplankton diversity influences nutrient uptake by phytoplankton and zooplankton grazing on phytoplankton, which subsequently affects nutrient level and community biomass of phytoplankton and zooplankton. The nutrient level in turn affects phytoplankton diversity. These processes collectively form feedbacks between phytoplankton diversity and dynamics of plankton and nutrient. More importantly, nutrient-diversity feedback introduced additional temporal variabilities in community biomass, which apparently implies a destabilizing effect of phytoplankton diversity on ecosystem. However, the variabilities made ecosystems more robust against extinction of plankton because increasing phytoplankton diversity facilitates resource consumptions when consumers prone to extinct; while, reducing diversity weakens destabilizing dynamics caused by over-growth. Our results suggest the presence of a novel stabilizing effect of biodiversity acting through nutrient-diversity feedback, being independent of portfolio mechanisms., Comment: Main text: 30 pages including 4 figures and 2 tables; Supplementary Information: 10 pages

The objective of this study is to find an effective method to improve Voc without Jsc loss for Cu2ZnSnSe4 (CZTSe) thin film solar cells, which have been fabricated by the one step co-evaporation technique. Surface sulfurization of CZTSe thin films is carried out by using one technique that does not utilize toxic H2S gas; a sequential evaporation of SnS after CZTSe deposition and the annealing of CZTSe thin films in selenium vapor. A Cu2ZnSn(S,Se)4 (CZTSSe) thin layer is grown on the surface of the CZTSe thin film after the annealing. The conversion efficiency of the completed device is improved due to the enhancement of Voc, which could be attributed to the formation of a hole-recombination barrier at the surface or the passivation of the surface and grain boundary by S incorporation.

To study the characteristics of arterial blood gas and electrolytes in patients with severe pulmonary tuberculosis with respiratory failure.In 50 patients with severe pulmonary tuberculosis, the arterial blood gas and electrolytes were measured after the onset of respiratory failure to define the types of respiratory failure and acid-base imbalance.Severe pulmonary tuberculosis with respiratory failure was characterized by development of hypoxia, and the degree of hypercapnia may vary; more extensive tuberculous involvement or longer disease course suggest greater chance of type II respiratory failure. Increment of the anion gap occurred irrespective of the pH value.Analysis of arterial blood gas and electrolytes may help monitor the progression of severe pulmonary tuberculosis and provides valuable information for implementing treatment and making prognostic decisions.

To explore the reason of delayed diagnosis or misdiagnosis of pulmonary tuberculosis.The clinical data of 458 patients pulmonary tuberculosis patients undergoing treatment between January 1999 and December 2003 in our hospital were retrospectively analysed.The reasons for delayed diagnosis or misdiagnosis are as follows: A careless attitude towards health condition by patients themselves; neglected bacteriological evidence or ignorance of tuberculosis by physicians.