Effects of forest thinning on sap flow dynamics and transpiration in a Japanese cedar forest.

Historically, forest thinning in Japan was conducted to obtain high-quality timber from plantations. Today, in contrast, thinning is also motivated by forest water balance and climate change considerations. It is in this context that the present study examines the effects of thinning on the ecophysiological responses of remaining trees, which are inadequately understood, especially in relation to changes in the magnitude and duration of transpiration. Sap flux densities were measured in both outer and inner sapwood to obtain stand-scale transpiration for two years in the pre-thinning state and three years post-thinning. The effects of thinning on transpiration were quantitatively evaluated based on canopy conductance models. The larger increases in outer sap flux density were found in the first year after the treatment, while those in inner sap flux density were detected in the second and third years. The remaining trees required a few of years to adjust to improved light conditions of the lower crown, resulting in a delayed response of inner sap flux density. As a result of this lag, transpiration was reduced to 71 % of the pre-thinning condition in the first year, but transpiration recovered to the pre-thinning levels in the second and third years due to compensating contributions from inner sap flow. In terms of more accurately chronicling the thinning effect, the distribution of sap flux density with respect to its radial pattern, is necessary. Such measurements are key to more comprehensively examining the ecophysiological response of forest plantations to thinning and, ultimately, its effect on the forest water balance.

A Stepwise Progression of Acute Bilateral Visual Loss Due to Onodi Cell Sinusitis.

Acute visual loss in an immunocompromised patient may be caused by acute invasive fungal sinusitis (AIFS), even if symptoms include only mild headache and computed tomography (CT) shows only mild sinusitis, especially of the Onodi cell. Herein, we report a case of a 71-year-old man with a medical history of dermatomyositis and type 2 diabetes mellitus who presented with a stepwise progression of acute bilateral visual loss, mild headache, and altered consciousness. Initially, as the plain cranial CT showed only mild fluid retention in the posterior ethmoid sinus without bone destruction, the sinusitis was considered unrelated to the visual loss. Afterward, however, contrast-enhanced cranial magnetic resonance imaging (MRI) showed mucosal thickening, fluid retention in the posterior ethmoid sinus, and spread of the contrast medium over the dura around the right posterior ethmoid sinus and bilateral optic nerve tracts. Aspergillus fumigatus was identified from endoscopic drainage of the sinus. The patient was diagnosed with AIFS and treated with amphotericin B 350 mg/day. The altered sensorium and headache rapidly improved, and his left visual acuity improved to counting fingers. Although AIFS is rare, it can cause severe sequela or death due to vascular or direct intracranial invasion. Therefore, immediate drainage of the sinus and intravenous antifungal therapy are essential for AIFS. Our findings will help physicians make accurate and rapid diagnoses of AIFS in future cases.

Effects of sturgeon fillet intake on top-ranked Japanese female long-distance runners.

AIMS: The aim of this study is to investigate whether consumption of sturgeon fillets reduces the oxidative stress marker urinary 8-hydroxy-2'-deoxyguanosine (8OHdG) in top-ranked Japanese female long-distance runners. METHODS: In a before-and-after study, nine professional long-distance female athletes ate 100 g/day of sturgeon fillets for 2 weeks. Urinalysis (8OHdG, an oxidative stress marker, and creatinine), blood tests (fatty acids and 25-hydroxyvitamin D [25OHD]), exercise intensity, subjective fatigue, muscle elasticity, muscle mass, body fat mass, and nutritional intake using image-based dietary assessment (IBDA) were compared before, immediately after, and 1 month after the intervention. RESULTS: Consumption of sturgeon fillets suppressed 8OHdG (p < 0.05) in the increased exercise intensity female athletes. Eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and 25OHD levels in blood increased from before to immediately after and 1 month after the intervention (p < 0.05). IBDA showed that intake of n-3 fatty acid increased after and one month after the intervention, whereas DHA, imidazole dipeptide and vitamin D intake increased after the intervention (p < 0.05) and then decreased after 1 month (p < 0.05). There were no significant changes in subjective fatigue, muscle elasticity, muscle mass, and body fat. CONCLUSIONS: The results suggest that eating sturgeon fillets during intense training may increase blood levels of EPA, DHA, and 25OHD, which may suppress urinary oxidative stress (8OHdG) in top-ranked Japanese long-distance runners.

Hybrid PBL and Pure PBL: Which one is more effective in developing clinical reasoning skills for general medicine clerkship?-A mixed-method study.

This study aims to compare the effectiveness of Hybrid and Pure problem-based learning (PBL) in teaching clinical reasoning skills to medical students. The study sample consisted of 99 medical students participating in a clerkship rotation at the Department of General Medicine, Chiba University Hospital. They were randomly assigned to Hybrid PBL (intervention group, n = 52) or Pure PBL group (control group, n = 47). The quantitative outcomes were measured with the students' perceived competence in PBL, satisfaction with sessions, and self-evaluation of competency in clinical reasoning. The qualitative component consisted of a content analysis on the benefits of learning clinical reasoning using Hybrid PBL. There was no significant difference between intervention and control groups in the five students' perceived competence and satisfaction with sessions. In two-way repeated measure analysis of variance, self-evaluation of competency in clinical reasoning was significantly improved in the intervention group in "recalling appropriate differential diagnosis from patient's chief complaint" (F(1,97) = 5.295, p = 0.024) and "practicing the appropriate clinical reasoning process" (F(1,97) = 4.016, p = 0.038). According to multiple comparisons, the scores of "recalling appropriate history, physical examination, and tests on clinical hypothesis generation" (F(1,97) = 6.796, p = 0.011), "verbalizing and reflecting appropriately on own mistakes," (F(1,97) = 4.352, p = 0.040) "selecting keywords from the whole aspect of the patient," (F(1,97) = 5.607, p = 0.020) and "examining the patient while visualizing his/her daily life" (F(1,97) = 7.120, p = 0.009) were significantly higher in the control group. In the content analysis, 13 advantage categories of Hybrid PBL were extracted. In the subcategories, "acquisition of knowledge" was the most frequent subcategory, followed by "leading the discussion," "smooth discussion," "getting feedback," "timely feedback," and "supporting the clinical reasoning process." Hybrid PBL can help acquire practical knowledge and deepen understanding of clinical reasoning, whereas Pure PBL can improve several important skills such as verbalizing and reflecting on one's own errors and selecting appropriate keywords from the whole aspect of the patient.

Association Between Physician Empathy and Difficult Patient Encounters: a Cross-Sectional Study.

BACKGROUND: Physicians frequently experience patients as difficult. Our study explores whether more empathetic physicians experience fewer patient encounters as difficult. OBJECTIVE: To investigate the association between physician empathy and difficult patient encounters (DPEs). DESIGN: Cross-sectional study. PARTICIPANTS: Participants were 18 generalist physicians with 3-8 years of experience. The investigation was conducted from August-September 2018 and April-May 2019 at six healthcare facilities. MAIN MEASURES: Based on the Jefferson Scale of Empathy (JSE) scores, we classified physicians into low and high empathy groups. The physicians completed the Difficult Doctor-Patient Relationship Questionnaire-10 (DDPRQ-10) after each patient visit. Scores ≥ 31 on the DDPRQ-10 indicated DPEs. We implemented multilevel mixed-effects logistic regression models to examine the association between physicians' empathy and DPE, adjusting for patient-level covariates (age, sex, history of mental disorders) and with physician-level clustering. KEY RESULTS: The median JSE score was 114 (range: 96-126), and physicians with JSE scores 96-113 and 114-126 were assigned to low and high empathy groups, respectively (n = 8 and 10 each); 240 and 344 patients were examined by physicians in the low and high empathy groups, respectively. Among low empathy physicians, 23% of encounters were considered difficulty, compared to 11% among high empathy groups (OR: 0.37; 95% CI = 0.19-0.72, p = 0.004). JSE scores and DDPRQ-10 scores were negatively correlated (r = -0.22, p < 0.01). CONCLUSION: Empathetic physicians were less likely to experience encounters as difficult. Empathy appears to be an important component of physician perception of encounter difficulty.

HMM-Based Action Recognition System for Elderly Healthcare by Colorizing Depth Map.

Addressing the problems facing the elderly, whether living independently or in managed care facilities, is considered one of the most important applications for action recognition research. However, existing systems are not ready for automation, or for effective use in continuous operation. Therefore, we have developed theoretical and practical foundations for a new real-time action recognition system. This system is based on Hidden Markov Model (HMM) along with colorizing depth maps. The use of depth cameras provides privacy protection. Colorizing depth images in the hue color space enables compressing and visualizing depth data, and detecting persons. The specific detector used for person detection is You Look Only Once (YOLOv5). Appearance and motion features are extracted from depth map sequences and are represented with a Histogram of Oriented Gradients (HOG). These HOG feature vectors are transformed as the observation sequences and then fed into the HMM. Finally, the Viterbi Algorithm is applied to recognize the sequential actions. This system has been tested on real-world data featuring three participants in a care center. We tried out three combinations of HMM with classification algorithms and found that a fusion with Support Vector Machine (SVM) had the best average results, achieving an accuracy rate (84.04%).

Real-Time Action Recognition System for Elderly People Using Stereo Depth Camera.

Smart technologies are necessary for ambient assisted living (AAL) to help family members, caregivers, and health-care professionals in providing care for elderly people independently. Among these technologies, the current work is proposed as a computer vision-based solution that can monitor the elderly by recognizing actions using a stereo depth camera. In this work, we introduce a system that fuses together feature extraction methods from previous works in a novel combination of action recognition. Using depth frame sequences provided by the depth camera, the system localizes people by extracting different regions of interest (ROI) from UV-disparity maps. As for feature vectors, the spatial-temporal features of two action representation maps (depth motion appearance (DMA) and depth motion history (DMH) with a histogram of oriented gradients (HOG) descriptor) are used in combination with the distance-based features, and fused together with the automatic rounding method for action recognition of continuous long frame sequences. The experimental results are tested using random frame sequences from a dataset that was collected at an elder care center, demonstrating that the proposed system can detect various actions in real-time with reasonable recognition rates, regardless of the length of the image sequences.

Deep time-delay Markov network for prediction and modeling the stress and emotions state transition.

To recognize stress and emotion, most of the existing methods only observe and analyze speech patterns from present-time features. However, an emotion (especially for stress) can change because it was triggered by an event while speaking. To address this issue, we propose a novel method for predicting stress and emotions by analyzing prior emotional states. We named this method the deep time-delay Markov network (DTMN). Structurally, the proposed DTMN contains a hidden Markov model (HMM) and a time-delay neural network (TDNN). We evaluated the effectiveness of the proposed DTMN by comparing it with several state transition methods in predicting an emotional state from time-series (sequences) speech data of the SUSAS dataset. The experimental results show that the proposed DTMN can accurately predict present emotional states by outperforming the baseline systems in terms of the prediction error rate (PER). We then modeled the emotional state transition using a finite Markov chain based on the prediction result. We also conducted an ablation experiment to observe the effect of different HMM values and TDNN parameters on the prediction result and the computational training time of the proposed DTMN.

A Study on the Gaze Range Calculation Method During an Actual Car Driving Using Eyeball Angle and Head Angle Information.

Car operation requires advanced brain function. Currently, evaluation of the motor vehicle driving ability of people with higher brain dysfunction is medically unknown and there are few evaluation criteria. The increase in accidents by elderly drivers is a social problem in Japan, and a method to evaluate whether elderly people can drive a car is needed. Under these circumstances, a system to evaluate brain dysfunction and driving ability of elderly people is needed. Gaze estimation research is a rapidly developing field. In this paper, we propose the gaze calculation method by eye and head angles. We used the eye tracking device (TalkEyeLite) made by Takei Scientific Instruments Cooperation. For our image processing technique, we estimated the head angle using the template matching method. By using the eye tracking device and the head angle estimate, we built a system that can be used during actual on-road car operation. In order to evaluate our proposed method, we tested the system on Japanese drivers during on-road driving evaluations at a driving school. The subjects were one instructor of the car driving school and eight general drivers (three 40-50 years old and five people over 60 years old). We compared the gaze range of the eight general subjects and the instructor. As a result, we confirmed that one male in his 40s and one elderly driver had narrower gaze ranges.

Gaze Estimation Method Using Analysis of Electrooculogram Signals and Kinect Sensor.

A gaze estimation system is one of the communication methods for severely disabled people who cannot perform gestures and speech. We previously developed an eye tracking method using a compact and light electrooculogram (EOG) signal, but its accuracy is not very high. In the present study, we conducted experiments to investigate the EOG component strongly correlated with the change of eye movements. The experiments in this study are of two types: experiments to see objects only by eye movements and experiments to see objects by face and eye movements. The experimental results show the possibility of an eye tracking method using EOG signals and a Kinect sensor.

EOG-sEMG Human Interface for Communication.

The aim of this study is to present electrooculogram (EOG) and surface electromyogram (sEMG) signals that can be used as a human-computer interface. Establishing an efficient alternative channel for communication without overt speech and hand movements is important for increasing the quality of life for patients suffering from amyotrophic lateral sclerosis, muscular dystrophy, or other illnesses. In this paper, we propose an EOG-sEMG human-computer interface system for communication using both cross-channels and parallel lines channels on the face with the same electrodes. This system could record EOG and sEMG signals as "dual-modality" for pattern recognition simultaneously. Although as much as 4 patterns could be recognized, dealing with the state of the patients, we only choose two classes (left and right motion) of EOG and two classes (left blink and right blink) of sEMG which are easily to be realized for simulation and monitoring task. From the simulation results, our system achieved four-pattern classification with an accuracy of 95.1%.

Unsupervised learnable neuron model with nonlinear interaction on dendrites.

Recent researches have provided strong circumstantial support to dendrites playing a key and possibly essential role in computations. In this paper, we propose an unsupervised learnable neuron model by including the nonlinear interactions between excitation and inhibition on dendrites. The model neuron self-adjusts its synaptic parameters, so that the synapse to dendrite, according to a generalized delta-rule-like algorithm. The model is used to simulate directionally selective cells by the unsupervised learning algorithm. In the simulations, we initialize the interaction and dendrite of the neuron randomly and use the generalized delta-rule-like unsupervised learning algorithm to learn the two-dimensional multi-directional selectivity problem without an external teacher's signals. Simulation results show that the directionally selective cells can be formed by unsupervised learning, acquiring the required number of dendritic branches, and if needed, enhanced and if not, eliminated. Further, the results show whether a synapse exists; if it exists, where and what type (excitatory or inhibitory) of synapse it is. This leads us to believe that the proposed neuron model may be considerably more powerful on computations than the McCulloch-Pitts model because theoretically a single neuron or a single layer of such neurons is capable of solving any complex problem. These may also lead to a completely new technique for analyzing the mechanisms and principles of neurons, dendrites, and synapses.

Elevated intraocular pressure, optic nerve atrophy, and impaired retinal development in ODAG transgenic mice.

PURPOSE: In an earlier study, a cDNA was cloned that showed abundant expression in the eye at postnatal day (P)2 but was downregulated at P10; it was named ODAG (ocular development-associated gene). Its biological function was examined by generating and analyzing transgenic mice overexpressing ODAG (ODAG Tg) in the eye and by identifying ODAG-binding proteins. METHODS: Transgenic mice were generated by using the mouse Crx promoter. EGFP was designed to be coexpressed with transgenic ODAG, to identify transgene-expressing cells. Overexpression of ODAG was confirmed by Northern and Western blot analysis. IOP was measured with a microneedle technique. The eyes were macroscopically examined and histologically analyzed. EGFP expression was detected by confocal microscope. Proteins associated with ODAG were isolated by pull-down assay in conjugation with mass spectrometry. RESULTS: Macroscopically, ODAG Tg exhibited gradual protrusion of the eyeballs. The mean IOP of ODAG Tg was significantly higher than that of wild-type (WT) littermates. Histologic analysis exhibited optic nerve atrophy and impaired retinal development in the ODAG Tg eye. EGFP was expressed highly in the presumptive outer nuclear layer and weakly in the presumptive inner nuclear layer in the ODAG Tg retina. Rab6-GTPase-activating protein (Rab6-GAP) and its substrate, Rab6, were identified as ODAG-binding proteins. CONCLUSIONS: Deregulated expression of ODAG in the eye induces elevated intraocular pressure and optic nerve atrophy and impairs retinal development, possibly by interfering with the Rab6/Rab6-GAP-mediated signaling pathway. These results provide new insights into the mechanisms regulating ocular development, and ODAG Tg would be a novel animal model for human diseases caused by ocular hypertension.

A polymorphism of LOC387715 gene is associated with age-related macular degeneration in the Japanese population.

Age-related macular degeneration (AMD) is one of the leading causes of blindness among older adults in developed countries and also in Japan. Previous research suggests that AMD is etiologically a complex disease, caused by multiple genes and environmental factors. Association studies have identified that a complement factor H gene (CFH) variant is a major risk factor for AMD in Caucasians. However, we and two other groups have reported no association between CFH and AMD in the Japanese population. Recent studies have suggested that LOC387715 on chromosome 10q26 may be the second major risk loci for AMD in Caucasians. In this study, we examined the association between LOC387715 and AMD in Japanese, and our results show that polymorphism of the LOC387715 gene is associated with AMD in Japanese as well as in Caucasians. Our data show a disease odds ratio of 6.20 (95% CI: 2.87-13.40) conferred by homozygosity for risk alleles at LOC387715 compared with the non-risk genotype. A polymorphism of LOC387715 gene is associated with AMD in the Japanese population.