Intake of Radionuclides in the Trees of Fukushima Forests 5. Earthquake Could Have Caused an Increase in Xyloglucan in Trees

A megathrust earthquake caused the Fukushima–Daiichi nuclear power plant accident, which dispersed abundant radioiodines, causing them to be bound to xyloglucan into forest trees. Nevertheless, targeted xyloglucan was found in increased quantities in the annual rings of forest trees affected by the earthquake. We propose that trees could acclimate rapidly to shaking stress through an increase in xyloglucan deposition as a plant response under natural phenomena

Network Dynamics in the 12 Regional Clusters (Japanese)

It has been observed that the origination of innovation tends to concentrate in areas in which environmental conditions are formed as clusters. It is networks with "small-world" architecture that underpin the high level of creative power for innovation that clusters possess. If it were possible, through policy efforts, to form networks of a highly small-world character that provide an environment that can facilitate a good balance between short-distance interaction and long-distance interaction, that would lead to the enhancement of a region's creative power for innovation. The cluster policy currently being implemented has completed its first phase and has reached a watershed at which it moves into the second phase. In this paper we attempt to formulate a method of objectively grasping and evaluating network architecture from the standpoint of these two types of interaction. Specifically, with regard to the architecture of major networks formed domestically, we use network analysis methods to conduct a comparative analysis of the 12 regions and fields before (in 2000) and after (in 2005) the implementation of cluster policy. As a result of this, we have clarified the following points. (1) Networks are expanding in all regions, (2) the networks that excel in long-distance interaction also excel in short-distance interaction, (3) with a small number of exceptions, the bigger the network is, the more both of these characteristics are enhanced, (4) during this five-year period there have been no major changes with regard to the comparative advantage of each region or field, (5) there is some degree of correlation between the independence of modules and the extent of their small-world character, and (6) disparities between regions are greater than disparities between industry sectors. Through the use of this analytical method it was possible to obtain a quantitative grasp of network architecture in a form that made possible comparisons with other regions and fields, and from this to extract objective information necessary for policy-making. We hope that efficient networking activity will be carried out in the future on the basis of the results of analysis of this kind.

Analysis of error responses in the negative patterning task in rats

This experiment studied the learning phenomena by three behavioral indicators. The configural association theory insists that the hippocampus is required to solve configural discrimination learning tasks in rats. The theory identifies the negative patterning discrimination task as a typical example. We used this task to examine three behavioral indicators, i.e., the number of responses during the inter-trial interval, reaction time, and response rate. The results showed the serial changes of these indicators depend on learning progress. At first, number of responses during inter-trial intervals was decreased. Next, reaction time of error responses became longer. Finally, response rate decreased in nonreinforced stimuli. Therefore, these three indicators can be classified into three phases; early, middle, and late phases of learning from different aspects. These error indexes showed clearly that the three phases of learning depend on the negative patterning task

Transient decline in hippocampal theta activity during the acquisition process of the negative patterning task.

Hippocampal function is important in the acquisition of negative patterning but not of simple discrimination. This study examined rat hippocampal theta activity during the acquisition stages (early, middle, and late) of the negative patterning task (A+, B+, AB-). The results showed that hippocampal theta activity began to decline transiently (for 500 ms after non-reinforced stimulus presentation) during the late stage of learning in the negative patterning task. In addition, this transient decline in hippocampal theta activity in the late stage was lower in the negative patterning task than in the simple discrimination task. This transient decline during the late stage of task acquisition may be related to a learning process distinctive of the negative patterning task but not the simple discrimination task. We propose that the transient decline of hippocampal theta activity reflects inhibitory learning and/or response inhibition after the presentation of a compound stimulus specific to the negative patterning task

Fabrication of Cu2ZnSnS4 (CZTS) by co-electrodeposition of Cu-Zn-Sn alloys, and effect of chemical composition of CZTS on their photoelectrochemical water splitting

Sulfide kesterite Cu2ZnSnS4 (CZTS), an intrinsic p-type semiconductor, provides an attractive low-cost, environmentally friendly photoelectrochemical (PEC) water splitting to evolve hydrogen. The purpose of this study was to clarify the effect of the chemical composition of CZTS on the PEC properties and the correlation with their structures. The CZTS was fabricated on a Mo/glass by a non-vacuum process, i.e., co-electrodeposition (co-ED) of Cu-Zn-Sn (CZT) alloys, followed by sulfurization with solid sulfur. To optimize the chemical composition of CZTS, the bath concentrations, applied potentials and amounts of electric charge for preparation conditions of the CZT precursors were examined. The CZTS with Cu-poor and Sn-rich composition compared with stoichiometry was found to exhibit relatively effective PEC water splitting. It was suggested that the high PEC performance was attributed to efficient charge carrier transport due to the presence of a small amount of SnO2 phase on the CZTS surface

Comparison of hippocampal theta power between correct-response and incorrect-response trials.

<p>This figure shows the hippocampal theta power between trials with correct lever press response for RFT and incorrect lever press responses for non-RFTs during the late stage of the negative patterning task. The 0 period was lever press timing. The analysis period from 1250 ms before lever press to 1500 ms after lever press was divided into 11 250-ms epochs. The 250-ms period from -1250 to -1000 ms was used as the baseline, and the relative theta activity for each period was calculated as follows: relative theta activity of each period = theta activity of each period/theta activity during the baseline period.</p

Negative patterning and simple discrimination paradigms.

<p>In the negative patterning task, lever presses were reinforced following either of the stimulus elements (Tone +, Light +), but not following the compound stimulus (Compound -; panel A). In the simple discrimination task, for 1 group, lever responses were rewarded when the tone stimulus was presented (Tone +), but not when the light stimulus was presented (Light -; panel B). For the other group, the relationship between cue modality and availability of reinforcement was reversed (Light +, Tone -).</p

The change in theta power during the non-RFTs during each learning stage of the negative patterning task.

<p>Panel A shows the change in hippocampal theta activity along a time course during non-RFTs on the early stage, panel B shows theta activity on the middle stage and panel C shows theta activity on late stage of negative patterning task. The x-axis is time (ms) and the y-axis is frequency (Hz). In each panel, the period is from 500 ms before stimulus onset to 4000 ms after stimulus onset. The period was divided into 19 sub-periods of 250 ms each. The mean hippocampal theta power during 500 ms before stimulus onset was counted as the -500-ms period (no stimuli were present and no rats pressed the lever during this period) and the relative theta power calculated for each period was normalized to that during the -500-ms period (relative theta activity of each period = theta power of each period/theta power at the -500-ms period). Panel D contains a comparison of the mean (± S.E.M.) relative hippocampal theta activity at 6–12 Hz among each learning stage (early, middle, and late) throughout the time course of the experiment during non-RFT of the negative patterning task (*: <i>p</i> < 0.05). Panel E contains a comparison of the mean (± S.E.M.) relative hippocampal theta activity at 6–12 Hz among each learning stage (early, middle, and late) throughout the time course of the experiment during non-RFT of the simple discrimination task.</p