Dissociated amplitude and phase effects of alpha oscillation in a nested structure of rhythm- and sequence-based temporal expectation.

The human brain can utilize various information to form temporal expectations and optimize perceptual performance. Here we show dissociated amplitude and phase effects of prestimulus alpha oscillation in a nested structure of rhythm- and sequence-based expectation. A visual stream of rhythmic stimuli was presented in a fixed sequence such that their temporal positions could be predicted by either the low-frequency rhythm, the sequence, or the combination. The behavioral modeling indicated that rhythmic and sequence information additively led to increased accumulation speed of sensory evidence and alleviated threshold for the perceptual discrimination of the expected stimulus. The electroencephalographical results showed that the alpha amplitude was modulated mainly by rhythmic information, with the amplitude fluctuating with the phase of the low-frequency rhythm (i.e. phase-amplitude coupling). The alpha phase, however, was affected by both rhythmic and sequence information. Importantly, rhythm-based expectation improved the perceptual performance by decreasing the alpha amplitude, whereas sequence-based expectation did not further decrease the amplitude on top of rhythm-based expectation. Moreover, rhythm-based and sequence-based expectations collaboratively improved the perceptual performance by biasing the alpha oscillation toward the optimal phase. Our findings suggested flexible coordination of multiscale brain oscillations in dealing with a complex environment.

Effects of biochar and freeze‒thaw cycles on the bacterial community and multifunctionality in a cold black soil area.

Global climate change has altered soil freeze‒thaw cycle events, and little is known about soil microbe response to and multifunctionality regarding freeze‒thaw cycles. Therefore, in this study, biochar was used as a material to place under seasonal freeze-thaw cycling conditions. The purpose of this study was to explore the ability of biochar to regulate the function of freeze-thaw soil cycles to ensure spring sowing and food production. The results showed that biochar significantly increased the richness and diversity of soil bacteria before and after freezing-thawing. In the freezing period, the B50 treatment had the greatest improvement effect (2.6% and 5.5%, respectively), while in the thawing period, the B75 treatment had the best improvement effect. Biochar changed the composition and distribution characteristics of the bacterial structure and enhanced the multifunctionality of freeze-thaw soil and the stability of the bacterial symbiotic network. Compared with the CK treatment, the topological characteristics of the bacterial ecological network of the B50 treatment increased the most. They were 0.89 (Avg.degree), 9.79 (Modularity), 9 (Nodes), and 255 (Links). The freeze-thaw cycle decreased the richness and diversity of the bacterial community and changed the composition and distribution of the bacterial community, and the total bacterial population decreased by 658 (CK), 394 (B25), 644 (B50) and 86 (B75) during the thawing period compared with the freezing period. The soil multifunctionality in the freezing period was higher than that during the thawing period, indicating that the freeze-thaw cycle reduced soil ecological function. From the perspective of abiotic analysis, the decrease in soil multifunctionality was due to the decrease in soil nutrients, enzyme activities, soil basic respiration and other singular functions. From the perspective of bacteria, the decrease in soil multifunctionality was mainly due to the change in the Actinobacteriota group. This work expands the understanding of biochar ecology in cold black soil. These results are conducive to the sustainable development of soil ecological function in cold regions and ultimately ensure crop growth and food productivity.

Effect of freeze-thaw cycles and biochar coupling on the soil water-soil environment, nitrogen adsorption and N2O emissions in seasonally frozen regions.

Freeze-thaw cycles (FTCs) usually occur in the nongrowing season of crops, and the temporal mismatch between soil nitrogen (N) supply and crop N utilization increases the risk of N loss. Crop straw burning is a seasonal air pollution source, and biochar provides new alternatives for waste biomass recycling and soil pollution remediation. To investigate the effect of biochar on N loss and N2O emissions under frequent FTCs, different biochar content treatments (0 %, 1 %, 2 %) were set, and laboratory simulated soil column FTC tests were conducted. Based on the Langmuir and Freundlich models, the surface microstructure evolution and N adsorption mechanism of biochar before and after FTCs were analyzed, and the change characteristics of the soil water-soil environment, available N and N2O emissions under the interactive effect of FTCs and biochar were studied. The results showed that FTCs increased the oxygen (O) content by 19.69 % and the N content by 17.75 % and decreased the carbon (C) content by 12.39 % of biochar. The increase in the N adsorption capacity of biochar after FTCs was related to changes in surface structure and chemical properties. Biochar can improve the soil water-soil environment, adsorb available nutrients, and reduce N2O emissions by 35.89 %-46.31 %. The water-filled pore space (WFPS) and urease activity (S-UE) were the main environmental factors determining N2O emissions. Ammonium nitrogen (NH4+-N) and microbial biomass nitrogen (MBN), as substrates of N biochemical reactions, significantly affected N2O emissions. The interaction of biochar content and FTCs in different treatments had significant effects on available N (p < 0.05). The application of biochar is an effective way to reduce N loss and N2O emissions under the action of frequent FTCs. These research results can provide a reference for the rational application of biochar and efficient utilization of soil hydrothermal resources in seasonally frozen soil areas.

Potentially migrating and residual components of biochar: Effects on phosphorus adsorption performance and storage capacity of black soil.

Biochar has great potential to increase the soil nutrient storage capacity. However, with aging, biochar gradually disintegrates and releases fractions with migration potential, resulting in unknown effects on soil nutrient regulation. Based on this problem, we used ultrasound to separate original biochar (TB) into potentially migrating biochar (DB) and residual biochar (RB). The elemental composition and pore characteristics of TB, DB and RB were analyzed. Different fractions of biochar were applied to black soil, and the kinetic model and isothermal adsorption models were used to explore the adsorption characteristics of different treatments. Then, the effects of initial pH and coexisting ions on adsorption were compared. The adsorption mechanism and potential leaching process of phosphorus in soil were investigated. The results showed that RB had higher O and H contents and was less stable than TB, while RB was more aromatic. The phosphorus adsorption capacity of different treatments was SRB (1.3318 mg g-1) > STB (1.2873 mg g-1) > SDB (1.3025 mg g-1) > SCK (1.1905 mg g-1). SRB had optimal phosphorus adsorption performance and storage capacity, with a maximum adsorption capacity of 1.6741 mg g-1 for the Langmuir isotherm, and it also showed excellent applicability in a pH gradient and with coexisting ions. The main adsorption mode of phosphorus by different treatments was monolayer chemisorption, related to electrostatic repulsion and oxygen-containing functional groups. DB was less effective in inhibiting soil phosphorus migration, with the cumulative leaching of SDB reaching 8.99 mg and the percentage of phosphorus in the 0-6 cm soil layer reaching only 15.42%. Overall, the results can help elucidate potential trends in the adsorption performance and migration process of soil phosphorus by biochar, and improve the comprehensive utilization efficiency of biochar.

Revisiting the color-motion asynchrony.

Color-motion asynchrony (CMA) refers to an illusion in which we perceive a change in color earlier than a change in motion direction when the two changes occur simultaneously. This phenomenon may indicate that color is processed earlier than motion in the visual system. However, the very existence of CMA is under question owing to contradictory findings and methodological deficits in previous studies. Here, we used both the motion and color correspondence tasks (experiment 1) and the temporal order judgment (TOJ) task (experiment 2) to re-examine CMA. Colored dots moved in one direction and changed their color/direction at some time, whereas the relative timing between color and direction changes varied across trials. In the correspondence task, participants reported which direction/color of dots with a particular color/direction lasted longer, the one before or after the change? In the TOJ task, participants reported whether the change in color or the change in motion direction occurred earlier. Results indicated that participants perceived the change in color earlier than the change in motion direction in either the motion or color correspondence task, with a stronger asynchrony in the former. In the TOJ task, although participants showed no difference in psychophysical measures, they responded faster when the change in color occurred before (versus after) the change in direction. Drift-diffusion modeling (DDM) revealed a lower decision threshold when the change in color occurred before (versus after) the change in direction, indicating less cautiousness was excised in judgment when the color changed earlier. These results confirmed the veracity of CMA in different tasks and point to the viability of analyzing response times in traditional psychophysical studies.

Reward makes the rhythmic sampling of spatial attention emerge earlier.

A growing body of evidence demonstrates a rhythmic characteristic of spatial attention, with the corresponding behavioral performance fluctuating periodically. Here, we investigate whether and how the rhythmic characteristic of spatial attention is affected by reward-an important factor in attentional selection. We adopted the classic spatial cueing paradigm with a time-resolved stimulus-onset-asynchrony (SOA) between the spatial cue and the target such that responses to the target in different phases could be examined. The color of the spatial cue was associated with either a high or low level of reward. Results showed that in the low-frequency band (<2 Hz) where classic exogenous spatial attention effects (i.e., facilitation and inhibition of return; IOR) appeared, reward enhanced the late IOR effect through facilitating behavioral responses to the target at the uncued location. Recurring lower alpha power (alpha inhibition) which fluctuated in a low-theta frequency (2-3 Hz) was observed at the cued location relative to the uncued location, irrespective of the reward level of the cue. Importantly, the recurring alpha inhibition emerged earlier (~120 ms) in the high-reward condition relative to the low-reward condition. We propose that the recurring alpha inhibition at the cued location implies a recurring attention sampling at the cued location and the expectation of a high reward makes the periodic attention sampling emerge earlier.

Fuzzy comprehensive evaluation of multiple environmental factors for swine building assessment and control.

In confined swine buildings, temperature, humidity, and air quality are all important for animal health and productivity. However, the current swine building environmental control is only based on temperature; and evaluation and control methods based on multiple environmental factors are needed. In this paper, fuzzy comprehensive evaluation (FCE) theory was adopted for multi-factor assessment of environmental quality in two commercial swine buildings using real measurement data. An assessment index system and membership functions were established; and predetermined weights were given using analytic hierarchy process (AHP) combined with knowledge of experts. The results show that multi-factors such as temperature, humidity, and concentrations of ammonia (NH3), carbon dioxide (CO2), and hydrogen sulfide (H2S) can be successfully integrated in FCE for swine building environment assessment. The FCE method has a high correlation coefficient of 0.737 compared with the method of single-factor evaluation (SFE). The FCE method can significantly increase the sensitivity and perform an effective and integrative assessment. It can be used as part of environmental controlling and warning systems for swine building environment management to improve swine production and welfare.

Lateral prefrontal/orbitofrontal cortex has different roles in norm compliance in gain and loss domains: a transcranial direct current stimulation study.

Sanction is used by almost all known human societies to enforce fairness norm in resource distribution. Previous studies have consistently shown that the lateral prefrontal cortex (lPFC) and the adjacent orbitofrontal cortex (lOFC) play a causal role in mediating the effect of sanction threat on norm compliance. However, most of these studies were conducted in gain domain in which resources are distributed. Little is known about the mechanisms underlying norm compliance in loss domain in which individual sacrifices are needed. Here we employed a modified version of dictator game (DG) and high-definition transcranial direct current stimulation (HD-tDCS) to investigate to what extent lPFC/lOFC is involved in norm compliance (with and without sanction threat) in both gain- and loss-sharing contexts. Participants allocated a fixed total amount of monetary gain or loss between themselves and an anonymous partner in multiple rounds of the game. A computer program randomly decided whether a given round involved sanction threat for the participants. Results showed that disruption of the right lPFC/lOFC by tDCS increased the voluntary norm compliance in the gain domain, but not in the loss domain; tDCS on lPFC/lOFC had no effect on compliance under sanction threat in either the gain or loss domain. Our findings reveal a context-dependent nature of norm compliance and differential roles of lPFC/lOFC in norm compliance in gain and loss domains.

A prediction model of ammonia emission from a fattening pig room based on the indoor concentration using adaptive neuro fuzzy inference system.

Ammonia (NH3) is considered one of the significant pollutions contributor to indoor air quality and odor gas emission from swine house because of the negative impact on the health of pigs, the workers and local environment. Prediction models could provide a reasonable way for pig industries and environment regulatory to determine environment control strategies and give an effective method to evaluate the air quality. The adaptive neuro fuzzy inference system (ANFIS) simulates human's vague thinking manner to solve the ambiguity and nonlinear problems which are difficult to be processed by conventional mathematics. Five kinds of membership functions were used to build a well fitted ANFIS prediction model. It was shown that the prediction model with "Gbell" membership function had the best capabilities among those five kinds of membership functions, and it had the best performances compared with backpropagation (BP) neuro network model and multiple linear regression model (MLRM) both in wintertime and summertime, the smallest value of mean square error (MSE), mean absolute percentage error (MAPE) and standard deviation (SD) are 0.002 and 0.0047, 31.1599 and 23.6816, 0.0564 and 0.0802, respectively, and the largest coefficients of determination (R2) are 0.6351 and 0.6483, repectively. The ANFIS prediction model could be served as a beneficial strategy for the environment control system that has input parameters with highly fluctuating, complexity, and non-linear relationship.

GAPIT Version 2: An Enhanced Integrated Tool for Genomic Association and Prediction.

Most human diseases and agriculturally important traits are complex. Dissecting their genetic architecture requires continued development of innovative and powerful statistical methods. Corresponding advances in computing tools are critical to efficiently use these statistical innovations and to enhance and accelerate biomedical and agricultural research and applications. The genome association and prediction integrated tool (GAPIT) was first released in 2012 and became widely used for genome-wide association studies (GWAS) and genomic prediction. The GAPIT implemented computationally efficient statistical methods, including the compressed mixed linear model (CMLM) and genomic prediction by using genomic best linear unbiased prediction (gBLUP). New state-of-the-art statistical methods have now been implemented in a new, enhanced version of GAPIT. These methods include factored spectrally transformed linear mixed models (FaST-LMM), enriched CMLM (ECMLM), FaST-LMM-Select, and settlement of mixed linear models under progressively exclusive relationship (SUPER). The genomic prediction methods implemented in this new release of the GAPIT include gBLUP based on CMLM, ECMLM, and SUPER. Additionally, the GAPIT was updated to improve its existing output display features and to add new data display and evaluation functions, including new graphing options and capabilities, phenotype simulation, power analysis, and cross-validation. These enhancements make the GAPIT a valuable resource for determining appropriate experimental designs and performing GWAS and genomic prediction. The enhanced R-based GAPIT software package uses state-of-the-art methods to conduct GWAS and genomic prediction. The GAPIT also provides new functions for developing experimental designs and creating publication-ready tabular summaries and graphs to improve the efficiency and application of genomic research.

[Research of Straw Biomass Based on NIR by Wavelength Selection of IPLS-SPA].

The whole spectrum usually contains a lot of redundant information in the near-infrared spectroscopy model, the presence of redundant information will increase the model resolution time and increase the difficulty of parsing model, Therefore, how to select the characteristic wavelength quickly and effectly is very crucial. In this paper, we combined the algorithm based on SPA (successive projections algorithm ) with IPLS (interval partial least squares ) to selec the characteristic wavelength in the fermentation of wheat straw microbial biomass, A total of 85 samples prepared by measuring microbial biomass using glucosamine method, 68 samples are chosen as calibration set and 17 simples are chosen as verification set. First, the whole spectral region 520 points are segmented modeling according to the interval wavelength point size 10, 20, 30, 40 and 4 450~4 925 cm-1, 9 194~9 993 cm-1 two-band range are selected as the characteristic wavelength band, then pick out the new feature wavelength points by Successive Projections Algorithm band and Genetic Algorithm (GA), comprehensive analysis and comparison the result of model. The experimental results show that the using of IPLS-SPA algorithm to select the combination band 4 450~4 925 cm-1 & 9 194~9 993 cm-1 has the best modeling effect, compared with the modeling of whole spectrum, the wavelength points decrease from 520 to 10, the correction coefficient of determination R2 rised from 0. 884 9 to 0. 945 28, root mean square error (RMSE) dropped from 11. 104 9 to 8. 203 3, although the genetic algorithm model achieved the better accuracy, but the results are instable and have a strong randomness , while IPLS combined SPA method can select characteristic wavelength information stability and accurately, which can improve the model calculation speed and reduce the fitting difficulty of the model, it can be used as a new reference method for band selection. The results show that using near infrared spectroscopy method for straw biomass rapid detection is feasible.