FACILITATING SMART VOLUME LEVELS FOR AUDIO DEVICES DURING AN ONLINE TELECONFERENCE

During an online teleconference, participants may interact with each other through a variety of audio sources or devices. In some instances, a teleconference participant may switch between audio devices during a teleconference. Automatic gain control (AGC) functionality provided for clients of a teleconference system is typically designed to balance audio volume during a teleconference regardless of the audio device being used. However, AGC adjustments can be delayed for converging to a reasonable volume range. Proposed herein are techniques to address such issues by providing a volume matching table that can be used to provide optimal volume parameters for different audio devices that may be used at a local client of a user that is participating in an online teleconference. In accordance with techniques of this proposal, when a participant joins a teleconference with a given audio device or switches their audio device during the teleconference, the user\u27s client can consult the volume matching table to determine optimal volume parameters for an audio device used by the user

An Emotional Skills Intervention for Elementary Children with Autism in China: A Pilot Study

The purpose of this pilot study was to examine the effects of an emotional skills intervention on behavioral and emotional competence, as well as on communication for children with autism in China. Eight children (seven boys and one girl), aged 7 to 8, participated in this study. We used a pre and posttest group design. The intervention consisted of 10 group sessions and four individual sessions. Each group session had two or three children. The intervention curriculum consisted of emotion recognition, emotion recognition within context, self-expression of emotions, seeking help when encountering problems, and techniques for emotion regulation. Results indicated that the intervention significantly improved children’s emotional skills, behavioral and emotional competence, and communication. The potential implications of this study for elementary children with autism in China are also discussed

Gut macrobiotic and its metabolic pathways modulate cardiovascular disease

Thousands of microorganisms reside in the human gut, and extensive research has demonstrated the crucial role of the gut microbiota in overall health and maintaining homeostasis. The disruption of microbial populations, known as dysbiosis, can impair the host’s metabolism and contribute to the development of various diseases, including cardiovascular disease (CVD). Furthermore, a growing body of evidence indicates that metabolites produced by the gut microbiota play a significant role in the pathogenesis of cardiovascular disease. These bioactive metabolites, such as short-chain fatty acids (SCFAs), trimethylamine (TMA), trimethylamine N-oxide (TMAO), bile acids (BAs), and lipopolysaccharides (LPS), are implicated in conditions such as hypertension and atherosclerosis. These metabolites impact cardiovascular function through various pathways, such as altering the composition of the gut microbiota and activating specific signaling pathways. Targeting the gut microbiota and their metabolic pathways represents a promising approach for the prevention and treatment of cardiovascular diseases. Intervention strategies, such as probiotic drug delivery and fecal transplantation, can selectively modify the composition of the gut microbiota and enhance its beneficial metabolic functions, ultimately leading to improved cardiovascular outcomes. These interventions hold the potential to reshape the gut microbial community and restore its balance, thereby promoting cardiovascular health. Harnessing the potential of these microbial metabolites through targeted interventions offers a novel avenue for tackling cardiovascular health issues. This manuscript provides an in-depth review of the recent advances in gut microbiota research and its impact on cardiovascular health and offers a promising avenue for tackling cardiovascular health issues through gut microbiome-targeted therapies

Experimental simulation on the electrochemical mechanism of iron pollution from “dual-source” in closed coal mine water

The closed coal mine water is mostly characterized by high iron. After mine closure and flooding, residual iron-prone devices and iron-bearing minerals form a “dual-source” iron pollution system in mine water, contributing to the release of iron in different periods after mine closure and creating environmental risks in groundwater. In order to clarify the process and reaction mechanism of “dual-source” iron release in closed coal mine water, to characterize the “dual-source” release mode of iron pollution, and compare the release rate, based on the principle of electrochemical simulation, the working electrodes were prepared by using pyrite and mining bolt as the simulated “dual-source”, and the redox reaction process and iron release mechanism in the acid mine water under the coexistence of “dual-source” at the early stage of coal mine closure were simulated using electrochemical methods such as cyclic voltammetry and polarization as well as X-ray photoelectron spectroscopy (XPS) material surface characterization techniques. The results showed that the dissolved oxygen content was an important inhibitory factor affecting the redox reaction of pyrite and bolt in acid mine drainage. The oxidation mechanism of pyrite and bolt is different, the passivation effect occurs on the surface of pyrite during oxidation, and the final oxidation products of both materials are Fe3+ and \begin{document}${ {\rm{SO}}_{4}^{2-}}$\end{document}. Pyrite releases iron mainly through the oxidation reaction of Fe2+ on the mineral surface. Bolt released iron mainly through the reaction of iron and its oxidation products on the surface of the material with the acid substances in the solution, and the oxide reacted preferentially over the monomer. In the simulated aerobic (DO=7.0 mg/L) acid mine drainage, the annual corrosion rates of pyrite and bolt reached 8.3636 mm/a and 7.8314 mm/a, respectively, and the annual iron release rates reached 1.2240 g/a and 3.9395 g/a, respectively. In the simulated underground anoxic (DO=3.5 mg/L) acid mine drainage, the annual corrosion rates of pyrite and bolt reached 0.7324 mm/a and 0.3642 mm/a, respectively, and the estimated annual iron release rates reached 0.1072 g/a and 0.1832 g/a, respectively. The integrated electrochemical parameters and static iron release experiments showed that the total iron release rate ratios were both dual-source > bolt > pyrite under the conditions of sufficient or lack of dissolved oxygen

Electrokinetic origin of swirling flow on nanoscale interface

The zeta ($\zeta$) potential is a pivotal metric for characterizing the electric field topology within an electric double layer - an important phenomenon on phase interface. It underpins critical processes in diverse realms such as chemistry, biomedical engineering, and micro/nanofluidics. Yet, local measurement of $\zeta$ potential at the interface has historically presented challenges, leading researchers to simplify a chemically homogenized surface with a uniform $\zeta$ potential. In the current investigation, we present evidence that, within a microchannel, the spatial distribution of $\zeta$ potential across a chemically homogeneous solid-liquid interface can become two-dimensional (2D) under an imposed flow regime, as disclosed by a state-of-art fluorescence photobleaching electrochemistry analyzer (FLEA) technique. The $\zeta$ potential' s propensity to become increasingly negative downstream, presents an approximately symmetric, V-shaped pattern in the spanwise orientation. Intriguingly, and of notable significance to chemistry and engineering, this 2D $\zeta$ potential framework was found to electrokinetically induce swirling flows in tens of nanometers, aligning with the streamwise axis, bearing a remarkable resemblance to the well-documented hairpin vortices in turbulent boundary layers. Our findings gesture towards a novel perspective on the genesis of vortex structures in nanoscale. Additionally, the FLEA technique emerges as a potent tool for discerning $\zeta$ potential at a local scale with high resolution, potentially accelerating the evolution and applications of novel surface material

Afforestation in Karst Area

In order to study the afforestation technology in rocky desertification area and provide guidance for the cultivation and management of artificial forest in the later stage, an experimental study was carried out on the artificial forest in National long term scientific research base for comprehensive control of rocky desertification in Wuling Mountain, Western Hunan Province. The experiences of afforestation, land preparation and forest management in this area were summarized. The result show that: 1. Through appropriate afforestation land preparation and forest management measures, the forest in rocky desertification area can be successfully restored. 2. Vegetation restoration in rocky desertification area has formed relatively healthy and stable multi tree species and multi-level forest communities. 3. The biological yield of each afforestation tree species was significantly different with different tree species. 4. The diversity index and evenness index of undergrowth plants in different stands were significantly different. 5. Young trees of dominant species dominated the undergrowth vegetation of different stands, and the natural regeneration of each stand has been stabilized. 6. There are some differences in soil chemical properties under different stands. There were significant differences in SOM, TN, NO3-N, NH4-N and AP contents in the soil of the eight stands

Driver distraction detection based on lightweight networks and tiny object detection

Real-time and efficient driver distraction detection is of great importance for road traffic safety and assisted driving. The design of a real-time lightweight model is crucial for in-vehicle edge devices that have limited computational resources. However, most existing approaches focus on lighter and more efficient architectures, ignoring the cost of losing tiny target detection performance that comes with lightweighting. In this paper, we present MTNet, a lightweight detector for driver distraction detection scenarios. MTNet consists of a multidimensional adaptive feature extraction block, a lightweight feature fusion block and utilizes the IoU-NWD weighted loss function, all while considering the accuracy gain of tiny target detection. In the feature extraction component, a lightweight backbone network is employed in conjunction with four attention mechanisms strategically integrated across the kernel space. This approach enhances the performance limits of the lightweight network. The lightweight feature fusion module is designed to reduce computational complexity and memory access. The interaction of channel information is improved through the use of lightweight arithmetic techniques. Additionally, CFSM module and EPIEM module are employed to minimize redundant feature map computations and strike a better balance between model weights and accuracy. Finally, the IoU-NWD weighted loss function is formulated to enable more effective detection of tiny targets. We assess the performance of the proposed method on the LDDB benchmark. The experimental results demonstrate that our proposed method outperforms multiple advanced detection models

Impact of Black Carbon on Surface Ozone in the Yangtze River Delta from 2015 to 2018

From MDPI via Jisc Publications RouterHistory: accepted 2021-05-10, pub-electronic 2021-05-13Publication status: PublishedFunder: National Natural Science Foundation of China; Grant(s): 41805096Funder: National Key Research and Development Program of China; Grant(s): 2016YFA0602001Despite the yearly decline in PM2.5 in China, surface ozone has been rapidly increasing recently, which makes it imperative to coordinate and control both PM2.5 and ozone in the atmosphere. This study utilized the data of pollutant concentrations and meteorological elements during 2015 to 2018 in Nanjing, China to analyze the daily correlation between black carbon and ozone (CBO), and the distribution of the pollutant concentrations under different levels of CBO. Besides, the diurnal variations of pollutant concentrations and meteorological elements under high positive and negative CBO were discussed and compared. The results show that the percentage of positive CBO had been increasing at the average rate of 7.1%/year, and it was 38.7% in summer on average, nearly twice of that in other seasons (19.2%). The average black carbon (BC), PM2.5 and NO2 under positive CBO was lower than those under negative CBO. It is noticeable that the surface ozone began to ascend when CBO was up to 0.2, with PM2.5 and NO2 decreasing and BC remaining steady. Under negative CBO, pollutant concentrations and meteorological elements showed obvious diurnal variations: BC showed a double-peak pattern and surface ozone, PM2.5, SO2 and CO showed single-peak patterns and NO2 showed a trough from 10:00 to 19:00. Wind speed and visibility showed a single-peak pattern with little seasonal difference. Relative humidity rose first, then it lowered and then it rose. Under positive CBO, the patterns of diurnal variations became less obvious, and some of them even showed no patterns, but just fluctuated at a certain level

T1 mapping combined with arterial spin labeling MRI to identify renal injury in patients with liver cirrhosis

PurposeWe investigated the capability and imaging criteria of T1 mapping and arterial spin labeling (ASL) MRI to identify renal injury in patients with liver cirrhosis.MethodsWe recruited 27 patients with cirrhosis and normal renal function (cirrhosis-NR), 10 with cirrhosis and renal dysfunction (cirrhosis-RD) and 23 normal controls (NCs). All participants were examined via renal T1 mapping and ASL imaging. Renal blood flow (RBF) derived from ASL was measured from the renal cortex, and T1 values were measured from the renal parenchyma (cortex and medulla). MRI parameters were compared between groups. Diagnostic performances for detecting renal impairment were statistically analyzed.ResultsCortical T1 (cT1) and medullary T1 (mT1) were significantly lower in the NCs than in the cirrhosis-NR group. The cortical RBF showed no significant changes between the NCs and cirrhosis-NR group but was markedly decreased in the cirrhosis-RD group. The areas under the curve (AUCs) for discriminating cirrhosis-NR from NCs were 0.883 and 0.826 by cT1 and mT1, respectively. Cortical RBF identified cirrhosis-RD with AUC of 0.978, and correlated with serum creatinine (r = −0.334) and the estimated glomerular filtration rate (r = 0.483). A classification and regression tree based on cortical RBF and cT1 achieved 85% accuracy in detecting renal impairment in the cirrhosis.ConclusionRenal T1 values might be sensitive predictors of early renal impairment in patients with cirrhosis-NR. RBF enabled quantifying renal perfusion impairment in patients with cirrhosis-RD. The diagnostic algorithm based on cortical RBF and T1 values allowed detecting renal injury during cirrhosis