Relationship between visual ability assessment and punch performance in competition in male amateur boxers.

Sport visual ability plays an important role in the performance of elite athletes in competition. However, its relationship with boxers' performance has not been fully understood. This study investigated the relationship between sports visual abilities and in-competition punching performance in 26 highly trained male amateur boxers. Ten visual abilities of the boxers were tested using the Senaptec Sensory Station (Senaptec, Beaverton, OR, United States), including Visual Clarity (VC), Contrast Sensitivity (CS), Depth Perception (DP), Near Far Quickness (NFQ), Target Capture (TC), Perception Span (PS), Multiple Object Tracking (MOT), Eye-Hand Coordination (EHC), Go/No Go (GNG), and Reaction Time (RT). Performance analyses were conducted on national boxing championships conducted by the boxers to analyze their punching accuracy. Correlation and regression analyses showed that punch performance %Hit was very strong correlated with DP, EHC, GNG, and RT, and showed a strong correlation with VC, CS, and PS. %Hit was moderate correlated with MOT, while there was no correlation with NFQ and TC. In addition, RT, EHC, and DP are important visual ability variables for boxers. The results of this study indicate that there is an overall relationship between sports visual ability and boxing performance, but there is also a specific relationship between variables in visual ability and boxing performance, especially faster reaction times, better processing of visual information, and decision-making abilities, and the ability to accurately recognize the distance and position of an opponent and their punches are essential for enhancing boxing performance. Further studies are needed to investigate the relationship between sport visual ability and more comprehensive performance in boxers, and the possibility of enhancing performance through specific visual training.

A Mixed-Field Circular and Non-Circular Source Localization Algorithm Based on Exact Spatial Propagation Geometry.

In passive localization techniques, as the scale of the array of the sensors used increases, the source distribution may be a coexistence of near-field (NF) and far-field (FF) sources. Most of the existing algorithms dedicated to the localization of mixed-field sources are based on a simplified model, which has model errors and cannot make good use of non-circular properties when non-circular signals are present in the sources. In this paper, we present a mixed-field circular and non-circular source localization algorithm based on exact spatial propagation geometry. First, we make an initial estimate of the source parameters using exact spatial geometry relations. The MUSIC algorithm is then used in combination with the non-circular properties of the signal to achieve an accurate estimate. The algorithm does not lose performance due to model mismatch and is able to make good use of the non-circular properties of the sources to improve the estimation accuracy. The simulation results show that the proposed algorithm can effectively distinguish between sources and that the algorithm performs satisfactorily.

An L-Shaped Three-Level and Single Common Element Sparse Sensor Array for 2-D DOA Estimation.

The degree of freedom (DOF) is an important performance metric for evaluating the design of a sparse array structure. Designing novel sparse arrays with higher degrees of freedom, while ensuring that the array structure can be mathematically represented, is a crucial research direction in the field of direction of arrival (DOA) estimation. In this paper, we propose a novel L-shaped sparse sensor array by adjusting the physical placement of the sensors in the sparse array. The proposed L-shaped sparse array consists of two sets of three-level and single-element sparse arrays (TSESAs), which estimate the azimuth and elevation angles, respectively, through one-dimensional (1-D) spatial spectrum search. Each TSESA is composed of a uniform linear subarray and two sparse subarrays, with one single common element in the two sparse subarrays. Compared to existing L-shaped sparse arrays, the proposed array achieves higher degrees of freedom, up to 4Q1Q2+8Q1-5, when estimating DOA using the received signal covariance. To facilitate the correct matching of azimuth and elevation angles, the cross-covariance between the two TSESA arrays is utilized for estimation. By comparing and analyzing performance parameters with commonly used L-shaped and other sparse arrays, it is found that the proposed L-shaped TSESA has higher degrees of freedom and array aperture, leading to improved two-dimensional (2-D) DOA estimation results. Finally, simulation experiments validate the excellent performance of the L-shaped TSESA in 2-D DOA estimation.

Spatial Multi-Source Information Fusion Localization Algorithm in Non-Line-of-Sight Environments.

In this paper, a high-accuracy localization problem under a complex non-line-of-sight (NLOS) condition is addressed by a new method that utilizes multiple NLOS paths to improve localization accuracy, as opposed to the traditional method of suppressing them. The spatial multi-path array fusion localization model is presented and analyzed, followed by an angle-of-arrival (AOA) and time-of-arrival (TOA) algorithm based on spatial multi-information fusion that seeks to improve localization accuracy. Multi-path of spatial signals, measurement of the multi-element antenna, and geographic environment information are integrated into the proposed method for localization optimization. Simulation experiments were carried out, and the results revealed that the proposed algorithm is capable of making full use of spatial multi-location information for localization, thus improving the accuracy of localization in a the NLOS environment effectively and increasing the locatable probability of complex environment localization applications.

The heterogeneous effects of environmental regulation on industrial carbon emission efficiency in China using a panel quantile regression.

In order to verify how environmental regulation affects the improvement of urban industrial carbon emission efficiency, this study first measures the balanced panel data of industrial carbon emission efficiency of 282 cities in China from 2003 to 2019, and evaluates the direct and regulating impact of environmental regulation on China's urban industrial carbon emission efficiency. Meanwhile, in order to investigate the potential heterogeneity and asymmetry, the panel quantile regression method is used. The empirical results show that (1) during the period 2003-2016, China's overall industrial carbon emission efficiency showed a upward trend, with a decreasing spatial pattern from the east-central-west-northeast region. At the urban scale in China, environmental regulation has a significant direct effect on industrial carbon emission efficiency, which is lagged and heterogeneous. At the low quantiles, a one-period lag in environmental regulation has a negative effect on the improvement of industrial carbon emission efficiency. At the middle and high quantiles, a one-period lag in environmental regulation has a positive effect on the improvement of industrial carbon emission efficiency. Environmental regulation has a moderating effect on industrial carbon efficiency. With increasing industrial emission efficiency, the positive moderating effect of environmental regulation on the relationship between technological progress and industrial carbon emission efficiency shows a pattern of diminishing marginal benefits. The main contribution of this study is the systematic analysis of the potential heterogeneity and asymmetry of the direct and moderating effects of environmental regulation on the industrial carbon emission efficiency at the city scale in China by using panel quantile regression method.

Comparative Analyses of the Fecal Microbiome of Five Wild Black-Billed Capercaillie (Tetrao parvirostris) Flocks.

Black-billed capercaillie (Tetrao parvirostris) was listed as a first-class state-protected animal because it was endangered in China (Category I). This study is the first to examine the diversity and composition of T. parvirostris gut microbiome in the wild. We collected fecal samples from five black-billed capercaillie flock roosting sites (each 20 km apart) in one day. Thirty fecal samples were sequenced with 16S rRNA gene amplicons on the Illumina HiSeq platform. This study is the first to analyze the fecal microbiome composition and diversity of black-billed capercaillie in the wild. At the phylum level, Camplyobacterota, Bacillota, Cyanobacteria, Actinomycetota, and Bacteroidota were the most abundant in the fecal microbiome of black-billed capercaillie. At the genus level, unidentified Chloroplast, Escherichia-Shigella, Faecalitalea, Bifidobacterium, and Halomonas were the dominant genera. Based on alpha and beta diversity analyses, we found no significant differences in the fecal microbiome between five flocks of black-billed capercaillie. Protein families: genetic information processing; protein families: signaling and cellular processes, carbohydrate metabolism; protein families: metabolism and energy metabolism are the main predicted functions of the black-billed capercaillie gut microbiome through the PICRUSt2 method. This study reveals the composition and structure of the fecal microbiome of the black-billed capercaillie under wild survival conditions, and this study provides scientific data for the comprehensive conservation of the black-billed capercaillie.

Null Broadening Robust Adaptive Beamforming Algorithm Based on Power Estimation.

In order to solve the problem of severely decreased performance under the situation of rapid moving sources and unstable array platforms, a null broadening robust adaptive beamforming algorithm based on power estimation is proposed in this paper. First of all, we estimate the interference signal power according to the characteristic subspace theory. Then, the correspondence between the signal power and steering vector (SV) is obtained based on the orthogonal property, and the interference covariance matrix (ICM) is reconstructed. Finally, with the aim of setting virtual interference sources, null broadening can be carried out. The proposed algorithm results in a deeper null, lower side lobes and higher tolerance of the desired signal steering vector mismatch under the condition of low complexity. The simulation results show that the algorithm also has stronger robustness.

Joint Estimation for Time Delay and Direction of Arrival in Reconfigurable Intelligent Surface with OFDM.

Recently, the joint estimation for time delay (TD) and direction of arrival (DOA) has suffered from the high complexity of processing multi-dimensional signal models and the ineffectiveness of correlated/coherent signals. In order to improve this situation, a joint estimation method using orthogonal frequency division multiplexing (OFDM) and a uniform planar array composed of reconfigurable intelligent surface (RIS) is proposed. First, the time-domain coding function of the RIS is combined with the multi-carrier characteristic of the OFDM signal to construct the coded channel frequency response in tensor form. Then, the coded channel frequency response covariance matrix is decomposed by CANDECOMP/PARAFAC (CPD) to separate the signal subspaces of TD and DOA. Finally, we perform a one-dimensional (1D) spectral search for TD values and a two-dimensional (2D) spectral search for DOA values. Compared to previous efforts, this algorithm not only enhances the adaptability of coherent signals, but also greatly decreases the complexity. Simulation results indicate the robustness and effectiveness for the proposed algorithm in independent, coherent, and mixed multipath environments and low signal-to-noise ratio (SNR) conditions.

Spatial Evolutionary Characteristics and Influencing Factors of Urban Industrial Carbon Emission in China.

Climate warming caused by carbon emissions is a hot topic in the international community. Research on urban industrial carbon emissions in China is of great significance for promoting the low-carbon transformation and spatial layout optimization of Chinese industry. Based on ArcGIS spatial analysis, Markov matrix and other methods, this paper calculates and analyzes the temporal and spatial evolution characteristics of industrial carbon emissions in 282 cities in China from 2003 to 2016. Based on the spatial Dubin model, the influencing factors of urban industrial carbon emissions in China and different regions are systematically analyzed. The study shows that (1) China's urban industrial carbon emissions generally show a trend of first growth and then slow decline. The trend of urban industrial carbon emissions in the western, central, northeastern and eastern regions of China is basically consistent with the overall national trend; (2) In 2003, China's urban industrial carbon emissions were dominated by low carbon emissions. In 2016, China's urban industrial carbon emissions were dominated by high carbon emissions, and the spatial trend is gradually decreasing from the eastern region to the central region to the northeast region to the western region; (3) In 2003, the evolution pattern of China's urban industrial carbon emissions was "low carbon-horizontal expansion" dominated by positive growth, and in 2016, it was "low carbon-vertical expansion" dominated by scale growth; (4) China's urban industrial carbon emissions have spatial viscosity, and the spatial viscosity decreases with the increase of industrial carbon emissions. (5) In 2004, the relationship between urban industrial carbon emissions and gross industrial output value in China is mainly weak decoupling. In 2016, various types of decoupling regions are more diversified and dispersed, and strong decoupling cities are mainly formed from weak decoupling cities in southwest China and eastern coastal areas; (6) From a national perspective, indicators that are significantly positively correlated with industrial carbon emissions are urban industrial structure, industrial agglomeration level, industrial enterprise scale and urban economic development level, in descending order. Indicators that are significantly negatively correlated with urban industrial carbon emissions are industrial structure and industrial ownership structure, in descending order. Due to the different stages of industrial development and industrial structure in different regions, the influencing factors are also different.

Lower extremity isokinetic strength characteristics of amateur boxers.

Aim: Sufficient strength and dynamic stability of the lower limbs are essential for improving punching force and preventing injury in amateur boxers. However, there are still no comprehensive reports on the isokinetic knee strength of boxers with different performance levels. The current study aimed to profile the isokinetic muscle strength of flexion and extension of the knee in boxers, as well as bilateral, unilateral, and functional ratios, and investigate the variation in these muscle strength characteristics associated with different performance levels. Methods: Boxers were divided in two performance groups, elite (five males and four females) and non-elite groups (five males and four females). Muscle strength of the knee was determined via an IsoMed2000 device. Parameters examined included peak torque of the hamstring (H) and quadriceps (Q) during concentric (con) and eccentric (ecc) contractions at low (60°/S), medium (180°/S), and high (240°/S) speed and bilateral ratios (BLs), unilateral ratios (ULs), and functional ratios of dominant (D) and non-dominant limbs. Results: In all angular velocities, the peak torque of H and Q was stronger in the elite group than in the non-elite group. ULs were lower in the elite group than in the non-elite group in Hcon/Qcon at 180D (p < 0.01) and 180ND (p < 0.05) and in Hecc/Qecc at 60D, 180D (p < 0.05) and 240D (p < 0.01). The elite group had higher BLs than the non-elite group in Hcon at 60°/S (p < 0.05) and Qcon at 180°/S (p < 0.05). The non-elite group had a higher functional ratio than elite boxers in Hecc/Qcon at 180D and 240D (p < 0.01). Conclusion: Elite boxers had stronger knee strength in con and ecc contractions. All boxers had normal Hecc/Qecc and Hcon/Qecc. Hcon/Qcon and Hecc/Qcon were abnormal at lower angular velocity. Elite boxers had higher BLs and lower ULs, indicating that they are at a higher risk of injury.

Acute effects of ballistic versus heavy-resistance exercises on countermovement jump and rear-hand straight punch performance in amateur boxers.

BACKGROUND: Ballistic and heavy-resistance exercises may potentially enhance lower body power, which is paramount for the punching performance of amateur boxers. This study aimed to determine the acute effects of ballistic exercise (BE) and heavy-resistance exercise (HRE) on countermovement jump (CMJ) and rear-hand straight punch performance in amateur boxers. METHODS: Ten amateur boxers performed two conditioning exercises in a randomized and counterbalanced order as follows: squat jump with 4 sets × 8 repetitions at 30% one-repetition maximum (1RM) for BE and squat with 3 sets × 5 repetitions at 80% 1RM for HRE. The jump height (JH), relative maximal force (RMF), relative maximal power (RMP) of the CMJ, punch force (PF), and punch speed (PS) of a rear-hand straight punch were measured before and 3, 6, 9, and 12 min after either BE or HRE. RESULTS: No significant condition × time interaction was found for JH (p = 0.303), RMF (p = 0.875), RMP (p = 0.480), PF (p = 0.939), and PS (p = 0.939). In addition, no main effect of the condition for JH (p = 0.924), RMF (p = 0.750), RMP (p = 0.631), PF (p = 0.678), and PS (p = 0.712). A significant main effect of time was observed for PF (p = 0.001) and PS (p = 0.001), whereas JH (p = 0.081), RMF (p = 0.141), and RMP (p = 0.430) were not. Pairwise comparison identified that PF (p = 0.031) and PS (p = 0.005) significantly increased at 9 min compared with those at baseline. CONCLUSIONS: The findings of this study demonstrated that BE and HRE protocols can potentiate the rear-hand straight punch performance at 9 min but bring less favorable improvements for JH, RMF, or RMP of CMJ.

Reagent free detection of SARS-CoV-2 using an antibody-based microwave sensor in a microfluidic platform.

The global COVID-19 pandemic caused by SARS-CoV-2 has resulted in an unprecedented economic and societal impact. Developing simple and accurate testing methods for point-of-care (POC) diagnosis is crucial not only for the control of COVID-19, but also for better response to similar outbreaks in the future. In this work, we present a novel proof-of-concept of a microfluidic microwave sensing method for POC diagnosis of the SARS-CoV-2 virus. This method relies on the antibody immobilized on the microwave sensor to selectively capture and concentrate the SARS-CoV-2 antigen or virus present in a buffer solution flowing through the sensor region in a microchannel. The capturing of the SARS-CoV-2 antigen or virus results in a change in the permittivity of the medium near the sensor region reflected by the resonance frequency shift which is used for detection. The use of microchannels offers precise control of the sample volume and the continuous flow nature also offers the potential to monitor the dynamic capturing process. The microwave-microfluidic device shows a good sensitivity of 0.1 ng ml-1 for the SARS-CoV-2 antigen and 4000 copies per ml for the SARS-CoV-2 virus. The resonance frequency shift presents a linear relationship with the logarithm of antigen or virus concentration, respectively. This detection method is able to distinguish SARS-CoV-2 from the antigen of human CD4 and two human coronaviruses (MERS and HKU1), which presents a new pathway towards POC diagnosis of the COVID-19 at the community level. It presents the potential to detect other viruses by functionalizing the microwave sensor with respective antibodies.

Microwave Heating Induced On-Demand Droplet Generation in Microfluidic Systems.

In this note, we report a simple, new method for droplet generation in microfluidic systems using integrated microwave heating. This method enables droplet generation on-demand by using microwave heating to induce Laplace pressure change at the interface of the two fluids. The distance between the interface and junction and microwave excitation power have been found to influence droplet generation. Although this method is limited in generating droplets with a high rate, the fact that it can be integrated with microwave sensing that can be used as the feedback to tune the supply flow of materials presents unique advantages for applications that require dynamic tuning of material properties in droplets.

Functional Control of Peptide Amphiphile Assemblies via Modulation of Internal Cohesion and Surface Chemistry Switch.

Understanding the impacts of the internal cohesion and surface chemistry of supramolecular systems on the collective behaviors in the contacts between the systems and biomolecules can greatly expand the functional diversity and adaptivity of supramolecular nanostructures. Here we show how the tuned molecular interactions modulate the morphologies and internal cohesion of peptide amphiphile (PA) self-assemblies and their resultant functions. Circular dichroism spectroscopy, fluorescence probing, atomic force and electron microscopy, along with molecular dynamics simulations, revealed that the PA self-assembly formed compact long fibers when surface charge repulsion was screened, but formed loose short fibers or micelle-like assemblies when hydrogen bonding was disrupted or hydrophobic core was enhanced. More importantly, depending on the strength of the phospholipid affinity for the cationic segment of the PA, the same internal cohesion of PA nanostructures can lead to either cell death or cell survival, providing unique insights into the design of supramolecular materials.

Association between Twist and multidrug resistance gene-associated proteins in Taxol®-resistant MCF-7 cells and a 293 cell model of Twist overexpression.

Multidrug resistance (MDR) severely limits the effectiveness of chemotherapy. Previous studies have identified Twist as a key factor of acquired MDR in breast, gastric and prostate cancer. However, the underlying mechanisms of action of Twist in MDR remain unclear. In the present study, the expression levels of MDR-associated proteins, including lung resistance-related protein (LRP), topoisomerase IIα (TOPO IIα), MDR-associated protein (MRP) and P-glycoprotein (P-gp), and the expression of Twist in cancerous tissues and pericancerous tissues of human breast cancer, were examined. In order to simulate Taxol® resistance in cells, a Taxol®-resistant human mammary adenocarcinoma cell subline (MCF-7/Taxol®) was established by repeatedly exposing MCF-7 cells to high concentrations of Taxol® (up to 15 µg/ml). Twist was also overexpressed in 293 cells by transfecting this cell line with pcDNA5/FRT/TO vector containing full-length hTwist cDNA to explore the dynamic association between Twist and MDR gene-associated proteins. It was identified that the expression levels of Twist, TOPO IIα, MRP and P-gp were upregulated and LRP was downregulated in human breast cancer tissues, which was consistent with the expression of these proteins in the Taxol®-resistant MCF-7 cell model. Notably, the overexpression of Twist in 293 cells increased the resistance to Taxol®, Trichostatin A and 5-fluorouracil, and also upregulated the expression of MRP and P-gp. Taken together, these data demonstrated that Twist may promote drug resistance in cells and cancer tissues through regulating the expression of MDR gene-associated proteins, which may assist in understanding the mechanisms of action of Twist in drug resistance.

Two-Dimensional DOA Estimation for Coherently Distributed Sources with Symmetric Properties in Crossed Arrays.

In this paper, a novel algorithm is proposed for the two-dimensional (2D) central direction-of-arrival (DOA) estimation of coherently distributed (CD) sources. Specifically, we focus on a centro-symmetric crossed array consisting of two uniform linear arrays (ULAs). Unlike the conventional low-complexity methods using the one-order Taylor series approximation to obtain the approximate rotational invariance relation, we first prove the symmetric property of angular signal distributed weight vectors of the CD source for an arbitrary centrosymmetric array, and then use this property to establish two generalized rotational invariance relations inside the array manifolds in the two ULAs. Making use of such relations, the central elevation and azimuth DOAs are obtained by employing a polynomial-root-based search-free approach, respectively. Finally, simple parameter matching is accomplished by searching for the minimums of the cost function of the estimated 2D angular parameters. When compared with the existing low-complexity methods, the proposed algorithm can greatly improve estimation accuracy without significant increment in computation complexity. Moreover, it performs independently of the deterministic angular distributed function. Simulation results are presented to illustrate the performance of the proposed algorithm.

[Detection of APC gene germline mutation in Chinese familial adenomatous polyposis by direct sequencing in combination with multiplex ligation-dependent probe amplification].

OBJECTIVE: To investigate the characteristics of APC gene germline mutation in Chinese patients with familial adenomatous polyposis (FAP). METHODS: The genomic DNA was extracted from peripheral venous blood drawn from probands of 14 Chinese FAP families from Beijing, Hebei, Henan, Anhui, Inner Mongolia, Shanxi and Fujian. The APC gene was amplified by PCR and underwent direct sequencing. Large fragment deletion was detected by multiplex ligation-dependent probe amplification (MLPA) only in micromutation-negative samples found by sequencing. RESULTS: APC gene micromutations were found in 9 probands and the micromutation detection rate was 64.3%, including 6 frameshift mutations, 2 splicing mutations and 1 nonsense mutation. Large fragment deletions of APC gene were detected in 2 probands (14.3%). The total mutation detection rate of micromutation and large fragment deletion was 78.6%. Four novel micromutations and 2 novel large fragment deletions were found, including c.2336-2337insT, c.3923-3929delAAGAAAA, c.532-2A > T, c.4179-4180GAdelinsT, large fragment deletions of exons 11 and 10A and large fragment deletion of exon 15 start. CONCLUSIONS: In Chinese FAP patients, the germline mutation type of APC gene is variable; the majority is of frameshift mutation. The most common mutation site is exon 15. The mutation detection rate of APC gene can be boosted effectively by direct sequencing in combination with MLPA.

APC gene mutations in Chinese familial adenomatous polyposis patients.

AIM: To study the characteristics of APC (adenomatous polyposis coli) gene germline mutation in Chinese patients with familial adenomatous polyposis (FAP). METHODS: APC gene from 14 FAP families was amplified by polymerase chain reaction (PCR) and underwent direct sequencing to determine the micromutation type. For the samples without micromutation, the large fragment deletion of APC gene was examined by multiplex ligation-dependent probe amplification (MLPA). RESULTS: There were gene micromutations in 9 families with a micromutation detection rate of 64.3% (9/14), including 6 frameshift mutations (66.7%), 1 nonsense mutation (11.1%) and 2 splicing mutations (22.2%). Large fragment deletions were detected by MLPA in 2 families. The total mutation detection rate of micromutations and large fragment deletions was 78.6% (11/14). CONCLUSION: The detection rate of APC gene germline mutation can be improved by direct sequencing combined with MLPA large fragment deletion detection.

[Study on the basic characteristics of Bohai Sea ice reflectance spectra].

For monitoring sea ice in Bohai Sea, the present paper performed a field observation experiment on sea ice reflectance spectrum in Bohai Sea by control experiment. In the experiment, three groups of sea ice samples from the Bayuquan in Liaodong Gulf were collected, which were clean even ice of different thickness, sea ice covered by melt snow layer and sea ice with sands. According to the series of observation data during the two years, the reflectance spectrum curve of clean even ice has double peaks (a big one and a small one) when the ice thickness is less than 30 cm. The principal reflection peak is in good relation to the thickness of the sea ice. The principal reflection spectral peak of ice covered by melt snow layer is obviously higher than that of the spectrum of clean even ice without the snow layer with the same ice thickness. The principal reflection spectral peak of the sea ice with sands increases sharply, and the spectrum curve arises slightly in the wavelength rang between 675 and 725 mm and then declines. Covering snow and sands are the key factors to result in the fact that the same ice thicknesses present different spectrum characteristics and the same spectrum characteristics present different thicknesses.