Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:predictors of patient prognosis

Patients with mild traumatic brain injury have a diverse clinical presentation,and the underlying pathophysiology remains poorly understood.Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neuro biological markers after mild traumatic brain injury.This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury.G raph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function.However,most previous mild traumatic brain injury studies using graph theory have focused on specific populations,with limited exploration of simultaneous abnormalities in structural and functional connectivity.Given that mild traumatic brain injury is the most common type of traumatic brain injury encounte red in clinical practice,further investigation of the patient characteristics and evolution of structural and functional connectivity is critical.In the present study,we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury.In this longitudinal study,we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 wee ks of injury,as well as 36 healthy controls.Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis.In the acute phase,patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network.More than 3 months of followup data revealed signs of recovery in structural and functional connectivity,as well as cognitive function,in 22 out of the 46 patients.Furthermore,better cognitive function was associated with more efficient networks.Finally,our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal changes in connectivity in patients with mild traumatic brain injury.These findings highlight the importance of integrating structural and functional connectivity in unde rstanding the occurrence and evolution of mild traumatic brain injury.Additionally,exploratory analysis based on subnetworks could serve a predictive function in the prognosis of patients with mild traumatic brain injury.

无人飞行器在不确定扰动下的动态目标跟踪

This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied environments.The proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target.A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is proposed.The depth model ensures image feature accuracy and image trajectory smoothness in rotating target tracking.The relative velocities of the UAV and the dynamic target are estimated using the proposed velocity observer.Thanks to the velocity observer,translational velocity measurements are not required,and the control chatter caused by noise-containing measurements is mitigated.An integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the antidisturbance ability.The stability of the velocity observer and IBVS controller is analyzed using the Lyapunov method.Comparative simulations and multistage experiments are conducted to illustrate the tracking stability,anti-disturbance ability,and tracking robustness of the proposed method with a dynamic rotating target.

The Enforcement of Occupational Safety and Health Requirements in Public and Private Sectors in the Emirate of Abu Dhabi, the United Arab Emirates

Research Problem: In Abu Dhabi, limited implementation of OSH Regulations contributes to the general unawareness among employees and workers about occupational hazards and safety measures, resulting in slow responsiveness toward enforcement measures and a lack of self-regulatory approaches within companies. Purpose: The purpose of this study is to examine the implementation methods practised in Abu Dhabi with those in developed countries with established OSH regulatory bodies. Methodology: Qualitative and quantitative research methods were employed to gather primary research data. Workers from various industries in Abu Dhabi were sampled on purpose and asked to respond to questionnaires and interviews on OSH protocol awareness and implementation, and circumstances of workplace incidence. Results: The findings of this study showed that the enforcement of OSH requirements in UAE positively correlated to a reduction in the rate of work-related injury and improved business performance. The quantitative research data showed that the energy sector had the highest score (15) while the tourism sector had the lowest score (5.3) in occupational health systems and improvements in business efficiency and productivity. Implications: The outcomes of this study shed light on the importance of implementing OSH Guidelines for companies to empower their safety managers to fully enforce OSH requirements in their organisations. In conclusion, effective OSH enforcement requires cooperation between general workers and OSH managers and facilitation from business owners.

Profiling Astronomical Objects Using Unsupervised Learning Approach

Attempts to determine characters of astronomical objects have been one of major and vibrant activities in both astronomy and data science fields.Instead of a manual inspection,various automated systems are invented to satisfy the need,including the classification of light curve profiles.A specific Kaggle competition,namely Photometric LSST Astronomical Time-Series Classification Challenge(PLAsTiCC),is launched to gather new ideas of tackling the abovementioned task using the data set collected from the Large Synoptic Survey Telescope(LSST)project.Almost all proposed methods fall into the supervised family with a common aim to categorize each object into one of pre-defined types.As this challenge focuses on developing a predictive model that is robust to classifying unseen data,those previous attempts similarly encounter the lack of discriminate features,since distribution of training and actual test datasets are largely different.As a result,well-known classification algorithms prove to be sub-optimal,while more complicated feature extraction techniques may help to slightly boost the predictive performance.Given such a burden,this research is set to explore an unsupervised alternative to the difficult quest,where common classifiers fail to reach the 50%accuracy mark.A clustering technique is exploited to transform the space of training data,from which a more accurate classifier can be built.In addition to a single clustering framework that provides a comparable accuracy to the front runners of supervised learning,a multiple-clustering alternative is also introduced with improved performance.In fact,it is able to yield a higher accuracy rate of 58.32%from 51.36%that is obtained using a simple clustering.For this difficult problem,it is rather good considering for those achieved by well-known models like support vector machine(SVM)with 51.80%and Naive Bayes(NB)with only 2.92%.

Classification of Adversarial Attacks Using Ensemble Clustering Approach

As more business transactions and information services have been implemented via communication networks,both personal and organization assets encounter a higher risk of attacks.To safeguard these,a perimeter defence likeNIDS(network-based intrusion detection system)can be effective for known intrusions.There has been a great deal of attention within the joint community of security and data science to improve machine-learning based NIDS such that it becomes more accurate for adversarial attacks,where obfuscation techniques are applied to disguise patterns of intrusive traffics.The current research focuses on non-payload connections at the TCP(transmission control protocol)stack level that is applicable to different network applications.In contrary to the wrapper method introduced with the benchmark dataset,three new filter models are proposed to transform the feature space without knowledge of class labels.These ECT(ensemble clustering based transformation)techniques,i.e.,ECT-Subspace,ECT-Noise and ECT-Combined,are developed using the concept of ensemble clustering and three different ensemble generation strategies,i.e.,random feature subspace,feature noise injection and their combinations.Based on the empirical study with published dataset and four classification algorithms,new models usually outperform that original wrapper and other filter alternatives found in the literature.This is similarly summarized from the first experiment with basic classification of legitimate and direct attacks,and the second that focuses on recognizing obfuscated intrusions.In addition,analysis of algorithmic parameters,i.e.,ensemble size and level of noise,is provided as a guideline for a practical use.

The Role of Deep Learning in Parking Space Identification and Prediction Systems

In today’s smart city transportation,traffic congestion is a vexing issue,and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40%of traffic congestion.Identifying parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives,resulting in the driver’s frustration and aggravating traffic jams while searching for another parking space.This explains the need to predict the availability of parking spaces.Recently,deep learning(DL)has been shown to facilitate drivers to find parking spaces efficiently,leading to a promising performance enhancement in parking identification and prediction systems.However,no work reviews DL approaches applied to solve parking identification and prediction problems.Inspired by this gap,the purpose of this work is to investigate,highlight,and report on recent advances inDLapproaches applied to predict and identify the availability of parking spaces.Ataxonomy of DL-based parking identification and prediction systems is established as a methodology by classifying and categorizing existing literature,and by doing so,the salient and supportive features of different DL techniques for providing parking solutions are presented.Moreover,several open research challenges are outlined.This work identifies that there are various DL architectures,datasets,and performance measures used to address parking identification and prediction problems.Moreover,there are some open-source implementations available that can be used directly either to extend existing works or explore a new domain.This is the first short survey article that focuses on the use of DL-based techniques in parking identification and prediction systems for smart cities.This study concludes that although the deployment of DL in parking identification and prediction systems provides various benefits,the convergence of these two types of systems and DL brings about new issues that must be resolved in the near future.

Connectome-based predictive modelling can predict follow-up craving after abstinence in individuals with opioid use disorders

Background Individual differences have been detected in individuals with opioid use disorders(OUD)in rehabilitation following protracted abstinence.Recent studies suggested that prediction models were effective for individual-level prognosis based on neuroimage data in substance use disorders(SUD).Aims This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome-based predictive modelling(CPM).Methods One hundred and eight inpatients with OUD underwent structural and functional magnetic resonance imaging(fMRI)scans at baseline.The Heroin Craving Questionnaire(HCQ)was used to assess craving levels at baseline and at the 8-month follow-up of abstinence.CPM with leave-one-out cross-validation was used to identify baseline networks that could predict follow-up HCQ scores and changes in HCQ(HCQtolow V-up-HCQpa baseline).Then,the follow-up aseline predictive ability of identified networks was tested in a separate,heterogeneous sample of methamphetamine individuals who underwent MRI scanning before abstinence for SUD.Results CPM could predict craving changes induced by long-term abstinence,as shown by a significant correlation between predicted and actual HCQ fllow-up(r=0.417,p<0.001)and changes in HCQ(negative:r=0.334,p=0.002;positive:r=0.233,p=0.038).Identified craving-related prediction networks included the somato-motor network(SMN),salience network(SALN),default mode network(DMN),medial frontal network,visual network and auditory network.In addition,decreased connectivity of frontal-parietal network(FPN)-SMN,FPN-DMN and FPN-SALN and increased connectivity of subcortical network(SCN)-DMN,SCN-SALNandSCN-SMN were positively correlated with craving levels.Conclusions These findings highlight the potential applications of CPM to predict the craving level of individuals after protracted abstinence,as well as the generalisation ability;the identified brain networks might be the focus of innovative therapies in the future.

天山乌鲁木齐河源末次冰期冰川沉积光释光测年

乌鲁木齐河源地区是中国冰川遗迹保存最丰富、地貌最典型的区域之一,是根据冰川遗迹重建第四纪冰川历史的理想地区。大量的研究工作以及技术测年结果也使其成为试验冰川沉积光释光(optically stimulated luminescence,OSL)测年可行性的理想地点。共采集了6个冰碛及上覆黄土样品用于光释光测年。提取38~63μm的石英颗粒,运用SAR-SGC法测试等效剂量。各种检验表明测试程序是适用的。通过地貌地层关系、重复样品、已有年代的对比等方法,检验该地冰川沉积OSL测年的可行性。结果表明,OSL年代结果与地貌地层新老关系非常吻合,与已有的其他测年技术的年代结果也具可比性,表明这些样品的OSL信号在沉积之前晒退较好,OSL年代是可信的。冰川观测站侧碛垄的OSL年代为14.8±1.2ka;9号冰川支谷口附近冰碛的OSL年代为13.5±1.1ka和17.2±1.3ka;上望峰冰碛的OSL年代为20.1±1.6ka。综合OSL年代结果与此前其他测年结果,这几套冰碛垄形成于深海氧同位素MIS2阶段应该是比较统一的认识。上望峰冰碛上覆黄土的OSL年代(10.5±0.8ka)也印证了该结论。OSL年代指示上望峰冰碛对应于末次冰期最盛期,冰川观测站和9号冰川支谷谷口冰碛对应于晚冰期。下望峰冰碛的OSL年代为36.3±2.8ka,对应于MIS3阶段。下望峰冰碛的形成时代,仍有待更多沉积学以及测年工作进一步确定。

不同光照与水分条件下2种白三叶生长特性比较

为探究不同光照和水分条件对不同品种白三叶(Trifolium repens L.)生长特性的影响,本研究以TKPR和TNSP 2个白三叶品种为试验对象,通过温室控制设定了3个光照梯度和3个水分梯度共9个组合处理,分析了不同处理下白三叶形态、生物量积累、生物量分配比及其可塑性指标的响应特征。结果表明:品种TKPR各指标受光照强度影响较大,品种TNSP受水分强度、光照与水分交互作用的影响较大;品种TNSP的相对生长速率大于TKPR;在适宜的环境下品种TNSP的生物量积累高于品种TKPR;光照与水分的交互作用对品种TKPR的开花繁殖策略影响较大;在不利的环境下品种TKPR适应可塑性较强,TNSP较弱。本研究结果为培育白三叶的新品种和高效生产栽培管理等方面提供了一定的参考依据。

高糖黑麦草在陇中黄土高原和河西绿洲引种试验初报

在陇中黄土高原和河西绿洲引入3种高糖黑麦草(Lolium perenne,HSR)‘明星’、‘神奇’和‘阿旺’。第1次刈割,在2个区域,HSR品种的可溶性碳水化合物含量均显著高于对照品种‘普通’(P<0.05);第2次刈割,在陇中黄土高原HSR品种的可溶性碳水化合物含量显著高于对照及河西绿洲HSR品种中的‘神奇’和‘阿旺’(P<0.05)。2个区域HSR品种的中性洗涤纤维、酸性洗涤纤维、粗蛋白等与对照品种差异不显著(P>0.05),但产量较低。在陇中黄土高原刈割增加分蘖密度、粗蛋白、中性洗涤纤维和酸性洗涤纤维含量,降低可溶性碳水化合物含量;而在河西绿洲呈现相反趋势。

Role of live microbial feed supplements with reference to anaerobic fungi in ruminant productivity: A review

To keep the concept of a safe food supply to the consumers, animal feed industries world over are showing an increasing interest in the direct-fed microbials（DFM） for improved animal performance in terms of growth or productivity. This becomes all the more essential in a situation, where a number of the residues of antibiotics and/or other growth stimulants reach in milk and meat with a number of associated potential risks for the consumers. Hence, in the absence of growth stimulants, a positive manipulation of the rumen microbial ecosystem to enhance the feedstuff utilization for improved production efficiency by ruminants has become of much interest to the researchers and entrepreneurs. A few genera of live microbes（i.e., bacteria, fungi and yeasts in different types of formulations from paste to powder） are infrequently used as DFM for the domestic ruminants. These DFM products are live microbial feed supplements containing naturally occurring microbes in the rumen. Among different DFM possibilities, anaerobic rumen fungi（ARF） based additives have been found to improve ruminant productivity consistently during feeding trials. Administration of ARF during the few trials conducted, led to the increased weight gain, milk production, and total tract digestibility of feed components in ruminants. Anaerobic fungi in the rumen display very strong cell-wall degrading cellulolytic and xylanolytic activities through rhizoid development, resulting in the physical disruption of feed structure paving the way for bacterial action. Significant improvements in the fiber digestibility were found to coincide with increases in ARF in the rumen indicating their role. Most of the researches based on DFM have indicated a positive response in nutrient digestion and methane reducing potential during in vivo and/or in vitro supplementation of ARF as DFM. Therefore, DFM especially ARF will gain popularity but it is necessary that all the strains are thoroughly studied for their beneficial properties to have a confirmed ‘generally regarded as safe＇ status for ruminants.

黄土高原高糖黑麦草的产量和品质预测

为探明黄土高原高糖黑麦草(Lolium perenne)粗蛋白、粗脂肪、中性洗涤纤维、酸性洗涤纤维、粗灰分、可溶性碳水化合物等指标及产草量与其生长时间、株高、分蘖之间的关系,本研究采用田间试验结合预测模型的方法,利用生长时间、株高、分蘖对高糖黑麦草在模拟轮牧和收获干草两种利用方式下的牧草产量及品质进行预测。结果表明,收获干草的Aberavon、Aberstar、Premium和Abermagic黑麦草生长时间、株高和分蘖均与各营养指标显著相关(P<0.05);模拟轮牧的Aberavon、Aberstar、Premium和Abermagic黑麦草株高与各营养指标均不相关(P>0.05),生长时间、分蘖与粗蛋白、粗灰分之外的其它品质指标均显著相关(P<0.05)。利用生长时间、株高、分蘖对4个黑麦草品种的产草量和饲用成分建立一元回归预测和多元回归预测模型,经预测值与实测值对比,预测结果准确度均较高,可为高糖黑麦草在黄土高原栽培和利用提供科学依据。

The different root apex zones contribute to drought priming induced tolerance to a reoccurring drought stress in wheat

Drought priming is a promising approach to improve tolerance to further drought in wheat.The root apex plays important roles in drought however,its contribution to drought priming remains unknown.To provide mechanistic insights into this process,the transcriptomes and proteomes at three different zones along the root axis under drought stress were analyzed.Physiological assessment of root growth indicated that priming augmented roots growth in response to drought and also the levels of protective proline and glycine betaine.Scanning across the proximal to the distal zones of the root apex indicated increases the transcription of genes involved in primary and secondary metabolism.Conversely,genes related to translation,transcription,folding,sorting and degradation,replication and repair were increased in the apex compared to the proximal zone.A single drought episode suppressed their expression but prior drought priming served to maintain expression with recurrent drought stress.The differentially primed responses genes were mainly involved in the pathways related to plant hormone signaling,stress defense and cell wall modification.The prediction of regulatory hubs using Cytoscape implicated signaling components such as the ABA receptor PYL4 as influencing antioxidant status and the cell cycle.Based our integrative transcriptomic-proteomic assessments we present a model for drought priming protected plant hormone signaling transduction pathways to drive the cell cycle and cell wall loosening to confer beneficial effects on roots to counter the effects of drought.This model provides a theoretical basis for improvement of drought tolerance in wheat,via an increased understanding of drought priming induced drought tolerance.

An Essential Oil Blend Decreases Methane Emissions and Increases Milk Yield in Dairy Cows

This study was conducted to investigate the effect of a commercial essential oil (EO) additive on milk production and methane (CH4) emissions from dairy cows. Early lactation Holstein-Friesian dairy cows were fed grass, whole crop wheat and corn silage total mixed ration. Cows were allocated to one of two experimental treatments: Control (no additive, CON) or 1 g/head/day of EO. Cows were housed in a free stall barn, split into two pens for the duration of the experiment. Two gas data loggers units used to measure CH4 emissions were provided per pen for the duration of the 22 week-long study. Milk yield was determined daily, and milk components were analyzed every two weeks. CH4 was recorded continuously, and daily values were tabulated. Body weight and body condition score were determined at the start and bi-weekly. Results were analyzed as a randomized complete block trial. In total, 149 cows participated in the study (76 CON, 73 EO). Milk yields were greater (P < 0.05) for the test treatment (28.3 CON, 31.2 EO) with no change in milk component concentrations. Milk component concentrations were unaffected (P > 0.05) by treatment. Yields of fat, protein, lactose, and solids were higher for EO fed cows (P 4 output was reduced with the EO compared to the CON treatment (411 g/day vs 438 g/day;13.8 g/L of milk vs 17.2 g/L of milk, P < 0.05) over the duration of the trial. There were no effects of treatment on reproductive performance or the occurrence of mastitis. Feeding EO to dairy cows reduced CH4 emissions whilst also increasing performance.

Using MiddRAD-seq data to develop polymorphic microsatellite markers for an endangered yew species

Microsatellites are highly polymorphic markers which have been used in a wide range of genetic studies.In recent years, various sources of next-generation sequencing data have been used to develop new microsatellite loci, but compared with the more common shotgun genomic sequencing or transcriptome data, the potential utility of RAD-seq data for microsatellite ascertainment is comparatively under-used.In this study, we employed MiddRAD-seq data to develop polymorphic microsatellite loci for the endangered yew species Taxus florinii. Of 8,823,053 clean reads generated for ten individuals of a population, 94,851(~1%) contained microsatellite motifs. These corresponded to 2993 unique loci, of which 526(~18%) exhibited polymorphism. Of which, 237 were suitable for designing microsatellite primer pairs, and 128 loci were randomly selected for PCR validation and microsatellite screening. Out of the 128 primer pairs, 16 loci gave clear, reproducible patterns, and were then screened and characterized in 24 individuals from two populations. The total number of alleles per locus ranged from two to ten(mean=4.875), and within-population expected heterozygosity from zero to 0.789(mean = 0.530),indicating that these microsatellite loci will be useful for population genetics and speciation studies of T. florinii. This study represents one of few examples to mine polymorphic microsatellite loci from ddRAD data.

A Method for Assessing the Fairness of Health Resource Allocation Based on Geographical Grid

The assessment of the fairness of health resource allocation is an important part of the study for the fairness of social development.The data used in most of the existing assessment methods comes from statistical yearbooks or field survey sampling.These statistics are generally based on administrative areas and are difficult to support a fine-grained evaluation model.In response to these problems,the evaluation method proposed in this paper is based on the query statistics of the geographic grid of the target area,which are more accurate and efficient.Based on the query statistics of hot words in the geographic grids,this paper adopts the maximum likelihood estimation method to estimate the population in the grid region.Then,according to the statistical yearbook data of Hunan province,the estimated number and actual number of hospitals in each grid are analyzed and compared to measure the fairness of health resource allocation in the target region.Experiments show that the geographical grid population assessment based on hot words is more accurate and close to the actual value.The estimated average error is only about 17.8 percent.This method can assess the fairness of health resource allocation in any scale,and is innovative in data acquisition and evaluation methods.

Electrolytic production of Ti-Ge intermetallics from oxides in molten CaCl_2-NaCl

Titanium germanium intermetallics （TixGey）were directly prepared from titanium oxide （TiO2） and germanium oxide（GeO2） powders mixture by using an electrodeoxidation process. The electrochemical experiment was carried out in a molten fluxCaCl2-NaCl at 800℃ with a potential of 3.0 V. The results show that monolithic germanide Ti5Ge3 intermetallic can be directlyproduced from TiO2-GeO2 or CaTiO3-GeO2 precursors （both molar ratios are 5：3）, and the obtained Ti5Ge3 powders exhibithomogenous particle structure. In addition, the phase composition of the final product can be dramatically affected by the initialmolar ratio of TiO2 to GeO2. The reaction mechanism of the electrodeoxidation process was discussed based on the experimentalresults. It is suggested that the electrodeoxidation process is an environmentally friendly method for the preparation of Ti-Geintermetallics.

Ion pickup by intrinsic low-frequency Alfvén waves with a spectrum

Ion pickup by a monochromatic low-frequency Alfv6n wave, which propagates along the background magnetic field, has recently been investigated in a low beta plasma （Lu and Li 2007 Phys. Plasmas 14 042303）. In this paper, the monochromatic Alfven wave is generalized to a spectrum of Alfven waves with random phase. It finds that the process of ion pickup can be divided into two stages. First, ions are picked up in the transverse direction, and then phase difference （randomization） between ions due to their different parallel thermal motions leads to heating of the ions. The heating is dominant in the direction perpendicular to the background magnetic field. The temperatures of the ions at the asymptotic stage do not depend on individual waves in the spectrum, but are determined by the total amplitude of the waves. The effect of the initial ion bulk flow in the parallel direction on the heating is also considered in this paper.

A multi-channel chemical sensor and its application in detecting hydrothermal vents

There are well-established chemical and turbidity anomalies in the plumes occurring vicinity of hydrothermal vents, which are used to indicate their existence and locations. We here develop a small, accurate multi-channel chemical sensor to detect such anomalies which can be used in deep-sea at depths of more than 4 000 m. The design allowed five all-solid-state electrodes to be mounted on it and each (apart from one reference electrode) could be changed according to chemicals to be measured. Two experiments were conducted using the chemical sensors. The first was a shallow-sea trial which included sample measurements and in situ monitoring. pH, Eh, CO3^2- and SO4^2- electrodes were utilized to demonstrate that the chemical sensor was accurate and stable outside the laboratory. In the second experiment, the chemical sensor was integrated with pH, Eh, CO3^2- and H2S electrodes, and was used in 29 scans of the seabed along the Southwest Indian Ridge (SWIR) to detect hydrothermal vents, from which 27 sets of valid data were obtained. Hydrothermal vents were identified by analyzing the chemical anomalies, the primary judging criteria were decreasing voltages of Eh and H2S, matched by increasing voltages of pH and CO3^2- . We proposed that simultaneous detection of changes in these parameters will indicate a hydrothermal vent. Amongst the 27 valid sets of data, five potential hydrothermal vents were targeted using the proposed method. We suggest that our sensors could be widely employed by marine scientists.

Sensory quality of meat from eight different types of cattle in relation with their biochemical characteristics

The present study compared eight breeds of cattle differing in gender （heifers, buls and steers） to determine associations between muscle characteristics and meat sensory qualities of theLongissimus thoracis muscle. Animal types differed in al the muscle characteristics and sensory qualities. Many correlations among muscle characteristics and among sensory qualities were consistent for most animal types. Isocitrate dehydrogenase （ICDH） activities alowed discrimination of muscles with respect to myosin heavy chain （MyHC）-I proportions for al animal types. Lactate dehydrogenase （LDH） and phos-phofructokinase （PFK） activities were positively correlated for most animal types. Overal liking was correlated with beef lfavour and abnormal lfavour in al animal types and with global tenderness for al animal types except for Charolais cross breed steers. For al animal types except for Angus×Friesian heifers, beef lfavour and abnormal lfavour were negatively correlated. Overal liking was not correlated with juiciness. PFK, ICDH and citrate synthase （CS） activities were strongly associated with tenderness, beef lfavour and overal liking when average values for al animal types were used. However, associations between muscle characteristics and sensory qualities within animal types were weak and inconsistent.