The effects of shoe temperature on the kinetics and kinematics of running

The aim of the current investigation was to examine the effects of cooled footwear on the kinetics and kinematics of running in comparison to footwear at normal temperature. Twelve participants ran at 4.0 m/s ± 5% in both cooled and normal temperature footwear conditions over a force platform. Two identical footwear were worn, one of which was cooled for 30 min. Lower extremity kinematics were obtained using a motion capture system and tibial accelerations were measured using a triaxial accelerometer. Differences between cooled and normal footwear temperatures were contrasted using paired samples t-tests. The results showed that midsole temperature (cooled = 4.21 °C and normal = 23.25 °C) and maximal midsole deformation during stance (cooled = 12.85 mm and normal = 14.52 mm) were significantly reduced in the cooled footwear. In addition, instantaneous loading rate (cooled = 186.21 B.W/s and normal = 167.08 B W/s), peak tibial acceleration (cooled = 12.75 g and normal = 10.70 g) and tibial acceleration slope (cooled = 478.69 g/s and normal = 327.48 g/s) were significantly greater in the cooled footwear. Finally, peak eversion (cooled = −10.57 ° and normal = −7.83°) and tibial internal rotation (cooled = 10.67 ° and normal = 7.77°) were also shown to be significantly larger in the cooled footwear condition. This study indicates that running in cooled footwear may place runners at increased risk from the biomechanical parameters linked to the aetiology of injuries

The influence of barefoot and barefoot inspired footwear on the kinetics and kinematics of running in comparison to conventional running shoes.

Barefoot running has experienced a resurgence in footwear biomechanics literature, based on the supposition that it serves to reduce the occurrence of overuse injuries in comparison to conventional shoe models. This consensus has lead footwear manufacturers to develop shoes which aim to mimic the mechanics of barefoot locomotion. This study compared the impact kinetics and 3-D joint angular kinematics observed whilst running: barefoot, in conventional cushioned running shoes and in shoes designed to integrate the perceived benefits of barefoot locomotion. The aim of the current investigation was therefore to determine whether differences in impact kinetics exist between the footwear conditions and whether shoes which aim to simulate barefoot movement patterns can closely mimic the 3-D kinematics of barefoot running. Twelve participants ran at 4.0 m.s-1±5% in each footwear condition. Angular joint kinematics from the hip, knee and ankle in the sagittal, coronal and transverse planes were measured using an eight camera motion analysis system. In addition simultaneous tibial acceleration and ground reaction forces were obtained. Impact parameters and joint kinematics were subsequently compared using repeated measures ANOVAs. The kinematic analysis indicates that in comparison to the conventional and barefoot inspired shoes that running barefoot was associated significantly greater plantar-flexion at footstrike and range of motion to peak dorsiflexion. Furthermore, the kinetic analysis revealed that compared to the conventional footwear impact parameters were significantly greater in the barefoot condition. Therefore this study suggests that barefoot running is associated with impact kinetics linked to an increased risk of overuse injury, when compared to conventional shod running. Furthermore, the mechanics of the shoes which aim to simulate barefoot movement patterns do not appear to closely mimic the kinematics of barefoot locomotion

Similarity Between Actual and Possible Selves and Its Relationship to Self-esteem

Prior research has shown that people who hold negative beliefs about a group of people (e.g., that they’re untrustworthy) will tend to hold more negative mental images of members of that group (Dotsch et al., 2008; 2013). Additional research has extended this idea further, suggesting that beliefs about the self (self-esteem) relate to how attractive a person imagines their own face (a self-face representation; Epley & Whitchurch, 2008; Shorten et al., 2017). Within the current study, we sought to expand this research further by demonstrating a positive relationship between participants’ scores in self-esteem and the positivity of their self-face representations. Additionally, we attempted to replicate previous findings describing a positive relationship between participants’ self-esteem scores and their self-face representation’s attractiveness. However, observed relationships proved low in magnitude, providing little to no support for our hypotheses. Given the lack of support, we identify several alterations to the original method that may aid further research

27th International Congress of Applied Psychology (ICAP 2010)

The general aim of this study was to describe some of the discursive practices for managing qualitative research interviews. The specific aim was to examine the form, function, and location of response tokens in a qualitative research interview. A conversation analysis (cf., Sacks, 1992) of 266 lines of transcribed talk from New Zealand Interview 2 (van den Berg, Wetherell, & Houtkoop-Steenstra, 2003) on race relations in New Zealand during the 1980s was completed. First, response tokens were identified in the transcript using Gardner’s taxonomy (Gardner, 2001). Second, the frequency was calculated for different classes of response tokens. Third, how the interviewer and the interviewee used response tokens to maintain or change speakership, maintain or change topic, and formulate answers were examined. Response tokens are a pervasive feature in qualitative research interviews accounting for 11.47% of all words spoken. The interviewer produced 60.7% and the respondent produced 39.3% of these. Continuers (e.g., Mm mhm), news-markers (e.g., Right), and acknowledgement tokens signalling hesitancy (e.g., Uhm), delicateness (e.g. Mm) and certainty (e.g., Yes) were oriented to points of grammatical completion in the talk and located at transition relevant places. Their function was therefore consistent with Gardner’s taxonomy. Response tokens were oriented to speakership enabling a speaker to hold the floor but allowing a recipient to signal continuing listenership or project an upcoming speaker’s bid. Response tokens shape the trajectory of a qualitative research interview by being oriented to the immediately prior turn. Response tokens manage multi-turn answers by marking mutual understanding as an ongoing accomplishment and by dealing with insertion sequences that divert talk away from the research question. Thus, they shape the overall structure of a qualitative research interview by helping to organise and design turns and speakership. These findings display how interviews are socially constructed and culturally informed events

Contrast and rate of light intensity decrease control directional swimming in the box jellyfish Tripedalia cystophora (Cnidaria, Cubomedusae)

Box jellyfish respond to visual stimuli by changing the dynamics and frequency of bell contractions. In this study, we determined how the contrast and the dimming time of a simple visual stimulus affected bell contraction dynamics in the box jellyfish Tripedalia cystophora. Animals were tethered in an experimental chamber where the vertical walls formed the light stimuli. Two neighbouring walls were darkened and the contraction of the bell was monitored by high-speed video. We found that (1) bell contraction frequency increased with increasing contrast and decreasing dimming time. Furthermore, (2) when increasing the contrast and decreasing the dimming time pulses with an off-centred opening had a better defined direction and (3) the number of centred pulses decreased. Only weak effects were found on the relative diameter of the contracted bell and no correlation was found for the duration of bell contraction. Our observations show that visual stimuli modulate swim speed in T. cystophora by changing the swim pulse frequency. Furthermore, the direction of swimming is better defined when the animal perceives a high-contrast, or fast dimming, stimulus

Secure access control for DAG-based distributed ledgers

Access control is a fundamental component of the design of distributed ledgers, influencing many aspects of their functionality, such as fairness, efficiency, traditional notions of network security, and adversarial attacks such as Denial-of-Service (DoS) attacksAttackers attempt to put stress on the network by sending a large amount of transactions to other nodes.. In this work, we consider the security of a recently proposed access control protocol for Directed Acyclic Graph-based distributed ledgers. We present a number of attack scenarios and potential vulnerabilities of the protocol and introduce a number of additional features which enhance its resilience. Specifically, a blacklisting algorithm, which is based on a reputation-weighted threshold, is introduced to handle both spamming and multi-rate malicious attackers. A solidification request component is also introduced to ensure the fairness and consistency of the network in the presence of attacks. Finally, a timestamp component is also introduced to maintain the consistency of the network in the presence of multi-rate attackers. Simulations to illustrate the efficacy and robustness of the revised protocol are also presented

DeepCapture: Image Spam Detection Using Deep Learning and Data Augmentation

Image spam emails are often used to evade text-based spam filters that detect spam emails with their frequently used keywords. In this paper, we propose a new image spam email detection tool called DeepCapture using a convolutional neural network (CNN) model. There have been many efforts to detect image spam emails, but there is a significant performance degrade against entirely new and unseen image spam emails due to overfitting during the training phase. To address this challenging issue, we mainly focus on developing a more robust model to address the overfitting problem. Our key idea is to build a CNN-XGBoost framework consisting of eight layers only with a large number of training samples using data augmentation techniques tailored towards the image spam detection task. To show the feasibility of DeepCapture, we evaluate its performance with publicly available datasets consisting of 6,000 spam and 2,313 non-spam image samples. The experimental results show that DeepCapture is capable of achieving an F1-score of 88%, which has a 6% improvement over the best existing spam detection model CNN-SVM with an F1-score of 82%. Moreover, DeepCapture outperformed existing image spam detection solutions against new and unseen image datasets.Comment: 15 pages, single column. ACISP 2020: Australasian Conference on Information Security and Privac