Stag beetle Cyclommatus mniszechi employs both mutual- and self-assessment strategies in male-male combat.

Animals may base contest decisions on their fighting ability alone (self-assessment) or also their opponents' (mutual assessment). Many male stag beetles develop disproportionately enlarged mandibles and use them as weapons. Information on their assessment strategy is limited. To investigate their assessment strategy and whether they adopt the same strategy at different stages of contests, we used food to encourage male Cyclommatus mniszechi of different (random pairings) or similar (ML-matched pairings) mandible length (ML) to interact. For the random pairings, losers had shorter mandibles than winners and were faster to feed. Overall contest duration and the tendency to escalate to tussles associated positively with winners' ML and average ML in the random and the ML-matched pairings, respectively, consistent with self-assessment. Non-tussle phase duration associated positively with average ML in the ML-matched pairings, consistent with self-assessment. Tussle phase duration, however, positively associated with losers' ML in the random pairings and had no association with average ML in the ML-matched pairings, consistent with mutual assessment. These results show that (1) the males employ both assessment strategies, (2) winners have more control over contest intensity than losers, and (3) males with shorter mandibles are quicker to feed and also more likely to lose fights.

Research on Chinese Speech Emotion Recognition Based on Deep Neural Network and Acoustic Features.

In recent years, the use of Artificial Intelligence for emotion recognition has attracted much attention. The industrial applicability of emotion recognition is quite comprehensive and has good development potential. This research uses voice emotion recognition technology to apply it to Chinese speech emotion recognition. The main purpose of this research is to transform gradually popularized smart home voice assistants or AI system service robots from a touch-sensitive interface to a voice operation. This research proposed a specifically designed Deep Neural Network (DNN) model to develop a Chinese speech emotion recognition system. In this research, 29 acoustic characteristics in acoustic theory are used as the training attributes of the proposed model. This research also proposes a variety of audio adjustment methods to amplify datasets and enhance training accuracy, including waveform adjustment, pitch adjustment, and pre-emphasize. This study achieved an average emotion recognition accuracy of 88.9% in the CASIA Chinese sentiment corpus. The results show that the deep learning model and audio adjustment method proposed in this study can effectively identify the emotions of Chinese short sentences and can be applied to Chinese voice assistants or integrated with other dialogue applications.

Allometry and Fighting Behaviour of a Dimorphic Stag Beetle Cyclommatus mniszechi (Coleoptera: Lucanidae).

Male stag beetles (Coleoptera: Lucanidae) use their mandibles as weapons to compete for resources and reproduction. Mandible size in stag beetles can be associated with different behaviours and the outcome of male contests. We investigated the allometric relationship between mandible and body size in males of the stag beetle Cyclommatus mniszechi to uncover distinct morphs. The results divided male C. mniszechi into majors and minors with the switch point of mandible length at 14.01 mm. The allometric slope of mandibles was positive for both morphs but was steeper for the minors. We also characterised the fighting behaviour of the different morphs in size-matched contests using sequential analyses. Males matched each other's behaviour in contests with many physical contacts, no injury and a progression from low towards high aggression and rare de-escalation. Major and minor males employed the same behavioural elements in contests, but major males were more likely to escalate directly into more aggressive phases and minor males tended to stay within phases. This finding suggests that major males may compete more aggressively than minor males in contests.

Preoperative Antibiotic Prophylaxis Does Not Reduce the Risk of Postoperative Infectious Complications in Patients Undergoing Elective Hepatectomy.

BACKGROUND AND AIM: Postoperative infection is not uncommon after hepatectomy. This study assessed the effectiveness of preoperative antibiotic prophylaxis in elective hepatectomy in a randomized clinical trial setting. METHODS: A total of 120 patients who were scheduled to undergo elective hepatectomy were equally randomized to receive either intravenous cefuroxime 1.5 g (group A) or placebo (group B) within 30 min prior to skin incision. RESULTS: Overall, postoperative infection occurred in 26 (21.6 %) of the 120 patients. There was no statistically significant difference between groups A and B in the incidence of overall infection (23.3 vs. 20.0 %, P = 0.658), surgical site infection (13.3 vs. 15 %, P = 0.793), and remote site infection (13.3 vs. 11.7 %, P = 0.783). CONCLUSION: The use of preoperative antibiotic prophylaxis as a routine practice in patients undergoing elective hepatectomy is unnecessary because it does not reduce the risk of postoperative infectious complications.

[Two Data Inversion Algorithms of Aerosol Horizontal Distributiol Detected by MPL and Error Analysis].

Atmospheric aerosols have important impacts on human health, the environment and the climate system. Micro Pulse Lidar (MPL) is a new effective tool for detecting atmosphere aerosol horizontal distribution. And the extinction coefficient inversion and error analysis are important aspects of data processing. In order to detect the horizontal distribution of atmospheric aerosol near the ground, slope and Fernald algorithms were both used to invert horizontal MPL data and then the results were compared. The error analysis showed that the error of the slope algorithm and Fernald algorithm were mainly from theoretical model and some assumptions respectively. Though there still some problems exist in those two horizontal extinction coefficient inversions, they can present the spatial and temporal distribution of aerosol particles accurately, and the correlations with the forward-scattering visibility sensor are both high with the value of 95%. Furthermore relatively speaking, Fernald algorithm is more suitable for the inversion of horizontal extinction coefficient.

[Intra-pulse spectroscopy based on room-temperature pulsed quantum-cascade laser for N2O detection].

Mid-infrared lasers are very suitable for high-sensitive trace-gases detection in that their wavelengths cover the fundamental absorption lines of most gases. Quantum-cascade lasers have been demonstrated to be ideal light sources with their especially high power, wide range of tuning capability and favorable operating condition on room-temperature. The intra-pulse spectroscopy based on a room-temperature distributed-feedback pulsed QC laser is a simple and effective trace gas detective method to detect trace-gas qualitatively or quantificationally. When a long excitation pulse is applied to a QC laser, the laser frequency tunes almost linearly to lower wave number (lower frequency) as a function of time so all absorption spectral elements are recorded during a single laser pulse. In the present paper, the method was introduced, and identification of N2O spectral fingerprint using this spectroscopy was demonstrated experimentally. The thermal chirp from a 500 ns long excitation pulse was applied to a quantum-cascade laser to get a fast wavelength scanning, thus a wave number tuning of about 1 cm(-1) was produced. The N2O absorption spectrum centered at 1 273.7 cm(-1) was also obtained. The measured absorption spectrum is consistent with HITRAN data precisely.

Effects of network structure and routing strategy on network capacity.

The capacity of maximum end-to-end traffic flow the network is able to handle without overloading is an important index for network performance in real communication systems. In this paper, we estimate the variations of network capacity under different routing strategies for three different topologies. Simulation results reveal that the capacity depends on the underlying network structure and the capacity increases as the network becomes more homogeneous. It is also observed that the network capacity is greatly enhanced when the new traffic awareness routing strategy is adopted in each network structure.