Corporate Social Responsibility Initiatives of Major Asian Airlines

Corporate social responsibility (CSR) plays an important role in the formation of airlines’ strategies due to the unique characteristics of the airline industry. Nevertheless, CSR in the airline industry has received relatively little attention from academics. The purpose of this study is to present a preliminary exploration of the CSR issues being addressed and reported by twelve major Asian airlines. This research is exploratory by nature and is based on he CSR reports published by the selected airlines and related CSR information on the company websites. The main focuses of major Asian airlines’ CSR commitments and practices are identified, which will set the foundation for future enquiry and research

Lattice-Boltzmann and finite-difference simulations for the permeability for three-dimensional porous media

Numerical micropermeametry is performed on three dimensional porous samples having a linear size of approximately 3 mm and a resolution of 7.5 $\mu$m. One of the samples is a microtomographic image of Fontainebleau sandstone. Two of the samples are stochastic reconstructions with the same porosity, specific surface area, and two-point correlation function as the Fontainebleau sample. The fourth sample is a physical model which mimics the processes of sedimentation, compaction and diagenesis of Fontainebleau sandstone. The permeabilities of these samples are determined by numerically solving at low Reynolds numbers the appropriate Stokes equations in the pore spaces of the samples. The physical diagenesis model appears to reproduce the permeability of the real sandstone sample quite accurately, while the permeabilities of the stochastic reconstructions deviate from the latter by at least an order of magnitude. This finding confirms earlier qualitative predictions based on local porosity theory. Two numerical algorithms were used in these simulations. One is based on the lattice-Boltzmann method, and the other on conventional finite-difference techniques. The accuracy of these two methods is discussed and compared, also with experiment.Comment: to appear in: Phys.Rev.E (2002), 32 pages, Latex, 1 Figur

Near-Optimal Defense Strategies against DDoS Attacks Based upon Packet Filtering and Blocking Enabled by Packet Marking

In the paper, the DDoS scenario is modelled as a mathematical programming problem. The defender strategically utilizes the limited resources to maximize the legitimate traffic, and he can adopt packet marking to observe the network status. The information extracts from the marking field can help the defender develop a defense strategy which combines packet filtering and packet blocking. A Lagrangean relaxation-based algorithm is proposed to optimally solve the problem

Fibrillation of chain branched poly (lactic acid) with improved blood compatibility and bionic structure

YesHighly-oriented poly (lactic acid) (PLA) with bionic fibrillar structure and micro-grooves was fabricated through solid hot drawing technology for further improving the mechanical properties and blood biocompatibility of PLA as blood-contacting medical devices. In order to enhance the melt strength and thus obtain high orientation degree, PLA was first chain branched with pentaerythritol polyglycidyl ether (PGE). The branching degree as high as 12.69 mol% can be obtained at 0.5 wt% PGE content. The complex viscosity, elastic and viscous modulus for chain branched PLA were improved resulting from the enhancement of molecular entanglement, and consequently higher draw ratio can be achieved during the subsequent hot stretching. The stress-induced crystallization of PLA occurred during stretching, and the crystal structure of the oriented PLA can be attributed to the α′ crystalline form. The tensile strength and modulus of PLA were improved dramatically by drawing. Chain branching and orientation could significantly enhance the blood compatibility of PLA by prolonging clotting time and decreasing hemolysis ratio, protein adsorption and platelet activation. Fibrous structure as well as micro-grooves can be observed for the oriented PLA which were similar to intimal layer of blood vessel, and this bionic structure was considered to be beneficial to decrease the activation and/or adhesion of platelets

Differentiated QoS Provisioning in Wireless Networks Based on Deep Reinforcement Learning

Wireless networks manage performance by adjusting the contention window, as they cannot directly detect collisions. Traditional contention window adjustment algorithms, such as the Binary Exponential Backoff (BEB) algorithm, may lead to lower throughput when multiple services with varying bandwidth demands coexist. To address this issue, this study aims to enhance network throughput by enabling differentiated bandwidth allocation for various services. Using deep reinforcement learning, the state space, action space, and reward functions are defined to optimize this differentiation. These definitions are integrated into the Deep Deterministic Policy Gradient (DDPG) technique, implemented in the Access Point (AP) to intelligently adjust the contention window. Leveraging DDPG’s capability for continuous actions, the proposed method provides Quality of Service (QoS) differentiation, ensuring that each service at its respective priority level meets its transmission requirements. Compared to the BEB algorithm, the proposed approach offers improved traffic allocation and higher network bandwidth utilization

Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors

A brain-computer interface (BCI) is a communication system that can help users interact with the outside environment by translating brain signals into machine commands. The use of electroencephalographic (EEG) signals has become the most common approach for a BCI because of their usability and strong reliability. Many EEG-based BCI devices have been developed with traditional wet- or micro-electro-mechanical-system (MEMS)-type EEG sensors. However, those traditional sensors have uncomfortable disadvantage and require conductive gel and skin preparation on the part of the user. Therefore, acquiring the EEG signals in a comfortable and convenient manner is an important factor that should be incorporated into a novel BCI device. In the present study, a wearable, wireless and portable EEG-based BCI device with dry foam-based EEG sensors was developed and was demonstrated using a gaming control application. The dry EEG sensors operated without conductive gel; however, they were able to provide good conductivity and were able to acquire EEG signals effectively by adapting to irregular skin surfaces and by maintaining proper skin-sensor impedance on the forehead site. We have also demonstrated a real-time cognitive stage detection application of gaming control using the proposed portable device. The results of the present study indicate that using this portable EEG-based BCI device to conveniently and effectively control the outside world provides an approach for researching rehabilitation engineering

Increased spinal prodynorphin gene expression in reinflammation-associated hyperalgesia after neonatal inflammatory insult

<p>Abstract</p> <p>Background</p> <p>Neuroplasticity induced by neonatal inflammation is the consequence of a combination of activity-dependent changes in neurons. We investigated neuronal sensitivity to a noxious stimulus in a rat model of neonatal hind-paw peripheral inflammation and assessed changes in pain behaviour at the physiological and molecular levels after peripheral reinflammation in adulthood.</p> <p>Results</p> <p>A decrease in paw withdrawal latency (PWL) after a heat stimulus was documented in rats that received inflammatory injections in their left hind paws on postnatal day one (P1) and a reinflammation stimulus at postnatal 6-8 weeks of age, compared with normal rats. An increase in the expression of the prodynorphin (<it>proDYN</it>) gene was noted after reinflammation in the spinal cord ipsilateral to the afferents of the neonatally treated hind paw. The involvement of the activation of extracellular signal-regulated kinases (ERK) in peripheral inflammatory pain hypersensitivity was evidenced evident by the increase in phospho-ERK (pERK) activity after reinflammation.</p> <p>Conclusions</p> <p>Our results indicate that peripheral inflammation in neonates can permanently alter the pain processing pathway during the subsequent sensory stimulation of the region. Elucidation of the mechanism underlying the developing pain circuitry will provide new insights into the understanding of the early pain behaviours and the subsequent adaptation to pain.</p

Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis

<p>Abstract</p> <p>Background</p> <p>The computer-aided identification of specific gait patterns is an important issue in the assessment of Parkinson's disease (PD). In this study, a computer vision-based gait analysis approach is developed to assist the clinical assessments of PD with kernel-based principal component analysis (KPCA).</p> <p>Method</p> <p>Twelve PD patients and twelve healthy adults with no neurological history or motor disorders within the past six months were recruited and separated according to their "Non-PD", "Drug-On", and "Drug-Off" states. The participants were asked to wear light-colored clothing and perform three walking trials through a corridor decorated with a navy curtain at their natural pace. The participants' gait performance during the steady-state walking period was captured by a digital camera for gait analysis. The collected walking image frames were then transformed into binary silhouettes for noise reduction and compression. Using the developed KPCA-based method, the features within the binary silhouettes can be extracted to quantitatively determine the gait cycle time, stride length, walking velocity, and cadence.</p> <p>Results and Discussion</p> <p>The KPCA-based method uses a feature-extraction approach, which was verified to be more effective than traditional image area and principal component analysis (PCA) approaches in classifying "Non-PD" controls and "Drug-Off/On" PD patients. Encouragingly, this method has a high accuracy rate, 80.51%, for recognizing different gaits. Quantitative gait parameters are obtained, and the power spectrums of the patients' gaits are analyzed. We show that that the slow and irregular actions of PD patients during walking tend to transfer some of the power from the main lobe frequency to a lower frequency band. Our results indicate the feasibility of using gait performance to evaluate the motor function of patients with PD.</p> <p>Conclusion</p> <p>This KPCA-based method requires only a digital camera and a decorated corridor setup. The ease of use and installation of the current method provides clinicians and researchers a low cost solution to monitor the progression of and the treatment to PD. In summary, the proposed method provides an alternative to perform gait analysis for patients with PD.</p