Miracle-dz/UniFAR-FTUs huggingface dataset:
Exciton acoustic-phonon coupling in single GaN/AlN quantum dots

Coupling of acoustic phonons to excitons in single wurtzite-type GaN/AlN quantum dots is investigated in detail by cathodoluminescence experiments and compared to theory. Numerical simulations of the coupling in the framework of the independent Boson model with realistic wave functions based on 8-band k · p theory show good agreement with observed emission line shapes. We analyze the influence of the geometry and the built-in dipole moment of the quantum dots on the spectral distribution of phonon-coupling strength and the different coupling mechanisms. We observe considerable contribution of the transversal phonons via piezoelectric coupling. The omnipresent broadening of the zero-phonon line is discussed in terms of spectral diffusion.
MPF: Prolonging Network Lifetime of Wireless Rechargeable Sensor Networks by Mixing Partial Charge and Full Charge

Recently, wireless power transfer is emerging as an enabling technology of wireless rechargeable sensor networks. Conventional methods that charge each sensor until its battery is full take unproportionally long time to finish, due to the limitation of charging efficiency and power transfer technologies. In this paper, we propose a mixed partial and full charge (MPF) scheme, including three specialized modules, i.e., evaluation module, adjustment module, and selection module. MPF allows nodes to be replenished "partially" by a mobile charging vehicle (MCV). When executing adjustment module, a concept of power and path adjustment window is proposed for determining a proper power allocation scheme as well as charging path. Then a scheduling strategy termed return mechanism is designed to further utilize the energy of the MCV and improve effective energy utilization. Finally, we build a high-accuracy charging test-bed and evaluate the applicability as well as performance of the proposed scheme. For large-scale networks, we also perform simulations to demonstrate the effectiveness of MPF in promoting survival rate and reducing traveling distance of the MCV.
Molecular cloning and expression analysis of heat shock protein 20 ( HSP 20 ) from the pearl

Small heat shock proteins (HSPs) are molecular chaperones with ATP-independent properties. They are involved in a variety of physiological and stress processes. In this study, the full-length HSP 20 (HSP20) from Pinctada martensii, designated as PmHSP20, was obtained from hemocytes using rapid amplification of cDNA ends technology. The PmHSP20 cDNA was 952 bp in length, containing an open reading frame of 534 bp that encoded 177-amino acid residues, with an isoelectric point of 5.86 and molecular weight of 20.24 kDa. The sequence of this deduced polypeptide contained typical structure and function domains conserved in the HSP20 family, providing evidence that PmHSP20 belongs to the HSP20 family. The PmHSP20 mRNA expression levels were detected in various tissues of P. martensii and in hemocytes after challenges with the bacteria Vibrio harveyi and lipopolysaccharide (LPS) using quantitative realtime polymerase chain reaction amplification. The results indicated that PmHSP20 is constitutively expressed in all tissues tested and might be involved in the immune response. The upregulation of PmHSP20 after V. harveyi and LPS challenge suggests that PmHSP20 plays an important role in anti-bacterial immunity. Studies on PmHSP20 are a
Ballistic and Diffusive Thermal Conductivity of Graphene

Phonon-related thermal conductivity of graphene is calculated as a function of the temperature and sample size of graphene in which the crossover of ballistic and diffusive thermal conductivity occurs at around 100 K. The diffusive thermal conductivity of graphene is evaluated by calculating the phonon mean free path for each phonon mode in which the anharmonicity of a phonon and the phonon scattering by a C isotope are taken into account. We show that phonon-phonon scattering of out-of-plane acoustic phonon by the anharmonic potential is essential for the largest thermal conductivity. Using the calculated results, we can design the optimum sample size, which gives the largest thermal conductivity at a given temperature for applying thermal conducting devices.
TRAUMA ASSESSMENT AND TREATMENT Development of the Trauma Appraisal Questionnaire

This study describes the development and psychometric properties of the Trauma Appraisal Questionnaire (TAQ). Items were generated based on interviews with 72 ethnically diverse community participants exposed to a range of trauma types. From the interviews, more than 600 items that tapped beliefs, emotions, and behaviors were generated for 9 appraisal categories (e.g., fear, betrayal, shame). Based on expert feedback, 108 items were retained for initial testing in a sample of 714 undergraduate volunteers. Using a factor analytic strategy, we arrived at a 6-scale, 54-item solution. The reliability and validity of the new measure were evaluated in community (N = 119) and undergraduate (Ns = 139 and 79) samples. The measure demonstrated excellent reliability (test–retest and internal consistency) and validity (convergent, discriminant, and concurrent).
Protective Effect of Grape Seed Oil on Hypercholesterolemia in Rats

This study was carried out to investigate that the effect of grape seed oil (GSO) on Hypercholesterolemia in rats. Thirty-five rats were divided into 5 groups, group 1 was given the basal diet as a negative control group (-ve), group 2 was given the basal diet with GSO instead of soybean oil as a negative control for GSO. Groups (3, 4 and 5) were fed on high cholesterol diet (HCD) (1% cholesterol powder and 0.5% bile salt for 8 weeks), Group 3 was +ve control, group 4 and 5 were treatment groups which received GSO 2% and 4% daily with HCD. The results of this study indicated that the GSO caused an improvement in the blood lipids especially 4% GSO. The 4% GSO decreased serum TC, TG, LDL-c and VLDL significantly (P ˂ 0.05), and caused a significant increase in HDL-C level. Also, 2% GSO decreased TG, LDL-C and VLDL significantly (P ˂ 0.05), whereas the level of HDL-C showed significant increases. Subsequently, GSO enhanced the lipid ratios: atherogenic coefficient (AC), cardiac risk ratio (CRR), LDL-c to HDL-c ratio and atherogenic index of plasma (AIP). Moreover, the serum, liver function (AST, ALT and ALP) levels also, enhanced in the GSO groups. However, 4% GSO led to significant decrease in serum MDA and elevated serum GST. Otherwise, histopathological examination showed enhanced in the heart and aorta of rats compared with the +ve control group. This study indicates that GSO effective in lowering total cholesterol, triglyceride and LDL-c and increasing HDL-c. Therefore, GSO have hypocholesterolemic effect and might be effective to protect against the risk of CVD.
Update on Plant Physiology and Climate Change Examining Plant Physiological Responses to Climate Change through an Evolutionary Lens 1 [ OPEN ]

Since the Industrial Revolution began approximately 200 years ago, global atmospheric carbon dioxide concentration ([CO2]) has increased from 270 to 401 mL L , and average global temperatures have risen by 0.85°C, with the most pronounced effects occurring near the poles (IPCC, 2013). In addition, the last 30 years were the warmest decades in 1,400 years (PAGES 2k Consortium, 2013). By the end of this century, [CO2] is expected to reach at least 700 mL L, and global temperatures are projected to rise by 4°C or more based on greenhouse gas scenarios (IPCC, 2013). Precipitation regimes also are expected to shift on a regional scale as the hydrologic cycle intensifies, resulting in greater extremes in dry versus wet conditions (Medvigy and Beaulieu, 2012). Such changes already are having profound impacts on the physiological functioning of plants that scale up to influence interactions between plants and other organisms and ecosystems as a whole (Fig. 1). Shifts in climate also may alter selective pressures on plants and, therefore, have the potential to influence evolutionary processes. In some cases, evolutionary responses can occur as rapidly as only a few generations (Ward et al., 2000; Franks et al., 2007; Lau and Lennon, 2012), but there is still much to learn in this area, as pointed out by Franks et al. (2014). Such responses have the potential to alter ecological processes, including species interactions, via ecoevolutionary feedbacks (Shefferson and Salguero-Gómez, 2015). In this review, we discuss microevolutionary and macroevolutionary processes that can shape plant responses to climate change as well as direct physiological responses to climate change during the recent geologic past as recorded in the fossil record. We also present work that documents how plant physiological and evolutionary responses influence interactions with other organisms as an example of how climate change effects on plants can scale to influence higher order processes within ecosystems. Thus, this review combines findings in plant physiological ecology and evolutionary biology for a comprehensive view of plant responses to climate change, both past and present. Due to rapid climate change, plants have become increasingly exposed to novel environmental conditions that are outside of their physiological limits and beyond the range to which they are adapted (Ward and Kelly, 2004; Shaw and Etterson, 2012). Plant migration may not keep pace with the unprecedented rate of current climate change (Loarie et al., 2009); therefore, rapid evolutionary responses may be the major process by which plants persist in the future (Franks et al., 2007; Alberto et al., 2013). In addition, although plants may have evolved physiological plasticity that produces a fitness advantage in novel environments, climate change may be so extreme as to push plants beyond
Emerging clinical applications of photoacoustic imaging.

Photoacoustic (PA) or optoacoustic imaging is a relatively new imaging modality based on the detection of light-excited ultrasound waves, has emerged as one of the most exciting research areas in biomedical imaging over the past decade [1-4]. In PA imaging, nanosecond pulsed (or modulated) electromagnetic radiation is delivered into tissues to excite ultrasound waves via photon absorption and thermos-elastic expansion. Subsequently ultrasound detection and image reconstruction are performed to generate an image of tissue optical absorption. This hybrid imaging technique thus combines advantages from both optical and ultrasound imaging, by encoding discriminative optical absorption contrast into ultrasound waves. Furthermore, PA imaging is capable of scaling its spatial resolution and imaging depth, enabling imaging of subjects ranging from organelles, cells, tissues, to organs, and with spatial resolution ranging from submicrometres to sub-millimetres. As such, PA imaging holds tremendous potential for a wide range of clinical applications.
An Evaluation of Different Input Techniques for a Tabletop Display Using Fitts ’ Reciprocal Tapping Task

User performance with a tabletop display was tested using touch-based and mouse-based interaction in a traditional pointing task. Dependent variables were throughput, accuracy, and movement time. In a study with 12 participants, touch had a better performance with average throughput of 5.53 bps in comparison to 3.83 bps for mouse. Touch also had a lower movement time on average, ranging from 403 ms to 1051 ms vs. mouse input that ranged from 607 ms to 1323 ms. Error rates were lower for the mouse at 2.1%, compared to 9.8% for touch. The high error rates using touch were substantially due to problems in selecting small targets with the finger. It is argued that overall, touch input is a preferred and efficient input technique for tabletop displays.
Learning to Grasp Objects with Reinforcement Learning

In this project we will use reinforcement learning, the CACLA algorithm, to let an agent learn to control a robotic arm. Inspired by domestic service robots that have to perform multiple complex tasks, manipulation is only a small part of it. Using neural networks an agent should be able to learn to complete a manipulation task without having to calculate paths and grasping points. We will be using a 6 degree of freedom robotica arm, Mico, and make use of a simulator called V-REP to perform the experiments. We compare the results to a traditional simple inverse kinematic solver to see if there is a gain in speed, accuracy or robustness. Whilst most agents use one neural network to perform their task, we will experiment with different architectures, namely the amount of neural networks that each control a sub-set of the joints, to see if this can improve results. Whilst for reinforcement learning exploration is very important we test two different exploration methods; Gaussian exploration and Ornstein-Uhlenbeck process exploration, to see if there is any influence in the training. We experimented first with letting the end effector of the arm move to a certain position without grasping an object. It was shown that when using only 1 joint learning is very easy, but when controlling more joints the problem of simply going to a single location becomes more difficult to solve. While adding more training iterations can improve results, it also takes a lot longer to train the neural networks. By showing a pre training stage consisting of calculating the forward kinematics without relying on any physics simulation to create the input state of the agent, we can create more examples to learn from and improve results and decrease the learning time. However when trying to grasp objects the extra pre training stage does not help at all. By increasing the training iterations we can achieve some good results and the agent is able to learn to grasp an object. However when using multiple networks to control a sub-set of joints we can improve on the results, even reaching a 100\% success rate for both exploration methods, not only showing that multiple networks can outperform a single network, also that exploration does not influence training all that much. The downside is that training takes a very long time. Whilst it does not outperform the inverse kinematic solver we do have to take into account that the setup was relatively easy, therefore making it very easy for the inverse kinematic solver.
INTERTIDAL MUSSEL MICROCLIMATES: PREDICTING THE BODY TEMPERATURE OF A SESSILE INVERTEBRATE

To elucidate the determinants of intertidal invertebrate body temperatures during aerial exposure, I developed deterministic models using the environmental inputs of solar radiation, air temperature, ground temperature, and wind speed to predict the body temperatures of intertidal mussels (Mytilus spp.). Combined with field studies, these models were used to determine the effects of body size on body temperature, and to compare the heat budgets of mussels living as solitary individuals vs. those living in aggregations (beds). On average, the model accurately predicted the body temperatures of solitary mussels in the field to within ∼1°C. Steady-state simulations (using constant environmental conditions) predicted that, under conditions where evaporative water loss is limited, smaller (5 cm) mussels experience lower body temperatures than larger (10 cm) mussels exposed to identical environmental parameters. When evaporative cooling is limited only by intolerance to desiccation, the trend in body size rever.
Effects of the Bloch-Siegert Oscillation on the Precision of Qubit Rotations: Direct Two-Level vs. Off-Resonant Raman Excitation

In a direct two-level qubit system, when the Rabi frequency is comparable to the resonance frequency, the rotating wave approximation is not appropriate. In this case, the Rabi oscillation is accompanied by another oscillation at twice the frequency of the driving field, the so called Bloch-Siegert oscillation (BSO), which depends on the initial phase of the driving field. This oscillation may restrict the precise rotation of a qubit made of direct two-level system. Here, we show that in case of an effectively two-level lambda system, the BSO is inherently negligible, implying a greater precision for rotation of a qubit made of such a lambda system when compared to a direct two-level qubit in a strong driving field.
Comparing U . S . and Euro Area Wage and Price Inflation Dynamics

In this paper we formulate a baseline disequilibrium AS-AD model based on sticky wages and prices, perfect foresight of current inflation rates and adaptive expectations concerning the inflation climate in which the economy operates. The model consists of a wage and a price Phillips curves, a dynamic IS curve as well as a dynamic employment adjustment equation and a Taylorrule-type interest rate law of motion. We estimate this theoretical model it with aggregate time series data for the U.S. and the Eurozone economies. The resulting structural parameter estimates support the specification of our theoretical model and show the important influence of the Blanchard-Katz error correction terms and the inflationary climate in the determination of wages and prices in the U.S. and the Eurozone economies. ———————
Discover Relevant Sources : A Multi-Armed Bandit Approach

Existing work on online learning for decision making takes the information available as a given and focuses solely on choosing the best actions given this information. Instead, in this paper, the decision maker needs to simultaneously learn both what decisions to make and what source(s) of information to consult/gather data from in order to inform its decisions such that its reward is maximized. We formalize this dual-learning and online decision making problem as a multi-armed bandit problem. If it were known in advance which sources were relevant for which decisions, the problem would be simple but they are not. We propose algorithms that discover the relevant source(s) over time, while simultaneously learning what actions to take based on the information revealed by the selected source(s). Our algorithm resembles that of the well-known UCB algorithm but adds to it the online discovery of what specific sources are relevant to consult to inform specific decisions. We prove logarithmic regret bounds and also provide a matching lower bound on the number of times a wrong source is selected, which is achieved by RSUCB for specific cases. The proposed algorithm can be applied in many applications including clinical decision assist systems for medical diagnosis, recommender systems, actionable intelligence, etc. where observing the complete information of a patient or a consumer or consulting all the available sources to gather intelligence is not feasible.
Security and Privacy Enhancing in Multi-Cloud Architecture with Data DeDuplication

Cloud computing makes IT more efficient and cost effective in today’s world. Cloud computing act as a virtual server that the user can access via internet on a needed basis and this eliminates the need for the companies to host their own servers and purchase of expensive software. On the other hand there arise many new types of cyber theft. The main concerns in cloud computing are data integrity, security and enhancement of storage space in the cloud. This paper focuses on maintaining data integrity and security from a user’s perspective and also provides clear understanding of achievable security merits by using multiple distinct clouds simultaneously and enhancing storage space of public cloud by DE duplication from a cloud service provider’s perspective. Symmetric key encryption is used to prevent unauthorized user from accessing data. Convergent encryption is used to maintain data confidentiality. KeywordData DE duplication, Data Confidentiality, Security, Data Integrity, Multi-Cloud __________________________________________________________________________________________________
A combined and intensive exercise model improves physical capacity in cardiac patients

Objective: We have measured the effect of combined strength and high intensity endurance training on physical capacity and lipid profile in patients with heart and coronary diseases. We wanted to see whether cardiac patients were able to increase training intensity to improve strength without losing endurance capacity. Methods: Thirty heart-operated subjects participated in an intervention period of 10 weeks. The age of the participants was between 52-72 years. The Resistance-Interval group (RE-INT) practiced four times a week with two intensive endurance (spinning) sessions and two strength training sessions. The endurance training consisted of intervals where the heart rate reached>90% of maximum heart rate. Strength training was performed in three series with a load of 8-12 repetition maximum (RM). The subjects in the control group (CON) performed two to three sessions per week according to a national program specialized for coronary patients (called “Ullevaal model”). We had a randomized controlled trial. Results: Maximal leg strength increased in both groups during the intervention, but the increase was higher in the RE-INT group (from 107.9 ± 8.1 kg to 162.0 ± 8.4 kg) compared to the CON group (from 110.8 ± 8.9 to 125.4 ± 9.5 ) (p<0.001). Strength in chest press, the maximal oxygen uptake and the concentration of high densitylipoprotein (HDL) protein increased in both groups during the test period. However, no differences were observed between the RE-INT and CON group. Low density-lipoprotein (LDL), blood pressure and body weight did not change during the intervention period in any of the groups. Conclusion: cardiac patients were able to increase training intensity, strength and maximal oxygen uptake during a period of 10 weeks. We found that combined training has an effective impact on the increase in leg strength. The increase in muscle strength can be vital for the everyday quality of life in cardiac patients.
- Based On-Chip 3 D Cell Rotation

Please note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. Accepted Manuscript Lab on a Chip
Memristive Crossbar Mapping for Neuromorphic Computing Systems on 3D IC

In recent years, neuromorphic computing systems based on memristive crossbar have provided a promising solution to enable acceleration of neural networks. Meanwhile, most of the neural networks used in realistic applications are often sparse. If such sparse neural network is directly implemented on a single memristive crossbar, it would result in inefficient hardware realizations. In this work, we propose 3D-FNC, a 3D floorplanning framework for neuromorphic computing systems in consideration of both crossbar utilization and design cost. 3D-FNC groups neurons that connect more common neurons into one cluster, where the optimal number of clusters is determined by L-method. As a result, the connections of a neural network can be effectively mapped to memristive crossbars or discrete synapses. Finally, a 3D floorplanning for memristive crossbars and neurons is developed to reduce area and wirelength cost. Experimental results show that 3D-FNC can achieve highly hardware-efficient designs, compared to state-of-the-art.