Miracle-dz/UniFAR-FTUs huggingface dataset:
Superior Thermoelectric Design via Antireflection Enabled Lineshape Engineering

We demonstrate theoretically a viable design of a superior thermoelectric generator based on “antireflection” enabled lineshape engineering. Using a minimal double-barrier structure, we show that enabling an antireflection design over it facilitates a bandpass transmission spectrum, which significantly enhances the thermoelectric performance. It is demonstrated that the best operating regime of this device offers a maximum power in the range of 0.7–0.9 MW/m2 at efficiencies ranging from 46% to 54% of Carnot efficiency. The physics of charge and heat transport in the ballistic regime of operation helps us to gain additional insights on how a large number of transverse current carrying modes boost the output power, and simultaneously, how the diminishing effects of high-energy parasitic currents aid the efficiency. Our device design also manifests a high immunity to the destructive effect of self-consistent charging, which aids the enhancement of the output power at high efficiencies. Finally, a comparative study with a conventional double barrier thermoelectric is presented in terms of standard performance parameters, which clarifies the potential benefits of enabling the antireflective region.
ReCom: An efficient resistive accelerator for compressed deep neural networks

Deep Neural Networks (DNNs) play a key role in prevailing machine learning applications. Resistive random-access memory (ReRAM) is capable of both computation and storage, contributing to the acceleration on DNNs by processing in memory. Besides, a significant amount of zero weights is observed in DNNs, providing a space to reduce computation cost further by skipping ineffectual calculations associated with them. However, the irregular distribution of zero weights in DNNs makes it difficult for resistive accelerators to take advantage of the sparsity as expected efficiently, because of its high reliance on regular matrix-vector multiplication in ReRAM. In this work, we propose ReCom, the first resistive accelerator to support sparse DNN processing. ReCom is an efficient resistive accelerator for compressed deep neural networks, where DNN weights are structurally compressed to eliminate zero parameters and become hardware-friendly. Zero DNN activation is also considered at the same time. Two technologies, Structurally-compressed Weight Oriented Fetching (SWOF) and In-layer Pipeline for Memory and Computation (IPMC), are particularly proposed. In our evaluation, ReCom can achieve 3.37x speedup and 2.41x energy efficiency compared to a state-of-the-art resistive accelerator.
An Adaptive Synchronous Parallel Strategy for Distributed Machine Learning

In recent years, distributed systems have mainly been used to train machine learning (ML) models. However, as a result of the different performances among computational nodes in a distributed cluster and delays in network transmission, the accuracies and convergence rates of ML models are relatively low. Therefore, it is necessary to design a reasonable strategy that provides dynamic communication optimization to improve the utilization of the cluster, accelerate the training times, and strengthen the accuracy of the training model. In this paper, we propose the adaptive synchronous parallel strategy for distributed ML. Through the performance monitoring model, the synchronization strategy of each computational node with the parameter server is adjusted adaptively by considering the full performance of each node, thereby ensuring higher accuracy. Furthermore, our strategy prevents the ML model from being affected by irrelevant tasks in the same cluster. Experiments show that our strategy fully improves clustering performance, and it ensures the accuracy and convergence speed of the model, increases the model training speed, and has good expansibility.
Identifying Anomalous Port-Specific Network Behavior

Abstract : Increasing trends in traffic volume on specific ports may indicate new interest in a vulnerability associated with that port. This activity can be a precursor to internet-wide attacks. Port-specific behavior can also arise from stealthy applications that migrate to different ports in order to evade firewalls. But detecting this subtle activity among thousands of monitored ports requires careful statistical modeling as well as methods for controlling false positives. The analysis documented in this report is a large-scale application of statistical outlier detection for determining unusual port-specific network behavior. The method uses a robust correlation measure to cluster related ports and to control for the background baseline traffic trend. A scaled, median-corrected process, called a Z-score, is calculated for the hourly volume measurements for each port. The Z-score measures how unusual each port's behavior is in comparison with the rest of the ports in its cluster. The researchers discuss lessons learned from applying the method to the hourly count of incoming flow records for a carrier-class network over a period of three weeks.
Literature survey of various maximum power point tracking techniques for photovoltaic systems

Increasing utilization of renewable energy has widened the scope of research for improving efficiency of solar PV technology. But the conversion efficiency obtained from solar PV module is not greater than 25%. Hence to improve operating efficiency, it is obligatory to have proficient and robust maximum power point tracking controller. Various MPP tracking techniques are discussed in this literature. This paper would be prerequisite for PV application in future.
Soft decision strategy design for signal demodulation in IEEE 802.11 protocol suite based wireless communication process

Orthogonal frequency division multiplexing (OFDM) technique has now been widely used as the core algorithms in various communication protocols which support high bit rate transmission, such as IEEE 802.11 protocol suite, for it has many advantages including higher efficiency in bandwidth utilization, stronger ability in anti multipath fading, and higher effectiveness in mitigating interference between narrow-band signal. Moreover, as all kinds of communication technologies are always in a fast developing process nowadays, OFDM has also been integrated with many other techniques, including soft decision, interleaving, trellis coded modulation (TCM), etc. To be specific, soft decision has been recognized as the most suitable technique in signal demodulation process, especially in those systems with higher integrated design complexity and higher data coding or modulating complexity. However, reports on soft decision applied wireless communication system based on IEEE 802.11 protocol suite cannot be easily found, even if wireless fidelity (WiFi) and dedicated short range communication (DSRC) based on IEEE 802.11a, b, g, n, or even p have been discussed so much in networking and performance analysis. In this paper, an effort has been tried to introduce soft decision strategy into the signal demodulation process for IEEE 802.11 protocol suite, the soft decision algorithm for quadrature amplitude modulation orthogonal frequency division multiplexing (QAM-OFDM) signal demodulation process has been designed and discussed in detail, and the feasibility of such design has been confirmed.
Comparison of conductometric behavior of two hydrogel based sensing polymeric composites in the physiological pH range

The pH dependent conductance of the Chitosan/Gelatin and Hydroxy-Ethyl Methacrylate (HEMA)/Gelatin hydrogel based systems was mapped out using a data acquisition system and several aspects of conductance characteristics namely accuracy, response time and sensitivity were compared and discussed. The material characteristics of these sensors were mapped out through FTIR. Specific accuracy tests were designed and conducted and both hydrogel based sensors have been found to give a reasonably predictable outcomes in the physiological pH range (4–10). Although Chitosan/Gelatin sensing systems have been explored with regards to conductivity, to the best of our knowledge, HEMA/Gelatin composite has not yet been explored in this respect. There are observable differences in the conductometric system analysis results of both hydrogels; it has been found that HEMA based hydrogels have a longer response time, but also offer a better sensitivity as compared to Chitosan based conductometric hydrogels. This difference in response may be attributed to the material based characteristics of the conductometric sensing system; the possible underlying mechanisms have also been discussed in this research. Our findings indicate that these conductometric composite hydrogels have the potential to be used in physiological applications; where varying response times are required, a hybrid sensor array comprising of both types of hydrogel sensors may be used; that can utilize the advantages of faster response time in case of Chitosan/Gelatin and better sensitivity in case of HEMA/Gelatin sensors.
History, Culture and Traditions: The Silent Spaces in the Study of Spirituality at the End of Life

Recent increase in the number of studies on spirituality manifests growing recognition of the importance of spirituality, as well as mounting interest in studying spirituality in healthcare. Most studies on spirituality in end of life care focus on identifying specific features of spirituality and often represent an individualistic understanding of spirituality. They seldom engage in a historical–cultural exploration of the contextual meanings of those features of spirituality. This paper aims to demonstrate the absence of contextual factors in studying spirituality at the end of life and to highlight the growing recognition of the importance of history, culture and traditions as resources to enrich our understanding of spirituality. An exploration of the concept of spirituality, an overview of the trajectory of the study of spirituality and a review of existing methodological stances reveal the silent space in current approaches to understanding spirituality at the end of life. Recognition of the importance of these contextual factors in understanding spirituality is growing, which is yet to influence the conceptualization and the conduct of spirituality research. Contextual understandings of spirituality that incorporate insights from the history, culture and traditions of specific contexts can inform effective means for providing spiritual support in clinical practice.
Design of smart cooling system for power transformer

The flexibility of a transformer enables it to have a wide range of applications. One of the most important parameters that has an influence on the transformer insulation is the temperature. Hence, the parameter to be controlled is the fan speed and flow rate of oil (using pumps) that varies invariantly with the load. The conventional control technique which is winding Temperature Indicator (WTI) fails to achieve this task. The mechanism for Cooling of power transformer is designed on the process of measuring top-oil temperature along-with a simulation used to find the point of highest temperature in the winding. WTI has some short-comings and researchers now prefer the presentation of fiber optic based temperature sensors for this critical function. Fiber optic sensors have been selected for the control of the cooling banks. The long-term performance of transformer cooling can be better achieved with these more accurate and modern fiber optic sensors. This paper presents a mechanism to control the temperature of power transformer using smart cooling system which includes Forced Oil (FO) pumps and fans. A comparative analysis is also performed between the WTI system and the proposed smart cooling system. Flow control of these cooling devices is controlled and monitored by the use of PID-controller via traditional Ziegler-Nichols algorithm and advanced Ziegler-Nichols algorithm organized with fresh developments in sensor technologies. This regulator pushes the designed system to operate in flow and temperature regimes which limit the problem of minimizing thermal degradation of the insulation.
Minimum loss operation of high-frequency inductors

This paper investigates the losses of a power inductor employed in a 2kW, 400V input DC-DC converter, in dependency of key operating parameters, i.e. switching frequency and current ripple. Based on detailed high-frequency winding and core loss models, including the implications of DC-bias, temperature and frequency on the core losses, and an analytic thermal model, a minimum loss inductor is designed for each combination of switching frequency, f, and current ripple, r. In the course of the optimization, the core (E55, N87) and the winding (litz wire, 100 μm) are considered given. Surprisingly, the evaluation of the losses calculated in the f-r domain reveals that nearly minimum inductor losses are obtained for a current ripple that is inversely proportional to the frequency, i.e., for a constant inductance. Further detailed investigations of the calculated inductor losses reveal a decrease of the losses for increasing frequencies up to a very high frequency of 500 kHz. In this regard, at f = 100kHz, minimum total losses of 4.0W result for r = 45%, which can be reduced to 1.8W at f = 500 kHz for r = 10%. Finally, the sensitivities of the losses with regard to different litz wires (71 μm, 200 μm) and a different core (E42, N87) are examined and a design guidance is extracted that summarizes the main findings of the detailed investigation. A calorimetric measurement set-up is used to measure the losses of a realized inductor at different operating points in order to confirm the theoretical considerations.
Supporting the Complex Social Lives of New Parents

One of the many challenges of becoming a parent is the shift in one's social life. As HCI researchers have begun to investigate the intersection of sociotechnical system design and parenthood, they have also sought to understand how parents' social lives can be best supported. We build on these strands of research through a qualitative study with new parents regarding the role of digital technologies in their social lives as they transition to parenthood. We demonstrate how sociotechnical systems are entangled in the ways new parents manage their relationships, build (or resist building) new friendships and ad hoc support systems, and navigate the vulnerabilities of parenthood. We discuss how systems designed for new parents can better support the vulnerabilities they internalize, the diverse friendships they desire, and the logistical challenges they experience. We conclude with recommendations for future design and research in this area.
Human Action Recognition Using Improved Sparse Gaussian Process Latent Variable Model and Hidden Conditional Random Filed

Owing to the fragile to external environment, current human activity recognition is still challenging in the area of computer vision. In particular, the recognition of subtle actions is a difficult task to distinguish from each other. In this paper, we proposed the methods for human action recognition based on improved sparse Gaussian process latent variable model (GPLVM) and hidden conditional random field (HCRF). We first fused the skeletal information and the motion characteristics of human body to extract human action features from a set of action sequences. And then, we proposed an improved sparse GPLVM algorithm for feature dimensionality reduction to satisfy the visualization and computation complexity for human actions recognition. Through sparse approximation with information vector machine and the dynamic process of human actions, the improved sparse GPLVM allows the action features to be represented by the low dimensional trajectory in manifold space. Furthermore, HCRF was applied to recognize the characteristics of human actions derived from manifold spaces and finally to classify human actions. The proposed methods are tested and evaluated on public action database. The experimental results show that our methods can achieve better performance of feature dimensionality reduction and visualization and obtain the average recognition accuracy of 93.68%.
On ultrasound measurement system estimating diameters of fallopian tube models

In this paper, a method of calculating inner and outer diameters of fallopian tubes is presented, provided that silicone rubber tubes are models for fallopian tubes. It is based on the ultrasound measurement using a single probe of which the nominal frequency is 5 MHz, and assumes that ultrasound waves emanating from the probe are reflected at the top outer surface, surfaces between water and silicone rubber, and bottom outer surface of the tube. It obtains envelope curves associated with the reflected waves, by applying Hilbert transformation to the waves. It next estimates top four maximal values on the envelope curves to acquire time points when the wave reflections occur. The inner and outer diameters of the tubes are easily estimated by substituting the above time points in simple formulas. Experimental results reveal that the proposed method can achieve substantial accuracy in estimating inner and outer diameters of the target tubes.
Fully Distributed Fault-Tolerant Consensus Protocols for Lipschitz Nonlinear Multi-Agent Systems

In this paper, we investigate the fault-tolerant consensus problems for multi-agent systems with actuator faults. Based on the relative state information, fully distributed adaptive protocols are designed for these agents described by Lipschitz nonlinear dynamics under leaderless and leader-follower communication structures. As the special case, for linear multi-agent systems, fault-tolerant consensus problems are also solved with the proposed protocols. First, for the leaderless multi-agent systems, all agents reach an agreement on a common value with undirected connected communication graphs. Second, for the leader-follower multi-agent systems, in which the state of the leader is only available to a subset of the followers, the state of each follower converges to the state of the leader, asymptotically. A distinctive feature of this paper is that the adaptive protocols here are independent of the eigenvalues of the Laplacian matrix associated with the whole communication graph, which means the protocols can be implemented by each agent in a fully distributed fashion. Simulation examples are provided to illustrate the theoretical results.
Adolescent-onset anorexia nervosa: 18-year outcome.

BACKGROUND The long-term outcome of anorexia nervosa is insufficiently researched. AIMS To study prospectively the long-term outcome and prognostic factors in a representative sample of people with teenage-onset anorexia nervosa. METHOD Fifty-one people with anorexia nervosa, recruited by community screening and with a mean age at onset of 14 years were compared with 51 matched comparison individuals at a mean age of 32 years (18 years after disorder onset). All participants had been examined at ages 16 years, 21 years and 24 years. They were interviewed for Axis I psychiatric disorders and overall outcome (Morgan-Russell assessment schedule and the Global Assessment of Functioning). RESULTS There were no deaths. Twelve per cent (n=6) had a persisting eating disorder, including three with anorexia nervosa. Thirty-nine per cent of the anorexia nervosa group met the criteria for at least one psychiatric disorder. The general outcome was poor in 12%. One in four did not have paid employment owing to psychiatric problems. Poor outcome was predicted by premorbid obsessive-compulsive personality disorder, age at onset of anorexia nervosa and autistic traits. CONCLUSIONS The 18-year outcome of teenage-onset anorexia nervosa is favourable in respect of mortality and persisting eating disorder.
From superresolution to nanodetection: overview of far field optical nanoscopy techniques for nanostructures

Far field optical nanoscopy has been brought to the forefront with the 2014 Nobel Prize for chemistry in fluorescent nanoscopy for revealing intra-cellular details of tens of nm. In this review, we present an improved classification scheme that summarizes the many optical nanoscopy techniques that exist. We place particular emphasis on unlabelledsuperresolution techniques that provide real improved resolving power and unlabellednanodetection techniques for characterizing unresolved nanostructures. Superresolution is illustrated with sub-100 nm imaging of diatoms with tomographic diffractive microscopyand adenoviruseswith submerged microsphere optical nanoscopy. Three sub-categories of nanodetectionare then presented. Contrast enhancement is illustrated with surface enhanced ellipsometric contrast microscopy for the study of bacterial motility and strobed phase contrast microscopy for measuring the mechanical properties of vesicle membranes. High sensitivity phase measurement using interference microscopy demonstrates how nanostructured surfaces and structures can be characterized in biomaterials, laser textured stainless steel and defects within thin polymer films. Finally, deconvolution is illustrated with the use of through-focus scanning optical microscopy in critical dimension measurement and characterization of 40 nm linewidths in microelectronic devices. In this way we show how new far field optical nanoscopy techniques are being developed for unlabelled characterization of nano and biomaterials.
A Planning Approach for the Network Configuration of AC-DC Hybrid Distribution Systems

This paper proposes a novel stochastic planning model for AC-DC hybrid distribution systems (DSs). Taking into account the possibility of each line/bus being AC or DC, the model finds the optimal AC-DC hybrid configuration of buses and lines in the DS. It incorporates consideration of the stochastic behavior of load demands and renewable-based distributed generators (DGs). The stochastic variations are addressed using a Monte-Carlo simulation technique. The objective of the planning model is the minimization of DS installation and operation costs. The optimal planning solution is obtained by dividing the hybrid planning problem into two nested optimization problems: 1) the main problem is formulated using a genetic algorithm (GA) to search for the optimal AC-DC configuration and 2) the subproblem is used for determining the optimal power flow solution for each configuration generated by the GA. The proposed model has been employed for finding the optimal configuration for a suggested case study that included photovoltaic panels, wind-based DG, and electric vehicle charging stations. The same case study was also solved using a traditional AC planning technique in order to evaluate the effectiveness of the proposed model and the associated cost-savings. The results demonstrate the advantages offered by the proposed model. The proposed framework represents an effective technique that can be used by DS operators to identify the optimal AC-DC network configuration of future DSs.
Spontaneous Bacterial Peritonitis due to Lactobacillus paracasei in Cirrhosis

Lactobacillus species colonize the human gastrointestinal tract and are rarely pathogenic. We present a case involving a cirrhotic patient who presented with sepsis and was found to have peritoneal cultures demonstrating Lactobacillus as the sole pathogen concerning for spontaneous bacterial peritonitis. Treatment was achieved with high-dose penicillin and clindamycin but the patient developed hepatorenal syndrome and died from acute renal failure. Intra-abdominal Lactobacillus infections are typically seen in patients undergoing peritoneal dialysis or who have recently had bowel perforation. There are few case reports of spontaneous Lactobacillus peritonitis in patients with cirrhosis. Our case report addresses the challenges of Lactobacillus treatment and suggests antibiotic coverage of commensal organisms in patients who do not improve with standard management.