Miracle-dz/UniFAR-FTUs huggingface dataset:
ESPRIT-based 2-D direction finding with a sparse uniform array of electromagnetic vector sensors

Aperture extension (interferometry baseline extension) is achieved in this novel ESPRIT-based two-dimensional (2-D) arrival angle estimation scheme using a sparse (a.k.a., thin or thinned) uniform rectangular array of electromagnetic vector sensors spaced much farther apart than a half-wavelength. An electromagnetic vector sensor is composed of six spatially co-located, orthogonally oriented, diversely polarized antennas, distinctly measuring all six electromagnetic-field components of an incident multisource wavefield. Each incident source's direction of arrival (DOA) is estimated from the source's electromagnetic-field vector component and serves as a coarse reference to disambiguate the cyclic phase ambiguities in ESPRIT's eigenvalues when the intervector sensor spacing exceeds a half wavelength. Simulations demonstrate the significant performance gain realizable by this method for radar and wireless mobile fading-channel communications.
Inter-subject variability of respiratory motion from 4D MRI

Respiratory motion affects image acquisition and also external beam radiotherapy (EBRT) treatment planning and delivery. Existing approaches for respiratory motion management are often based on a generic view of respiratory motion such as the general movement of organ, tissue or fiducials. This paper aims to present a more in depth analysis of respiratory motion based on 4D MRI, which can then be integrated into motion correction approaches in image acquisition or image based EBRT. In this paper we analyse the respiratory motion of organs for five volunteers on a per-organ basis, separately for each volunteer and together comparatively. We also compare with a separate study of respiratory motion for 20 patients. The motion extracted from 4D MRI on general was found to be consistent with what has been reported in literature and a similar process can be used in future to extract and quantify respiratory motion on a larger dataset.
Towards an Open Dependable Operating System

This paper introduces a new dependable operating system project, called DEOS, started in 2006, and scheduled to continue for six years. In this project, a safety extension mechanism called P-Bus is to be designed, and implemented in the Linux kernel so that a future dependability attribute is implemented with P-Bus. A hardware abstraction layer, called SPUMONE, is introduced so that a light-weight operating system, called ArcOS, and a monitoring service on top of ArcOS monitors the Linux kernel to provide a safety-net for the Linux kernel. New dependability metrics are being designed to enable developers and users to decide which hardware or software solution meets their dependability requirements, and thus can be used.
A smart home control system based on indoor location and attitude estimation

The emergence of new technologies about the smart home system provides more innovative ideas and solutions, and the smart home system based on the Internet of Things can achieve the convenience of life by sensing, interconnection and intelligent control. However, most methods of controlling the appliances are based on the expatiatory menu, and users usually need to choose the electrical appliances by page turning of the menu items, which is not convenient. Therefore, this paper proposed a distinctive system based on indoor location and attitude estimation. Further more, the indoor location algorithm is achieved with the combination of image pattern recognition and fingerprint matching. The user can choose the appliances that he wants and control them by touching the screen of the mobile device while the mobile device is pointing to the appliance. The prototype of the smart home system is implemented and the availability test is conducted. It proved that the solution will simplify the control operation procedure and improve the user's experience.
Extracellular vesicle transfer of cancer pathogenic components

Extracellular vesicles (EV), known as exosomes and microvesicles, serve as versatile intercellular communication vehicles. Increasing evidence has shown that cancer cell‐derived EV carry pathogenic components, such as proteins, messenger RNA (mRNA), microRNA (miRNA), DNA, lipids and transcriptional factors, that can mediate paracrine signaling in the tumor microenvironment. These data suggest that EV transfer of cancer pathogenic components enable long‐distance crosstalk between cancer cells and distant organs, resulting in the promotion of the initial steps for pre‐metastatic niche formation. Understanding the metastatic mechanisms through EV transfer may open up a new avenue for cancer therapeutic strategies. Furthermore, the circulating EV have also been of interest as a source for liquid biopsies. EV in body fluids provide a reliable source of miRNA and proteins for cancer biomarkers. The tumor‐specific components in EV effectively provide various messages on the physiological and pathological status of cancer patients. Although many researchers are searching for EV biomarkers using miRNA microarrays and proteome analyses, the detection technology for circulating EV in body fluids has not yet reached the point of clinical application. In this review, we summarize recent findings regarding EV function, specifically in metastasis through the transfer of cancer pathogenic components. Furthermore, we highlight the potential of using circulating EV for cancer diagnosis.
Kinetic analysis of drug release from nanoparticles.

PURPOSE Comparative drug release kinetics from nanoparticles was carried out using conventional and our novel models with the aim of finding a general model applicable to multi mechanistic release. Theoretical justification for the two best general models was also provided for the first time. METHODS Ten conventional models and three models developed in our laboratory were applied to release data of 32 drugs from 106 nanoparticle formulations collected from literature. The accuracy of the models was assessed employing mean percent error (E) of each data set, overall mean percent error (OE) and number of Es less than 10 percent. RESULTS Among the models the novel reciprocal powered time (RPT), Weibull (W) and log- probability (LP) ones produced OE values of 6.47, 6.39 and 6.77, respectively. The OEs of other models were higher than 10%. Also the number of errors less than 10 percent for the models was 84.9, 80.2 and 78.3 percents of total number of data sets. CONCLUSIONS Considering the accuracy criteria the reciprocal powered time model could be suggested as a general model for analysis of multi mechanistic drug release from nanoparticles. Also W and LP models were the closest to the suggested model.
Building search context with sliding window for information seeking

With the rapid development of Internet, how to obtain and represent personalized information in user's activity of information seeking is a key issue in information retrieval. This paper presents a novel method to build personalized search context which represents semantic background in user's information seeking. Search context is composed of terms and semantic relation which is extracted based on Web-snippets returned from search engine. In addition, sliding window algorithm is applied in mining semantic relation in search context. Experimental results demonstrate the effectiveness of our method in clustering algorithm which plays an important role in information retrieval. It can be seen that this method has a brilliant perspective in the field of personalized search.
Exploring Sentiment Summarization

We introduce the idea of a sentiment summary, a single passage from a document that captures a key aspect of the author’s opinion about his or her subject. Using supervised data from the Rotten Tomatoes website, we examine features that appear to be helpful in locating a good summary sentence. These features are used to fit Naive Bayes and regularized logistic regression models for summary extraction.
Consanguinity, inbreeding, and genetic drift in Italy

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Squalene Inhibits ATM-Dependent Signaling in γIR-Induced DNA Damage Response through Induction of Wip1 Phosphatase

Ataxia telangiectasia mutated (ATM) kinase plays a crucial role as a master controller in the cellular DNA damage response. Inhibition of ATM leads to inhibition of the checkpoint signaling pathway. Hence, addition of checkpoint inhibitors to anticancer therapies may be an effective targeting strategy. A recent study reported that Wip1, a protein phosphatase, de-phosphorylates serine 1981 of ATM during the DNA damage response. Squalene has been proposed to complement anticancer therapies such as chemotherapy and radiotherapy; however, there is little mechanistic information supporting this idea. Here, we report the inhibitory effect of squalene on ATM-dependent DNA damage signals. Squalene itself did not affect cell viability and the cell cycle of A549 cells, but it enhanced the cytotoxicity of gamma-irradiation (γIR). The in vitro kinase activity of ATM was not altered by squalene. However, squalene increased Wip1 expression in cells and suppressed ATM activation in γIR-treated cells. Consistent with the potential inhibition of ATM by squalene, IR-induced phosphorylation of ATM effectors such as p53 (Ser15) and Chk1 (Ser317) was inhibited by cell treatment with squalene. Thus, squalene inhibits the ATM-dependent signaling pathway following DNA damage through intracellular induction of Wip1 expression.
Sliding-switching power supply circuit for class-D audio amplifier

The paper presents a robust power supply circuit for class-D audio amplifier especially for multilevel converter. Based on pulse-width-modulation (PWM) buck converter, we develop a sliding-switching technique comprises a loading monitor and a voltage level controller. The loading monitor continuously checks the internal control signal of class-D amplifier to identify whether the loading is light or heavy. The voltage level controller then feedbacks corresponding voltage level to modulate pulse width of control signal in buck converter and adjust supplying current and power delivery. The proposed sliding-switching technique stabilizes the voltage variation of power supply under the situation of alternating light and heavy loading and consequently enhances the performance of total-harmonic-distortion (THD). To demonstrate the practicability, an integrated multilevel class-D amplifier with proposed power supply circuit is implemented under TSMC 0. 35µm process. The simulation results show that the total-harmonic-distortion is improved more than 11dB without increasing power consumption of circuit.
Twitter in the Cross Fire—The Use of Social Media in the Westgate Mall Terror Attack in Kenya

On September 2013 an attack on the Westgate mall in Kenya led to a four day siege, resulting in 67 fatalities and 175 wounded. During the crisis, Twitter became a crucial channel of communication between the government, emergency responders and the public, facilitating the emergency management of the event. The objectives of this paper are to present the main activities, use patterns and lessons learned from the use of the social media in the crisis. Using TwitterMate, a system developed to collect, store and analyze tweets, the main hashtags generated by the crowd and specific Twitter accounts of individuals, emergency responders and NGOs, were followed throughout the four day siege. A total of 67,849 tweets were collected and analyzed. Four main categories of hashtags were identified: geographical locations, terror attack, social support and organizations. The abundance of Twitter accounts providing official information made it difficult to synchronize and follow the flow of information. Many organizations posted simultaneously, by their manager and by the organization itself. Creating situational awareness was facilitated by information tweeted by the public. Threat assessment was updated through the information posted on social media. Security breaches led to the relay of sensitive data. At times, misinformation was only corrected after two days. Social media offer an accessible, widely available means for a bi-directional flow of information between the public and the authorities. In the crisis, all emergency responders used and leveraged social media networks for communicating both with the public and among themselves. A standard operating procedure should be developed to enable multiple responders to monitor, synchronize and integrate their social media feeds during emergencies. This will lead to better utilization and optimization of social media resources during crises, providing clear guidelines for communications and a hierarchy for dispersing information to the public and among responding organizations.
Switched-capacitor realization of presynaptic short-term-plasticity and stop-learning synapses in 28 nm CMOS

Synaptic dynamics, such as long- and short-term plasticity, play an important role in the complexity and biological realism achievable when running neural networks on a neuromorphic IC. For example, they endow the IC with an ability to adapt and learn from its environment. In order to achieve the millisecond to second time constants required for these synaptic dynamics, analog subthreshold circuits are usually employed. However, due to process variation and leakage problems, it is almost impossible to port these types of circuits to modern sub-100nm technologies. In contrast, we present a neuromorphic system in a 28 nm CMOS process that employs switched capacitor (SC) circuits to implement 128 short term plasticity presynapses as well as 8192 stop-learning synapses. The neuromorphic system consumes an area of 0.36 mm2 and runs at a power consumption of 1.9 mW. The circuit makes use of a technique for minimizing leakage effects allowing for real-time operation with time constants up to several seconds. Since we rely on SC techniques for all calculations, the system is composed of only generic mixed-signal building blocks. These generic building blocks make the system easy to port between technologies and the large digital circuit part inherent in an SC system benefits fully from technology scaling.
A decoherence theorem in quantum-network synchronization

In this paper, we study the decoherence property of synchronization master equation for networks of qubits interconnected by swapping operators. The network Hamiltonian is assumed to be diagonal with different entries so that it might not be commutative with the swapping operators. We prove a theorem establishing a general condition under which almost complete decohernece is achieved, i.e., all but two of the off-diagonal entries of the network density operator asymptotically tend to zero. This result explicitly shows that quantum dissipation networks tend to forget the information initially encoded when the internal (induced by network Hamiltonian) and external (induced by swapping operators) qubit interactions do not comply with each other.
SPATIAL PATTERN IN MODELING ELECTRICITY PRICES: EVIDENCE FROM THE PJM MARKET

This paper analyses the evolution of electricity prices in deregulated market. I formulate a model that takes into account the spatial features of a network of a market. The model is applied to equilibrium electricity spot prices of the PJM market. An empirical analysis indicates that the problem of unobserved spatial correlation in the network can be modeled by the Spatial Error Model providing an additional insight about the spot electricity prices in the PJM market. The topology of the network and the structure of the market are responsible for the spatial correlation, which should not be ignored by careful research. 1 WVU Department of Economics, PO Box 6025, Morgantown, WV, 26506-6025. E-mail: jnpopova@mail.wvu. edu This research was sponsored in part by US DOE/EPSCoR WV State Implementation Award. The author is with the Advanced Power and Electricity Research Center, West Virginia University.
Optical coherence tomography for neurosurgical imaging of human intracortical melanoma.

OBJECTIVE Intraoperative identification of brain tumors and tumor margins has been limited by either the resolution of the in vivo imaging technique or the time required to obtain histological specimens. Our objective was to evaluate the feasibility of using optical coherence tomography (OCT) as a high-resolution, real-time intraoperative imaging technique to identify an intracortical melanoma. INSTRUMENTATION OCT is a new, noncontact, high-speed imaging technology capable of resolutions on the micrometer scale. OCT is analogous to ultrasound B-mode imaging, except that reflections of infrared light, rather than sound, are detected. OCT uses inherent tissue contrast, rather than enhancement with dyes, to differentiate tissue types. The compact, fiberoptic-based design is readily integrated with surgical instruments. METHODS A portable handheld OCT surgical imaging probe has been constructed for imaging within the surgical field. Cadaveric human cortex with metastatic melanoma was harvested and imaged in two and three dimensions. Changes in optical backscatter intensity were used to identify regions of tumor and to locate tumor margins. Structures within the optical coherence tomographic images were compared with the histological slides. RESULTS Two-dimensional images showed increased optical backscatter from regions of tumor, which was quantitatively used to determine the tumor margin. The images correlated well with the histological findings. Three-dimensional reconstructions revealed regions of tumor penetrating normal cortex and could be resectioned at arbitrary planes. Subsurface cerebral vascular structures could be identified and were therefore avoided. CONCLUSION OCT can effectively differentiate normal cortex from intracortical melanoma based on variations in optical backscatter. The high-resolution, high-speed imaging capabilities of OCT may permit the intraoperative identification of tumor and the more precise localization of tumor margins.
Economic Inequality and the Provision of Schooling

The school finance landscape has changed dramatically in the past thirty years. Most states have undertaken major changes to their school finance programs, motivated principally by the notion that the unequal school resources associated with unequal incomes and community sorting lead to unequal educational and labor market outcomes. This paper describes the empirical evidence on the relationship between school finance reforms and student outcomes and presents new evidence on the effects of these policies on community and school composition.
In Vitro Protective Effect and Antioxidant Mechanism of Resveratrol Induced by Dapsone Hydroxylamine in Human Cells

Dapsone (DDS) hydroxylamine metabolites cause oxidative stress- linked adverse effects in patients, such as methemoglobin formation and DNA damage. This study evaluated the ameliorating effect of the antioxidant resveratrol (RSV) on DDS hydroxylamine (DDS-NHOH) mediated toxicity in vitro using human erythrocytes and lymphocytes. The antioxidant mechanism was also studied using in-silico methods. In addition, RSV provided intracellular protection by inhibiting DNA damage in human lymphocytes induced by DDS-NHOH. However, whilst pretreatment with RSV (10–1000 μM significantly attenuated DDS-NHOH-induced methemoglobinemia, but it was not only significantly less effective than methylene blue (MET), but also post-treatment with RSV did not reverse methemoglobin formation, contrarily to that observed with MET. DDS-NHOH inhibited catalase (CAT) activity and reactive oxygen species (ROS) generation, but did not alter superoxide dismutase (SOD) activity in erythrocytes. Pretreatment with RSV did not alter these antioxidant enzymes activities in erythrocytes treated with DDS-NHOH. Theoretical calculations using density functional theory methods showed that DDS-NHOH has a pro-oxidant effect, whereas RSV and MET have antioxidant effect on ROS. The effect on methemoglobinemia reversion for MET was significantly higher than that of RSV. These data suggest that the pretreatment with resveratrol may decrease heme-iron oxidation and DNA damage through reduction of ROS generated in cells during DDS therapy.
First Issue Editorial

When the founders of this Journal -- Cynthia Dwork, Stephen Fienberg and Alan Karr -- made its initial call for papers, they and we identified many constituencies that participate in the scientific analysis of privacy and confidentiality. Statisticians, particularly those working within national statistical offices, have developed the field of statistical disclosure limitation. Com- puter scientists contribute work in privacy-preserving data-mining and cryptographic analyses of privacy. Lawyers and social scientists study the role of government and regulation in the creation and protection of individual and business privacy. Health researchers struggle with the trade-off between a patient’s privacy and the contribution to science that access to inte- grated medical records might allow. Survey designers in all fields of human endeavor wrestle with methods of enticing survey cooperation under a variety of ethical and privacy guarantees. Gargantuan online services gather petabytes of data on search queries, online purchases, e-mail exchanges, and other social network interactions while pushing their computer scientists to exploit the corporate asset these data represent without damaging the companies’ ability to do future business by breaching the confidence of their client/users. And many, many data users from all of the fields listed above perform analyses that are conditioned on the privacy and confidentiality protections imposed on their work without all the means to assess the consequences of those measures on the inferences they have made. We are certainly not the first journal to venture into this domain. But we are the first journal to solicit actively contributions from the entire community that are aimed at multiple constituencies within that community. We think that a brief illustration of how the research questions share a common theme would provide a useful introduction to this first volume.
THEME ―Efficient and Effective Algorithm Detection of Node Replication Attacks in Mobile Sensor Networks"

Wireless sensor networks are often deployed in hostile environments, where an adversary can physically capture some of the nodes. Once a node is captured, the attacker can re-program it and replicate the node in a large number of replicas, thus easily taking over the network. The detection of node replication attacks in a wireless sensor network is therefore a fundamental problem. Compared to the extensive exploration on the defense against node replication attacks in static networks, only a few solutions in mobile networks have been presented. Moreover, while most of the existing schemes in static networks rely on the witness-finding strategy, which cannot be applied to mobile networks, the velocity-exceeding strategy used in existing schemes in mobile networks incurs efficiency and security problems. In this paper Localized algorithms are proposed to resist node replication attacks in mobile sensor networks. The Merits of proposed algorithms are, it can effectively detect the node replication in localized manner. These algorithms are, also avoid network-wide synchronization and network-wide revocation.