Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution of synapses in the lateral geniculate nucleus of the cat: Differences between laminae A and A1 and between relay cells and interneurons

Laminae A and A1 of the lateral geniculate nucleus in the cat are generally considered to be a structurally and functionally matched pair of inputs from two eyes, although there are subtle light microscopic and physiological differences. The present study aims to display ultrastructural differences between these two laminae based on electron microscopic observances on the connectivity patterns of their afferents onto two main cell types: relay cells, and interneurons present in this nucleus. In a design of population measurement from randomized sample areas in laminae A and A1 from six brains, all synaptic contacts made by three terminal types of the geniculate nucleus were identified, and a number of relative distribution properties were analyzed. When the A‐laminae were considered as a homogeneous structure, the distribution of the three terminal types on geniculate cells was similar to previously reported results, confirming the validity of the sampling strategies used; RLP (retinal) terminals provided one‐fifth of all synapses, whereas RD (from cortex and brainstem) and F (inhibitory) types constituted one‐half and one‐third, respectively. The relay cells alone received a similar composition of afferents. However, interneurons alone received approximately equal amounts of synapses from the three sources. Similar analyses comparing the distributions in lamina A and A1 revealed that RD and F terminals, but not RLP terminals, innervate these two laminae differently; more RD and fewer F terminals were found in lamina A1. This difference was also present in the distribution of terminals on relay cells alone, but not on interneurons. These results suggest that (1) retinal terminals form a significantly larger fraction of the input to interneurons than to relay cells; correspondingly, cortex and brainstem provide a smaller fraction of all inputs to interneurons than to relay cells; and (2) laminae A and A1 are not strictly equivalent projection sites of the two retinae. The results are discussed in relation to the Y‐cell subpopulation in lamina A1 that is involved in corticotectal, as well as corticogeniculate circuits, as opposed to Y‐cells of lamina A that are involved in only the latter. J. Comp. Neurol. 390:247–255, 1998. © 1998 Wiley‐Liss, Inc.
Routing algorithms in computers networks

Routing in computer network is an essential functionality, which influence both the network management as the quality of services in global networks. The management of the traffic flows has to satisfy requirements for volume of traffic to be transmitted as avoidance of congestions for decreasing the transmission delays. These two requirements in general are contradictory. The optimal traffic management is a key issue for the quality of the information services. Routing in networks, applying shortest path algorithm is widely used in communication protocols in WAN. Short explanations and illustration of these algorithms is given.
Methods for Linking and Mining Massive Heterogeneous Databases

Many real-world KDD expeditions involve investigation of relationships between variables in different, heterogeneous databases. We present a dynamic programming technique for linking records in multiple heterogeneous databases using loosely defined fields that allow free-style verbatim entries. We develop an interestingness measure based on non-parametric randomization tests, which can be used for mining potentially useful relationships among variables. This measure uses distributional characteristics of historical events, hence accommodating variable-length records in a natural way. As an illustration, we include a successful application of the proposed methodology to a real-world data mining problem at Lucent Technologies.
Development of the quadruped walking robot, TITAN-IX — mechanical design concept and application for the humanitarian de-mining robot

This paper proposes a quadruped walking robot that has high performance as a working machine. This robot is needed for various tasks controlled by tele-operation, especially for humanitarian mine detection and removal. Since there are numerous personnel landmines that are still in place from many wars, it is desirable to provide a safe and inexpensive tool that civilians can use to remove those mines. The authors have been working on the concept of the humanitarian demining robot systems for 4 years and have performed basic experiments with the first prototype VK-I using the modified quadruped walking robot, TITAN-VIII. After those experiments, it was possible to refine some concepts and now the new robot has a tool (end-effector) changing system on its back, so that by utilizing the legs as manipulation arms and connecting various tools to the foot, it can perform mine detection and removal tasks. Toaccomplish these tasks, we developed various end-effectors that can be attached to the working leg. In this paper we will discuss the mechanical design of the new walking robot called TITAN-IX to be applied to the new system VK-II.
Privacy-Preserving Smart Metering with Authentication in a Smart Grid

The traditional security objectives of smart grids have been availability, integrity, and confidentiality. However, as the grids incorporate smart metering and load management, user and corporate privacy is increasingly becoming an issue in smart grid networks. Although transmitting current power consumption levels to the supplier or utility from each smart meter at short intervals has an advantage for the electricity supplier’s planning and management purposes, it threatens user privacy by disclosing fine-grained consumption data and usage behavior to utility providers. In this study, we propose a distributed incremental data aggregation scheme where all smart meters on an aggregation path are involved in routing the data from the source meter to the collection unit. User privacy is preserved by symmetric homomorphic encryption, which allows smart meters to participate in the aggregation without seeing any intermediate or final result. Aggregated data is further integrated with an aggregate signature to achieve data integrity and smart meter authentication in such a way that dishonest or fake smart meters cannot falsify data en route. Only the collection unit can obtain the aggregated data and verify its integrity while the individual plain data are not exposed to the collection unit. Therefore, user privacy and security are improved for the smart metering in a smart grid network.
Electronic Transport in Helium Beam Modified Graphene and Ballistic Josephson Junctions

This thesis describes the capabilities of the helium ion microscope (HIM) and that of graphene to explore fundamental physics and novel applications. While graphene offers superior electronic properties, the helium ion microscope allows us to combine imaging and modification of materials at the nanoscale. We used the capabilities of HIM to grow 3D-AFM probes, which can be used in the critical dimension semiconductor metrology. Moreover, we studied the ion-material interactions, needed to enable the fabrication of functional graphene nanoribbons. Similarly, we used the superior electronic properties of graphene to make ballistic Josephson junctions and studied the current-phase relation (CPR) of these junctions. The core of this thesis is focused on the fabrication and electronic characterization of He+ beam modified graphene, He+ beam etched graphene nanoribbons, and graphene-based Josephson junctions (JJs). The graphene devices were prepared by a new polymer-free transfer "van der Waals pick-up" technique. The fabricated devices comprise graphene encapsulated in hexagonal boron nitride (BN) and contacted along the edge by either a normalmetal (Cr/Au) or by a superconductor. The encapsulation in BN keeps the graphene clean and the edge contacting technique provides transparent interfaces. The thesis is divided into two main topics. In particular, the first three studies are dedicated to the research based on the helium ion microscope, and the next three are dedicated to the research based on boron nitride encapsulated graphene Josephson junctions.
Knowledge Acquisition with Supervised Ontology Population

Ontology plays a crucial role in capturing and disseminating business information (e.g., products, services, relationships of businesses) for effective human computer interactions. However, manual construction of domain ontology is very labour intensive and time consuming. This paper illustrates a novel ontology population method for semi-automatic business knowledge acquisition from text. In particular, the proposed method is underpinned by the effective SVM-struct algorithm which treats ontology population as a sequence labelling problem. By automatically exploring taxonomy knowledge captured in domain ontology, our ontology population method can effectively classify objects to multiple categories. The initial experimental results show that the SVM-struct based ontology population method which utilizes taxonomy knowledge outperforms other traditional methods in a benchmark ontology population task.
Directional control of lamellipodia extension by constraining cell shape and orienting cell tractional forces

Directed cell migration is critical for tissue morphogenesis and wound healing, but the mechanism of directional control is poorly understood. Here we show that the direction in which cells extend their leading edge can be controlled by constraining cell shape using micrometer‐sized extracellular matrix (ECM) islands. When cultured on square ECM islands in the presence of motility factors, cells preferentially extended lamellipodia, filopodia, and microspikes from their corners. Square cells reoriented their stress fibers and focal adhesions so that tractional forces were concentrated in these corner regions. When cell tension was dissipated, lamellipodia extension ceased. Mechanical interactions between cells and ECM that modulate cytoskeletal tension may therefore play a key role in the control of directional cell motility. —Parker, K. K. , Brock, A. L. , Brangwynne, C. , Mannix, R. J., Wang, N. , Ostuni, E. , Geisse, N. A. , Adams, J. C. , Whitesides, G. M. , Ingber, D. E. Directional control of lamellipodia extension by constraining cell shape and orienting cell tractional forces. FASEB J. 16, 1195–1204 (2002)
Pharmacology and Antifungal Properties of Anidulafungin, a New Echinocandin

Anidulafungin is the third echinocandin antifungal agent to receive approval from the United States Food and Drug Administration. It is indicated for the treatment of esophageal candidiasis, candidemia, and other candidal infections. Anidulafungin is fungicidal against Candida species, including Candida glabrata and isolates resistant to azoles and polyenes. The drug's efficacy is comparable to that of fluconazole for the treatment of esophageal candidiasis, and it is effective in patients with invasive candidiasis and candidemia. Anidulafungin is distinct among the echinocandins in that it undergoes slow, nonenzymatic chemical degradation. As a consequence, impairments in renal or hepatic function do not substantially alter its pharmacokinetics. In addition, anidulafungin has not demonstrated any drug‐drug interactions because it is not a substrate, inhibitor, or inducer of the cytochrome P450 enzyme system. Anidulafungin is well tolerated in adults and pediatric patients, with few reported adverse drug events. The safety, tolerability, and potent fungicidal activity of anidulafungin against Candida species make it a reasonable alternative in the treatment of patients with serious candidal infections.
When big data meets software-defined networking: SDN for big data and big data for SDN

Both big data and software-defined networking (SDN) have attracted great interests from both academia and industry. These two important areas have traditionally been addressed separately in the most of previous works. However, on the one hand, the good features of SDN can greatly facilitate big data acquisition, transmission, storage, and processing. On the other hand, big data will have profound impacts on the design and operation of SDN. In this paper, we present the good features of SDN in solving several issues prevailing with big data applications, including big data processing in cloud data centers, data delivery, joint optimization, scientific big data architectures and scheduling issues. We show that SDN can manage the network efficiently for improving the performance of big data applications. In addition, we show that big data can benefit SDN as well, including traffic engineering, cross-layer design, defeating security attacks, and SDN-based intra and inter data center networks. Moreover, we discuss a number of open issues that need to be addressed to jointly consider big data and SDN in future research.
Comprehensibility and efficiency of multiview framework for measurement plan design

Understanding the results of measurements is a primary issue for continuous software process improvement. Models provide support for better understanding measures. One of the problems often encountered in defining a measurement plan is its dimensions in terms of goals and metrics. This inevitably impacts on the usability of a measurement plan in terms of effort needed for interpreting the measurement results and accuracy of interpretation itself. The authors validate an approach (multiview framework) for designing a measurement plan, according to the GQM model, and structured in order to improve usability. For this reason an experiment was executed to validate the approach and provide evidence that a GQM designed according to the multiview framework is more usable, and that interpretation depends on the collected measures and is independent of who interprets them. In the experiment the authors verify that a measurement plan designed according to the proposed model doesn't negatively impact on efficiency of interpretation. The experimental results are positive and encourage further replications and studies.
Development of Nanoradiopharmaceuticals by Labeling Polymer Nanoparticles with Tc-99m

Nanomedicine is considered as the future of modern medicine. Hence, serious global efforts are being made for the development of nanopharmaceuticals. Among all the nanopharmaceuticals developed so far, radiopharmaceuticals constitute only a very small portion, as noted in the published literature. The procedures for development of nanoradiopharmaceuticals are complex. In this paper we discuss the results of a research directed at developing nanoradiopharmaceuticals based on three different types of nanopharmaceuticals as alternative drug delivery systems.
A facilitation workshop for the implementation stage : A case study in health care

Research on facilitation in discrete event simulation (DES) is gathering pace but there is still a need to put forward real examples to explain the process to newcomers. Most of the research has focussed on facilitation in the initial stages of the simulation modelling process. In this paper we focus on one of the postmodel coding stages. More specifically we focus on the implementation stage, the final stage in the modelling process. The primary contributions of this paper are the description of the process followed and the introduction of tools that can be used during this stage to support workshop activities. A real case study is provided describing the sequence of the interactions undertaken in the workshop. Extracts from the transcripts are also included, with the view to bringing evidence of the stakeholders’ involvement and their mood during the workshop. The paper concludes with a discussion on the process followed and the importance of using tools in this stage.
Application-level task execution issues in mobile cloud computing

In order to maximize the throughput of computation intensive applications in smartphones; Mobile Cloud Computing (MCC) architecture was introduced in which mobile devices are connected to the adjacent cloud servers for the execution of such applications. Many researchers has been focusing on the division and execution of applications between mobile and cloud; in order to maximize the throughput and minimize the work load on mobile. In this paper we present some of the comparison issues in the augmented execution of applications among cloud and mobile. We conclude this paper with a critical analysis of challenges that have not yet been fully met, and highlight directions for future work.
Tensile and conductivity properties of epoxy composites containing carbon black and graphene nanoplatelets

Adding conductive fillers to an insulating polymer matrix produces composites with unique properties. Varying amounts of carbon black (0.33, 0.67, and 1 wt%) and graphene nanoplatelets (5, 10, 15, and 20 wt%) were added to epoxy. In addition, a few carbon black/graphene nanoplatelet/epoxy formulations were also fabricated. The conductivity and tensile properties were determined and analyzed. The single filler composites containing 5 and 10 wt% graphene nanoplatelet and 0.33 wt% carbon black could be used for electrically insulating applications. Composites containing 15 and 20 wt% graphene nanoplatelet could be used for static dissipative applications. The following composites could be used for semi-conductive applications: 0.67 wt% carbon black/epoxy, 1 wt% carbon black/epoxy, 0.33 wt% carbon black/5 wt% graphene nanoplatelet/epoxy, and 0.33 wt% carbon black/10 wt% graphene nanoplatelet/epoxy. At the 95% confidence level, the combination of 0.33 wt% carbon black with 5 wt% graphene nanoplatelet caused the composite electrical resistivity (1/electrical conductivity) to significantly decrease from ∼1015 ohm-cm to ∼104 ohm-cm. It is likely that the highly branched, high surface area carbon black is forming an electrically conductive network with graphene nanoplatelets. Concerning single filler composites, adding ≤1 wt% carbon black did not significantly lower the composite tensile strain; however, adding graphene nanoplatelet did decrease tensile strain and increase modulus. One possible application for the 10 wt% graphene nanoplatelet/epoxy composite is in Polymer Core Composite Conductors for power transmission lines, which need to be electrically insulating, have improved thermal conductivity (increased from 0.2 to 0.3 W/m-K), increased tensile modulus (increased from 2.7 to 3.3 GPa), and good tensile strength (70 MPa) and strain (3.3%).
Cyanobacterial Toxin Degrading Bacteria: Who Are They?

Cyanobacteria are ubiquitous in nature and are both beneficial and detrimental to humans. Benefits include being food supplements and producing bioactive compounds, like antimicrobial and anticancer substances, while their detrimental effects are evident by toxin production, causing major ecological problems at the ecosystem level. To date, there are several ways to degrade or transform these toxins by chemical methods, while the biodegradation of these compounds is understudied. In this paper, we present a meta-analysis of the currently available 16S rRNA and mlrA (microcystinase) genes diversity of isolates known to degrade cyanobacterial toxins. The available data revealed that these bacteria belong primarily to the Proteobacteria, with several strains from the sphingomonads, and one from each of the Methylobacillus and Paucibacter genera. Other strains belonged to the genera Arthrobacter, Bacillus, and Lactobacillus. By combining the ecological knowledge on the distribution, abundance, and ecophysiology of the bacteria that cooccur with toxic cyanobacterial blooms and newly developed molecular approaches, it is possible not only to discover more strains with cyanobacterial toxin degradation abilities, but also to reveal the genes associated with the degradation of these toxins.
Low-dose computed tomography image restoration using previous normal-dose scan.

PURPOSE In current computed tomography (CT) examinations, the associated x-ray radiation dose is of a significant concern to patients and operators. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) or kVp parameter (or delivering less x-ray energy to the body) as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and the noise would propagate into the CT image if no adequate noise control is applied during image reconstruction. Since a normal-dose high diagnostic CT image scanned previously may be available in some clinical applications, such as CT perfusion imaging and CT angiography (CTA), this paper presents an innovative way to utilize the normal-dose scan as a priori information to induce signal restoration of the current low-dose CT image series. METHODS Unlike conventional local operations on neighboring image voxels, nonlocal means (NLM) algorithm utilizes the redundancy of information across the whole image. This paper adapts the NLM to utilize the redundancy of information in the previous normal-dose scan and further exploits ways to optimize the nonlocal weights for low-dose image restoration in the NLM framework. The resulting algorithm is called the previous normal-dose scan induced nonlocal means (ndiNLM). Because of the optimized nature of nonlocal weights calculation, the ndiNLM algorithm does not depend heavily on image registration between the current low-dose and the previous normal-dose CT scans. Furthermore, the smoothing parameter involved in the ndiNLM algorithm can be adaptively estimated based on the image noise relationship between the current low-dose and the previous normal-dose scanning protocols. RESULTS Qualitative and quantitative evaluations were carried out on a physical phantom as well as clinical abdominal and brain perfusion CT scans in terms of accuracy and resolution properties. The gain by the use of the previous normal-dose scan via the presented ndiNLM algorithm is noticeable as compared to a similar approach without using the previous normal-dose scan. CONCLUSIONS For low-dose CT image restoration, the presented ndiNLM method is robust in preserving the spatial resolution and identifying the low-contrast structure. The authors can draw the conclusion that the presented ndiNLM algorithm may be useful for some clinical applications such as in perfusion imaging, radiotherapy, tumor surveillance, etc.