Miracle-dz/UniFAR-FTUs huggingface dataset:
Packaging biological cargoes in mesoporous materials: opportunities for drug delivery

Introduction: Confinement of biomolecules in structured nanoporous materials offers several desirable features ranging from chemical and thermal stability, to resistance to degradation from the external environment. A new generation of mesoporous materials presents exciting new possibilities for the formulation and controlled release of biological agents. Such materials address niche applications in enteral and parenteral delivery of biologics, such as peptides, polypeptides, enzymes and proteins for use as therapeutics, imaging agents, biosensors, and adjuvants. Areas covered: Mesoporous silica Santa Barbara Amorphous-15 (SBA-15), with its unique, tunable pore diameter, and easily functionalized surface, provides a representative example of this new generation of materials. Here, we review recent advances in the design and synthesis of nanostructured mesoporous materials, focusing on SBA-15, and highlight opportunities for the delivery of biological agents to various organ and tissue compartments. Expert opinion: The SBA-15 platform provides a delivery carrier that is inherently separated from the active biologic due to distinct intra and extra-particle environments. This permits the SBA-15 platform to not require direct modification of the active biological therapeutic. Additionally, this makes the platform universal and allows for its application independent of the desired methods of discovery and development. The SBA-15 platform also directly addresses issues of targeted delivery and controlled release, although future challenges in the implementation of this platform reside in particle design, biocompatibility, and the tunability of the internal and external material properties. Examples illustrating the flexibility in the application of the SBA-15 platform are also discussed.
Color Graphs for Automated Cancer Diagnosis and Grading

This paper reports a new structural method to mathematically represent and quantify a tissue for the purpose of automated and objective cancer diagnosis and grading. Unlike the previous structural methods, which quantify a tissue considering the spatial distributions of its cell nuclei, the proposed method relies on the use of distributions of multiple tissue components for the representation. To this end, it constructs a graph on multiple tissue components and colors its edges depending on the component types of their endpoints. Subsequently, it extracts a new set of structural features from these color graphs and uses these features in the classification of tissues. Working with the images of colon tissues, our experiments demonstrate that the color-graph approach leads to 82.65% test accuracy and that it significantly improves the performance of its counterparts.
Applying p-cycles to multi-service photonic network

The paper discusses issues related to the support of the p-cycles concept in the multiservice photonic network (MSPN), with the emphasis on the design issues. Design procedure is based on general heuristic search techniques such as genetic algorithm. Performance measures have been defined to evaluate the solution quality. The design procedure has been applied to the Pan European topology, with the analysis of obtained p-cycle protection performance results.
Nucleic Acids Research

A series of restriction fragment length polymorphisms which are due to DNA rearrangements have been identified within two highly variable regions flanking the human a globin genes. The existence of such hiahly polymorphic areas provides a large number of individual genetic markers for the a globin gene cluster on chromosome 16. If, as seems likely, such regions occur frequently throughout the human genome they should be of considerable value in the antenatal diagnosis of genetic disease.
The Life and Work of Marvin Kenneth Simon

It is a measure of the importance and profundity of Marvin Kenneth Simon’s contributions to communication theory that a tribute article and tutorial about his life and work is of current research relevance in spite of the continually accelerating rate of evolution in this area. Marv, as the entire community affectionately knew him, was one of the most prolific and influential communications researchers of his generation. Moreover, he laid the foundation for many of the techniques used in communication systems today. Marv’s death on September 23, 2007 continues to engender pangs not only of sadness at the passing of a great friend to many in our community, but also of regret that he is no longer with us to help in resolving the many challenges facing communication systems today.
Effects of carbon nanotube and conducting polymer coated microelectrodes on single-unit recordings in vitro

Neuronal networks cultured on microelectrode arrays (MEAs) have been utilized as biosensors that can detect all or nothing extracellular action potentials, or spikes. Coating the microelectrodes with carbon nanotubes (CNTs), either pristine or conjugated with a conductive polymer, has been previously reported to improve extracellular recordings presumably via reduction in microelectrode impedance. The goal of this work was to examine the basis of such improvement in vitro. Every other microelectrode of in vitro MEAs was electrochemically modified with either conducting polymer, poly-3,4-ethylenedioxythiophene (PEDOT) or a blend of CNT and PEDOT. Mouse cortical tissue was dissociated and cultured on the MEAs to form functional neuronal networks. The performance of the modified and unmodified microelectrodes was evaluated by activity measures such as spike rate, spike amplitude, burst duration and burst rate. We observed that the yield, defined as percentage of microelectrodes with neuronal activity, was significantly higher by 55% for modified microelectrodes compared to the unmodified sites. However, the spike rate and burst parameters were similar for modified and unmodified microelectrodes suggesting that neuronal networks were not physiologically altered by presence of PEDOT or PEDOT-CNT. Our observations from immunocytochemistry indicated that neuronal cells were more abundant in proximity to modified microelectrodes.
Word boundary agreementto combine multi-microphone hypotheses in distant speech recognition

In this paper we propose a technique for combining hypotheses generated in a multi-microphone setting, which exploits complementarity and collective agreement among ASR outputs of different channels. The technique draws upon the information encoded in the available set of word lattices. As a first step, we identify word boundaries in which a comprehensive inter-channel agreement is found; then, these boundaries are used to reduce the global hypothesis search space. Global word posterior probabilities are estimated for the candidate words associated to each of the bounded segments. As a result, a single combined confusion network is generated from the multiple lattices. This approach offers a novel perspective to state of the art solutions based on confusion network combination. Promising results were obtained from an experimental evaluation in a simulated domestic environment equipped with a distributed microphone network. The development and test sets were simulated using real impulse responses estimated for a large set of microphone-speaker position pairs.
Goal Babbling Permits Direct Learning of Inverse Kinematics

We present an approach to learn inverse kinematics of redundant systems without prior- or expert-knowledge. The method allows for an iterative bootstrapping and refinement of the inverse kinematics estimate. The essential novelty lies in a path-based sampling approach: we generate training data along paths, which result from execution of the currently learned estimate along a desired path towards a goal. The information structure thereby induced enables an efficient detection and resolution of inconsistent samples solely from directly observable data. We derive and illustrate the exploration and learning process with a low-dimensional kinematic example that provides direct insight into the bootstrapping process. We further show that the method scales for high dimensional problems, such as the Honda humanoid robot or hyperredundant planar arms with up to 50 degrees of freedom.
Symboliccsubsymbolic Sentence Analysis: Exploiting the Best of Two W Orlds 1

Despite some recent speculations about the changing methodological styles in arti cial intelligence, it is still possible to learn something by writing exploratory computer programs. This is especially true when a new processing technique or synthesis of di erent techniques is being attempted for the rst time. In this spirit, we have designed and implemented a conceptual sentence analyzer, CIRCUS, which integrates three distinct information processing architectures.
OMNI: OpenFlow MaNagement Infrastructure

Managing computer networks is challenging because of the numerous monitoring variables and the difficulty to autonomously configure network parameters. This paper presents the OpenFlow MaNagement Infrastructure (OMNI), which helps the administrator to control and manage OpenFlow networks by providing remote management based on a web interface. OMNI provides flow monitoring and dynamic flow configuration through a service-oriented architecture. OMNI also offers an Application Programming Interface (API) for collecting data and configuring the OpenFlow network. We propose a multi-agent system based on OMNI API that reduces packet loss rates. We evaluate both the OMNI management applications and the multi-agent system performance using a testbed. Our results show that the multi-agent system detects and reacts to a packet-loss condition in less than three monitoring intervals.
Mechanical Properties of Metal Matrix Nanocomposites Synthesized by Selective Laser Melting Measured by Depth Sensing Indentation Technique

This work presents an investigation of basic mechanical properties (hardness, Young modulus) of metal matrix composites (MMC) reinforced with non-oxide ceramic nanoparticles by means of nanoindentation measurements. The evaluated materials were manufactured by selective laser melting (SLS/M). As a matrix 316L stainless steel and as a reinforcing phase TiC nanoparticles were used. The influence of nanoscale reinforcement on the mechanical properties of MMC manufacturing with SLS/M process was examined. In this case statistical evaluation of hardness and Young modulus based on nanoindentation data was performed.
A journey from reductionist to systemic cell biology aboard the schooner Tara

In this essay I describe my personal journey from reductionist to systems cell biology and describe how this in turn led to a 3-year sea voyage to explore complex ocean communities. In describing this journey, I hope to convey some important principles that I gleaned along the way. I realized that cellular functions emerge from multiple molecular interactions and that new approaches borrowed from statistical physics are required to understand the emergence of such complex systems. Then I wondered how such interaction networks developed during evolution. Because life first evolved in the oceans, it became a natural thing to start looking at the small organisms that compose the plankton in the world's oceans, of which 98% are … individual cells—hence the Tara Oceans voyage, which finished on 31 March 2012 in Lorient, France, after a 60,000-mile around-the-world journey that collected more than 30,000 samples from 153 sampling stations.
An Innovative and Low-Cost Industrial Flow for Reliability Characterization of SoCs

This paper describes a novel approach to enhance the process of reliability characterization for VLSI SoC products. To do this, we exploit Design for Test and Diagnosis structures in combination with new low-cost tester features and architecture. The main focus of our work is to obtain a modeling of the degradation of selected parameters measurable through at-speed testing. The paper reviews the current approach for reliability characterization and shows the achieved enhancement on efficiency and effectiveness. Results shown are related to experiments run on a vehicle released on a 90 nm technology.
Low complexity implementation of per-survivor processing for carrier-phase tracking in uncertain environments

Performance of Maximum Likelihood Sequence Estimation (MLSE) in receivers highly depends on the reliability of the channel parameters estimation. Traditionally, the channel parameters are estimated based on the tentative decisions before the MLSE detector. Per-survivor Processing (PSP) technique, as compared to traditional Viterbi algorithm, was shown to improve the performance of MLSE in uncertain environments. The PSP technique mainly comes from the idea that the estimation of unknown channel parameters can be embedded into the Viterbi decoder. The higher performance of the technique is achieved at the expense of higher complexity. In this paper we introduce a modification to the PSP algorithm to reduce the number of per-survivors and therefore the associated parameter updating modules. This modification was shown to lower the implementation complexity of the algorithm while keeping the performance at an acceptable level. The performance of phase tracking based on the PSP technique was also compared to traditional phase trackers through simulation.
Ternary superconductor "NbTiTa" for high field superfluid magnets

The possibility of obtaining a higher Hc/sub 2/ upper critical field in the NbTi system, which is normally limited by a spin-orbit coupling term, is discussed. The introduction of scattering reduces this coupling, The spin-orbit scattering rate is proportional to Z/sup 4/ and therefore leads logically to the introduction of a high-atomic-number element which is more or less similar with respect to all element which is more or less similar with respect to all of the other properties, i.e. T/sub c/. Previous studies have shown tantalum to be an excellent choice. In the present work, an attempt to obtain a high-current-density, high-field ternary magnet conductor (J/sub c/ (10T, 2 K, rho /sub eff/=10/sup -12/ Omega -cm))>2000 A/mm/sup 2/ is reported. This goal was met, but the conductor was clearly not optimized. >
Monitoring and organizational-level adaptation of multi-agent systems

Static organizational structures are not always suited for large-scale open multi-agent systems. On the other hand, emergent organizational structures may lead to undesirable behavior despite agent-level adaptation. We thus propose a new adaptive multi-agent architecture with both agent-level and organization-level adaptation. The global-level adaptation is based on the monitoring of the systemýs behavior and the dynamic reification of an organizational structure. This structure is used to prevent or detect undesirable behavior and take the required corrective actions. This architecture is applied to fault-tolerant multi-agent systems.
Risk-Driven Revision of Requirements Models

Requirements incompleteness is often the result of unanticipated adverse conditions which prevent the software and its environment from behaving as expected. These conditions represent risks that can cause severe software failures. The identification and resolution of such risks is therefore a crucial step towards requirements completeness. Obstacle analysis is a goal-driven form of risk analysis that aims at detecting missing conditions that can obstruct goals from being satisfied in a given domain, and resolving them. This paper proposes an approach for automatically revising goals that may be under-specified or (partially) wrong to resolve obstructions in a given domain. The approach deploys a learning-based revision methodology in which obstructed goals in a goal model are iteratively revised from traces exemplifying obstruction and non-obstruction occurrences. Our revision methodology computes domain-consistent, obstruction-free revisions that are automatically propagated to other goals in the model in order to preserve the correctness of goal models whilst guaranteeing minimal change to the original model. We present the formal foundations of our learning-based approach, and show that it preserves the properties of our formal framework. We validate it against the benchmarking case study of the London Ambulance Service.
An Implementation of Artificial Emotion Based on Fuzzy State Machine

This article focuses on how to implement Artificial Emotion for virtual reality applications with Fuzzy State Machine, and revisits the OCC emotion model. We discuss the features of human emotions and FuSM. An FuSM can deal with multi-emotions simultaneously, so we can use FuSM in our implementation to simulate emotions and control character behaviors. And the results of experiments show that we can use FuSM to create artificial emotional characters with high believability.
A hybrid KNN-LR classifier and its application in customer churn prediction

This paper presents a hybrid approach for building a binary classifier. The approach is the combination of the k-nearest neighbor algorithm, handling separately m 1-dimensional data sets divided from a data set in m-dimension, and the logistic regression method. This hybrid KNN-LR classifier improves the performance of the logistic regression in classification accuracy in some situations where the predictor and target variables exhibit complex nonlinear relationships. The results of the experiment on four benchmark data sets show the proposed approach compares favorably with the well-known classification algorithms such as C4.5 and RBF. Furthermore, its effectiveness is illustrated by its application in customer churn prediction based on real-world customer data sets.
Antenatal diagnosis of the congenital craniopharyngioma

Summary Background: Craniopharyngioma is a rare fetal and neonatal tumor. Case Report: We report a case of a congenital craniopharyngioma diagnosed by prenatal magnetic resonance. This diagnosis was confirmed by postnatal MR imaging, neurosurgical treatment and histopathological examination. Conclusions: Outcome of neonatal craniopharyngioma is very poor, even if radical surgery is performed. The main problems are pituitary insufficiency, diabetes insipidus, and visual disturbance.
Introducing Intelligent Agents Potential into a competent Integral Multi-Agent Sensor Network Simulation Architecture Design

During this research we spot several key issues concerning WSN design process and how to introduce intelligence in the motes. Due to the nature of these networks, debugging after deployment is unrealistic, thus an efficient testing method is required. WSN simulators perform the task, but still code implementing mote sensing and RF behaviour consists of layered and/or interacting protocols that for the sake of designing accuracy are tested working as a whole, running on specific hardware. Simulators that provide cross layer simulation and hardware emulation options may be regarded as the last milestone of the WSN design process. Especially mechanisms for introducing intelligence into the WSN decision making process but in the simulation level is an important aspect not tackled so far in the literature at all. The herein proposed multi-agent simulation architecture aims at designing a novel WSN simulation system independent of specific hardware platforms but taking into account all hardware entities and events for testing and analysing the behaviour of a realistic WSN system. Moreover, the design herein outlined involves the basic mechanisms, with regards to memory and data management, towards Prolog interpreter implementation in the simulation level.
DESIGN ISSUES AND REQUIREMENTS OF A GENERAL PURPOSE DESKTOP HAPTIC INTERFACE

Haptics is a complement to visual and auditory perception for a more complete experience of being in an environment, be it real, remote, or virtual. Haptic interface allows users to interact with the environment through touch or manipulation. Many of these devices have been built in the recent years. This paper reviews the design requirements of a haptic device in pursuit of a haptic interface that provides a more realistic sensation to the user. Two popular haptic devices: the PHANToM and the DELTA haptic devices are discussed.
Genetic Changes to a Transcriptional Silencer Element Confers Phenotypic Diversity within and between Drosophila Species

The modification of transcriptional regulation has become increasingly appreciated as a major contributor to morphological evolution. However, the role of negative-acting control elements (e.g. silencers) in generating morphological diversity has been generally overlooked relative to positive-acting “enhancer” elements. The highly variable body coloration patterns among Drosophilid insects represents a powerful model system in which the molecular alterations that underlie phenotypic diversity can be defined. In a survey of pigment phenotypes among geographically disparate Japanese populations of Drosophila auraria, we discovered a remarkable degree of variation in male-specific abdominal coloration. In testing the expression patterns of the major pigment-producing enzymes, we found that phenotypes uniquely correlated with differences in the expression of ebony, a gene required for yellow-colored cuticle. Assays of ebony’s transcriptional control region indicated that a lightly pigmented strain harbored cis-regulatory mutations that caused correlated changes in its expression. Through a series of chimeric reporter constructs between light and dark strain alleles, we localized function-altering mutations to a conserved silencer that mediates a male-specific pattern of ebony repression. This suggests that the light allele was derived through the loss of this silencer’s activity. Furthermore, examination of the ebony gene of D. serrata, a close relative of D. auraria which secondarily lost male-specific pigmentation revealed the parallel loss of this silencer element. These results demonstrate how loss-of-function mutations in a silencer element resulted in increased gene expression. We propose that the mutational inactivation of silencer elements may represent a favored path to evolve gene expression, impacting morphological traits.
Repurposing Drugs in Oncology (ReDO)—nitroglycerin as an anti-cancer agent

Nitroglycerin (NTG), a drug that has been in clinical use for more than a century, has a range of actions which make it of particular interest in an oncological setting. It is generally accepted that the main mechanism of action of NTG is via the production of nitric oxide (NO), which improves cardiac oxygenation via multiple mechanisms including improved blood flow (vasodilation), decreased platelet aggregation, increased erythrocyte O2 release and decreased mitochondrial utilization of oxygen. Its vasoactive properties mean that it has the potential to exploit more fully the enhanced permeability and retention effect in delivering anti-cancer drugs to tumour tissues. Moreover NTG can reduce HIF-1α levels in hypoxic tumour tissues and this may have anti-angiogenic, pro-apoptotic and anti-efflux effects. Additionally NTG may enhance anti-tumour immunity. Pre-clinical and clinical data on these anti-cancer properties of NTG are summarised and discussed. While there is evidence of a positive action as a monotherapy in prostate cancer, there are mixed results in NSCLC where initially positive results have yet to be fully replicated. Based on the evidence presented, a case is made that further exploration of the clinical benefits that may accrue to cancer patients is warranted. Additionally, it is proposed that NTG may synergise with a number of other drugs, including other repurposed drugs, and these are discussed in the supplementary material appended to this paper.