Miracle-dz/UniFAR-FTUs huggingface dataset:
Photo activation of HPPH encapsulated in “Pocket” liposomes triggers multiple drug release and tumor cell killing in mouse breast cancer xenografts

We recently reported laser-triggered release of photosensitive compounds from liposomes containing dipalmitoylphosphatidylcholine (DPPC) and 1,2 bis(tricosa-10,12-diynoyl)-sn-glycero-3-phosphocholine (DC8,9PC). We hypothesized that the permeation of photoactivated compounds occurs through domains of enhanced fluidity in the liposome membrane and have thus called them “Pocket” liposomes. In this study we have encapsulated the red light activatable anticancer photodynamic therapy drug 2-(1-Hexyloxyethyl)-2-devinyl pyropheophorbide-a (HPPH) (Ex/Em410/670 nm) together with calcein (Ex/Em490/517 nm) as a marker for drug release in Pocket liposomes. A mole ratio of 7.6:1 lipid:HPPH was found to be optimal, with >80% of HPPH being included in the liposomes. Exposure of liposomes with a cw-diode 660 nm laser (90 mW, 0–5 minutes) resulted in calcein release only when HPPH was included in the liposomes. Further analysis of the quenching ratios of liposome-entrapped calcein in the laser treated samples indicated that the laser-triggered release occurred via the graded mechanism. In vitro studies with MDA-MB-231-LM2 breast cancer cell line showed significant cell killing upon treatment of cell-liposome suspensions with the laser. To assess in vivo efficacy, we implanted MDA-MB-231-LM2 cells containing the luciferase gene along the mammary fat pads on the ribcage of mice. For biodistribution experiments, trace amounts of a near infrared lipid probe DiR (Ex/Em745/840 nm) were included in the liposomes. Liposomes were injected intravenously and laser treatments (90 mW, 0.9 cm diameter, for an exposure duration ranging from 5–8 minutes) were done 4 hours postinjection (only one tumor per mouse was treated, keeping the second flank tumor as control). Calcein release occurred as indicated by an increase in calcein fluorescence from laser treated tumors only. The animals were observed for up to 15 days postinjection and tumor volume and luciferase expression was measured. A significant decrease in luciferase expression and reduction in tumor volume was observed only in laser treated animal groups injected with liposomes containing HPPH. Histopathological examination of tumor tissues indicated tumor necrosis resulting from laser treatment of the HPPH-encapsulated liposomes that were taken up into the tumor area.
An Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease Monitoring

New smart technologies and the internet of things increasingly play a key role in healthcare and wellness, contributing to the development of novel healthcare concepts. These technologies enable a comprehensive view of an individual’s movement and mobility, potentially supporting healthy living as well as complementing medical diagnostics and the monitoring of therapeutic outcomes. This overview article specifically addresses smart shoes, which are becoming one such smart technology within the future internet of health things, since the ability to walk defines large aspects of quality of life in a wide range of health and disease conditions. Smart shoes offer the possibility to support prevention, diagnostic work-up, therapeutic decisions, and individual disease monitoring with a continuous assessment of gait and mobility. This overview article provides the technological as well as medical aspects of smart shoes within this rising area of digital health applications, and is designed especially for the novel reader in this specific field. It also stresses the need for closer interdisciplinary interactions between technological and medical experts to bridge the gap between research and practice. Smart shoes can be envisioned to serve as pervasive wearable computing systems that enable innovative solutions and services for the promotion of healthy living and the transformation of health care.
An average John theorem

We prove that the $\frac12$-snowflake of a finite-dimensional normed space $(X,\|\cdot\|_X)$ embeds into a Hilbert space with quadratic average distortion $$O\Big(\sqrt{\log \mathrm{dim}(X)}\Big). $$ We deduce from this (optimal) statement that if an $n$-vertex expander embeds with average distortion $D\geqslant 1$ into $(X,\|\cdot\|_X)$, then necessarily $\mathrm{dim}(X)\geqslant n^{\Omega(1/D)}$, which is sharp by the work of Johnson, Lindenstrauss and Schechtman (1987). This improves over the previously best-known bound $\mathrm{dim}(X)\gtrsim (\log n)^2/D^2$ of Linial, London and Rabinovich (1995), strengthens a theorem of Matou\v{s}ek (1996) which resolved questions of Johnson and Lindenstrauss (1982), Bourgain (1985) and Arias-de-Reyna and Rodr{\'{\i}}guez-Piazza (1992), and answers negatively a question that was posed (for algorithmic purposes) by Andoni, Nguyen, Nikolov, Razenshteyn and Waingarten (2016).
Entanglement Hamiltonians in 1D free lattice models after a global quantum quench

We study the temporal evolution of the entanglement Hamiltonian of an interval after a global quantum quench in free lattice models in one spatial dimension. In a harmonic chain we explore a quench of the frequency parameter. In a chain of free fermions at half filling we consider the evolution of the ground state of a fully dimerised chain through the homogeneous Hamiltonian. We focus on critical evolution Hamiltonians. The temporal evolutions of the gaps in the entanglement spectrum are analysed. The entanglement Hamiltonians in these models are characterised by matrices that provide also contours for the entanglement entropies. The temporal evolution of these contours for the entanglement entropy is studied, also by employing existing conformal field theory results for the semi-infinite line and the quasi-particle picture for the global quench.
Recursive Least M-Estimate based Control Algorithm for Grid Interfaced Solar PV System

This paper deals with a single stage grid interfaced, multifunctional solar photovoltaic (PV) system for (1) feeding the solar PV array power into the grid with improved power quality (PQ) (2) supplying local nonlinear loads, (3) balancing the grid currents (4) providing the harmonics compensation and reactive power compensation. For achieving these functionalities, the voltage source converter of the PV system is controlled using the RLM (Recursive Least M-Estimate) based current control algorithm with FOAANF (Fourth Order Amplitude Adaptive Notch Filter) based voltage filter. This control algorithm makes the convergence of the control fast, and robust under impulsive noise environment, and unbalanced loading condition with grid voltages distortion. Moreover, the proposed RLM based control algorithm offers good steady state and dynamic performances with simple implementation. Experimental results obtained on a developed prototype in the laboratory, have demonstrated the performance of proposed control algorithm with grid currents distortion within the limits of the IEEE-519 standard.
An area-efficient hybrid high-voltage charge pump design for IoT applications

A new hybrid charge pump topology is proposed to achieve high voltage DC supply in a TSMC 0.13 μm BCD technology. The design incorporates a hybrid cross-coupled and serial-parallel topologies which permits the use of MEM capacitors through-out the design and, thus, minimizes the overall area required for the same voltage gain. The paper proposes a new zero-reversion loss cross-coupled charge pump and a new serial-parallel charge pump design to reduce the overall area required for the charge pump by up to 50 % and provides a strong basis for different gain charge pump implementations.
Importance of van der Waals interactions for ab initio studies of topological insulators

We investigate the lattice and electronic structures of the bulk and surface of the prototypical layered topological insulators Bi2Se3 and Bi2Te3 using ab initio density functional methods, and systematically compare the results of different methods of including van der Waals (vdW) interactions. We show that the methods utilizing semi-empirical energy corrections yield accurate descriptions of these materials, with the most precise results obtained by properly accounting for the long-range tail of the vdW interactions. The bulk lattice constants, distances between quintuple layers and the Dirac velocity of the topological surface states (TSS) are all in excellent agreement with experiment. In Bi2Te3, hexagonal warping of the energy dispersion leads to complex spin textures of the TSS at moderate energies, while in Bi2Se3 these states remain almost perfectly helical away from the Dirac point, showing appreciable signs of hexagonal warping at much higher energies, above the minimum of the bulk conduction band. Our results establish a framework for unified and systematic self-consistent first principles calculations of topological insulators in bulk, slab and interface geometries, and provides the necessary first step toward ab initio modeling of topological heterostructures.
Deep Residual Reinforcement Learning

We revisit residual algorithms in both model-free and model-based reinforcement learning settings. We propose the bidirectional target network technique to stabilize residual algorithms, yielding a residual version of DDPG that significantly outperforms vanilla DDPG in the DeepMind Control Suite benchmark. Moreover, we find the residual algorithm an effective approach to the distribution mismatch problem in model-based planning. Compared with the existing TD($k$) method, our residual-based method makes weaker assumptions about the model and yields a greater performance boost.
Validating an extension to participatory heuristic evaluation: quality of work and quality of work life

: We describe an extension and validation of Nielsen’s heuristic evaluation approach, to include “humanistic” aspects of systems. Three additional heuristics addressed quality of work product, quality of work life, and respect for users’ skills. In a participatory heuristic evaluation of an intelligent tutoring system, the three new heuristics performed comparably to earlier sets of heuristics.
Volatile logging in n-fault-tolerant distributed systems

The authors introduce two enhancements to optimistic recovery which allow messages to be logged without performing any I/O to stable storage. The first permits messages to be instantaneously logged in volatile storage, as in the sender-based message logging technique of D.B. Johnson and W. Zwaenepoel (1987), but without their restriction of single-fault-tolerance. The second permits message data and/or message arrival orders not to be logged in circumstances where this information can be reconstructed in other ways. They show that the combination of these two optimizations yields a transparent n-fault-tolerant system which logs to stable storage only those messages received from the outside world and a very small number of additional messages. <<ETX>>
Synthesis and sst2 binding profiles of new [Tyr3]octreotate analogs

One of the main objectives of our current work is the development of new somatostatin analogs that would retain the general characteristics of [Tyr3]octreotate (Tate) while showing potential for clinical application. In this respect, study of their interaction with the sst2 is crucial in providing preliminary structure‐activity relationships data. In the present work we report on the synthesis and the preliminary biological evaluation of a total of 15 new structurally modified [Tyr3]octreotate analogs. The binding affinities were determined during competition binding assays in sst2‐positive rat acinar pancreatic AR4‐2J cell membranes using [125I‐Tyr3]octreotide as the radioligand. Copyright © 2008 European Peptide Society and John Wiley & Sons, Ltd.
An Incentive Mechanism Design for Socially Aware Crowdsensing Services with Incomplete Information

Traditional crowdsensing platforms rely on sensory information collected from a group of independent users or sensors. Recently, socially aware crowdsensing services have been introduced as the integration of social networks and crowdsensing platforms. For example, in health-related crowdsensing applications, a user benefits from information regarding food, exercise, medicine, and medical treatment collected and shared by his/her socially connected friends and family members. In this article, we first introduce basic concepts of socially aware crowdsensing services and highlight the importance of "social network effects" in the services. Typically adopted in social networks, network effects are used to quantify the influence of an action or preference of one user on other users with social ties. With this focus, we then discuss important aspects of socially aware crowdsensing services with network effects and some technical challenges. We find that game theory is a suitable analytical tool to investigate such crowdsensing services, for which important related work is surveyed. To address existing research gaps, we propose a game model for an incentive mechanism design with incomplete information about social network effects in socially aware crowdsensing. The proposed model is shown to improve the benefits of the crowdsensing service provider as well as those of the users.
Analysis and Prevention of Phishing Attacks in Cyber Space

Now-a-days internet become a very unsafe space to deal with. Hackers are constantly trying to gain the user’s personal information, and detailed credentials. So many websites on the internet, even though safe, this safety cannot be assured by all websites. These rule breakers avoid abiding by rules, and try to employ methods like trickery and hacking to gain illegal access to private information. To be able to overcome this problem, we need to first understand the intricacies of how the virus is designed. This paper mainly deals with the analysis of phishing attacks in the cyberspace and any malicious content that is associated with the web, and is carried out within the browser. The files which are downloaded with virus, and involve third party applications from the PC, cannot be checked for virus. For instance, if there is a word file that is downloaded to the PC, it uses apps outside the web in the VM, and hence cannot be controlled by the VM.
School Improvement in New York City: The Evolution of a Project

et al., "Creating effective schools. " Educational Leadership, 1982, 40 (3). 72-73. Venezky, R. L. , & Winfield, L. F. Schools tha t succeed beyond expectations in teaching. (Studies in Education Technical Report No. 1). Newark: University of Delaware, 1979. Wang, M. Evaluating the effectiveness of compensatory education. Paper presented at the annual meeting of American Educa t iona l Research Association, Boston, April 1980. Weber, G. Inner-city children can be taught to read: Four successful schools. Washington, D.C.: Council for Basic Education, 1971. Williams. F. Whitehead, J. L. , & Miller, L. Relations between language att i tudes and teacher expectancy. American Educational Research Journal, 1972, 7, 447-491. Wiley, D. E. , & Harnischfeger, A. Explosion of a myth: Quantity of schooling and exposure to instruction, major educational vehicles. Educational Researcher, 1974,3 (4), 7-12.
Automatic Speaker Recognition System based on Machine Learning Algorithms

Speaker recognition is a technique used to automatically recognize a speaker from a recording of their voice or speech utterance. Speaker recognition technology has improved over recent years and has become inexpensive and and reliable method for person identification and verification. Research in the field of speaker recognition has now spanned over five decades and has shown fruitful results, however there is not much work done with regards to South African indigenous languages. This paper presents the development of an automatic speaker recognition system that incorporates classification and recognition of Sepedi home language speakers. Four classifier models, namely, Support Vector Machines, K-Nearest Neighbors, Multilayer Perceptrons (MLP) and Random Forest (RF), are trained using WEKA data mining tool. Auto-WEKA is applied to determine the best classifier model together with its best hyper-parameters. The performance of each model is evaluated in WEKA using 10-fold cross validation. MLP and RF yielded good accuracy surpassing the state-of-the-art with an accuracy of 97% and 99.9% respectively, the RF model is then implemented on a graphical user interface for development testing.
Intra-Articular Corticosteroids in Addition to Exercise for Reducing Pain Sensitivity in Knee Osteoarthritis: Exploratory Outcome from a Randomized Controlled Trial

Objective To assess the effects of one intra-articular corticosteroid injection two weeks prior to an exercise-based intervention program for reducing pain sensitivity in patients with knee osteoarthritis (OA). Design Randomized, masked, parallel, placebo-controlled trial involving 100 participants with clinical and radiographic knee OA that were randomized to one intra-articular injection on the knee with either 1 ml of 40 mg/ml methylprednisolone (corticosteroid) dissolved in 4 ml lidocaine (10 mg/ml) or 1 ml isotonic saline (placebo) mixed with 4 ml lidocaine (10 mg/ml). Two weeks after the injections all participants undertook a 12-week supervised exercise program. Main outcomes were changes from baseline in pressure-pain sensitivity (pressure-pain threshold [PPT] and temporal summation [TS]) assessed using cuff pressure algometry on the calf. These were exploratory outcomes from a randomized controlled trial. Results A total of 100 patients were randomized to receive either corticosteroid (n = 50) or placebo (n = 50); 45 and 44, respectively, completed the trial. Four participants had missing values for PPT and one for TS at baseline; thus modified intention-to-treat populations were analyzed. The mean group difference in changes from baseline at week 14 was 0.6 kPa (95% CI: -1.7 to 2.8; P = 0.626) for PPT and 384 mm×sec (95% CI: -2980 to 3750; P = 0.821) for TS. Conclusions These results suggest that adding intra-articular corticosteroid injection 2 weeks prior to an exercise program does not provide additional benefits compared to placebo in reducing pain sensitivity in patients with knee OA. Trial Registration EU clinical trials (EudraCT): 2012-002607-18
S-parameter calibration procedure for multiport microwave imaging systems

Multitude of antennas are typically used in microwave imaging systems. Here we outline a simple and effective calibration method for multiport imaging systems. By using only one additional component, an electronic calibration module (ECal), one port is calibrated and the calibration plane is thereby moved to the antenna connector. Assuming all antennas interact with the test phantom in the same way, the one-port calibration is transferred to all other antennas. For full calibration including the transmission path between antennas, the unknown thru technique is used. This calibration procedure is simple and it can be fully automated, and no RF components are perturbed.
Learning Task Models from Multiple Human Demonstrations

In this paper, we present a novel method for learning robot tasks from multiple demonstrations. Each demonstrated task is decomposed into subtasks that allow for segmentation and classification of the input data. The demonstrated tasks are then merged into a flexible task model, describing the task goal and its constraints. The two main contributions of the paper are the state generation and contraints identification methods. We also present a task level planner, that is used to assemble a task plan at run-time, allowing the robot to choose the best strategy depending on the current world state
LGI1 and LGI4 bind to ADAM22, ADAM23 and ADAM11

The transmembrane protein ADAM22 is expressed at high levels in the brain. From its molecular structure, ADAM22 is thought to be an adhesion molecule or a receptor because it has functional disintegrin-like and cysteine-rich sequences in its ectodomain. The phenotypic analysis of ADAM22-deficient mice has indicated the important roles played by ADAM22 in proper neuronal function and peripheral nerve development, however, the precise molecular function of ADAM22 is still unknown. To understand the function of ADAM22 on a molecular basis, we identified ADAM22 binding proteins by using immunoprecipitation and mass spectrometric analysis. This analysis revealed that Leucine-rich glioma inactivated 1 (LGI1) is the most potent ADAM22 binding protein in mouse brain. By our quantitative cell-ELISA system, we demonstrated the specific binding of LGI1 with ADAM22. Furthermore, we showed that LGI4, a putative ADAM22 ligand, also bound to ADAM22. Characterization of the binding specificity of LGI1 and LGI4 suggested that ADAM22 is not a sole receptor, because ADAM11 and ADAM23 had a significant binding ability to LGI1 or LGI4. Therefore, LGI-ADAM system seems to be regulated not only by the affinity but also by the cell-type-specific expression of each protein. Our findings provide new clues to understand the functions of LGI1 and LGI4 as an ADAMs ligand.
Mapping Exceptions to High-Level Source Code on a Heterogeneous Architecture

Network packet processing architectures use heterogeneous processors as accelerators to speed-up classic application domain tasks. Our platform compiles applications to bytecodes for a generalized packet processing machine, then uses microcoded interpreters running in parallel to trigger accelerators as needed. To make the system effective re-quires helping users debug apps, which includes tracking runtime exceptions. Exception tracking is complicated when a system-thrown exception is detected on an accelerator and the current binary form is far removed from the original high-level language source or associated assembly code. We tackle this problem by (1) instrumenting the compiler and a low-level bytecode tool, (2) reporting exceptions with the interpreter, (3) creating a specialized tool to collate the higher-level program forms with the lower-level bytecode forms. This functionality provides data needed for post-mortem program analysis.