Miracle-dz/UniFAR-FTUs huggingface dataset:
Size-tunable drug-delivery capsules composed of a magnetic nanoshell

Nano-sized FePt capsules with two types of ultrathin shell were fabricated using a template method for use in a nano-scale drug delivery system. One capsule was composed of an inorganic-organic hybrid shell of a water-soluble polymer and FePt nanoparticles, and the other capsule was composed of a network of fused FePt nanoparticles. We demonstrated that FePt nanoparticles selectively accumulated on the polymer molecules adsorbed on the template silica particles, and investigated the morphologies of the particle accumulation by changing the concentration of the polymer solution with which the template particles were treated. Capsular size was reduced from 340 to less than 90 nm by changing the size of the silica template particles, and the shell thickness was controlled by changing the amount of FePt nanoparticles adsorbed on the template particles. The hybrid shell was maintained by the connection of FePt nanoparticles and polymer molecules, and the shell thickness was 10 nm at the maximum. The FePt network shell was fabricated by hydrothermal treatment of the FePt/polymer-modified silica composite particles. The FePt network shell was produced from only the FePt alloy, and the shell thickness was 3 nm. Water-soluble anti-cancer drugs could be loaded into the hollow space of FePt network capsules, and lipid-coated FePt network capsules loaded with anti-cancer drugs showed cellular toxicity. The nano-sized capsular structure and the ultrathin shell suggest applicability as a drug carrier in magnetically guided drug delivery „systems.
Fastpass

An ideal datacenter network should provide several properties, including low median and tail latency, high utilization (throughput), fair allocation of network resources between users or applications, deadline-aware scheduling, and congestion (loss) avoidance. Current datacenter networks inherit the principles that went into the design of the Internet, where packet transmission and path selection decisions are distributed among the endpoints and routers. Instead, we propose that each sender should delegate control---to a centralized arbiter---of when each packet should be transmitted and what path it should follow. This paper describes Fastpass, a datacenter network architecture built using this principle. Fastpass incorporates two fast algorithms: the first determines the time at which each packet should be transmitted, while the second determines the path to use for that packet. In addition, Fastpass uses an efficient protocol between the endpoints and the arbiter and an arbiter replication strategy for fault-tolerant failover. We deployed and evaluated Fastpass in a portion of Facebook's datacenter network. Our results show that Fastpass achieves high throughput comparable to current networks at a 240x reduction is queue lengths (4.35 Mbytes reducing to 18 Kbytes), achieves much fairer and consistent flow throughputs than the baseline TCP (5200x reduction in the standard deviation of per-flow throughput with five concurrent connections), scalability from 1 to 8 cores in the arbiter implementation with the ability to schedule 2.21 Terabits/s of traffic in software on eight cores, and a 2.5x reduction in the number of TCP retransmissions in a latency-sensitive service at Facebook.
A Hypervisor for MIPS-Based Architecture Processors - A Case Study in Loongson Processors

Loongson is a family of general purpose processors based on MIPS architecture designed and manufactured in Mainland China. With the maturity of Loongson CPUs, applications are widely available with the increasing development of software tools and hardware platforms by research teams in academia and industry. In recent years, products based on Loongson have been mainly used in education, personal computers and server systems. Meanwhile, it is not yet popularly used in industrial real-time control fields, so such products have large room and potential to further development and deployment. The M-Hyper visor discussed in this paper is a real-time hyper visor designed for MIPS architecture and implemented in Loongson2F processor. It is based on the management program of para-virtualization whilst multiple partitions are scheduled to execute according to their priorities. The design and implementation of M-Hyper visor is discussed, along with details as timer, interrupts, memory management, partition loading and scheduling, to enrich real-time virtualized applications for MIPS architecture. Evaluation results show the performance and viability of proposed design, being promising to new deployments.
An integrated statistical model for multimedia evidence combination

Given the rich content-based features of multimedia (e.g., visual, text, or audio) and the development of various approaches to automatic detectors (e.g., SVM, Adaboost, HMM or GMM, etc), can we find an efficient approach to combine these evidences? In the paper, we address this issue by proposing an Integrated Statistical Model (ISM) to combine diverse evidences extracted from the domain knowledge of detectors, the intrinsic structure of modality distribution and inter-concept associations. The ISM provides a unified framework for evidence fusion, having the following unique advantages: 1) the intrinsic modes in the modality distribution are discovered and modeled by a generative model; 2) each mode is a partial description of structure of the modality and the mode configuration, i.e. a set of modes, and is a new representation of the document content; 3) mode discrimination is automatically learned; 4) prior knowledge such as detector correlations and inter-concept relations can be explicitly described and integrated. More importantly, an efficient pseudo-EM algorithm is realized for training the statistical model. The learning algorithm relaxes the computational cost due to the normalized factor and latent variables in the graphical model. We evaluate system performance of our multimedia semantic concept detection with the TRECVID 2005 development dataset, in terms of efficiency and capacity. Our experimental results demonstrate that the ISM fusion outperforms the SVM based discriminative fusion method.
Factors Affecting Employees' Organizational Commitment-A Study of Banking Staff in Ho Chi Minh City, Vietnam

Commitment-based organizations believe that staff's organizational commitment contributes to workforce stability and better customer service, hence increase business performance. This study explores the factors affecting employees' organizational commitment in banks in Ho Chi Minh City, the biggest commercial city in Vietnam. A quantitative survey of 201 banking staff in 11 banks in this city, selected according to convenience sampling method, confirmed the impact of a set of high-performance human resources managerial practices on staff's organizational commitment. The study also indicated job satisfaction as a pathway to bridge this set with organization commitment. The pathway from human resources practices to organizational commitment, mediated by job satisfaction, has never been statistically tested in banks in Vietnam before. The findings again recommend commitment-based organizations continue and reinforce organizational support for their staff. 
Robust equilibria under non-common priors

This paper considers the robustness of equilibria to a small amount of incomplete information, where players are allowed to have heterogenous priors. An equilibrium of a complete information game is robust to incomplete information under non-common priors if for every incomplete information game where each player's prior puts high probability on the event that the players know at arbitrarily high order that the payoffs are given by the complete information game, there exists a Bayesian Nash equilibrium that generates behavior close to the equilibrium in consideration. It is shown that for generic games, an equilibrium is robust under non-common priors if and only if it consists of the unique rationalizable action profile. Set valued concepts are also introduced, and for generic games, a smallest robust set is shown to exist and coincide with the set of a posteriori equilibria.
Investigation of antibacterial, acid and bile tolerance properties of lactobacilli isolated from Koozeh cheese

Lactobacillus strains are a major part of the probiotics, microflora of the intestine and of fermented dairy products, and are found in a variety of environments. The aim of this study was to find out the ability of bile and acid tolerance and antibacterial properties of the twenty eight isolates of three group lactobacilli namely Lactobacillus plantarum, Lactobacillus casei and Lactobacillus delbruki. For this purpose Twenty eight different Lactobacillus strains that isolated from Koozeh cheese as a traditional cheese were screened. The acid tolerance test was studied under pH 2.0 and 3.0 with 7.5 as control. The cell count for the acid tolerance test was obtained at an interval of 0, 1, 2 and 3 hours respectively and was pour plated on Man, Rogosa, and Sharpe (MRS) agar to be incubated at 37 °C for 24 hours. All cells were selected for bile tolerance test in MRS broth containing bile concentrations of 0% as control and 0.3% as test. Then cell counts were enumerated after 24 hours of incubation on MRS agar. Results showed twenty seven isolates did not have ability to tolerate acid and bile salts and antimicrobial activity against four indicator bacteria included Eshirichia coli, Listeria monocytogenesis, bacillus cereus, Salmonella entritidis. Only one Isolate namely Lactobacillus casei could tolerate acid and bile salt and had antibacterial activity against of L. monocytogenesis. Therefore we can consider this strain as a native probiotic but extra examinations was required.
Structure Learning on Large Scale Common Sense Statistical Models of Human State

Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined and preexisting common sense data and traditional probabilistic machine learning techniques to improve recognition of the state of everyday human life. In this paper, we demonstrate effective techniques for structure learning on graphical models designed for this domain, improving the SRCS system of (Pentney et al. 2006) by learning additional dependencies between variables. Because the models used for common sense reasoning typically involve a large number of variables, issues of scale arise in searching for additional dependencies; we discuss how we use data mining techniques to address this problem. We show experimentally that these techniques improve the accuracy of state prediction, and that, with a good prior model, the use of a common sense model with structure learning provides better prediction of unlabeled variables as well as labeled variables. The results also demonstrate that it is possible to collect new common sense information about daily life using such a statistical model and labeled data.
Managing the storage and battery resources in an image capture device (digital camera) using dynamic transcoding

Advances in hardware imaging technology and user demand for convenient mobile electronic image capture are fueling the development of inexpensive image capture devices that can acquire images rivaling the image quality of photographic film. Improvements in the hardware imaging technology have to be matched with intelligent image storage mechanisms that are aware of local storage and battery constraints. In this paper, we explore using a dynamic, informed image transcoding technique to manage the consumed battery and storage resources in digital cameras. Such application aware technologies are fundamental for the mass consumer acceptance of these newer digital technologies. We show that this technique can allow the camera to store an order of magnitude more images. For a moderate number of images (e.g. 40), transcoding techniques can also maintain high quality images. The availability of fast wireless networks can allow the camera to capture 58 high quality images (51 uploaded) before running out of battery power. Storage technologies with expensive read and write operations (such as micro disks) can have a minor negative impact on battery life because of the extra read and write operations associated with transcoding operations. We show that the ability to effectively communicate the power vs. size vs. quality tradeoff to the end user is important for applications to adapt to the prevailing operating conditions.
Supplementation of T3 Recovers Hypothyroid Rat Liver Cells from Oxidatively Damaged Inner Mitochondrial Membrane Leading to Apoptosis

Hypothyroidism is a growing medical concern. There are conflicting reports regarding the mechanism of oxidative stress in hypothyroidism. Mitochondrial oxidative stress is pivotal to thyroid dysfunction. The present study aimed to delineate the effects of hepatic inner mitochondrial membrane dysfunction as a consequence of 6-n-propyl-2-thiouracil-induced hypothyroidism in rats. Increased oxidative stress predominance in the submitochondrial particles (SMP) and altered antioxidant defenses in the mitochondrial matrix fraction correlated with hepatocyte apoptosis. In order to check whether the effects caused by hypothyroidism are reversed by T3, the above parameters were evaluated in a subset of T3-treated hypothyroid rats. Complex I activity was inhibited in hypothyroid SMP, whereas T3 supplementation upregulated electron transport chain complexes. Higher mitochondrial H2O2 levels in hypothyroidism due to reduced matrix GPx activity culminated in severe oxidative damage to membrane lipids. SMP and matrix proteins were stabilised in hypothyroidism but exhibited increased carbonylation after T3 administration. Glutathione content was higher in both. Hepatocyte apoptosis was evident in hypothyroid liver sections; T3 administration, on the other hand, exerted antiapoptotic and proproliferative effects. Hence, thyroid hormone level critically regulates functional integrity of hepatic mitochondria; hypothyroidism injures mitochondrial membrane lipids leading to hepatocyte apoptosis, which is substantially recovered upon T3 supplementation.
Optimal Popov controller analysis and synthesis for systems with real parameter uncertainties

Robust performance analysis plays an important role in the design of controllers for uncertain multivariable systems. Recent research has investigated the use of absolute stability criteria to develop less conservative analysis tests for systems with linear and nonlinear real parameter uncertainties. This note extends previous work on optimal /spl Hscr/2 performance analysis using the Popov criterion by presenting a numerical homotopy algorithm that can be used to analyze systems with less restrictive assumptions on the structure of the uncertainty block. The technique is used to compare relative robustness capabilities of the various control algorithms that have been designed for the Middeck active control experiment (MACE). The analysis is combined with the previously presented Popov controller synthesis to yield compensators that guarantee robust performance for systems with real parameter uncertainty.
Exploiting device mismatch in neuromorphic VLSI systems to implement axonal delays

Axonal delays are used in neural computation to implement faithful models of biological neural systems, and in spiking neural networks models to solve computationally demanding tasks. While there is an increasing number of software simulations of spiking neural networks that make use of axonal delays, only a small fraction of currently existing hardware neuromorphic systems supports them. In this paper we demonstrate a strategy to implement temporal delays in hardware spiking neural networks distributed across multiple Very Large Scale Integration (VLSI) chips. This is achieved by exploiting the inherent device mismatch present in the analog circuits that implement silicon neurons and synapses inside the chips, and the digital communication infrastructure used to configure the network topology and transmit the spikes across chips. We present an example of a recurrent VLSI spiking neural network that employs axonal delays and demonstrate how the proposed strategy efficiently implements them in hardware.
Common Adult Stem Cells in the Human Breast Give Rise to Glandular and Myoepithelial Cell Lineages: A New Cell Biological Concept

Breast biology and pathology are currently shaped by the two-cell concept that recognizes only glandular and myoepithelial cells. In the present study, we have visualized a previously unidentified cell population within the epithelial compartment of the breast, which displays the phenotypic characteristics of a committed stem cell.Immunofluorescence double labeling with digital image processing and Western blotting were applied to normal breast tissue as well as to noninvasive and invasive breast cancers using antibodies to basal cytokeratin 5 (Ck5), glandular cytokeratins 8/18 (Ck8/18/19), and smooth muscle α-actin (SMA) as markers for myoepithelial cells (SMA). A distinct population of cells was identified that expressed Ck5 in the absence of Ck8/18/19 or SMA. These cells differentiate toward glandular epithelial or myoepithelial Ck5-negative end cells passing through either Ck5/Ck8/18/19 or Ck5/SMA-positive intermediates. Our experiments clearly demonstrate a precursor or committed stem cell function of the Ck5-positive cell that is responsible for regeneration of the human adult breast epithelium. However, the observation that the vast majority of breast cancers display the glandular epithelial immunophenotype strongly suggests that the neoplastic cells derive from a late stage of the glandular epithelial differentiation pathway. The significance of this new cell biological model is that it might serve as a tool to unravel the regulatory mechanisms that govern regeneration and abnormal proliferation of breast epithelium at the cellular level.
A New Class of Materials for Magneto-Optical Applications: Transparent Amorphous Thin Films of Fe–B–Nb and Fe–B–Nb–Y Metallic Glassy Alloys

Optically highly transparent, soft magnetic thin films (4-18 nm thick) of Fe-B-Nb and Fe-B-Nb-Y-based glassy metal targets were grown on quartz substrates by pulsed laser deposition, and their optical and magneto-optical properties were investigated over the visible spectrum (400-700 nm). All the films found to be fully amorphous in structure were continuous with uniform thickness and surface morphology. Their optical transmittance in the range 50%-85% was found to be film thickness dependent over the entire visible regime. The Verdet constant (V) and Faraday rotation angle (θf ) for different films (~4-18 nm) investigated as a function of wavelength (λ) show considerably higher values for the films of Fe-B-Nb-Y alloy as compared with those for Fe-B-Nb films, e.g., the ~4 nm film of Fe-B-Nb-Y alloy exhibits V ~ 49°/Oe cm and θf ~ 26°/μm while it decreased to ~29.4°/Oe and ~11.8°/μm, respectively, for the Fe-B-Nb alloy at λ = 611 nm. A linear relationship is found for the wavelength dependence of V and θf for both alloy systems. To the best of our knowledge, these values are considerably higher than those reported for any other magneto-optic material. The films are found to be soft magnetic with a high saturation moment while their magnetic coercivity values increases with thinness of the films. The observed combination of optical and magneto-optical properties of this new class of amorphous metallic films makes them viable for multifunctional magneto-optical applications.
Improving the Rate of Sufficient Sweat Collected in Infants Referred for Sweat Testing in Michigan

Objective. Sweat collected for testing should have quantity not sufficient (QNS) rate of ≤10% in babies ≤3 months of age. Michigan (MI) cystic fibrosis (CF) centers’ QNS rates were 12% to 25% in 2009. This project was initiated to reduce sweat QNS rates in MI. Methods/Steps. (a) Each center’s sweat testing procedures were reviewed by a consultant. (b) Each center received a report with recommendations to improve QNS rates. (c) Technicians visited other participating centers to observe their procedures. Results. A total of 778 infants were identified as positive via CF newborn screening over a 2-year period. The mean age at time of sweat test was 23.2 days (SD ± 13.0 days). The overall QNS percent decreased from 14.4% to 9.5% (P = .04) during the study. Conclusion. This project and teamwork approach led to a decrease of sweat test QNS rates, opportunities to solve a common problem, and improved quality of care.
Path-Congestion-Aware Adaptive Routing With a Contention Prediction Scheme for Network-on-Chip Systems

Network-on-chip systems can achieve higher performance than bus systems for chip multiprocessor systems. However, as the complexity of the network increases, the channel and switch congestion problems become major performance bottlenecks. An effective adaptive routing algorithm can help minimize path congestion through load balancing. However, conventional adaptive routing schemes only use channel-based information to detect the congestion status. Due to the lack of switch-based information, channel-based information is difficult to reveal the real congestion status along the routing path. Therefore, in this paper, we remodel the path congestion information to show hidden spatial congestion information and improve the effectiveness of routing path selection. We propose a path-congestion-aware adaptive routing (PCAR) scheme based on the following techniques: 1) a path-congestion-aware selection strategy that simultaneously considers switch congestion and channel congestion, and 2) a contention prediction technique that uses the rate of change in the buffer level to predict possible switch contention. The experimental results show that the proposed PCAR scheme can achieve a high saturation throughput with an improvement of 15.4%-48.7% compared to existing routing schemes. The proposed PCAR method also includes a VLSI architecture, which has higher area efficiency with an improvement of 16%-35.7% compared with the other router designs.
Attribution analysis of changing pan evaporation in the Qinghai–Tibetan Plateau, China

Pan evaporation (Epan) is reported to have exhibited a decreasing trend in many regions of the world over the past several decades. However, recently, the latest studies have discovered the inconsistent phenomenon that the Epan of some regions showed an increasing trend with climate change. Epan is regarded as a critical indicator that plays a significant role in atmospheric evaporative demand, and its trend has an important significant indication to climate change and ecological environment changes. In this article, we adopted the PenPan model and the method of the total short‐wave irradiance of the pan to reparameterize the PenPan‐20 model for the Qinghai–Tibet Plateau (QTP). In addition, we employed sensitivity and a contribution model to analyse the attribution of changes in Epan under climate change over the QTP in 1970–2011. The results showed that the PenPan model can be applied to QTP. Furthermore, the results showed significant decreasing trends of Epan in 1970–2001 and insignificant increasing trends of Epan in 2002–2011. Therefore, we compartmentalized the two periods to analyse the cause of changing Epan by sensitivity and contribution rate. Trend analysis determined that the combined effects of decreasing net radiation and wind speed contributed to the decreasing of Epan in 1970–2001, and the increasing vapour pressure deficit contributed to the increasing of Epan in the study area in 2002–2011. Meanwhile, sensitivity analysis revealed that net radiation was the most sensitive factor. In addition, the results of analysis of the contribution rate were consistent with trend analysis. The dominant factor of changing Epan varied in different periods via qualitative and quantitative analysis.