Miracle-dz/UniFAR-FTUs huggingface dataset:
AKT inhibitor suppresses hyperthermia-induced Ndrg2 phosphorylation in gastric cancer cells

Hyperthermia is one of the most effective adjuvant treatments for various cancers with few side effects. However, the underlying molecular mechanisms still are not known. N-myc downstream-regulated gene 2 (NDRG2), a tumor suppressor, has been shown to be involved in diverse cellular stresses including hypoxia, lipotoxicity, etc. In addition, Ndrg2 has been reported to be related to progression of gastric cancer. In the current study, our data showed that the apoptosis rate of MKN28 cells increased relatively rapidly to 13.4% by 24 h after treatment with hyperthermia (42°C for 1 h) compared to 5.1% in control cells (P < 0.05). Nevertheless, there was no obvious change in the expression level of total Ndrg2 during this process. Further investigation demonstrated that the relative phosphorylation levels of Ndrg2 at Ser332, Thr348 increased up to 3.2- and 1.9-fold (hyperthermia group vs control group) at 3 h in MKN28 cells, respectively (P < 0.05). We also found that heat treatment significantly increased AKT phosphorylation. AKT inhibitor VIII (10 µM) decreased the phosphorylation level of Ndrg2 induced by hyperthermia. Accordingly, the apoptosis rate rose significantly in MKN28 cells (16.4%) treated with a combination of AKT inhibitor VIII and hyperthermia compared to that (6.8%) of cells treated with hyperthermia alone (P < 0.05). Taken together, these data demonstrated that Ndrg2 phosphorylation could be induced by hyperthermia in an AKT-dependent manner in gastric cancer cells. Furthermore, AKT inhibitor VIII suppressed Ndrg2 phosphorylation and rendered gastric cancer cells susceptible to apoptosis induced by hyperthermia.
VDJtools: Unifying Post-analysis of T Cell Receptor Repertoires

Despite the growing number of immune repertoire sequencing studies, the field still lacks software for analysis and comprehension of this high-dimensional data. Here we report VDJtools, a complementary software suite that solves a wide range of T cell receptor (TCR) repertoires post-analysis tasks, provides a detailed tabular output and publication-ready graphics, and is built on top of a flexible API. Using TCR datasets for a large cohort of unrelated healthy donors, twins, and multiple sclerosis patients we demonstrate that VDJtools greatly facilitates the analysis and leads to sound biological conclusions. VDJtools software and documentation are available at https://github.com/mikessh/vdjtools.
Adaptive guaranteed cost control for time-delay systems

The guaranteed cost control problem for time-delay systems is investigated. The main contribution in this paper is an adjustable parameter is introduced in the controller, which helps to improve the feedback gain and decrease the guaranteed cost. Furthermore, by designing the adaptive law of adjustable parameter and introducing it into the stability condition, the feedback gains changing with time are gotten. Compared with the results by fixed feedback gain, the proposed method leads to less conservatism. Simulation example is given to show the effectiveness of the proposed approach.
Grasping at the routes of biological invasions: a framework for integrating pathways into policy

Summary 1. Pathways describe the processes that result in the introduction of alien species from one location to another. A framework is proposed to facilitate the comparative analysis of invasion pathways by a wide range of taxa in both terrestrial and aquatic ecosystems. Comparisons with a range of data helped identify existing gaps in current knowledge of pathways and highlight the limitations of existing legislation to manage introductions of alien species. The scheme aims for universality but uses the European Union as a case study for the regulatory perspectives. 2. Alien species may arrive and enter a new region through three broad mechanisms: importation of a commodity, arrival of a transport vector, and/or natural spread from a neighbouring region where the species is itself alien. These three mechanisms result in six principal pathways: release, escape, contaminant, stowaway, corridor and unaided. 3. Alien species transported as commodities may be introduced as a deliberate release or as an escape from captivity. Many species are not intentionally transported but arrive as a contaminant of a commodity, for example pathogens and pests. Stowaways are directly associated with human transport but arrive independently of a specific commodity, for example organisms transported in ballast water, cargo and airfreight. The corridor pathway highlights the role transport infrastructures play in the introduction of alien species. The unaided pathway describes situations where natural spread results in alien species arriving into a new region from a donor region where it is also alien. 4. Vertebrate pathways tend to be characterized as deliberate releases, invertebrates as contaminants and plants as escapes. Pathogenic micro-organisms and fungi are generally introduced as contaminants of their hosts. The corridor and unaided pathways are often ignored in pathway assessments but warrant further detailed consideration. 5. Synthesis and applications. Intentional releases and escapes should be straightforward to monitor and regulate but, in practice, developing legislation has proved difficult. New introductions continue to occur through contaminant, stowaway, corridor and unaided pathways. These pathways represent special challenges for management and legislation. The present framework should enable these trends to be monitored more clearly and hopefully lead to the development of appropriate regulations or codes of practice to stem the number of future introductions.
Archetypal analysis of galaxy spectra

ABSTRACT Archetypal analysis represents each individual member of a set of data vectors as a mixture (aconstrained linear combination)of the pure types or archetypes of the data set. The archetypesare themselves required to be mixtures of the data vectors. Archetypal analysis may be partic-ularlyuseful in analysingdata sets comprisinggalaxyspectra, since each spectrumis, presum-ably, a superposition of the emission from the various stellar populations, nebular emissionsand nuclear activity making up that galaxy, and each of these emission sources corresponds toa potential archetype of the entire data set. We demonstrate archetypal analysis using sets ofcomposite synthetic galaxy spectra, showing that the method promises to be an effective andefﬁcient way to classify spectra. We show that archetypal an alysis is robust in the presence ofvarious types of noise.Key words: methods: data analysis – methods: statistical – galaxies: e volution – galaxies:fundamental parameters – galaxies: stellar content
Simple and effective speech steganography in G.723.1 low-rate codes

This paper presents a simple and effective steganography approach applied to 5.3 Kbps G.723. 1 low-rate coded speech, based on analyzing the redundancy of coded parameters. Augmented identity matrix is used to reduce the modification to cover speech and enhance the imperceptibility of the mixed speech correspondingly. The scheme is with good transparency and low computational complexity, which is easy to be implemented in real applications.
Empirical policy functions as benchmarks for evaluation of dynamic capital structure models

This paper presents a set of benchmark moments for evaluation or estimation of quantitative capital structure models. The moments are directly related to the models being studied: the main features of each models' empirical policy functions. The paper describe a general method for estimating these benchmarks and shows that they ‘capture’ a substantial part of the actual variation in firms actions in the data. Two versions of these benchmarks are presented: one dimensional ones and two dimensional ones. In both cases we express these as the total change in the control variable and the change relative to the change in the state variable. The empirical policy functions turn out to be smooth and mostly monotonous. Three key numbers that we suggest quantitative dynamic models have match closely are that within firms, for every 10% increase in debt relative to assets investment relative to assets declines 3.7%, debt issuance relative to market value decreases 1.1% and equity issuance relative to market value increases 0.5%.
Tracking states of massive electrical appliances by lightweight metering and sequence decoding

To smartly control the massive electrical appliances in buildings to save energy, the real-time on/off states of the electrical appliances are critically required as the fundamental information. However, it is generally a very difficult and costly problem, because N appliances have 2N states and the appliances are massively in modern buildings. This paper propose a novel compressive sensing model for monitoring the massive appliances' states, in which the sparseness of on/off switching events within a short observation interval is exploited. Based on such a temporal sparseness feature, a lightweight state tracking framework is proposed to track the on/off states of N appliances by deploying only m smart meters on the power load tree, where m ≪ N. Particularly, it firstly presents an online state decoding algorithm based on a Hidden Markov Model of sparse state transitions. It reduces the traditional O(t22N) complexity of Viterbi decoding to polynomial complexity of O(tnU+1) where n < N and U is an upper bound of the simultaneous switching events. To minimize the meter deployment cost, i. e. , m, an entropy-based necessary condition for deploying the minimal number of meters while guaranteeing the state tracking accuracy is presented. Based on it, a greedy algorithm to optimize the meter deployment to meet any given state decoding accuracy requirement is proposed. These proposed results are verified extensively based on the simulated data and the real PowerNet data. Simulation results confirm the the good performances of the proposed methods, and also demonstrate some interesting structures of the problem.
Lock-contention-aware scheduler: A scalable and energy-efficient method for addressing scalability collapse on multicore systems

In response to the increasing ubiquity of multicore processors, there has been widespread development of multithreaded applications that strive to realize their full potential. Unfortunately, lock contention within operating systems can limit the scalability of multicore systems so severely that an increase in the number of cores can actually lead to reduced performance (i.e., scalability collapse). Existing efforts of solving scalability collapse mainly focus on making critical sections of kernel code fine-grained or designing new synchronization primitives. However, these methods have disadvantages in scalability or energy efficiency. In this article, we observe that the percentage of lock-waiting time over the total execution time for a lock intensive task has a significant correlation with the occurrence of scalability collapse. Based on this observation, a lock-contention-aware scheduler is proposed. Specifically, each task in the scheduler monitors its percentage of lock waiting time continuously. If the percentage exceeds a predefined threshold, this task is considered as lock intensive and migrated to a Special Set of Cores (i.e., SSC). In this way, the number of concurrently running lock-intensive tasks is limited to the number of cores in the SSC, and therefore, the degree of lock contention is controlled. A central challenge of using this scheme is how many cores should be allocated in the SSC to handle lock-intensive tasks. In our scheduler, the optimal number of cores is determined online by the model-driven search. The proposed scheduler is implemented in the recent Linux kernel and evaluated using micro- and macrobenchmarks on AMD and Intel 32-core systems. Experimental results suggest that our proposal is able to remove scalability collapse completely and sustains the maximal throughput of the spin-lock-based system for most applications. Furthermore, the percentage of lock-waiting time can be reduced by up to 84%. When compared with scalability collapse reduction methods such as requester-based locking scheme and sleeping-based synchronization primitives, our scheme exhibits significant advantages in scalability, power consumption, and energy efficiency.
Nanoforce estimation with Kalman filtering applied to a force sensor based on diamagnetic levitation

Nano force sensors based on passive diamagnetic levitation with a macroscopic seismic mass are a possible alternative to classical Atomic Force Microscopes when the force bandwidth to be measured is limited to a few Hertz. When an external unknown force is applied to the levitating seismic mass, this one acts as a transducer that converts this unknown input into a displacement that is the measured output signal. Because the little damped and long transient response of this kind of macroscopic transducer can not be neglected, it is then necessary to deconvolve the output to correctly estimate the unknown input force. The deconvolution approach proposed in this article is based on a Kalman filter that use an uncertain a priori model to represent the unknown nanoforce to be estimated. The main advantage of this approach is that the end-user can directly control the unavoidable trade-off that exists between the wished resolution on the estimatedforce and the response time of the estimation.
Distributed Fault-Tolerant Control of Large-Scale Systems: An Active Fault Diagnosis Approach

The paper proposes a methodology to effectively address the increasingly important problem of distributed fault-tolerant control for large-scale interconnected systems. The approach dealt with combines, in a holistic way, a distributed fault detection and isolation algorithm with a specific tube-based model predictive control scheme. A distributed fault-tolerant control strategy is illustrated to guarantee overall stability and constraint satisfaction even after the occurrence of a fault. In particular, each subsystem is controlled and monitored by a local unit. The fault diagnosis component consists of a passive set-based fault detection algorithm and an active fault isolation one, yielding fault-isolability subject to local input and state constraints. The distributed active fault isolation module–thanks to a modification of the local inputs–allows to isolate the fault that has occurred, avoiding the usual drawback of controllers that possibly hide the effect of the faults. The Active Fault Isolation method is used as a decision support tool for the fault-tolerant control strategy after fault detection. The distributed design of the tube-based model predictive control allows the possible disconnection of faulty subsystems or the reconfiguration of local controllers after fault isolation. Simulation results on a well-known power network benchmark show the effectiveness of the proposed methodology.
Multicast Routing with Quality of Service in Mobile Ad hoc Networks

Recently, multimedia and group-oriented computing become increasingly popular for the users of wireless mobile networks. Quality of service (QoS) issues has initiated to be studied in Mobile Ad hoc NETworks (MANETs) to support multimedia and real-time applications. MANETs can provide users with the mobility they demand, if efficient QoS multicasting strategies are to be developed. In this paper, we study the QoS requirements with multicast routing in ad hoc networks and propose a new cross-layer framework which provides QoS guarantees to multicast routing in MANETs. We propose a multicast routing protocol with mechanisms to ensure QoS guarantees to multicast session (call-admission, bandwidth reservation and delay constrain). The proposed routing protocol uses forward group to apply multicast routing with QoS from source(s) to a group of destinations.
On the k-regularity of some projective manifolds

The conjecture on the (\textit{degree - codimension} + 1) - regularity of projective varieties is proved for smooth linearly normal polarized varieties ($X,L$) with $L$ very ample, for low values of $\Delta(X,L)$ =\textit{degree - codimension} - 1. Results concerning the projective normality of some classes of special varieties including scrolls over curves of genus 2 and quadric fibrations over elliptic curves, are proved.
Flexibility analysis on a supply chain contract using a parametric Linear Programming model

This research paper builds on existing knowledge in the field of parametric Linear Programming (pLP) and proposes a continuous mathematical model that considers a multi-period Quantity Flexibility (QF) contract between a car manufacturer (buyer) and external parts supplying company. The supplier periodically delivers parts to the car manufacturer as agreed in the contract. Due to the uncertainty of the demand for parts, the car manufacturer -in concert with the supplier-aims to develop a policy -at strategic level, that determines the optimal nominal order quantity (Q) and variation rate (β) underpinning the contract that ensures the actual order quantity satisfies the actual demand and the total cost is minimised over the contract length. The behaviour of the mathematical model has been examined in order to establish its feasibility and convexity, consequently guaranteeing an optimal solution. Simulations have been carried out to evaluate the relationship of the total cost with respect to the variation rate and the nominal quantity ordered.
Comparison of several acoustic features for the vowel sequence reproduction of a talking robot

This study compares several acoustic features for developing an automatic vowel sequence reproduction system for a talking robot, which is a mechanical vocalization system modeling the human articulatory system. Matlab-based control system is used to analyze a recorded sound and drives the articulatory motors of the talking robot. A novel method based on short-time energy analysis is used to extract a human speech and translate into a sequence of sound elements for the sequence of vowels reproduction. Then, several phonemes detection methods including the direct cross-correlation analysis, the linear predictive coding (LPC) association, the partial correlation (PARCOR) coefficients analysis, and the formant frequencies comparison are applied to each sound element to give the corrected command for the talking robot to repeat the sound sequentially. Finally, experiments to compare these techniques and verify the working behavior of the robot are performed. The result of the tests indicates that the robot is able to repeat a sequence of vowels spoken by a human with a successful rate of more than 70% for the PARCOR analysis technique and the formant frequencies comparison technique. The greatest accuracy for repeating the sequence is given by the formant comparison method, while the direct cross-correlation method delivers the least accuracy.
Assertiveness and Anxiety Effects in Traditional and Online Interactions

The present study explored the extent to which self-esteem is a significant predictor of social network use and the level of anxiety and assertiveness participants feel during traditional and online interactions. Using a survey design N=184, it was found that lower self-esteem was not associated with more intensive social network use, in contrast to the social compensation theory. Self-esteem was a significant negative predictor of social anxiety as well as a positive predictor of assertiveness in traditional and online settings. Higher social anxiety was also associated with lower social assertiveness in both settings. Exploratory results showed that participants who engaged more frequently in online activities also reported significantly higher levels of assertiveness and lower levels of anxiety. These findings suggest that online behaviors reflect different personality characteristics, with self-esteem being an important variable to consider in the exploration of online behaviors and experiences.
Memory/logic interconnect flexibility in FPGAs with large embedded memory arrays

As the capacities of field-programmable gate arrays (FPGAs) grow, it becomes desirable to create FPGAs with embedded memory arrays. This paper examines the flexibility of the interconnect structure that joins memory and logic. For architectures with only a few memory arrays, we find that both the routability and the delay of circuits are insensitive to the memory/logic interconnect flexibility, which implies that this interconnection can be made very inflexible. This is in contrast to the logic connection block flexibility, which has been shown to require high flexibility. For architectures with more arrays, the memory/logic interconnect flexibility requirements increase and approach those of logic interconnect.
High prevalence of shoulder pain among elite Norwegian female handball players

Clinical experience indicates that a substantial number of handball players may suffer from shoulder pain, but they continue to play despite having shoulder pain problems. The aim of this study was to evaluate the prevalence and consequences of shoulder pain problems among Norwegian female elite handball players. In the preseason of the 2007–2008 season, 179 players from all 12 teams of the Norwegian elite league went through the following tests: internal and external shoulder range of motion, apprehension, relocation test, and shooting velocity. All players completed the Fahlström questionnaire and, for players with current pain, the Western Ontario shoulder instability index questionnaire. Sixty‐five (36%) players reported shoulder pain on the test day, and 40 (22%) players reported previous shoulder pain. Two thirds of the players with pain reported a gradual onset. For players with current or previous pain, 22 (36%) and 14 (36%) had missed match play, and 43 (68%) and 28 (76%) reported changing their training habits. A positive apprehension and relocation test was found among 51 (29%) of the players. In conclusion, a high proportion of female elite handball players experience shoulder pain and problems and have an unstable shoulder.
Growth Inhibition and Morphological Alterations of Trichophyton Rubrum Induced by Essential oil from Cymbopogon Winterianus Jowitt Ex Bor

Trichophyton rubrum is one of the most common fungi causer of dermatophytosis, mycosis that affect humans and animals around the world. Researches aiming new products with antifungal activity become necessary to overcome difficulties on treatment of these infections. Accordingly, this study aimed to investigate the antifungal activity of essential oil from Cymbopogon winterianus against the dermatophyte T. rubrum. The antifungal screening was performed by solid medium diffusion method with 16 T. rubrum strains, minimum inhibitory concentration (MIC) and minimum fungicide concentration (MFC) were determined using the microdilution method. The effects on mycelial dry weight and morphology were also observed. Screening showed essential oil in natura inhibited all the tested strains, with inhibition zones between 24-28 mm diameter. MIC50 and MIC90 values of the essential oil were 312 μg/mL for nearly all the essayed strains (93.75 %) while the MFC50 and MFC90 values were about eight times higher than MIC for all tested strains. All tested essential oil concentrations managed to inhibit strongly the mycelium development. Main morphological changes on the fungal strains observed under light microscopy, which were provided by the essential oil include loss of conidiation, alterations concerning form and pigmentation of hyphae. In the oil presence, colonies showed folds, cream color and slightly darker than the control, pigment production was absent on the reverse and with evident folds. It is concluded that C. winterianus essential oil showed activity against T. rubrum. Therefore, it could be known as potential antifungal compound especially for protection against dermatophytosis.