Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse reconstruction based structure estimation of GRNs using time series experimental data

A strategy for estimating structure of gene regulatory networks (GRNs) is proposed on basis of time series experimental data in this paper. This strategy is an essential for transforming the problem of identifying a GRN into that of sparse reconstruction whose measurement matrix is composed of the nonlinear functions of a GRN. Differently from tradition methods, this method is well suitable for a large scale network identification, and may avoid both linearized inaccuracy and limitation of the length of time series data. We utilize an algorithm of the stagewise modified orthogonal matching pursuit (SmOMP) to estimate the sparse vector that denote a gene regulated by other genes. Compared with robust state estimator (RSE), the well known extended Kalman filter (EKF) and unscented Kalman filter (UKF) based method, the efficiency of this method has been verified by numerical simulations. Actual results show that this suggested method not only has better convergence speed and higher estimate accuracy, but also can significantly reduce the computational complexity in GRN inferences.
Classifying Options for Deep Reinforcement Learning

In this paper we combine one method for hierarchical reinforcement learning - the options framework - with deep Q-networks (DQNs) through the use of different "option heads" on the policy network, and a supervisory network for choosing between the different options. We utilise our setup to investigate the effects of architectural constraints in subtasks with positive and negative transfer, across a range of network capacities. We empirically show that our augmented DQN has lower sample complexity when simultaneously learning subtasks with negative transfer, without degrading performance when learning subtasks with positive transfer.
Thirteen Hard Cases in Visual Tracking

Visual tracking is a fundamental task in computer vision. However there has been no systematic way of analyzing visual trackers so far. In this paper we propose a method that can help researchers determine strengths and weaknesses of any visual tracker. To this end, we consider visual tracking as an isolated problem and decompose it into fundamental and independent subproblems. Each subproblem is designed to associate with a different tracking circumstance. By evaluating a visual tracker onto a specific subproblem, we can determine how good it is with respect to that dimension. In total we come up with thirteen subproblems in our decomposition. We demonstrate the use of our proposed method by analyzing working conditions of two state-of-theart trackers.
Learning from Demonstrations with High-Level Side Information

We consider the problem of learning from demonstration, where extra side information about the demonstration is encoded as a co-safe linear temporal logic formula. We address two known limitations of existing methods that do not account for such side information. First, the policies that result from existing methods, while matching the expected features or likelihood of the demonstrations, may still be in conflict with high-level objectives not explicit in the demonstration trajectories. Second, existing methods fail to provide a priori guarantees on the out-of-sample generalization performance with respect to such high-level goals. This lack of formal guarantees can prevent the application of learning from demonstration to safetycritical systems, especially when inference to state space regions with poor demonstration coverage is required. In this work, we show that side information, when explicitly taken into account, indeed improves the performance and safety of the learned policy with respect to task implementation. Moreover, we describe an automated procedure to systematically generate the features that encode side information expressed in temporal logic.
Intrusion detection model based on Android

In this paper, the traditional intrusion detection system based on computer is applied to Android platform. Taking into account the performance and storage capacity of smart phone, we proposed a light weight intrusion detection model based on Android — LIDS which changes the traditional passive antivirus to active defense. The Snort intrusion detection technology is used on mobile phones and the key pattern matching algorithm of Snort is improved.
Evaluation of the Method for Lowering Stress Concentration at the Thread Root of Bolted Joints With Modifications of Nut Shape

Many studies have been devoted to investigate how the maximum stress occurred in the bolted joint could be reduced. Patterson and Kenny suggest that a modified nut with a straight bevel at the bearing surface is effective. However, they only dealt with M30, and estimations on the nut geometry had not been necessarily sufficient. In this study, an extensive finite element approach for solving general multi-body contact problem is proposed by incorporating a regularization method into stiffness matrices with singularity involved; thus, numerical analyses are executed to accurately determine the optimal shape of the modified nut for various design factors. A modified nut with a curved bevel is also treated, and it is concluded that the modified nuts are significantly effective for bolts with larger nominal diameter and fine pitch, and are practically useful compared to pitch modification and tapered thread methods.
Exploring Synergy in Combinations of Tumor-Derived Vaccines That Harbor 4-1BBL, OX40L, and GM-CSF

Recent studies have demonstrated that combination of modulatory immune strategies may potentiate tumor cell elimination. Most strategies rely on the use of monoclonal antibodies that can block cell surface receptors to overcome tumor-induced immunosuppression or acting as costimulatory ligands to boost activation of T cells. In this study, we evaluate the use of combinations of genetically modified tumor-derived cell lines that harbor the costimulatory T cell ligands 4-1BB ligand, OX40L, and the cytokine GM-CSF. The aim of these treatments is to boost the activation of T cells and the elimination of cancer cells. These tumor-derived cells are able to activate or reinforce T cell activation, thereby generating a potent and specific antitumor response. We developed a high-content in vitro imaging assay that allowed us to investigate synergies between different tumor-derived cells expressing modulatory immune molecules, as well as the influence on effector T cells to achieve tumor cell death. These results were then compared to the results of in vivo experiments in which we challenged immunocompetent animals using the B16F10 syngeneic model of melanoma in C57BL6 mice. Our results suggest that there is a substantial therapeutic benefit to using combinations of syngeneic tumor vaccines that express immune modulators. In addition, we observed that combinations of tumor-derived cells that expressed costimulatory ligands and GM-CSF induced a long-term protective effect by preventing cancer development in both cured and rechallenged animals.
Clinical Evaluation of Neurosensory Changes in the Infraorbital Nerve Following Surgical Management of Zygomatico-Maxillary Complex Fractures.

INTRODUCTION Zygomatico-orbital fractures are the second most common facial injuries. Trauma to mid-facial region can lead to an alteration or loss of sensation in the facial region which sometimes requires early surgical intervention to aid in an early recovery. AIM To evaluate the different neurosensory changes in the infraorbital nerve function following common treatment modalities used in the management of zygomatico-maxillary complex fractures. MATERIALS AND METHODS Thirteen patients selected for the study had unilateral zygomatic complex fracture with altered sensation in the region of distribution of the infraorbital nerve. The fractures were managed either by reduction followed by internal fixation with mini-plates (Group A), reduction alone (Group B) or conservatively (Group C). Infraorbital nerve function tests were done by mechanical, heat and pain threshold detection. Evaluation was done on 1(st), 3(rd), 7(th) day, one month, three months and six months interval in a manner similar to that done at the beginning of the study (Day0). RESULTS A male predominance with male:female ratio of 5.5:1 and an age range of 21 to 50 years was found with the right side mostly affected. Road traffic accident was the most common aetiology. Most common clinical presentations were sub-conjunctival haemorrhage (84.61%), flattening of the malar prominence (69.23%) with deficit in neurosensory function of infra orbital nerve. Recovery in the infraorbital nerve function was relatively complete in 76.92% cases with partial recovery in 23.07% of the patients. CONCLUSION Marked improvement in the neurosensory function of the infraorbital nerve was found when some form of treatment either in the form of Open Reduction and Internal Fixation (ORIF) or approach through Gillie's temporal or Keen's intraoral approach were applied as compared to when conservative treatment was provided. In zygomatic complex fractures, any form of treatment employed brought about decompression of the infraorbital nerve which aided in the recovery of the nerve within a span of 1-6 months, except when no treatment was applied.
B(eo)W(u)LF: Facilitating recurrence analysis on multi-level language

Discourse analysis may seek to characterize not only the overall composition of a given text but also the dynamic patterns within the data. This technical report introduces a data format intended to facilitate multi-level investigations, which we call the by-word long-form or B(eo)W(u)LF. Inspired by the long-form data format required for mixed-effects modeling, B(eo)W(u)LF structures linguistic data into an expanded matrix encoding any number of researchers-specified markers, making it ideal for recurrence-based analyses. While we do not necessarily claim to be the first to use methods along these lines, we have created a series of tools utilizing Python and MATLAB to enable such discourse analyses and demonstrate them using 319 lines of the Old English epic poem, Beowulf, translated into modern English.
Predicting user interface preferences of culturally ambiguous users

To date, localized user interfaces are still being adapted to one nation, not taking into account cultural ambiguities of people within this nation. We have developed an approach to cultural user modeling, which allows to personalize user interfaces to an individual's cultural background. The study presented in this paper shows how we use this approach to predict user interface preferences. Results show that we are able to reduce the absolute error on this prediction to 1.079 on a rating scale of 5. These findings suggest that it is possible to automate the process of localization and, thus, to automatically personalizing user interfaces for users of different cultural backgrounds.
Reducing I/O demand in video-on-demand storage servers

Recent technological advances have made multimedia on-demand services, such as home entertainment and home-shopping, important to the consumer market. One of the most challenging aspects of this type of service is providing access either instantaneously or within a small and reasonable latency upon request. In this paper, we discuss a novel approach, termed adaptive piggybacking, which can be used to provide on-demand or nearly-on-demand service and at the same time reduce the I/O demand on the multimedia storage server.
MicroRNA399 is a long-distance signal for the regulation of plant phosphate homeostasis

The presence of microRNA species in plant phloem sap suggests potential signaling roles by long-distance regulation of gene expression. Proof for such a role for a phloem-mobile microRNA is lacking. Here we show that phosphate (Pi) starvation-induced microRNA399 (miR399) is present in the phloem sap of two diverse plant species, rapeseed and pumpkin, and levels are strongly and specifically increased in phloem sap during Pi deprivation. By performing micro-grafting experiments using Arabidopsis, we further show that chimeric plants constitutively over-expressing miR399 in the shoot accumulate mature miR399 species to very high levels in their wild-type roots, while corresponding primary transcripts are virtually absent in roots, demonstrating shoot-to-root transport. The chimeric plants exhibit (i) down-regulation of the miR399 target transcript (PHO2), which encodes a critical component for maintenance of Pi homeostasis, in the wild-type root, and (ii) Pi accumulation in the shoot, which is the phenotype of pho2 mutants, miR399 over-expressers or chimeric plants with a genetic knock-out of PHO2 in the root. Hence the transported miR399 molecules retain biological activity. This is a demonstration of systemic control of a biological process, i.e. maintenance of plant Pi homeostasis, by a phloem-mobile microRNA.
Processing and Properties of 2D Cf/Si-O-C Composites Using Silicone Resin

SR-249, a kind of polysiloxane (PSO), was used as the precursor for the first time to fabricate carbon fiber cloth reinforced silicon oxycarbide (2D Cf/Si-O-C) composites. The cure and pyrolysis of the SR-249 as well as the mechanical properties, oxidation and thermal shock behavior of the composites were investigated in the paper. The flexural strength and fracture toughness of the composites reached 217.6 MPa and 12.5 MPa·m1/2, respectively. After soaked at 1300°C under the static air for 10 min, the composites retained 58.5% flexural strength and 64.5% fracture toughness. The thermal shock behavior of the composites was studied by water quenched method. The composites retained 49.3% flexural strength and 47.4% fracture toughness after 10 times of quenching from 1200 to 20°C.
Benefits of short inspiratory muscle training on exercise capacity, dyspnea, and inspiratory fraction in COPD patients

Static lung hyperinflation has important clinical consequences in patients with chronic obstructive pulmonary disease (COPD). Given that most of these patients have respiratory and peripheral muscle weakness, dyspnea and functional exercise capacity may improve as a result of inspiratory muscle training (IMT). The present study is designed to investigate the benefits of a short outpatient program of IMT on inspiratory muscle performance, exercise capacity, perception of dyspnea, and the inspiratory fraction (IF). Thirty patients (24 males, 6 females) with significant COPD (forced expiratory volume in one second [FEV1] = 46.21% ± 6.7% predicted, FEV1 = 33.6% ± 8.04% predicted) were recruited for this study and had 3 months of IMT (30 minutes/day for 6 days/week) in an outpatient clinic. Following IMT, there was a statistically significant increase in inspiratory muscle performance (an increase of the maximal inspiratory pressure from 59% ± 19.1% to 79% ± 21.85% predicted; p = 0.0342), a decrease in dyspnea (from 5.8 ± 0.78 to 1.9 ± 0.57; p = 0.0001), an increase in the distance walked during the 6 minute walk test, from 245 ± 52.37 m to 302 ± 41.30 m, and finally an increase in the IF (the new prognostic factor in COPD) from 27.6 ± 9.7% to 31.4% ± 9.8%. The present study concludes that in patients with significant COPD, IMT results in improvement in performance, exercise capacity, sensation of dyspnea, and moreover an improvement in the IF prognostic factor.
On the Scalability of Graph Kernels Applied to Collaborative Recommenders

We study the scalability of several recent graph kernel-based collaborative recommendation algorithms. We compare the performance of several graph kernel-based recommendation algorithms, focussing on runtime and recommendation accuracy with respect to the reduced rank of the subspace. We inspect the exponential and Laplacian exponential kernels, the resistance distance kernel, the regularized Laplacian kernel
Approaching the Chasm at Depth Four

Agrawal-Vinay [AV08] and Koiran [Koi12] have recently shown that an exp(ω(√n log2 n)) lower bound for depth four homogeneous circuits computing the permanent with bottom layer of × gates having fanin bounded by √n translates to super-polynomial lower bound for general arithmetic circuits computing the permanent. Motivated by this, we examine the complexity of computing the permanent and determinant via such homogeneous depth four circuits with bounded bottom fanin. We show here that any homogeneous depth four arithmetic circuit with bottom fanin bounded by √n computing the permanent (or the determinant) must be of size exp(Ω(√n)).
Supervised Nonlinear Unmixing of Hyperspectral Images Using a Pre-image Methods

Spectral unmixing is an important issue to analyze remotely sensed hyperspectral data. This involves the decomposition of each mixed pixel into its pure endmember spectra, and the estimation of the abundance value for each endmember. Although linear mixture models are often considered because of their simplicity, there are many situations in which they can be advantageously replaced by nonlinear mixture models. In this chapter, we derive a supervised kernel-based unmixing method that relies on a pre-image problem-solving technique. The kernel selection problem is also briefly considered. We show that partially-linear kernels can serve as an appropriate solution, and the nonlinear part of the kernel can be advantageously designed with manifold-learning-based techniques. Finally, we incorporate spatial information into our method in order to improve unmixing performance.
Conditional Knockout Mice Reveal Distinct Functions for the Global Transcriptional Coactivators CBP and p300 in T-Cell Development

ABSTRACT The global transcriptional coactivators CREB-binding protein (CBP) and the closely related p300 interact with over 312 proteins, making them among the most heavily connected hubs in the known mammalian protein-protein interactome. It is largely uncertain, however, if these interactions are important in specific cell lineages of adult animals, as homozygous null mutations in either CBP or p300 result in early embryonic lethality in mice. Here we describe a Cre/LoxP conditional p300 null allele (p300 flox ) that allows for the temporal and tissue-specific inactivation of p300. We used mice carrying p300 flox and a CBP conditional knockout allele (CBP flox ) in conjunction with an Lck-Cre transgene to delete CBP and p300 starting at the CD4− CD8− double-negative thymocyte stage of T-cell development. Loss of either p300 or CBP led to a decrease in CD4+ CD8+ double-positive thymocytes, but an increase in the percentage of CD8+ single-positive thymocytes seen in CBP mutant mice was not observed in p300 mutants. T cells completely lacking both CBP and p300 did not develop normally and were nonexistent or very rare in the periphery, however. T cells lacking CBP or p300 had reduced tumor necrosis factor alpha gene expression in response to phorbol ester and ionophore, while signal-responsive gene expression in CBP- or p300-deficient macrophages was largely intact. Thus, CBP and p300 each supply a surprising degree of redundant coactivation capacity in T cells and macrophages, although each gene has also unique properties in thymocyte development.
A New Power-Efficient Scheme to Deliver Time-Sensitive Data in Sensor Networks

We present a power-efficient scheme to deliver time sensitive data packets in sensor networks. Data generated by sensors are frequently time sensitive in applications such as hazard monitoring systems, traffic controlling systems and battlefield commanding systems. Such data are associated with end-to-end deadlines, within which they must reach the base station. We make two contributions in this work. First, we propose a novel load-balanced routing scheme that distributes data packets evenly among the nodes relaying data towards the base station, avoiding bottlenecks and increasing the likelihood that packets will meet their deadlines. Second, we propose a method of grouping smaller packets into larger ones by delaying data transmissions at the relaying nodes whenever slack times are positive. Our packet grouping scheme significantly reduces packet transmissions, reduces congestion, and saves power in the sensor network. We verify the effectiveness of our approach through extensive simulations using the ns-2 simulation package
Preparatory object reorientation for task-oriented grasping

This paper describes a new task-oriented grasping method to reorient a rigid object to its nominal pose, which is defined as the configuration that it needs to be grasped from, in order to successfully execute a particular manipulation task. Our method combines two key insights: (1) a visual 6 Degree-of-Freedom (DoF) pose estimation technique based on 2D-3D point correspondences is used to estimate the object pose in real-time and (2) the rigid transformation from the current to the nominal pose is computed online and the object is reoriented over a sequence of steps. The outcome of this work is a novel method that can be effectively used in the preparatory phase of a manipulation task, to permit a robot to start from arbitrary object placements and configure the manipulated objects to the nominal pose, as required for the execution of a subsequent task. We experimentally demonstrate the effectiveness of our approach on a full-size humanoid robot (WALK-MAN) using different objects with various pose settings under real-time constraints.
The biochemical assessment of insulin resistance

Insulin resistance is a common condition, recognized to be a central feature of the metabolic syndrome, and strongly associated with an increased risk of cardiovascular disease and diabetes. The quantitative assessment of insulin sensitivity is not used for routine clinical purposes, but the emerging importance of insulin resistance has led to its wider application to research studies that have examined its pathogenesis, aetiology and consequences. The gold standard method for the determination of insulin sensitivity is the euglycaemic hyperinsulinaemic clamp from which indices of insulin sensitivity can be derived. The clamp technique is both expensive and complex to undertake and has prompted the use of surrogate methods, notably the insulin tolerance test and frequently sampled intravenous glucose tolerance test. Indices may be derived from these methods and correlate well with those derived from clamp studies. Indices can also be derived from measurements made during a standard oral glucose tolerance test and from one-off fasting specimens (e.g. homeostasis model assessment and quantitative insulin sensitivity check index). These indices lend themselves for use in large population studies where a relatively simple, inexpensive assessment is necessary. However, these tests all suffer from important limitations, including poor precision. Insulin resistance is increasingly being assessed in clinical situations, where relatively simple markers are required. Insulin-like growth factor binding protein-1 is an emerging marker which may be useful in this context.