Miracle-dz/UniFAR-FTUs huggingface dataset:
The Yeast Protein Database (YPD): a curated proteome database for Saccharomyces cerevisiae

The Yeast Protein Database (YPD) is a curated database for the proteome of Saccharomyces cerevisiae . It consists of approximately 6000 Yeast Protein Reports, one for each of the known or predicted yeast proteins. Each Yeast Protein Report is a one-page presentation of protein properties, annotation lines that summarize findings from the literature, and references. In the past year, the number of annotation lines has grown from 25 000 to approximately 35 000, and the number of articles curated has grown from approximately 3500 to >5000. Recently, new data types have been included in YPD: protein-protein interactions, genetic interactions, and regulators of gene expression. Finally, a new layer of information, the YPD Protein Minireviews, has recently been introduced. The Yeast Protein Database can be found on the Web at http://www.proteome. com/YPDhome. html
Ultrasensitive nanosensor based on gold nanoparticles to detect vascular endothelial growth factor (VEGF)

We report on the use of new biosensor that enable a surface Plasmon resonance (SPR) sensor to detec VEGF in tissue extracts and cell lysates. This sensor consist of gold nanoparticles functionalized with antibodies anti-VEGF. To analyze the optical properties and their sensing ability was held optical absorption experiments in band plasmon resonance. We demonstrate that this approach makes it possible for the SPR biosensor to detect VEGF in tissues at low concentrations.
Explicable Robot Planning as Minimizing Distance from Expected Behavior

In order for robots to be integrated effectively into human work-flows, it is not enough to address the question of autonomy but also how their actions or plans are being perceived by their human counterparts. When robots generate task plans without such considerations, they may often demonstrate what we refer to as inexplicable behavior from the point of view of humans who may be observing it. This problem arises due to the human observer's partial or inaccurate understanding of the robot's deliberative process and/or the model (i.e. capabilities of the robot) that informs it. This may have serious implications on the human-robot work-space, from increased cognitive load and reduced trust in the robot from the human, to more serious concerns of safety in human-robot interactions. In this paper, we propose to address this issue by learning a distance function that can accurately model the notion of explicability, and develop an anytime search algorithm that can use this measure in its search process to come up with progressively explicable plans. As the first step, robot plans are evaluated by human subjects based on how explicable they perceive the plan to be, and a scoring function called explicability distance based on the different plan distance measures is learned. We then use this explicability distance as a heuristic to guide our search in order to generate explicable robot plans, by minimizing the plan distances between the robot's plan and the human's expected plans. We conduct our experiments in a toy autonomous car domain, and provide empirical evaluations that demonstrate the usefulness of the approach in making the planning process of an autonomous agent conform to human expectations.
Humanized mice with ectopic artificial liver tissues

“Humanized” mice offer a window into aspects of human physiology that are otherwise inaccessible. The best available methods for liver humanization rely on cell transplantation into immunodeficient mice with liver injury but these methods have not gained widespread use due to the duration and variability of hepatocyte repopulation. In light of the significant progress that has been achieved in clinical cell transplantation through tissue engineering, we sought to develop a humanized mouse model based on the facile and ectopic implantation of a tissue-engineered human liver. These human ectopic artificial livers (HEALs) stabilize the function of cryopreserved primary human hepatocytes through juxtacrine and paracrine signals in polymeric scaffolds. In contrast to current methods, HEALs can be efficiently established in immunocompetent mice with normal liver function. Mice transplanted with HEALs exhibit humanized liver functions persistent for weeks, including synthesis of human proteins, human drug metabolism, drug–drug interaction, and drug-induced liver injury. Here, mice with HEALs are used to predict the disproportionate metabolism and toxicity of “major” human metabolites using multiple routes of administration and monitoring. These advances may enable manufacturing of reproducible in vivo models for diverse drug development and research applications.
Big-Five Personality Prediction Based on User Behaviors at Social Network Sites

Many customer services are already available at Social Network Sites (SNSs), including user recommendation and media interaction, to name a few. There are strong desires to provide online users more dedicated and personalized services that fit into individual's need, usually strongly depending on the inner personalities of the user. However, little has been done to conduct proper psychological analysis, crucial for explaining the user's outer behaviors from their inner personality. In this paper, we propose an approach that intends to facilitate this line of research by directly predicting the so called Big-Five Personality from user's SNS behaviors. Comparing to the conventional inventory-based psychological analysis, we demonstrate via experimental studies that users' personalities can be predicted with reasonable precision based on their online behaviors. Except for proving some former behavior-personality correlation results, our experiments show that extraversion is positively related to one's status republishing proportion and neuroticism is positively related to the proportion of one's angry blogs (blogs making people angry).
Antimicrobial drimane sesquiterpenes and their effect on endophyte communities in the medical tree Warburgia ugandensis

Metabolite profiles (GC–−MS), drimane sesquiterpenes, sugars and sugar alcohols, were compared with bacterial and fungal endophyte communities (T-RFLP, DNA clones, qPCR) in leaves and roots of the pepper bark tree, Warburgia ugandensis (Canellaceae). Ten individuals each were assessed from two locations east and west of the Great Rift Valley, Kenya, Africa, which differed in humidity and vegetation, closed forest versus open savannah. Despite organ- and partially site-specific variation of drimane sesquiterpenes, no clear effects on bacterial and fungal endophyte communities could be detected. The former were dominated by gram-negative Gammaproteobacteria, Pseudomonadaceae and Enterobacteriaceae, as well as gram-positive Firmicutes; the fungal endophyte communities were more diverse but no specific groups dominated. Despite initial expectations, the endophyte community of the pepper bark tree did not differ from other trees that much.
Feed-Forward Control of Open Channel Flow Using Differential Flatness

This brief derives a method for open-loop control of open channel flow, based on the Hayami model, a parabolic partial differential equation resulting from a simplification of the Saint-Venant equations. The open-loop control is represented as infinite series using differential flatness, for which convergence is assessed. A comparison is made with a similar problem available in the literature for thermal systems. Numerical simulations show the effectiveness of the approach by applying the open-loop controller to irrigation canals modeled by the full Saint-Venant equations.
Temporal dynamics of sensorimotor integration in speech perception and production: independent component analysis of EEG data

Activity in anterior sensorimotor regions is found in speech production and some perception tasks. Yet, how sensorimotor integration supports these functions is unclear due to a lack of data examining the timing of activity from these regions. Beta (~20 Hz) and alpha (~10 Hz) spectral power within the EEG μ rhythm are considered indices of motor and somatosensory activity, respectively. In the current study, perception conditions required discrimination (same/different) of syllables pairs (/ba/ and /da/) in quiet and noisy conditions. Production conditions required covert and overt syllable productions and overt word production. Independent component analysis was performed on EEG data obtained during these conditions to (1) identify clusters of μ components common to all conditions and (2) examine real-time event-related spectral perturbations (ERSP) within alpha and beta bands. 17 and 15 out of 20 participants produced left and right μ-components, respectively, localized to precentral gyri. Discrimination conditions were characterized by significant (pFDR < 0.05) early alpha event-related synchronization (ERS) prior to and during stimulus presentation and later alpha event-related desynchronization (ERD) following stimulus offset. Beta ERD began early and gained strength across time. Differences were found between quiet and noisy discrimination conditions. Both overt syllable and word productions yielded similar alpha/beta ERD that began prior to production and was strongest during muscle activity. Findings during covert production were weaker than during overt production. One explanation for these findings is that μ-beta ERD indexes early predictive coding (e.g., internal modeling) and/or overt and covert attentional/motor processes. μ-alpha ERS may index inhibitory input to the premotor cortex from sensory regions prior to and during discrimination, while μ-alpha ERD may index sensory feedback during speech rehearsal and production.
A Stochastic Optimization Approach for Joint Relay Assignment and Power Allocation in Orthogonal Amplify-and-Forward Cooperative Wireless Networks

This paper addresses the joint relay assignment and power allocation problem for orthogonal multiuser systems using amplify-and-forward (AF) relaying nodes in the downlink. Our aim is to maximize the sum-rate subject to individual and total power constraints on the relays and a relay assignment constraint. In the case of fixed relay selection, the power allocation optimization is convex and an efficient recursive algorithm is proposed to achieve the optimum. The joint optimization of relay selection and power allocation, however, appears to be non-convex and is not known to be tractable. To tackle this, we propose a novel algorithm using Markov chain Monte-Carlo with Kullback-Leibler divergence minimization (MCMC-KLDM), which is proved to converge to the global optimum almost surely. Results show that the proposed scheme significantly outperforms a greedy approach and achieves near-optimal performance at very low complexity.
On the role of ocean circulation in seasonal and interannual ice-edge variations in the Bering Sea

A 40 km-resolution ice—ocean model of the Bering Sea is used to investigate the effects of ocean circulation and vertical convection on the seasonal and interannual ice extent variations in the Bering Sea. The model is driven with daily time-varying atmospheric forcing from 1981–83. A series of sensitivity studies is carried out to examine the effects of the vertical diffusion and precipitation on the ice margin and the effect of stratification on the ocean circulation. For comparison, an ice-only simulation, with a motionless oceanic boundary layer of fixed depth, is also carried out. In the Aleutian Basin, the ice-ocean model exhibits a cyclonic ocean circulation which consists mainly of a baroclinic current component. On the eastern Bering Sea shelf the flow is mainly barotropic, with a northwestern shelf flow along the Alaskan coast and a return southeastern flow along the shelf break. The seasonal and interannual variability of the ice margin is significantly better simulated by the ice-ocean model than by the ice-only model, especially when an enhanced vertical diffusion is used. However, the seasonal cycle of ice extent exhibits too little ice in the southeastern Bering Sea and excessive ice in the northwest. The advance and retreat of the ice edge also tends to lag behind the observed results by a few weeks. The inclusion of precipitation improves the ice extent in the southeast. The results suggest that an enhanced vertical resolution, together with a more complete boundary layer formulation, will be required to achieve realistic seasonal simulations of the Bering Sea ice–ocean system.
A Model of Reward- and Effort-Based Optimal Decision Making and Motor Control

Costs (e.g. energetic expenditure) and benefits (e.g. food) are central determinants of behavior. In ecology and economics, they are combined to form a utility function which is maximized to guide choices. This principle is widely used in neuroscience as a normative model of decision and action, but current versions of this model fail to consider how decisions are actually converted into actions (i.e. the formation of trajectories). Here, we describe an approach where decision making and motor control are optimal, iterative processes derived from the maximization of the discounted, weighted difference between expected rewards and foreseeable motor efforts. The model accounts for decision making in cost/benefit situations, and detailed characteristics of control and goal tracking in realistic motor tasks. As a normative construction, the model is relevant to address the neural bases and pathological aspects of decision making and motor control.
Main Content Extraction from Web Pages Based on Node Characteristics

Main content extraction of web pages is widely used in search engines, web content aggregation and mobile Internet browsing. However, a mass of irrelevant information such as advertisement, irrelevant navigation and trash information is included in web pages. Such irrelevant information reduces the efficiency of web content processing in content-based applications. The purpose of this paper is to propose an automatic main content extraction method of web pages. In this method, we use two indicators to describe characteristics of web pages: text density and hyperlink density. According to continuous distribution of similar content on a page, we use an estimation algorithm to judge if a node is a content node or a noisy node based on characteristics of the node and neighboring nodes. This algorithm enables us to filter advertisement nodes and irrelevant navigation. Experimental results on 10 news websites revealed that our algorithm could achieve a 96.34% average acceptable rate.
Whiplash patients' experience of a multimodal rehabilitation programme and its usefulness one year later

Objective. The study aimed to explore and analyse how, 1 year after completing a rehabilitation programme, persons with long-term pain due to whiplash-associated disorders (WAD) experienced their participation, and what knowledge and strategies they had gained from it for handling their daily occupations. Methods. The study had an emergent design. Thematised research interviews were conducted with nine informants. The results were analysed according to the constant-comparison grounded-theory method. Results. Data analysis resulted in one core category, ‘learning to manage WAD, a rehabilitation process’, and three associated categories: ‘chaos in life’, ‘a light in the tunnel’ and ‘managing long-term pain’. The core category and the categories describe the process the informants underwent from how they experienced life when starting rehabilitation to one year after completion. Conclusion. The informants described living with long-term whiplash-associated pain as ‘chaos’ before the rehabilitation programme. Participation helped them realise that there was a possible way for them to control their pain, regain their daily occupation and return to work. One year after rehabilitation the informants had started to accept their situation and regain occupations and life roles.
Counterfactual Reasoning in Linear Structural Equation Models

Consider the case where causal relations among variables can be described as a Gaussian linear structural equation model. This paper deals with the problem of clarifying how the variance of a response variable would have changed if a treatment variable were assigned to some value (counterfactually), given that a set of variables is observed (actually). In order to achieve this aim, we reformulate the formulas of the counterfactual distribution proposed by Balke and Pearl (1995) through both the total effects and a covariance matrix of observed variables. We further extend the framework of Balke and Pearl (1995) from point observations to interval observations, and from an unconditional plan to a conditional plan. The results of this paper enable us to clarify the properties of counterfactual distribution and establish an optimal plan.
Scalable Programming for SDN Controllers

Introduction. A major recent development in computer networking is the notion of Software-Defined Networking (SDN), which allows a network to customize its behaviors through centralized policies at a conceptually centralized network controller. In particular, Openflow [4] has made significant progress by establishing (1) flow tables as a standard data-plane abstraction for distributed switches, (2) a protocol for the centralized controller to install forwarding rules and query state at switches, and (3) a protocol for a switch to forward to the controller packets not matching any rules in its switch-local forwarding table. This progress has provided critical components in realizing the vision that a network operator configures a network by writing a simple, centralized network control program, with a global view of network state, thus decoupling the program from the complexities of managing distributed state. We refer to the programming of the centralized controller as SDN programming, and a network operator who conducts SDN programming as an SDN programmer, or just a programmer. A critical component in realizing the full benefits of SDN is the SDN programming model, through which a programmer defines its network behaviors. Existing programming models require either explicit or restricted declarative specification of flow patterns, introducing a major source of complexity in SDN programming. In this project, we explore an SDN programming model that enables an SDN programmer to apply a high-level algorithmic approach to define network-wide forwarding behaviors of network flows. Specifically, the programmer simply defines a function f , expressed in a general-purpose, high-level programming language, which the centralized controller conceptually runs on every packet entering the network. When designing the function f , the programmer does not need to adapt to a new programming model but uses a standard programming language to design arbitrary algorithms to classify input packets and return a network-wide forwarding path describing how each packet should be forwarded to organize traffic. We refer to this model as SDN programming of algorithmic policies. We emphasize that algorithmic policies and declarative policies do not exclude each other. Our system supports both, but this paper focuses on algorithmic policies.
An Information System Design Product Theory for Integrated Order, Transportation and Warehouse Management Systems

Globalization, lead time reduction and cost pressures, and other factors make it nontrivial for most companies to devise and manage effective logistics services to meet client requirements. They are better off using the services of specialized third party logistics service providers. These providers compete fiercely and need to develop and improve their services continuously to gain competitive advantage. Integrating the logistics process for improving communication and coordination is the most feasible way for third party logistics providers to deal with these pressures. Yet, the extant literature provides little theoretical guidance for integrating the logistics life-cycle, including ordering, transportation, and warehousing. This paper develops an Information System Design Product Theory for the class of integrated Order, Transportation and Warehouse Management Systems based on a case study and a literature review. The theory helps clients and service providers to acquire and design information systems for designing, managing and controlling transparent and seamless logistics processes that improve service effectiveness.
Small Intestinal Contrast Ultrasonography-Based Scoring System: A Promising Approach for the Diagnosis and Follow-Up of Celiac Disease

Background: Small intestinal ultrasonography with anechoic contrast agents (SICUS) has been shown to have a diagnostic accuracy on small bowel morphology similar to X-ray barium follow-through. Although extremely investigated by transabdominal ultrasonography, celiac disease, a common disorder of the small bowel, has been never studied by SICUS. Aim: To asses SICUS characteristics of celiac disease patients. Patients and Methods: SICUS was performed using PEG 4000 as contrast agent. Twenty-three patients with celiac disease at the first diagnosis were enrolled and 30 healthy volunteers, matched for sex and age, were selected as control group. Celiac disease diagnosis was based on anti-gluten, anti-endomysium, and anti-transglutaminase positivity as well as jejunal histology. The following seven echographic parameters were considered: liquid endoluminal content before contrast, loop diameter, Kerckring's folds, peristaltic waves, ileal jejunalization, mesenteric lymphoadenomegaly, and Doppler resistance index (RI) of mesenteric superior artery. Statistical analysis was performed by Student's t test for unpaired data; one-way analysis of variance was used to correlate echographic and histologic pictures. Results: Loop diameter, Kerckring's fold number, peristaltic waves, and Doppler RI appeared to be significantly different between celiac disease patients and controls. Additionally, liquid content, ileal jejunalization, and mesenteric lymphoadenomegaly were present only in the celiacs (52.1%, 47.7%, and 95.6%, respectively), but not in controls. Only Doppler RI values significantly correlated with the histologic degree of damage. Conclusions: SICUS could be a reliable and noninvasive technique to confirm a diagnosis of celiac disease performed using conventional investigations. The possibility of investigating the whole small bowel and the safety of repeating examinations could be useful in the follow-up of celiac patients.
When Reputation Enforces Evolutionary Cooperation in Unreliable MANETs

In self-organized mobile ad hoc networks (MANETs), network functions rely on cooperation of self-interested nodes, where a challenge is to enforce their mutual cooperation. In this paper, we study cooperative packet forwarding in a one-hop unreliable channel which results from loss of packets and noisy observation of transmissions. We propose an indirect reciprocity framework based on evolutionary game theory, and enforce cooperation of packet forwarding strategies in both structured and unstructured MANETs. Furthermore, we analyze the evolutionary dynamics of cooperative strategies and derive the threshold of benefit-to-cost ratio to guarantee the convergence of cooperation. The numerical simulations verify that the proposed evolutionary game theoretic solution enforces cooperation when the benefit-to-cost ratio of the altruistic exceeds the critical condition. In addition, the network throughput performance of our proposed strategy in structured MANETs is measured, which is in close agreement with that of the full cooperative strategy.