Miracle-dz/UniFAR-FTUs huggingface dataset:
Fine Oral Filaments in Paramecium: a Biochemical and Immunological Analysis

Abstract In Paramecium, several kinds of the oral networks of fine filaments are defined at the ultrastructural level. Using the sodium chloride-treated oral apparatus of Paramecium as an antigen to produce monoclonal antibodies, we have begun to identify the proteins constituting these networks. Immunoblotting showed that all positive antibodies were directed against three bands (70-, 75- and 83-kD), which corresponded to quantitatively minor components of the antigen; there was no antibody specific for the quantitatively major components (58- and 62-kD). Immunolocalization with four of these antibodies directed against one or several of these three bands showed that these proteins are components of the fine filaments supporting the oral area; a decoration of the basal bodies and the outer lattice was also observed on the cortex. Immunofluorescence on interphase cells suggested that the three proteins colocalized on the left side of the oral apparatus, whereas only the 70-kD band was detected on the right side. During division, the antigens of the antibodies were detected at different stages after oral basal body assembly. The antibodies cross-reacted with the tetrins, which are oral filament-forming proteins in Tetrahymena, demonstrating that tetrin-related proteins are quantitatively minor components of the oral and the somatic cytoskeleton of Paramecium.
Effects of Swimming Exercise on Limbic and Motor Cortex Neurogenesis in the Kainate-Lesion Model of Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is a common neurological disease and antiseizure medication is often inadequate for preventing apoptotic cell death. Aerobic swimming exercise (EX) augments neurogenesis in rats when initiated immediately in the postictal period. This study tests the hypothesis that aerobic exercise also augments neurogenesis over the long term. Male Wistar rats (age of 4 months) were subjected to chemical lesioning using KA and to an EX intervention consisting of a 30 d period of daily swimming for 15 min, in one experiment immediately after KA lesioning (immediate exposure) and in a second experiment after a 60 d period of normal activity (delayed exposure). Morphometric counting of neuron numbers (NN) and dendritic branch points and intersections (DDBPI) was performed in the CA1, CA3, and dentate regions of hippocampus, in basolateral nucleus of amygdala, and in several areas of motor cortex. EX increased NN and DDBPI in the normal control and the KA-lesioned rats in all four limbic and motor cortex areas studied, after both immediate and 60 d delayed exposures to exercise. These findings suggest that, after temporal lobe epileptic seizures in rats, swimming exercise may improve neural plasticity in areas of the brain involved with emotional regulation and motor coordination, even if the exercise treatment is delayed.
Mammalian Stem Cells Reprogramming in Response to Terahertz Radiation

We report that extended exposure to broad-spectrum terahertz radiation results in specific changes in cellular functions that are closely related to DNA-directed gene transcription. Our gene chip survey of gene expression shows that whereas 89% of the protein coding genes in mouse stem cells do not respond to the applied terahertz radiation, certain genes are activated, while other are repressed. RT-PCR experiments with selected gene probes corresponding to transcripts in the three groups of genes detail the gene specific effect. The response was not only gene specific but also irradiation conditions dependent. Our findings suggest that the applied terahertz irradiation accelerates cell differentiation toward adipose phenotype by activating the transcription factor peroxisome proliferator-activated receptor gamma (PPARG). Finally, our molecular dynamics computer simulations indicate that the local breathing dynamics of the PPARG promoter DNA coincides with the gene specific response to the THz radiation. We propose that THz radiation is a potential tool for cellular reprogramming.
[Evaluation of gingival inflammation related to different retraction agents].

OBJECTIVE To choose the best retraction agent for the clinic by evaluating the gingival inflammation related to three kinds of retraction agents. METHODS 40 maxillary premolars were divided into four groups according to the randomized block design: Ferric sulfate group, aluminum chloride group, epinephrine group, sodium chloride group(control group), each 10 teeth, respectively used 25% AlCl3, 15.5% Fe2(SO4)3, 0.1% HCl-epinephrine, sodium chloride as retraction agents. The quantity of gingival crevicular fluid (GCF) and the active level of aspartate amino-transferase (AST) in gingival crevicular fluid were measured before and 1, 3, 5, 7, 9 days after retracting gingiva by four kinds retraction agents. The changes of GCF were calculated. RESULTS The change of the GCF from the smallest to the largest was sodium chloride, 0.1% HCl-epinephrine, 25% AlCl,, 15.5% Fe2 (SO)3. Compared with sodium chloride, only 15.5% Fe2 (SO)3 in AST was the significant difference in the first day and the third day (P < 0.05). AST of ferric sulfate group after 1, 3 days greater than 800 IU. CONCLUSION 0.1% HCl-epinephrine is suggested in patient without cardiovascular disease. For patient with cardiovascular disease, the better substitute is 25% AlCl3. 15.5% Fe2 (SO4)3 will not be used until its concentration is fallen.
Permission-Based E-Mail Marketing Websites Success: An Integrated Perspective

Extant research on websites success has paid insufficient attention to the success of permission-based e-mail marketing PEM websites. In order to bridge this knowledge gap, the contribution of this study lies in synthesizing information management/e-commerce, media/communication, as well as customer/marketing research to propose a PEM websites success model consisting of antecedent i.e., functional, process, and relational benefits, mediator i.e., relationship quality, and outcome variables i.e., relationship outcomes. Data collected from 294 respondents in Taiwan were tested against the research model using structural equation modeling. The result shows that functional and process benefits i.e., information quality, ease of use, and entertainment benefits except entertainment benefits can indirectly influence relationship outcomes i.e., user loyalty and positive word of mouth through the mediation of relationship quality i.e., user satisfaction and commitment. The result also indicates that relational benefits i.e., confidence, social, and special treatment benefits can not affect relationship outcomes directly or indirectly through relationship quality. It concludes that, unlike the brick-and-mortar context, relational benefits emphasized by customer/marketing research do not play a significant role in influencing relationship outcomes in the context of PEM websites. Rather, the empirically validated model highlights the importance of functional and process benefits in establishing PEM websites success, supporting the perspectives from information management/e-commerce research as well as media/communication research.
Walk-assist robot: A novel approach to gain selection of a braking controller using differential flatness

With the growth of elderly population in our society, technology will play an important role in providing functional mobility to humans. From the perspective of human safety, it is desirable that controllers for walk-assist robots be dissipative, i.e., the energy is supplied by the human to the walker, while the controller modulates this energy, also the motion of the walker, while dissipating this energy. The simplest form of a dissipating controller is a brake, where resistive torques are applied to the wheels proportional to their speeds. The fundamental question that we ask in this paper is how to modulate these proportionality gains over time for the two wheels so that the walker can perform point-to-point motions in the state space. The unique contribution of this paper is a novel way in which the theory of differential flatness is used to plan the trajectory of these braking gains. Since the user input force is not known prior, the theory of model predictive control is used to periodically compute the trajectory of these braking gains. The simulation results show that the walking assist robot, along with the structure of this proposed control scheme, can guide the user to a goal accurately.
Scalable, MDP-based planning for multiple, cooperating agents

This paper introduces an approximation algorithm for stochastic multi-agent planning based on Markov decision processes (MDPs). Specifically, we focus on a decentralized approach for planning the actions of a team of cooperating agents with uncertainties in fuel consumption and health-related models. The core idea behind the algorithm presented in this paper is to allow each agent to approximate the representation of its teammates. Each agent therefore maintains its own planner that fully enumerates its local states and actions while approximating those of its teammates. In prior work, the authors approximated each teammate individually, which resulted in a large reduction of the planning space, but remained exponential (in n - 1 rather than in n, where n is the number of agents) in computational scalability. This paper extends the approach and presents a new approximation that aggregates all teammates into a single, abstracted entity. Under the persistent search & track mission scenario with 3 agents, we show that while resulting performance is decreased nearly 20% compared with the centralized optimal solution, the problem size becomes linear in n, a very attractive feature when planning online for large multi-agent teams.
Maximum a posteriori adaptation of network parameters in deep models

We present a Bayesian approach to adapting parameters of a well-trained context-dependent, deep-neural-network, hidden Markov model (CD-DNN-HMM) to improve automatic speech recognition performance. Given an abundance of DNN parameters but with only a limited amount of data, the effectiveness of the adapted DNN model can often be compromised. We formulate maximum a posteriori (MAP) adaptation of parameters of a specially designed CD-DNN-HMM with an augmented linear hidden networks connected to the output tied states, or senones, and compare it to feature space MAP linear regression previously proposed. Experimental evidences on the 20,000-word open vocabulary Wall Street Journal task demonstrate the feasibility of the proposed framework. In supervised adaptation, the proposed MAP adaptation approach provides more than 10% relative error reduction and consistently outperforms the conventional transformation based methods. Furthermore, we present an initial attempt to generate hierarchical priors to improve adaptation efficiency and effectiveness with limited adaptation data by exploiting similarities among senones.
A graph theory based characterization of controllability for multi-agent systems with fixed topology

The paper studies a class of formation control problem, i.e. the controllability for multi-agent systems under leader-follower framework. A new concept leader-follower connectedness is proposed to deal with what is the desired extent of connectivity between the leader and follower subgraphs for a multi-agent system to be controllable. Analysis based on this concept yields graph theory based characterizations for the controllability of interconnection dynamic networks with fixed topologies.
Online Next-Best-View Planning for Accuracy Optimization Using an Extended E-Criterion

Next-best-view (NBV) planning is an important aspect for three-dimensional (3D) reconstruction within controlled environments, such as a camera mounted on a robotic arm. NBV methods aim at a purposive 3D reconstruction sustaining predefined goals and limitations. Up to now, literature mainly presents NBV methods for range sensors, model-based approaches or algorithms that address the reconstruction of a finite set of primitives. For this work, we use an intensity camera without active illumination. We present a novel combined online approach comprising feature tracking, 3D reconstruction, and NBV planning that addresses arbitrary unknown objects. In particular we focus on accuracy optimization based on the reconstruction uncertainty. To this end we introduce an extension of the statistical E-criterion to model directional uncertainty, and we present a closed-form, optimal solution to this NBV planning problem. Our experimental evaluation demonstrates the effectivity of our approach using an absolute error measure.
Plant Science Today

Natural antioxidant capacity of five important folk medicinal plants measured in vitro. Total phenolic content (TPC), flavonoid content (FC) and free radical scavenging capacity of ethanolic, methanolic and aqueous leaf extracts of Lippia alba (LA), Annona squamosa (AS), Hyptis suaveolens (HS), Commiphora wightii (CW) and Milletia pinnata (MP) was assessed using spectrophotometric method. Folin ciocalteu and aluminium chloride method employed to optimise TPC and FC. Free radical scavenging potentiality of leaf extracts was assessed using Ferrous ion chelation (FIC), 2, 2'-diphenyl-1-picrylhydrazyl (DPPH ) scavenging, Hydroxyl (OH) radical scavenging (HRS) and Superoxide (O 2) radical scavenging (SRS) methods. Results revealed that the TPC (96.22±5.85 to 519.23±34.90 μg GAE/gm dry weight) were found significant in aqueous extracts from all the plants except AS ( p<0.05). For FC (μg QCE/gm dry weight), ethanol was found optimum for LA (463.94±6.49), CW (289.99±2.70) and MP (347.47±4.50) whereas, aqueous was found more appropriate for rest two plants were found significant instead of ethanol and methanol (all p<0.05). The lowest IC50 (μg/ml) were recorded from A. squamosa (27.72±8.95), H. suaveolens (27.78±0.88), C. wightii (27.18±0.16) and M. pinnata (27.30±0.03). All plants have reflected a high antioxidant capacity; however, the highest antioxidant activity was reported from ethanolic extract of H. suaveolens followed by L. alba, A. squamosa, C. wightii and M. pinnata. Hence, these studies show that all folk medicinal plants contain potential antioxidant bioactive compounds.
Estimation of land surface temperature using modis thermal infrared and weather station data in Iraq

Recently Iraq experienced many environmental problems, caused by global climate changes. Therefore, it is important to monitor the real change in temperature. In order to achieve this goal, it requires a very large network of ground stations. MOD11A1 product is a tile of daily LST product (land surface temperature) at 1 km spatial resolution with a reasonable accuracy that needs to be improved. By a statistical model that relates ground truth temperature with result of LST from MODIS data it is possible to generate a correction algorithm. Lumping all daily average data of six Iraqi cities over three years a regression line that correlate، daily average truth ground temperature (TG) with daily average LST obtained from MODIS data. This correlation can be used to get a better estimation to the average daily truth temperature for any area within 1 km2 resolution in Iraq region for any given MODIS average daily LST of this area.
Eliciting Bid Taker Non-price Preferences in (Combinatorial) Auctions

Recent algorithms provide powerful solutions to the problem of determining cost-minimizing (or revenue-maximizing) allocations of items in combinatorial auctions. However, in many settings, criteria other than cost (e.g., the number of winners, the delivery date of items, etc.) are also relevant in judging the quality of an allocation. Furthermore, the bid taker is usually uncertain about her preferences regarding tradeoffs between cost and nonprice features. We describe new methods that allow the bid taker to determine (approximately) optimal allocations despite this. These methods rely on the notion of minimax regret to guide the elicitation of preferences from the bid taker and to measure the quality of an allocation in the presence of utility function uncertainty. Computational experiments demonstrate the practicality of minimax computation and the efficacy of our elicitation techniques.
Last call for the buffet: economics of cellular networks

Voice and data traffic growth over the last several years has become a major challenge for cellular operators with a direct impact on revenues, infrastructure investments, and end-user performance. The economics of these operators depend on various incentives used to attract users in the form of unlimited, buffet-like voice/sms/data packages. However, our understanding of the effects of user behavior under these offerings on operator revenues/costs remains poor. Using two years of detailed usage information of ~1 million users across three services, voice, sms and data, combined with payment and cost information, we study how user behavior affects the economics of cellular operators. We discover that around 20% of the users consume more resources than what they pay for and hence are non-profitable. In addition to the individual user behavior, we study how the user interactions in the call graph affect the operator's revenues and cost, drawing on tools from social network analysis. We develop a framework that incorporates both the individual and social user behavior for studying how volume caps influence the revenues and the traffic costs. Using this framework we empirically show that volume caps can increase the difference between the revenues and the traffic costs of the studied operator by a factor of 2, while affecting only 16% of the existing user base.
Purification of Rubbing Axis Trace by Harmonic Window Method

In order to purify rubbing axis trace, a novel purification way that does not need to decompose was proposed by using the harmonic window method. On the base of research for part decomposition in frequency domain, this method had the ability to decompose the arbitrary detail into frequency section, then the interested frequency band could be abstracted and reconstructed in time domain, so the purification of axis trace in one or more interested frequency bands could be realized. The advantage of harmonic window method in axis trace purification has been proved by the successful purification of firstly seven frequency sections from the miniature rotor test-bed’s vibration signals. This method also has simple algorithm and easy to be realized; it provides a new method for purification of rubbing axis trace. Keywords-harmonic window; rotor; rubbing; axis trace; purification
Genetics and molecular biology.

The transforming growth factor beta 1 (TGFB1) is a pro-inflammatory cytokine that plays a key role in the mechanisms of angiogenesis and breakdown of the blood-retina barrier, which are implicated in the pathogenesis of diabetic retinopathy (DR). Polymorphisms in the TGFB1 gene have been associated with DR; however, results are still contradictory. Therefore, the aim of this study was to investigate the potential association between two TGFB1 polymorphisms and DR. This study included 992 patients with diabetes mellitus (DM): 546 patients with DR (cases) and 446 patients without DR and with ≥10 years of DM (controls). The TGFB1 rs1800469 and rs1800470 polymorphisms were genotyped by real-time PCR. Frequency of rs1800469 T/T genotype was higher in controls compared to DR cases (18.3% vs. 12.7%, P= 0.022). This genotype remained associated with protection for DR, adjusting for covariables (OR= 0.604; 95% CI 0.395 – 0.923; P= 0.020, recessive model). The rs1800470 C/C genotype was observed in 25.4% of the controls and 18.0% of the cases (P= 0.015); thus, being associated with protection against DR under the recessive model (OR= 0.589; 95% CI 0.405 – 0.857; P= 0.006), adjusting for covariables. In conclusion, the TGFB1 rs1800469 and rs1800470 polymorphisms are associated with protection against DR in DM patients from Southern Brazil.
Chapter # Policy-based Agent Directability

Many potential applications for agent technology require humans and agents to work together to achieve complex tasks effectively. In contrast, most of the work in the agents community to date has focused on technologies for fully autonomous agent systems. This paper presents a framework for the directability of agents, in which a human supervisor can define policies to influence agent activities at execution time. The framework focuses on the concepts of adjustable autonomy for agents (i.e., varying the degree to which agents make decisions without human intervention) and strategy preference (i.e., recommending how agents should accomplish assigned tasks). These mechanisms enable a human to customize the operations of agents to suit individual preferences and situation dynamics, leading to improved system reliability and increased user confidence over fully automated agent systems. The directability framework has been implemented within a BDI environment, and applied to a multiagent intelligence-gathering domain.
Wintertime Atmospheric Blocking Events over Western Siberia in the Period 2004–2016 and Their Influence on the Surface Temperature Anomalies

We study wintertime blocking events in 2004–2016 over Western Siberia (WS) and their influence on the surface temperature. The period 2004–2016 is very interesting for study because there has been an increase in the blocking frequency over WS beginning with 2004. We used data ECMWF ERA-Interim and blocking criterion proposed by Tibaldi and Molteni. We investigated blockings events with duration of 5 days or more for winter interval (1 November–31 March). We have chosen 15 blockings events. For each event we calculate surface temperature anomaly in the grid points for two sectors 60–90 E; 50–60 N (southern part of WS) and 60–90 E; 60–70 N (northern part of WS). To estimate advective transfer for studied events we analyzed the potential temperature on the dynamical tropopause. We showed that wintertime blocking events over WS lead to the surface temperature increase in the northern part of West Siberia and to the surface temperature decrease in the southern part of WS. This feature apparently due to warm air masses advection from south-west on the western periphery of the blocking ridge and arctic air masses intrusion to the southern part of the WS on the eastern periphery of this ridge.
Predict Software Failure-prone by Learning Bayesian Network

We explore the software metrics and build a Bayesian Network Model for defect prediction. Much previous work has concentrated on how to select the software metrics that are most likely to indicate fault-proneness, based on the hypnosis that these metrics are independent. But in reality, software metric values are predicted not only correlated with fault-proneness, but also observed internal complex relationship with each other. In this paper, we build a Bayesian network model to represent the probability distribution of each factor and how they affect defects, considering strong or weak correlations are existed between individual metric attributes. We perform a comparative experimental study of effectiveness of Bayesian Network, logistic regression and Naive Bayes on a public data set from an open source software system. The result shows that our approach produces statistically significant estimations.