Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of varying the interval from follicular wave emergence to progestin withdrawal on follicular dynamics and the synchrony of estrus in beef cattle.

The objective of this experiment was to examine the effects of varying the interval from follicular wave emergence to progestin (controlled internal drug-releasing insert, CIDR) withdrawal on follicular dynamics and the synchrony of estrus. A secondary objective was to assess the effects of causing the dominant follicle (DF) to develop in the presence or absence of a corpus luteum (CL) on follicular dynamics and the synchrony of estrus and ovulation. The experiment was designed as a 2 x 2 x 2 factorial arrangement of treatments with injection of GnRH or estradiol-17 beta and progesterone (E2 + P4) at treatment initiation, duration of CIDR treatment, and injection of PG (prostaglandin F2 alpha) or saline at the time of CIDR insertion as main effects. Estrous cycles (n = 49) in Angus cows were synchronized, and treatments commenced on d 6 to 8 of the estrous cycle. Cows were randomly assigned to receive a CIDR containing 1.9 g of P4 for 7 or 9 d. Approximately half the cows from each CIDR group received either GnRH (100 micrograms) or E2 + P4 (1 mg of E2 + 100 mg of P4) at CIDR insertion. Cows in GnRH or E2 + P4 groups were divided into those that received PG (37.5 mg) or saline at CIDR insertion. All cows received PG (25 mg) 1 d before CIDR removal. Daily ovarian events were monitored via ultrasound. The intervals from GnRH or E2 + P4 treatment to follicular wave emergence were 1.4 and 3.3 d, respectively (P < 0.05). The interval from follicular wave emergence to CIDR removal was longer (P < 0.05) for cows treated with GnRH (6.6 d) than those treated with E2 + P4 (4.7 d) and longer (P < 0.05) for those fitted with a CIDR for 9 d (6.5 d) than those with a CIDR in place for 7 d (4.8 d). Cows treated with PG or GnRH at CIDR insertion had a larger (P < 0.05) DF at CIDR removal than those treated with saline or E2 + P4. Treatment with a CIDR for 9 d also resulted in a larger (P < 0.07) DF at CIDR removal compared with cows fitted with a CIDR for 7 d. The interval from CIDR removal to estrus was shorter (P < 0.05) in cows treated with PG than those treated with saline. The synchrony of estrus and ovulation was not affected by any of the treatments (P > 0.05). Altering the interval from follicular wave emergence to progestin removal or creating different luteal environments in which the DF developed caused differences in the size of the DF at CIDR removal and the timing of the onset of estrus, but it did not affect the synchrony of estrus or ovulation.
New Insights into Checkpoint Kinase 1 in the DNA Damage Response Signaling Network

The DNA damage response (DDR) represents a complex network of multiple signaling pathways involving cell cycle checkpoints, DNA repair, transcriptional programs, and apoptosis, through which cells maintain genomic integrity following various endogenous (metabolic) or environmental stresses. In cancer treatment, the DDR occurs in response to various genotoxic insults by diverse cytotoxic agents and radiation, representing an important mechanism limiting chemotherapeutic and radiotherapeutic efficacy. This has prompted the development of agents targeting DDR signaling pathways, particularly checkpoint kinase 1 (Chk1), which contributes to all currently defined cell cycle checkpoints, including G1/S, intra-S-phase, G2/M, and the mitotic spindle checkpoint. Although numerous agents have been developed with the primary goal of enhancing the activity of DNA-damaging agents or radiation, the therapeutic outcome of this strategy remains to be determined. Recently, new insights into DDR signaling pathways support the notion that Chk1 represents a core component central to the entire DDR, including direct involvement in DNA repair and apoptotic events in addition to checkpoint regulation. Together, these new insights into the role of Chk1 in the DDR machinery could provide an opportunity for novel approaches to the development of Chk1 inhibitor strategies. Clin Cancer Res; 16(2); 376–83
Recommend-Me: recommending query regions for image search

In typical image retrieval systems, to search for an object, users must specify a region bounding the object in an input image. There are situations that the queried region does not have any match with regions in images of the retrieved database. Finding a region in the input image to form a good query, which certainly returns relevant results, is a tedious task because users need to try all possible query regions without prior knowledge about what objects are really existed in the database. This paper presents a novel recommendation system, named Recommend-Me, which automatically recommends good query regions to users. To realize good query regions, their matches in the database must be found. A greedy solution based on evaluating all possible region pairs, given a pair is formed by one candidate region in the input image and one region in an image of the database, is infeasible. To avoid that, we propose a two-stage approach to significantly reduce the search space and the number of similarity evaluations. Specifically, we first use inverted index technique to quickly filter out a large number of images having insufficient similarities with the input image. We then propose and apply a novel branch-and-bound based algorithm to efficiently identify region pairs with highest scores. We demonstrate the scalability and performance of our system on two public datasets of over 100K and 1 million images.
Tracking Endocardium Using Optical Flow along Iso-Value Curve

In cardiac image analysis, optical flow techniques are widely used to track ventricular borders as well as estimate myocardial motion fields. The optical flow computation is typically performed in Cartesian coordinates, and not constrained from a priori knowledge of normal myocardium deformation patterns. However, for cardiac motion analysis, displacements along specific directions and their derivatives are usually more interesting than 2D or 3D displacement fields themselves. In this context, we propose a general frame work on optical flow estimation along iso-value curves. We applied the proposed framework in a specific application: for endocardium tracking on cine cardiac MRI series. The endocardial surfaces tracked with the proposed algorithm were quantitatively compared with manual tracing at each frame. The proposed method was also compared to the regular Lucas-Kanade optical flow method directly applied to MRI image data in Cartesian coordinates. Quantitative comparison showed a positive improvement in average tracking errors, through the whole cardiac cycle
Human-robot cooperative manipulation with motion estimation

A control method of robots for human-robot cooperative manipulation is investigated. We propose estimating human motion using the minimum jerk model for smooth cooperation. Using a nonlinear least-squares method, we identify two parameters of the minimum jerk model in real-time. The estimated position of the human hand is used to determine the desired position of the end-effector of the manipulator in virtual compliance control. The effectiveness of the proposed method is verified by experimentation with an industrial 6-degree-of-freedom manipulator. Energy transfer in cooperative manipulation is studied for quantitative evaluation of achieved cooperation from the viewpoint of adaptation theory.
Relations of granular worlds

In this study, we are concerned with a two-objective development of information granules completed on a basis of numeric data. The first goal of this design concerns revealing and representing a structure in a data set. As such it is very much oriented towards coping with the underlying relational aspects of the experimental data. The second goal deals with a formation of a mapping between information granules constructed in two spaces (thus it concentrates on the directional aspect of information granulation). The quality of the mapping is directly affected by the information granules over which it operates, so in essence we are interested in the granules that not only reflect the data but also contribute to the performance of such a mapping. The optimization of information granules is realized through a collaboration occurring at the level of the data and the mapping between the data sets. The operational facet of the problem is cast in the realm of fuzzy clustering. As the standard techniques of fuzzy clustering (including a well-known approach of FCM) are aimed exclusively at the first objective identified above, we augment them in order to accomplish sound mapping properties between the granules. This leads to a generalized version of the FCM (and any other clustering technique for this matter). We propose a generalized version of the objective function that includes an additional collaboration component to make the formed information granules in rapport with the mapping requirements (that comes with a directional component captured by the information granules). The additive form of the objective function with a modifiable component of collaborative activities makes it possible to express a suitable level of collaboration and to avoid a phenomenon of potential competition in the case of incompatible structures and the associated mapping. The logic-based type of the mapping (that invokes the use of fuzzy relational equations) comes as a consequence of the logic framework of information granules. A complete optimization method is provided and illustrated with several numeral studies.
A GPGPU accelerated descriptor for mobile devices

We present a modified upright SURF feature descriptor for mobile phone GPUs. Our implementation called uSURF-ES is multiple times faster than a comparable CPU variant on the same device. Our results proof the feasibility of modern mobile graphics accelerators for GPGPU tasks especially for the detection phase in natural feature tracking used in Augmented Reality applications.
Large Scale Use of Common Sense for Activity Recognition and Analysis

The problem of human activity recognition has attracted increasing interest in recent years. Systems capable of recognizing activities of daily living (ADLs) would be of use in assisting in human monitoring; for example, those suffering from cognitive disorders could be more easily supervised or assisted with such systems. Here we propose a model for a system designed to (1) recognize ADLs based on collected sensor data and (2) reason about the state of the user’s environment based on this data. Two particular difficulties with producing such a system are the difficulty in providing enough labeled activity data to learn a model of human activity, and the difficulty in providing the “common sense” data that such a system needs to reason about the state of the environment. We propose solutions to both of these problems using two major sources of large-scale common sense data: publicly available collaborative knowledge bases such as the Open Mind Indoor Common Sense (OMICS) database, and the World Wide Web. Using data mined from these sources, we will produce a model of everyday human activity and seed the system with necessary common sense information to analyze the context and results of such activity.
Implications of Oxytocin in Human Linguistic Cognition: From Genome to Phenome

The neurohormone oxytocin (OXT) has been found to mediate the regulation of complex socioemotional cognition in multiple ways both in humans and other animals. Recent studies have investigated the effects of OXT in different levels of analysis (from genetic to behavioral) chiefly targeting its impact on the social component and only indirectly indicating its implications in other components of our socio-interactive abilities. This article aims at shedding light onto how OXT might be modulating the multimodality that characterizes our higher-order linguistic abilities (vocal-auditory-attentional-memory-social systems). Based on evidence coming from genetic, EEG, fMRI, and behavioral studies, I attempt to establish the promises of this perspective with the goal of stressing the need for neuropeptide treatments to enter clinical practice.
Regulators of epithelial mesenchymal transition in pancreatic cancer

Pancreatic cancer is a leading cause of cancer-related death due to its invasive nature. Despite the improvement of diagnostic strategy, early diagnosis of pancreatic cancer is still challenging. Surgical resection is the only curative therapy, while vast majority of patients are not eligible for this therapeutic option. Complex biological processes are involved in the establishment of invasion and metastasis of pancreatic cancer and epithelial-mesenchymal transition (EMT) has been reported to play crucial role. EMT is part of the normal developmental processes which mobilizes epithelial cells and yields mesenchymal phenotype. Deregulation of EMT inducing molecules in pancreatic cancer is reported, such as multiple cytokines, growth factors and downstream transcriptional factors. In addition to these molecules, non-coding RNA including miRNA also contributes to EMT. EMT of cancer cell also correlates with cancer stem cell (CSC) properties such as chemoresistance or tumorigenicity, therefore these upstream regulators of EMT could be attractive therapeutic targets and several candidates are examined for clinical application. This review summarizes recent advances in this field, focusing the regulatory molecules of EMT and their downstream targets. Further understanding and research advances will clarify the cryptic mechanism of cancer metastasis and delineate novel therapeutic targets.
Sonography of the Acetabular Labrum

Objective. The purpose of this series was to describe the improved conspicuity in the sonographic appearance of acetabular labral injuries during routine sonographically guided intra‐articular injections. Methods. Sonographic examinations of patients undergoing routine sonographically guided intra‐articular hip injections were reviewed for evidence of labral injuries (n = 21). Sonographic examinations were then correlated with magnetic resonance images of the ipsilateral hip when available (n = 14). Results. Before injection, 13 acetabular labra had linear or irregular hypoechoic clefts or fissures through the normally hyperechoic fibrocartilaginous labrum, thought to represent tears. Eight of the labra showed a more globular alteration in morphologic characteristics, with diffuse thickening and irregularity. During intra‐articular injection, the visualized injected fluid outlined the labrum, yielding a “sonoarthrographic effect,” providing a fluid interface along the labral boundaries, and confirming the presence of a tear by imbibition of injected material into the defect with a resultant subjective improvement in the labral injury. Conclusions. Evaluating the labrum after injection may improve visualization of labral injuries, as a result of greater labral conspicuity.
Sound representations underlying the duration mismatch negativity (MMN) in a rapid dichotic listening task

The locus of auditory attention’s influence has been controversial. Mismatch negativity (MMN), a component of the event-related potential (ERP) theorised to reflect an auditory change-detecting comparator, is used to investigate this matter. Some theories place attentive influence prior to this MMN comparator, and cite attentive modulation of the MMN component amplitude as evidence. Other theories argue that attention alters only the comparator output, leaving the inputs unaffected. This thesis aims to test whether attention influences the MMN comparator input. Duration change MMN is examined in experiments applying robust control of attention through the use of a rapid dichotic listening task. Experiment 1 confirmed the sole existing report of modulation of the duration MMN amplitude by attention. To distinguish whether this modulation reflected change to the comparator inputs or simply to the output, Experiment 2 followed a previous suggestion to investigate whether attention also shifted the threshold for duration MMN elicitation. No threshold shift was found. Seemingly, attention did not affect the MMN comparator inputs. Subsequently, an attention mechanism in which the sensory data of stimuli at the attentive focus was segregated away from all other sensory data, was proposed. For such a mechanism, use of a dichotic listening task paradigm with only two sets of sounds meant that segregation of the attended set of sounds also implied segregation (and hence equivalent attentional benefit) for the other (unattended) set. Experiment 3 demonstrated highly segregated and independently-changeable MMN duration representations. Experiment 4 proposed that presentation of three or more sets of sounds, one set attended, would demonstrate fusion of the multiple unattended sound sets. Evidence for this was found. It was concluded that (1) attention acted prior to the MMN comparator by segregating the attended sound representation; (2) that, despite a high level of independence of the segregated representation, attention did not modify the sensory information of either the attended or unattended sounds, contrary to filtering theories; and (3) a collective representation of multiple unattended sets of sounds arises, even when auditory scene analysis suggests they might segregate.
DNA Methylation Supports Intrinsic Epigenetic Memory in Mammalian Cells

We have investigated the role of DNA methylation in the initiation and maintenance of silenced chromatin in somatic mammalian cells. We found that a mutated transgene, in which all the CpG dinucleotides have been eliminated, underwent transcriptional silencing to the same extent as the unmodified transgene. These observations demonstrate that DNA methylation is not required for silencing. The silenced CpG-free transgene exhibited all the features of heterochromatin, including silencing of transcriptional activity, delayed DNA replication, lack of histone H3 and H4 acetylation, lack of H3-K4 methylation, and enrichment in tri-methyl-H3-K9. In contrast, when we tested for transgene reactivation using a Cre recombinase-mediated inversion assay, we observed a marked difference between a CpG-free and an unmodified transgene: the CpG-free transgene resumed transcription and did not exhibit markers of heterochromatin whereas the unmodified transgene remained silenced. These data indicate that methylation of CpG residues conferred epigenetic memory in this system. These results also suggest that replication delay, lack of histone H3 and H4 acetylation, H3-K4 methylation, and enrichment in tri-methyl-H3-K9 are not sufficient to confer epigenetic memory. We propose that DNA methylation within transgenes serves as an intrinsic epigenetic memory to permanently silence transgenes and prevent their reactivation.
RELIABILITY AND ACCURACY OF NEURAL NETWORKS FOR EXCHANGE RATE

Most exchange rates are volatile and mainly rely on the principle of supply and demand. Millions of people around the world are influenced, one way or another, by the variation in exchange rates. In this research we demonstrate that the Artificial Intelligence, specifically Artificial Neural Networks (ANN), can improve the accuracy of forecasting exchange rates compared to statistical techniques such as regression. When we compared the results from regression and artificial neural network, it was clear that the ANN outperformed regression in forecasting exchange rates. Moreover, it became clear that using ANNs instead of regression for forecasting exchange rates is rewarding and necessary because the average error given by an ANN is smaller than the average error given by regression. Accuracy in forecasting became a major issue and not a minor detail. It was the combination between Artificial Intelligence and Macro Economics that made these two models come into reality, making it possible to use computer sciences and engineering fields in the service of an economical problem. The results of our research showed that using ANN with the right parameters and variables rather than using a regression model will yield a result with a lower error margin.
Characterization of muscarinic acetylcholine receptors in the avian salt gland

Electrolyte and fluid secretion by the avian salt gland is regulated by activation of muscarinic acetylcholine receptors (R). In this study, these receptors were characterized and quantitated in homogenates of salt gland from domestic ducks adapted to conditions of low (freshwater, FW) and high (saltwater, SW) salt stress using the cholinergic antagonist [3H]-quinuclidinyl benzilate (QNB). Specific binding of the antagonist to receptors in both FW- and SW-adapted glands reveals a single population of high affinity binding sites (KdFW = 40.1 +/- 3.0 pM; KdSW = 35.1 +/- 2.1 pM). Binding is saturable; RLmaxFW = 1.73 +/- 0.10 fmol/micrograms DNA; RLmaxSW = 4.16 +/- 0.31 fmol/micrograms DNA (where L is [3H]QNB and RL the high affinity complex). Calculated average cellular receptor populations of 5,800 sites/cell in FW-adapted glands and 14,100 sites/cell in SW-adapted glands demonstrate that upward regulation of acetylcholine receptors in the secretory epithelium follows chronic salt stress. The receptor exhibits typical pharmacological specificities for muscarinic cholinergic antagonists (QNB, atropine, scopolamine) and agonists (oxotremorine, methacholine, carbachol). In addition, the loop diuretic furosemide, which interferes with ion transport processes in the salt gland, competitively inhibits [3H]QNB binding. Preliminary studies of furosemide effects on [3H]QNB binding to rat exorbital lacrimal gland membranes showed a similar inhibition, although the diuretic had no effect on antagonist binding to rat brain or atrial receptors.
Neural Network Based Sliding Mode Control for Uncertain Discrete-Time Nonlinear Systems with Time-Varying Delay

The present paper discusses the stability analysis of discrete-time uncertain nonlinear systems with time-varying delay, uncertainties related to parametric uncertainty and unknown nonlinearity. The time-varying delay considered has minimum and maximum bounds. The novelty of Chebyshev Neural Network (CNN) is that it requires much less computation time as compared to multi layer neural network (MLNN) and radial basis function network (RBFN). It is preferred to approximate the unknown nonlinearities. Furthermore, results for robust stabilization of discrete-time uncertain nonlinear systems with timevarying delay are given on the basis of linear matrix inequalities (LMI). The sufficient condition is derived for the asymptotic stability of the defined systems. The proposed controller guarantees the system state trajectory to the designed sliding surface in the presence of uncertainties and time-varying delay. Simulation results illustrate the validity of the proposed approach. Key-words: Chebyshev Neural Network; Sliding Mode Control; Linear Matrix Inequalities; Lyapunov-Krasovskii Function; Time-varying Delay
Carrier-based PWM for Z-Source Inverters

Z-Source Inverters have the ability to boost the dc link voltage, thus increasing the output ac voltage beyond the values reached by conventional inverters. The enhanced ratio from ac output voltage to dc link voltage is possible due to an impedance network connected between the dc power supply and the main converter. In order to boost the voltage, shoot-through states are needed. Shoot-through is produced by the inverter legs, thus shoot-through states have to be embedded into the modulation. Moreover, root-mean-square values of current and voltage in the Z-source depends on the modulation technique. Therefore, the inverter efficiency also depends on the modulation. This paper presents one way to embed shoot-through states in a standard carrier-based PWM. This novel technique is easy to implement, assures the best dc link utilisation, avoids extra switching for the shoot-through states, and equates the conduction losses obtained by other z-source modulators.