Miracle-dz/UniFAR-FTUs huggingface dataset:
Fecal Microbiota Transplant From Highly Feed Efficient Donors Affects Cecal Physiology and Microbiota in Low- and High-Feed Efficient Chickens

Fecal microbiota transplants (FMT) may be used to improve chicken’s feed efficiency (FE) via modulation of the intestinal microbiota and microbe-host signaling. This study investigated the effect of the administration of FMT from highly feed efficient donors early in life on the jejunal and cecal microbiota, visceral organ size, intestinal morphology, permeability, and expression of genes for nutrient transporters, barrier function and innate immune response in chickens of diverging residual feed intake (RFI; a metric for FE). Chicks (n = 110) were inoculated with the FMT or control transplant (CT) on 1, 6, and 9 days posthatch (dph), from which 56 chickens were selected on 30 dph as the extremes in RFI, resulting in 15 low and 13 high RFI chickens receiving the FMT and 14 low and 14 high RFI chickens receiving the CT. RFI rank and FMT only caused tendencies for alterations in the jejunal microbiota and only one unclassified Lachnospiraceae genus in cecal digesta was indicative of high RFI. By contrast, the FMT caused clear differences in the short-chain fatty acid (SCFA) profile in the crop and cecal microbiota composition compared to the CT, which indicated alterations in amylolytic, pullulanolytic and hemicellulolytic bacteria such as Lactobacillus, Dorea, and Ruminococcus. Moreover, the FMT caused alterations in intestinal development as indicated by the longer duodenum and shallower crypts in the ceca. From the observed RFI-associated variation, energy-saving mechanisms and moderation of the mucosal immune response were indicated by higher jejunal permeability, shorter villi in the ileum, and enhanced cecal expression of the anti-inflammatory cytokine IL10 in low RFI chickens. Relationships obtained from supervised multigroup data integration support that certain bacteria, including Ruminococcocaceae-, Lactobacillus-, and unclassified Clostridiales-phylotypes, and SCFA in jejunal and cecal digesta modulated expression levels of cytokines, tight-junction protein OCLN and nutrient transporters for glucose and SCFA uptake. In conclusion, results suggest that the intestine only played a moderate role for the RFI-associated variation of the present low and high RFI phenotypes, whereas modulating the early microbial colonization resulted in long-lasting changes in bacterial taxonomic and metabolite composition as well as in host intestinal development.
On the Complexity of String Matching for Graphs

Exact string matching in labeled graphs is the problem of searching paths of a graph G=(V, E) such that the concatenation of their node labels is equal to a given pattern string P[1.m]. This basic problem can be found at the heart of more complex operations on variation graphs in computational biology, of query operations in graph databases, and of analysis operations in heterogeneous networks. We prove a conditional lower bound stating that, for any constant ε > 0, an O(|E|1 - ε m) time, or an O(|E| m1 - ε)time algorithm for exact string matching in graphs, with node labels and pattern drawn from a binary alphabet, cannot be achieved unless the Strong Exponential Time Hypothesis (SETH) is false. This holds even if restricted to undirected graphs with maximum node degree 2—that is, to zig-zag matching in bidirectional strings, or to deterministic directed acyclic graphs whose nodes have maximum sum of indegree and outdegree 3. These restricted cases make the lower bound stricter than what can be directly derived from related bounds on regular expression matching (Backurs and Indyk, FOCS’16). In fact, our bounds are tight in the sense that lowering the degree or the alphabet size yields linear time solvable problems. An interesting corollary is that exact and approximate matching are equally hard (i.e., quadratic time) in graphs under SETH. In comparison, the same problems restricted to strings have linear time vs quadratic time solutions, respectively (approximate pattern matching having also a matching SETH lower bound (Backurs and Indyk, STOC’15)).
A New Feature Extraction Method for Ship-Radiated Noise Based on Improved CEEMDAN, Normalized Mutual Information and Multiscale Improved Permutation Entropy

Extracting useful features from ship-radiated noise can improve the performance of passive sonar. The entropy feature is an important supplement to existing technologies for ship classification. However, the existing entropy feature extraction methods for ship-radiated noise are less reliable under noisy conditions because they lack noise reduction procedures or are single-scale based. In order to simultaneously solve these problems, a new feature extraction method is proposed based on improved complementary ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), normalized mutual information (norMI), and multiscale improved permutation entropy (MIPE). Firstly, the ICEEMDAN is utilized to obtain a group of intrinsic mode functions (IMFs) from ship-radiated noise. The noise reduction process is then conducted by identifying and eliminating the noise IMFs. Next, the norMI and MIPE of the signal-dominant IMFs are calculated, respectively; and the norMI is used to weigh the corresponding MIPE result. The multi-scale entropy feature is finally defined as the sum of the weighted MIPE results. Experimental results show that the recognition rate of the proposed method achieves 90.67% and 83%, respectively, under noise free and 5 dB conditions, which is much higher than existing entropy feature extraction algorithms. Hence, the proposed method is more reliable and suitable for feature extraction of ship-radiated noise in practice.
Fully Convolutional Networks for Automatic Pavement Crack Segmentation

Pavement cracks are an increasing threat to public safety. Automatic pavement crack segmentation remains a very challenging problem due to crack texture inhomogeneity, high outlier potential, large variability of topologies, and so on. Due to this, automatic pavement crack detection has captured the attention of the computer vision community, and a great quantity of algorithms for solving this task have been proposed. In this work, we study a U-Net network and two variants for automatic pavement crack detection. The main contributions of this research are: 1) two U-Net based network variations for automatic pavement crack detection, 2) a series of experiments to demonstrate that the proposed architectures outperform the state-of-the-art for automatic pavement crack detection using two public and well-known challenging datasets: CFD and AigleRN and 3) the code for this approach.
An automatic segmentation algorithm for moving objects in video sequences under multi-constraints

A new algorithm under multi-constraints for automatic segmentation of video moving objects is proposed. First, the temporal segmentation separates the initial areas including moving objects accurately from the background by continuous frame difference. Then, the spatial segmentation segments the initial areas into spatially consistent regions by the watershed algorithm based on a color gradient. Finally, regions are classified as foreground/background by maximizing the a posterior probability (MAP) of the MRF with spatial, temporal and adjacent constraints. Experimental results demonstrate that the algorithm is not sensitive to objects' irregular movement and illumination, and it can extract moving video objects accurately.
Determination of Arylamine N-Acetyltransferase 2 Acetylation Genotype by PCR and Phenotyping Using Dapsone Through High-Pressure Liquid Chromatography Assay: A Gender Wise Study

The main aim of the study was to establish the acetylation status of local population of Pakistan by N-acetyltransferase 2 (NAT2) enzyme and to find out the concordance between phenotypic and genotypic methods for the determination of NAT2 acetylation. Gender-wise comparison of selected healthy male and female volunteers aged greater than 18 years was also conducted to see the effect of sex on NAT2 acetylation. Phenotypically, the rate of acetylation was determined by high-pressure liquid chromatography with dapsone (DDS) probe drug, while genotypically, NAT2 acetylation was determined by using specific primers for NAT2 variant alleles (M1, M2, and M3) amplified in separate polymerase chain reactions. High-pressure liquid chromatography results indicated 64% of the male volunteers to be fast acetylators while 36% were slow acetylators, while ratio of fast and slow acetylators for female was found to be 66% and 34%, respectively. Genotypically, the ratio of fast and slow for male was 60% and 40% and for female was 66% and 34%, respectively. The distribution of 3 NAT2 variant alleles was found in invariable number. For male volunteers, the highest frequency distribution showed by M2 allele was 56%, while for M1 and M3 the frequency was 32% and 12%, respectively, and for female volunteers highest frequency (51%) was shown by the M2 variant allele while lowest frequency (18%) was shown by M3 allele. There was the 94% concordance between the DDS phenotype and genotype. Gender effect on the acetylation was found to be nonsignificant (P > .05). Therefore, it is concluded that NAT2 acetylation rate can be used to check in vivo acetylation status with dapsone as probe drug. It is concluded that NAT2 acetylation rate was unaffected by gender and can be used to check in vivo acetylation status with dapsone as probe drug, which is inexpensive and less time-consuming.
Phosphorus Consumption Within 1 Hour Prior to Blood Work and Associated Serum Levels of Phosphate, Calcium, and PTH in Adult Patients Receiving Hemodialysis Treatment

Background: While dietary intake is known to influence serum markers of chronic kidney disease–mineral and bone disorder (CKD-MBD), the effects of recent food and beverage intake, particularly phosphorus consumption on these serum markers (phosphate, calcium, and parathyroid hormone [PTH]), are unknown in hemodialysis patients. An understanding of these effects could have direct and important implications on the management of CKD-MBD. Objective: To determine whether serum phosphate, calcium, and PTH levels were higher in hemodialysis patients who had consumed dietary phosphorus within 1 hour prior to their routine dialysis-related blood work (non–phosphorus-fasted) compared with patients who did not (phosphorus-fasted). Design: Observational, cross-sectional study. Setting: Kingston Health Sciences Center—Kingston General Hospital Site and its affiliated satellite hemodialysis units. Patients: Two hundred fifty-four adult patients receiving outpatient hemodialysis treatment for end-stage kidney disease were recruited. Measurements: The main measurements for this study included an assessment of dietary phosphorus intake as well as serum phosphate, calcium, PTH, albumin, Kt/V, and urea reduction ratio. Methods: A direct patient interview was performed to assess dietary phosphorus intake within 1 hour prior to routine dialysis-related blood work. The Canadian Nutrient File was then used to estimate dietary phosphorus based on the specific foods and beverages (including portion sizes and brands where applicable) identified in the interview. Serum measures of phosphate, PTH, calcium, albumin, and dialysis adequacy (Kt/V and urea reduction ratio) were obtained from participants’ routine dialysis-related blood work. Results: Non–phosphorus-fasted participants had nonsignificantly higher serum PTH levels compared to phosphorus-fasted participants (61.2 ± 64.7 vs 47.9 ± 39.7, P = .05). Non–phosphorus-fasted participants with PTH levels at the Kidney Disease Improving Global Outcomes (KDIGO) “target” (between 15 and 60 pmol/L) had significantly higher serum phosphate levels relative to phosphorus-fasted participants (1.6 ± 0.3 vs 1.4 ± 0.4, P = .006). In non–phosphorus-fasted participants, there was a nonsignificant association between the number of items containing inorganic phosphate additives and higher levels of serum phosphate and lower levels of serum calcium. Limitations: Some limitations include the cross-sectional nature of this study, self-reporting biases and estimates (as opposed to direct measurements) related to the dietary assessment, and the use of single (and not serial) assessments of serum measures. Conclusions: Dietary phosphorus intake in close proximity to blood work may contribute to subtle alterations in some key serum CKD-MBD parameters in adult outpatient hemodialysis patients but may not meaningfully alter CKD-MBD management.
Control of large discrete event systems: constructive algorithms

An automata-based theory has been developed by W.M. Wonham and P.J. Ramadge (SMIA J. Control Optimiz. vol.25, p.206-30, 637-59, 1987) and their associates. Its practical implementation in large real-life systems requires automatic programming schemes, which yield supervisory control programs, and models of the controlled system's behavior (for the purpose of performance analysis). The available data for these constructions would normally consist of a set of local structural models and local operational requirements. In the present study, the authors illuminate the relationship between local and global models and outline some of the basic elements of such schemes based on integration of local data. >
A study on apportionment of credits of fuzzy classifier system for knowledge acquisition of large scale systems

This paper studies a knowledge acquisition of large scale systems using a fuzzy classifier system (FCS). A new method for apportionment of credits is proposed in this paper. The new method makes it possible to fully utilize the feature of the genetic algorithm, i.e. the effects of the crossover operator. Simulations to obtain avoiding rules of a ship are done to show that the FCS can acquire fuzzy rules for complex tasks. <<ETX>>
A PC-based software tool for statistical pattern classifier design

Interactive software systems for pattern analysis and recognition represent powerful scientific, research and development tools for pattern recognition system design. In this paper, we discuss one such scientific software system, named PC-PARIS (Pattern Analysis and Recognition Interactive System for PC compatible computers). A variety of pattern recognition and clustering algorithms, implemented in PC-PARIS, is briefly described. As application examples, we present sensitivity analysis of statistical pattern classifiers, implemented in PC-PARIS, to the increasing number of features in the limited training data set conditions, for both synthesized and real data classification.
Probe-based admission control for multicast

End-to-end measurement based admission controls (MBAC) have recently been proposed to support quality of service for real-time transfer of data. All these designs share the idea of decentralizing the admission decision by requiring each end host to probe the network before transmission. These schemes are solely targeted at unicast communications, while multicast data has not yet been addressed. We study a probing procedure to perform admission decisions for multicast senders and receivers. The admission control offers a reliable upper bound on the packet loss for the multicast session even with short probe phase durations (e.g. half a second). Our probing mechanism only requires the routers to differentiate between two classes of packets: high priority data and low priority probes. Simulation results of the performance of the procedure are presented and evaluated.
Design Optimization of Energy and Delay Efficient Wireless Sensor Network with the help of Particle Swarm Optimization and Cluster based Least Spanning Tree Algorithm

In WSN sensors are randomly deployed in the sensor field which brings the coverage problem and limited energy resources. Hence energy and coverage problem are very scarce resources for such sensor systems and has to be managed wisely in order to extend the life of the sensors and maximizing coverage for the duration of a particular mission. In past a lot of cluster based algorithm and techniques were used. In this paper we propose combination of PSO based algorithm and cluster based Least Spanning Tree algorithm, which are very effective alone for WSN, and we also obtain life of sensor node and data transmission by LST based PSO algorithm. These techniques effectively overcome the problems of low energy and coverage of
Performance evaluation framework and quality of service issues for mobile ad hoc networks in the MOSAIC ATD

This paper identifies and describes the issues facing quality of service (QoS) provisioning in multihop mobile ad hoc networks, particularly in tactical environments such as those described by the multifunctional on-the-move secure adaptive integrated communications (MOSAIC) advanced technology demonstration (ATD). The MOSAIC ATD focuses on integrating a highly adaptive communications infrastructure that supports the seamless flow of multi-media services across terrestrial and space based platforms using advanced QoS techniques, ad hoc networking, bandwidth management, and traffic scaling. The paper first discusses issues and challenges related to wireless communications in tactical mobile ad hoc networks and then describe some performance evaluation criteria that should be used to assess the capabilities of network protocols as they operate in such environments. It also identifies issues associated with QoS, presents some parameters that should be used to evaluate QoS support, and discusses some solutions in order to support QoS in ad hoc networks and wireless ATM. Finally it concludes with areas of future work that would be appropriate for the extension of QoS technologies.
A New Graph Theory based Routing Protocol for Wireless Sensor Networks

Energy efficiency in wireless sensor network [WSN] is the highly sorted area for the researchers. Number of protocols has been suggested for energy efficient information gathering for sensor networks. These protocols come under two broad categories called tree based approach and clustering techniques. In these techniques clustering is more suitable for real time applications and has much more scalability factor when compared with its previous counterpart. This paper presents the importance and factors affecting the clustering. Also this paper surveyed the different clustering algorithms with its extensions till date and proposed the clustering technique using Minimum Spanning Tree [MST] and shortest path concept with its strength and limitations.
Analysis of S-Circuit Uncertainty

Analysis of S-Circuit Uncertainty. (April 2011) Taahir David Ahmed Department of Electrical and Computer Engineering Department of Physics Texas A&M University Research Advisor: Dr. Dylan Shell Department of Computer Science and Engineering The theory of sensori-computational circuits provides a capable framework for the description and optimization of robotic systems, including on-line optimizations. This theory, however, is inadequate in that it does not account for uncertainty in a robot’s environment, sensing, and control. In order to allow meaningful optimization of robotic systems, a method for estimating the output uncertainty of an s-circuit in terms of the uncertainty in its input is formulated. This method is expressly designed to have low information requirements, to ensure that it is feasible to apply in practice. The method is subjected to experimental verification on two representational s-circuits, which confirms the validity of its predictions.
A generalized design method for multifunction converters used in a photovoltaic system

In this paper, a general design method for multifunction converters using photovoltaic systems is proposed. With the proposed converter, the photovoltaic generator can provide flexibility, accuracy, and fast responses in both harmonic suppression and power injection modes in all cases of the grid-connected load. The controller for the proposed converter is designed based on the Lyapunov technique, along with the generalized algorithm for determining the global optimal values of the stability bounds. Therefore, the proposed converter can perform accurately and efficiently in the case of fixed system parameters as well as in the case of varying system parameters. Simulations and experimental results are presented to validate the accuracy and effectiveness of the proposed model and control strategy.
ON THE THROUGHPUT GAIN OF RAPID SYMBOL DURATION ADAPTATION WITH DYNAMIC SPREADING GAIN CONTROL

In [1] [2], methods for symbol-by-symbol (SBS) channel feedback and symbol duration adaptation by rapid dynamic spreading gain control were proposed by the authors. Previous research showed that, in an uncoded system, the symbol-by-symbol duration adaptation can theoretically achieve a throughput gain by orders of magnitude over non-adaptation or a frame-by-frame (FBF) adaptation in a fast time-varying fading environment. This thesis extends the study of the throughput gain to the cases in which, the symbol duration can only be chosen from a discrete finite set, the channel is varying during each symbol duration, and the duration adaption is implemented in a coded system. The results show that for an uncoded system the throughput gain is still significant even within discrete duration sets and over the channel varying during each symbol duration. In coded systems, the performance depends on the coding scheme and the interleaver size. For many commonly used codes without interleaving, symbol-by-symbol duration adaptation can also bring a large throughput gain. However, if the system adopts a superior forward error correction (FEC) code, e.g., DVB-S2 LDPC codes, or if the system employs a large size interleaver to make the channel much less time correlated, there will be little benefit to apply SBS duration adaptation to increase the throughput. This thesis also presents the analysis on the throughput gain with outdated and imperfect channel information. The numerical results illustrates how the throughput gain will diminish as the correlation between the available channel information and the true channel condition decreases.
A novel torsional microactuator using bulk PZT

A torsional microactuator was developed using standard bulk lead zirconium titanate placed upon a small rectangular prism made from phosphor bronze, with a tapered conical end serving as a horn and a carefully machined interior to improve the actuator's response. The results of testing indicate torsional motion was obtained from the device, with torsional vibration velocities of 295 mm/s at 190 kHz being obtained at 27.5 V/sub RMS/ at the output, amounting to 19,320 deg/sec vibration velocity along the outer circumference of the tip. A new method for measuring the actuator characteristics is described, and the method was used to measure the torque versus speed performance of the actuator system at 189.6 kHz, where a peak speed of 800 rpm and a peak torque of 0.27 mN-m were achieved.
RELIABILITY MODELLING WITH FUZZY COVARIATES

In this research, we focus on covariate modelling to explore the interactions between industrial system and its enviroment in terms of the modelling fundamental characteristic — random and fuzzy uncertaity with an intention to decrease the fatal weakness of the modern dissection methodology. We extend the additive and multiplicative covariate models from these considering randomness alone into these considering both randomness and fuzziness in the sense as a mathematical extension to the existing covariate modelling. In terms of the form of logical function an engineering oriented fuzzy reliability model which could potentially count all the aspects associated with an operating system and its environment is proposed. Statistical estimation on the parameters of system fuzzy reliability is considered based on the general theory of the point processes. The impacts on the optimal plant maintenance from the engineering oriented fuzzy reliability modelling is also discussed. Finally we use an industrial example to illustrate the main theoretical developments.