Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Different Doses of Fructooligosaccharides (FOS) on the Composition of Mice Fecal Microbiota, Especially the Bifidobacterium Composition

Fructooligosaccharides (FOS) are a well-known class of prebiotic and are considered to selectively stimulate the growth of bifidobacteria in the gut. Previous studies focused on the growth stimulation of Bifidobacterium, but they did not further investigate the bifidobacterial composition and the specific species that were stimulated. In this study, mice were fed with FOS in different doses for four weeks and the composition of fecal microbiota, in particular Bifidobacterium, was analyzed by sequencing the V3–V4 region and the groEL gene on the MiSeq platform, respectively. In the high-dose group, the relative abundance of Actinobacteria was significantly increased, which was mainly contributed by Bifidobacterium. At the genus level, the relative abundances of Blautia and Coprococcus were also significantly increased. Through the groEL sequencing, 14 species of Bifidobacterium were identified, among which B. pseudolongum was most abundant. After FOS treatment, B. pseudolongum became almost the sole bifidobacterial species (>95%). B. pseudolongum strains were isolated and demonstrated their ability to metabolize FOS by high performance liquid chromatography (HPLC). Therefore, we inferred that FOS significantly stimulated the growth of B. pseudolongum in mice. Further investigations are needed to reveal the mechanism of selectiveness between FOS and B. pseudolongum, which would aid our understanding of the basic principles between dietary carbohydrates and host health.
Face Detection With Different Scales Based on Faster R-CNN

In recent years, the application of deep learning based on deep convolutional neural networks has gained great success in face detection. However, one of the remaining open challenges is the detection of small-scaled faces. The depth of the convolutional network can cause the projected feature map for small faces to be quickly shrunk, and most detection approaches with scale invariant can hardly handle less than $15\times 15$ pixel faces. To solve this problem, we propose a different scales face detector (DSFD) based on Faster R-CNN. The new network can improve the precision of face detection while performing as real-time a Faster R-CNN. First, an efficient multitask region proposal network (RPN), combined with boosting face detection, is developed to obtain the human face ROI. Setting the ROI as a constraint, an anchor is inhomogeneously produced on the top feature map by the multitask RPN. A human face proposal is extracted through the anchor combined with facial landmarks. Then, a parallel-type Fast R-CNN network is proposed based on the proposal scale. According to the different percentages they cover on the images, the proposals are assigned to three corresponding Fast R-CNN networks. The three networks are separated through the proposal scales and differ from each other in the weight of feature map concatenation. A variety of strategies is introduced in our face detection network, including multitask learning, feature pyramid, and feature concatenation. Compared to state-of-the-art face detection methods such as UnitBox, HyperFace, FastCNN, the proposed DSFD method achieves promising performance on popular benchmarks including FDDB, AFW, PASCAL faces, and WIDER FACE.
Gestural Control of Augmented Instrumental Performance: A Case Study of the Concert Harp

We present a gestural control system to augment harp performance with real-time control of computer-based audio affects and processing. While the lightweight system was designed for use alongside any instrument, our choice of the concert harp represented a unique case study in gestural control of music. The instrument's large size and physically demanding playing technique leaves the performer with little spare bandwidth to devote to other tasks. A motion capture study analyzed instrumental and ancillary gestures of natural harp performances that could be mapped effectively to control of additional signal processing parameters. The initial findings of the study helped to guide the design of custom gesture control devices and user software, and a new work for solo harpist and electronics was created. We discuss our findings, successes and challenges in the study and design of gesture control for augmented instrumental performance, with particular focus on the concert harp.
Incorporating Consistency Verification into Neural Data-to-Document Generation

Recent neural models for data-to-document generation have achieved remarkable progress in producing fluent and informative texts. However, large proportions of generated texts do not actually conform to the input data. To address this issue, we propose a new training framework which attempts to verify the consistency between the generated texts and the input data to guide the training process. To measure the consistency, a relation extraction model is applied to check information overlaps between the input data and the generated texts. The non-differentiable consistency signal is optimized via reinforcement learning. Experimental results on a recently released challenging dataset ROTOWIRE show improvements from our framework in various metrics.
A Simple Active Power Control for a High-Power Wireless Power Transmission System Considering Coil Misalignment and Its Design Method

A series–series compensated capacitors topology of the wireless power transmission (WPT) system has a characteristic of increasing active power at coil misalignment when controlled using the conventional secondary dc-link voltage control. This results in a larger total capacity of the primary and secondary sides’ converters. To cope with these problems, this paper proposes a simple constant secondary active power control method, where the secondary dc-link voltage is regulated according to the onboard active power rating and secondary current. The effectiveness of the control method is verified by 100 W experimental systems. The numerical simulation that considers the harmonic components is established to be compared and justified by the experimental results, which is then used to design the capacity of a 300 kW WPT system assuming actual railway vehicle application. By the proposed method, the design criteria of the rating voltage and current of the primary and secondary sides’ components can be determined.
Reliable Planar Object Pose Estimation in Light Fields From Best Subaperture Camera Pairs

A light-field camera can obtain richer information about a scene than a usual camera. This property offers a lot of potential for robot vision. In this letter, we present a method for pose estimation of a planar object with a light-field camera. The light-field camera can be regarded as a set of subaperture cameras. Although any combination of them can theoretically be used for the pose estimation, the accuracy depends on the combination. We show that the estimated pose error can be reduced by selecting the best pair of subaperture cameras. We have evaluated the accuracy of our approach with real experiments using a light-field camera in front of planar targets held by an industrial manipulator for ground truth comparison.
A Single-Phase Inverter/Rectifier Topology With Suppressed Double-Frequency Ripple

This paper introduces a new bidirectional single-phase inverter topology. The proposed topology has three ports: a dc port, an ac port, and a ripple port. The ac and dc ports are bidirectional to support rectifier or inverter operation. A small inductor, which is of alternating current, exchanges power between different ports of the single-phase system. The proposed topology is capable of accomplishing voltage step-up or step-down, suppressing the ripple power, and performing inversion or rectification operation in one stage of power conversion. The proposed configuration offers an active decoupling function, which not only eliminates the double-frequency ripple power at the dc port but also achieves minimum capacitance requirements to minimize the size of the decoupling capacitor. This facilitates the use of a very small thin-film capacitor, which offers a much longer life-cycle and higher reliability compared with a bulky electrolytic capacitor. A control approach is also developed to regulate the dc-port and ac-port currents and manage the ripple power through proper distribution of power between each port. Moreover, a very small capacitor can be placed in parallel with the inductor to reinforce the proposed configuration with soft-switching operation, which enhances the overall efficiency and minimizes the voltage stress over the semiconductor devices. This converter is capable of accommodating an arbitrary number of dc or single-phase ac sources and/or loads configuring a multiple-input multiple-output inverter without introducing any additional passive elements or sacrificing the performance of the inverter. The primary focus of this paper is dc-to-ac conversion mode of operation, in spite of the fact that it can easily be configured to serve as a rectifier. Experimental and simulation results are presented to validate the operation of the proposed topology and its control strategy.
BRACELET: Hierarchical Edge-Cloud Microservice Infrastructure for Scientific Instruments’ Lifetime Connectivity

Recent advances in cyber-infrastructure have enabled digital data sharing and ubiquitous network connectivity between scientific instruments and cloud-based storage infrastructure for uploading, storing, curating, and correlating of large amounts of materials and semiconductor fabrication data and metadata. However, there is still a significant number of scientific instruments running on old operating systems that are taken offline and cannot connect to the cloud infrastructure, due to security and performance concerns. In this paper, we propose BRACELET an edge-cloud infrastructure that augments the existing cloud-based infrastructure with edge devices and helps to tackle the unique performance & security challenges that scientific instruments face when they are connected to the cloud through public network. With BRACELET, we put a networked edge device, called cloudlet, in between the scientific instruments and the cloud as the middle tier of a three-tier hierarchy. The cloudlet will shape and protect the data traffic from scientific instruments to the cloud, and will play a foundational role in keeping the instruments connected throughout its lifetime, and continuously providing the otherwise missing performance and security features for the instrument as its operating system ages.
STIGMA RECEPTIVITY AND POLLEN VIABILITY OF Melaleuca alternifolia

Stigma receptivity based on seed set and pollen tubes growth following controlled pollination of flowers of different ages was examined in Melaleuca alternifolia . The stigma secretion during 10 days after anthesis and pollen viability under three different temperatures and five storage times were also observed . These series of research were undertaken because successful controlled pollination of M. alternifolia depends on the application of viable pollen to the receptive compatible stigma. The objective of this research was therefore to determine the stigma receptivity and pollen viability of M. alternifolia . Results showed that the stigma receptivity began to develop on day one and finished on day seven after anthesis, peak receptivity occurred from day three to day six. The stigma receptivity also coincides with the appearance of secretion in the stigma, occurring from day three to day seven after anthesis. Therefore, the time for pollination of M. alternifolia appeared to extend for approximately 7 days after anthesis. Data for M. alternifolia showed that regardless of storage temperature, pollen was still viable after 26 weeks of storage; results also demonstrated that the lowest temperature (-18oC) was the best regime for long term storage.
The performance of three-dimensional ultrasound reconstruction of the bile ducts in the diagnosis and assessment of extrahepatic cholestasis – a clinical trial on 48 patients

Aim . The assessment of three-dimensional (3D) ultrasound reconstructions using the transparent and the inverse mode for the diagnosis and description of obstructive jaundice of various etiologies. Material and Method . 48 patients with bile ducts dilations, most of them documented by retrograde endoscopic cholangiography (43/48) and 9 control subjects without bile duct pathology. 3D ultrasound followed conventional 2D examination and the examination protocol included an image algorithm based on the transparent and inverse modes. The 2D and 3D techniques were compared in order to evidence the diagnostic value and final relevance of the image. Results . The biliary tree was visualized by 2D ultrasound in 6 control subjects and by 3D in 4 subjects, the images being relevant in 8 patients with 2D and in 4 with 3D respectively. In the obstructive jaundice group the bile ducts dilations were visualized by 2D in 89,6% of the patients and by 3D in 86.5%. Cholestasis was confirmed in 77.1% of the cases after 2DUS examination and in 79.2% of the cases after 3D reconstructions. The cause of biliary obstruction has been determined using 2D US in 38 of the 43 patients also explored by ERCP, the sensitivity being 55.8% for 3D reconstructions. The reconstruction mode with the best results was “transparency” mode, although for upper obstructions the “surface” mode was more successful. The average duration for the first acquisition was 1min 42s. Conclusion . 3D ultrasound in the transparent mode combined with inverse mode allows the identification of the dilated bile ducts and the level of the obstruction. The method does not allow the establishment of the cause of the obstruction and does not provide information on the tumoral features. The 3D image is relevant and illustrative of the amplitude of the biliary dilations, which contributes to the reliability of the diagnosis obtained by 2D ultrasound.
Reliable Underwater Feedback Transmission via Software-Defined Acoustic Modems

Underwater wireless communication provides great potential through semi-autonomous aquatic robots that have use in scientific research, pollution monitoring, and maintenance of underwater facilities. However, the underwater setting poses a unique array of difficulties for wireless communication, including path attenuation, colored noise, Doppler shifting, multipath propagation, and bandwidth limitations. Current underwater robot communication systems lack a robust and reliable feedback channel that mitigates the impact of underwater transmission challenges. This research concludes that the use of low-rate binary frequency shift keying (BFSK) maximizes accuracy of the feedback channel.
The Qualitative Report The Qualitative Report Practicing Reflexivity in the Study of Italian Migrants in London Practicing Reflexivity in the Study of Italian Migrants in London

Abstract This article discusses the centrality of reflexivity in qualitative research through examples from my study on the role new media play in the lives of Italians in London. My hypothesis was that Italians were "in transit" in London and they were using new media to build "temporary" communities. I conducted in-depth interviews with members of the Italianialondra.com online community. I found they settled in London and the online community, instead of supporting "nomadic" identities, was used for re-territorialization. Through reflexivity I was able to determine the reasons for a partially wrong hypothesis. I also identified biases that clouded my interpretations of the object of study; thus promoting rich insight and enabling public scrutiny of the integrity of the research. This article discusses the centrality of reflexivity in qualitative research through examples from my study on the role new media play in the lives of Italians in London. My hypothesis was that Italians were “in transit” in London and they were using new media to build “temporary” communities. I conducted in-depth interviews with members of the Italianialondra.com online community. I found they settled in London and the online community, instead of supporting “nomadic” identities, was used for re-territorialization. Through reflexivity I was able to determine the reasons for a partially wrong hypothesis. I also identified biases that clouded my interpretations of the object of study; thus promoting rich insight and enabling public scrutiny of the integrity of the research.
Microplastic contamination in an urban area: a case study in Greater Paris

This study investigates the microplastic contamination of both urban compartments (wastewater and total atmospheric fallout) and surface water in a continental environment (Greater Paris, France). These first investigations on urban environment confirm the presence of microplastics in sewage, freshwater and total atmospheric fallout and provide knowledge on the type and size distribution of microplastics in the [100 µm-5 000 µm] range. For the first time, the presence of microplastics, mostly fibers, is highlighted in total atmospheric fallout (29-280 particles/m2/day). High levels of fibers were found in wastewater (260-320 x103 particles/m3). In treated effluent, the contamination significantly decreases to 14-50 x103 particles/m3. In River Seine, two sampling devices are used to collect both large and small microplastic particles: i) a plankton net (80 µm mesh) and ii) a manta trawl (330 µm mesh). Sampling with the plankton net showed a predominance of fibers with concentrations ranging from 3 to 108 particles/m3. A greater diversity of both microplastic shapes and types was encountered during manta trawl sampling but at much lower concentrations (0.28-0.47 particles/m3). This combined approach could be relevant and implemented in future studies to provide an accurate overview of microplastic distribution in freshwater.
Possible health and growth implications of prostitution in Nigeria: A theoretical perspective

The desire to meet the basic needs of life in the face of poverty and increasing income inequality has propelled individuals in the country to look outward and beam their search light on alternative sources of income to either complement or substitute existing source. Prostitution, although demeaning and widely socially impugned, has been identified by some individuals as one of the feasible solutions to addressing the problem of financing basic human needs (BHNs) in the present Nigerian economic situation. Thus, the paper examines the possible health and growth implications of prostitution in Nigeria. The paper views the primary driver of prostitution through the conflict theory’s lens. As a result, the study identifies the unemployed, orphans, widows, divorcees, and members of low income households as the vulnerable groups in the economy. The paper concludes that the growth of poverty and income inequality will continue to drive prostitution among vulnerable groups, and the developmental efforts of the country will be undermined as a result of its possible associated health crisis and the sapping of human resources that otherwise could have been channeled to productive sectors of the economy. Thus, the paper suggests appropriate policy remedies that may assist in reducing the growth of prostitution among individuals and set the country on the path of growth and sustainable development.
Porting Speech Recognition Systems to New Languages Supported by Articulatory Feature Models

Linguists estimate the number of currently existing languages to be between 5,000 and 7,000. In order to be able to cover as many languages as possible, techniques have to be developed in order to rapidly port speech recognition systems to new languages in a cost efficient way. In the past, phoneme based, language independent acoustic models have been studied for bootstrapping an acoustic model in a new language. These language independent models usually have seen multiple languages during training, and work under the assumption that phonemes are pronounced the same across languages. Similarly, models for acoustic features, describing the articulator targets of the different phonemes, can also be accurately recognized across languages and can be trained to become language independent in the same way as phonemes can. In the past we combined them with phoneme based models and their behavior on the training languages of the multilingual models was examined. In this paper we present experiments examining the suitability of monolingual and multilingual acoustic features for porting speech recognition systems to new languages. We combined them with monolingual and multilingual, phoneme based models in a stream based frame work in order to bootstrap a model in a new language. The results show that the incorporation of models for articulatory features into the porting framework significantly improves the performance when porting ASR systems to new languages, reducing the word error rate by up to 4.5% relative.
Assisting the practice of motor skills by humans with a probability distribution over trajectories

In sports training, rehabilitation or in the practice of motor skills in general, errors in the execution of movements may go unnoticed when a human instructor is not available. In these situations, a computer system or robotic device able to detect movement errors and propose corrections could be helpful. This extended abstract presents an approach for detecting errors in the execution of movements and for providing feedback to the user in order to correct these errors.
Attributional Style and Engagement/Disengagement Responses in the Chinese Workforce

Internal attribution for bad events, along with stable and global attributions, has been regarded as a component of pessimism, a precursor of negative work outcomes. Most evidence in support of this conceptualisation has come from research conducted in individualist cultures. We questioned if internal attribution has the same pessimistic implication in a collectivist culture. Findings from two studies conducted on Chinese employees supported our expectations that the stability and globality dimensions (but not the internality dimension) would predict disengagement responses (such as quitting and being neglectful at work) and lack of engagement responses (such as voicing suggestions and being loyal to the organisation). A reconceptualisation of pessimism in the workplace is therefore necessary. A dimensional, rather than a composite, scoring method is proposed for maintaining the predictive and construct validities of attributional style as an indicator of pessimism.
The Footprint of Evolutionary Processes of Learning and Selection Upon the Statistical Properties of Industrial Dynamics

Evolutionary theories of economic change identify the processes of idiosyncratic learningby individual firms and of market selection as the two main drivers of the dynamics of industries. Are such processes able to robustly account for the statistical regularities which industrial structures and dynamics display? In this work we address this question by means of a simple agent-based model formalizing the mechanisms of learning and selection. The interplay between these two engines shapes the dynamics of entry-exit and market shares and, collectively, the productivity and the size distributions and their patterns of growth. As such, and despite its simplicity, the model is able to robustly reproduce an ensemble of empirical stylised facts, including ample heterogeneity in productivity distributions, persistent market turbulence and fat-tailed distribution of growth rates.