Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Label Image Classification via Category Prototype Compositional Learning

Real-world images are often compositions of multiple objects with different categories, scales, poses and locations. Adding nonexistent objects to an image (composing) or removing existent objects from an image (decomposing) leads to higher discrepancy in appearance, which reveals an important but long-neglected compositional nature of multi-label images. In light of this observation, we propose a novel end-to-end compositional learning framework named Category Prototype Compositional Learning (CPCL) to model such compositional nature for multi-label image classification. In CPCL, each image is represented by a collection of category-related features used to eliminate the negative effects from location information. Then, a compositional learning module is introduced to compose and decompose the category-related features with their corresponding category prototypes, which are derived from the semantic representations of categories. If the image has the given object, the output after composing should be closer to the original input than the output after decomposing. Contrarily, if the image does not have the given object, the output after decomposing should be closer to the original input than the output after composing. We introduce the Transformed Appearance Distance (TAD) to measure the appearance change between the composed and decomposed features relative to the category-related features with respect to each category. Finally, multi-label image classification is accomplished by performing a TAD-based metric learning. Experimental results on three multi-label image classification benchmarks, i.e., NUS-WIDE, MS-COCO and VOC 2007, validate the effectiveness and superiority of our work in comparison with the state-of-the-arts. The source codes of our model have been released on https://github.com/ZFT-CQU/CPCL.
Multi-Phase Clock Generation for Phase Interpolation With a Multi-Phase, Injection-Locked Ring Oscillator and a Quadrature DLL

We present a high-accuracy, low-jitter, multi-phase clock generator (MPCG) based on a multi-phase, injection-locked ring oscillator (MPIL-ROSC) with a quadrature delay-locked loop (QDLL). The QDLL tunes the ring oscillator (ROSC) self-oscillation frequency (<inline-formula> <tex-math notation="LaTeX">${f}_{{0}}$ </tex-math></inline-formula>) and provides it with multi-phase injection signals. The proposed architecture breaks the intrinsic tradeoff between jitter and phase accuracy in two-phase injection-locked ROSCs. The MPCG’s eight-phase output clock drives a 7-bit phase interpolator (PI) for phase and frequency deskew. A 1.2-V 65-nm CMOS MPCG prototype chip has a better-than-1° eight-phase accuracy and <inline-formula> <tex-math notation="LaTeX">$58.8~\mathrm {fs}_{\mathrm {rms}}$ </tex-math></inline-formula> jitter (integrated from 100 kHz to 1 GHz), while consuming 15.6 mW at 7 GHz, yielding a −252.7-dB figure of merit (<inline-formula> <tex-math notation="LaTeX">$\mathrm {FOM}_{\mathrm {jitter}}$ </tex-math></inline-formula>). The peak-to-peak integral nonlinearity (INL) and the peak-to-peak differential nonlinearity (DNL) of the PI are less than 1.9 and 1.2 LSB, respectively, across a frequency range from 5 to 8 GHz.
Multi Layered Maps for Enhanced Environmental Perception

Traditionally, an in-vehicle map consists of only one type of data, tailored for a single user function. For example, the navigation maps contain spatial information about the roads. On the other hand, a map built for adaptive cruise control use consists of the detected vehicles and their properties. In autonomous vehicle research, the maps are often built up as an occupancy grid where areas are classified as passable or impassable. Using these kinds of maps separately, however, is not enough to support the traffic safety enhancing and advanced driver assistance systems of today and tomorrow.Instead of using separate systems to handle individual safety or planning tasks, information could be stored in one shared map containing several correlated layers of information. Map information can be collected by any number of different sensor devices, and fusion algorithms can be used to enhance the quality of the information. User functions that base their decisions on the multi-layered map can then retrieve any subset of the stored information making them scalable in terms of processor and memory use.The advantages of using a shared multi-layer spatial data storage are several:Sensors and user functions are decoupled. This can make it easier and more cost efficient to implement additional functions.Data quality is enhanced. Since fusion techniques can be used to generate estimates of physical properties from several sensors, the fused data is based on all available information.Using models that describe a certain entity, properties that are not even measured can be estimated by the system.This work describes an experimental semi-autonomous ground vehicle system, where on-line generated maps containing multiple layers of information are used for obstacle avoidance and planning of a suitable path between waypoints. The system is primarily simulated using physical vehicle models in a suitable environment, but limited real-world experiments with a subset of functions are also performed.
Remediation of copper-contaminated soils using Tagetes patula L., earthworms and arbuscular mycorrhizal fungi

Abstract Arbuscular mycorrhizal fungi (AMF) and earthworms have potential uses in the bioremediation of contaminated soils. In recent years, heavy metal-contaminated sites have been remediated by adding plants and AMF or earthworms to the soil. However, there are few studies on remediation using combinations of plants, animals, and microbes, especially for the remediation of Cu-contaminated soil. The present study investigated the separate and combined effects of AMF and earthworms on Cu-contaminated soil in which Tagetes patula L. was grown. The results show that the combined application of AMF and earthworms markedly increased the biomass of plant shoots and roots by more than 100%. It also increased Cu extraction by T. patula by 270%. The combined treatment was effective in increasing the CEC, contents of OM, and available Cu, P and K, but reduced the soil pH. Furthermore, the combined treatment significantly increased the abundance and diversity of the soil microbial community. In particular, the abundances of the bacteria Bacteroides, Proteobacteria, and Actinobacteria were increased, with the genera Flavobacterium, Pedobacter, Algoriphagus, Gaetbulibacter, Pseudomonas, Luteimonas, and Arthrobacter dominating. Meanwhile, the abundance of the fungus Zygomycota was increased, with Mortierella dominating. Moreover, inoculation with earthworms greatly improved the structure of the soil microbial community. NOVELTY STATEMENT Compared with phytoremediation or microbial remediation alone, combined remediation was considered to be a more efficient remediation strategy. This study describes the effects of the combined remediation of T. patula, AMF, and earthworms on the physiochemical properties and microbial community of Cu-contaminated soil. This provides a comprehensive strategy to improve the phytoremediation efficiency in Cu-contaminated soil.
A Q‐band high‐gain substrate‐integrated waveguide slot antenna

A broadband, high‐gain substrate‐integrated waveguide (SIW) slot antenna fabricated on a PCB is presented in this article. Measured return loss reaches 25 dB at 45 GHz with the bandwidth of 4.72 GHz. The simulated gain is 9.6 dBi at 46.2 GHz and the efficiency is 96%. The measured gain is 7.8 dBi at 46.2 GHz. Good agreement is achieved between measured and simulated antenna patterns and return losses. It is shown that the antenna behavior can be enhanced by oversizing the bottom ground and properly selecting dimensions of top metal. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:1370–1374, 2015
An Optimized Machine Learning and Big Data Approach to Crime Detection

Crime detection is one of the most important research applications in machine learning. Identifying and reducing crime rates is crucial to developing a healthy society. Big Data techniques are applied to collect and analyse data: determine the required features and prime attributes that cause the emergence of crime hotspots. The traditional crime detection and machine learning-based algorithms lack the ability to generate key prime attributes from the crime dataset, hence most often fail to predict crime patterns successfully. This paper is aimed at extracting the prime attributes such as time zones, crime probability, and crime hotspots and performing vulnerability analysis to increase the accuracy of the subject machine learning algorithm. We implemented our proposed methodology using two standard datasets. Results show that the proposed feature generation method increased the performance of machine learning models. The highest accuracy of 97.5% was obtained when the proposed methodology was applied to the Naïve Bayes algorithm while analysing the San Francisco dataset.
Collaborative Evolution Mechanism of PMC Project Organizational Management System from the Perspective of Organizational Conflict

Limited by traditional construction project management ideas and systems, the implementation of the PMC model in China still has serious problems such as opposition and frequent conflicts. How to reveal the causes of organizational conflicts and explore the key mechanism of the implementation of the PMC model from the system perspective are urgent problems to be solved. Based on the idea of engineering system view, this paper abstracts the PMC project participants with self-organizing characteristics of the organizational management system, in which the internal structure is closely related, and defines the connotation of synergy and synergistic evolution of the PMC project organizational management system. Using the Cucker–Smale model to describe the group movement, the hierarchical system and the acceleration efficiency function of the project legal person’s free will are constructed, and the structure, movement, and development law of the system itself are emphasized to simulate the ordered evolution trend of PMC project organizational management system and reveal the intrinsic causes of conflicts in PMC project and the key mechanisms of the PMC model application. The results show that first, the intensity of information communication between PMC subjects has a significant positive contribution to the orderliness of the organizational management system; second, too much acceleration of the project legal person’s free will causes group chaos in the system, while too little slows down the group stabilization time, which has a negative impact on cost and schedule; third, the more the organizational structure of PMC contractors tends to the whole-process integrated control, the more it can drive the group to gather in an orderly manner and form a synergistic control mode combining self-organization and other organizations; and fourth, the implementation of the PMC model should focus on eliminating the traditional institutional and conceptual barriers, forming a project management model with integrated control of the whole process of the PMC project contractor and effective macro supervision of the project legal person. The research results of this paper revealed the intrinsic causes of conflicts in PMC projects and the key mechanisms of PMC model application; it can help solve the confrontational situation of PMC project participants, promote the development of the PMC model, and give full play to the investment benefits.
Coherent noise attenuation in the radial trace domain

Coherent noise is a persistent problem in seismic imaging, and a number of techniques have been developed to attenuate it. The radial trace (RT) transform, a simple seismic data mapping algorithm, can be used as the basis for a particularly flexible and effective method for attenuating coherent noise on both prestack and poststack seismic data. Described here are the principles and some practical application details for attenuating coherent noise in the RT domain. A comparison between frequency–wavenumber (f–k) and RT domain filtering on a synthetic model is presented, and some of the differences and advantages of RT methods are identified. Next, RT coherent noise attenuation is demonstrated using a set of good‐quality field data; it is then applied to a very noisy data set. The results obtained with this last set prove to be as good as, or better than, those produced using f–k filtering.
The effect of food additive on physicochemical characteristics of seaweed stick snack and consumer acceptance

Seaweed is considered high class marine and fisheries sector in international demand for its derivative products. One of traditional use of seaweed as food is stick snack which is widely consumed due to its crunchiness and deliciousness. The objective of this study was to characterize the proximate analysis, hardness, and sensory perception of stick snack derived from seaweed. Seaweed stick were prepared with varying food additives such as sodium acid phyorposphate (SAPP), steaoryl lactylate (SSL), sodium bicarbonate (NaHCO3), and control (without addition of food additives). The results confirmed that the use of food additives induce change in proximate, hardness, and sensory perception. Seaweed stick with addition NaHCO3 has the highest fat content while seaweed stick with addition of SAPP has the highest crispness. In addition, sensory test showed that seaweed stick with addition with NaHCO3 provide the highest acceptance in texture and flavour.
Double annular‐ring dielectric resonator antenna for ultra‐wideband application

A new dielectric resonator antenna (DRA) is proposed in this article for ultra‐wideband (UWB) application. A larger annular‐ring DRA is placed concentrically outside a smaller one to form a double annular‐ring DRA. The antenna is operating at the end‐fire mode. The effects of antenna parameters, such as the radiuses and heights of the dielectric resonators as well as the probe length are investigated. The proposed double annular‐ring DRA can offer an impedance bandwidth up to 3–11.2 GHz for a return loss less than −10 dB. The radiation patterns are stable in the passband. © 2006 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 362–366, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22140
IN VITRO AND IN VIVO CHARACTERISATION OF ISOLATES OF CRYPTOCOCCUS 1 NEOFORMANS CAUSING MENINGITIS IN HIV INFECTED AND UNINFECTED PATIENTS

27 Most cryptococcal meningitis cases occur in immunocompromised individuals and are caused 28 by Cryptococcus neoformans var.grubii. We previously reported cryptococcal meningitis in 29 Vietnam arising atypically in HIV-uninfected, apparently immunocompetent patients, caused by 30 a single amplified fragment length polymorphism (AFLP) cluster of C. neoformans (VNI-γ). This 31 variant was less common in HIV-infected individuals. It is unclear why this lineage is associated 32 with HIV-uninfected, apparently immunocompetent patients. To better delineate the 33 phenotypic characteristics of C. neoformans VNI-γ in comparison with other C. neoformans 34 lineages we selected 30 representative isolates and compared their genotype-specific in vitro 35 pathogenic potential and in vivo virulence, and ability to induce inflammatory response in the 36 A/J mouse model. All isolates were genotyped using multi-locus sequence typing. All previously 37 AFLP-defined VNI-γ isolates were identified as sequence type (ST) 5. Compared with non-ST5 38 strains, ST5 isolates had significantly increased variability in cell and capsule size (p<0.001). ST5 39 and non-ST5 strains exhibited similar characteristics in relation to previously defined virulence 40 factors including melanization, growth at 37C, and growth in cerebrospinal fluid. However, A/J 41 . CC-BY-NC-ND 4.0 International license under a not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available The copyright holder for this preprint (which was this version posted September 15, 2017. ; https://doi.org/10.1101/189274 doi: bioRxiv preprint
Emotion Embedding Spaces for Matching Music to Stories

Content creators often use music to enhance their stories, as it can be a powerful tool to convey emotion. In this paper, our goal is to help creators find music to match the emotion of their story. We focus on text-based stories that can be auralized (e.g., books), use multiple sentences as input queries, and automatically retrieve matching music. We formalize this task as a cross-modal text-to-music retrieval problem. Both the music and text domains have existing datasets with emotion labels, but mismatched emotion vocabularies prevent us from using mood or emotion annotations directly for matching. To address this challenge, we propose and investigate several emotion embedding spaces, both manually defined (e.g., valence/arousal) and data-driven (e.g., Word2Vec and metric learning) to bridge this gap. Our experiments show that by leveraging these embedding spaces, we are able to successfully bridge the gap between modalities to facilitate cross modal retrieval. We show that our method can leverage the well established valence-arousal space, but that it can also achieve our goal via data-driven embedding spaces. By leveraging data-driven embeddings, our approach has the potential of being generalized to other retrieval tasks that require broader or completely different vocabularies.
Pilot-Controller Communication Problems and an Initial Exploration of Language-Engineering Technologies as a Potential Solution

This paper examines pilot-controller miscommunications and a potential solution to minimise these. Since there is no up-to-date literature on the current level of such problems, a small-scale study was conducted. This involved analysing 531 British accident/incident reports, 531 CHIRP (Confidential Human Factors Incident Reporting Programme) reports, and 21 four-week communication flight logs recorded by eight British pilots. The results indicate that miscommunications remain numerous and directly affect pilots and controllers in terms of workload and situation awareness. The results also show that the number of communication problems identified in the accident/incident and CHIRP reports differ to those reported by the pilots, who recorded higher numbers. This seems to indicate a more problematic communication situation than the analysis of communication problems in the CHIRP and accident/incidents reports suggests. We hence argue that since voice communications remain beset with problems and the planned expanded controller-pilot data link communications (CPDLC) will only resolve some of the problems, it is vital to reduce these issues by developing an additional communication system using language-engineering technologies in automatic speech recognition, machine translation, and terminology extraction. The paper outlines how such a system might work and ameliorate pilot and controller workload and situation awareness.
Analysis of Momentous Fragmentary Formants in Talaqi-like Neoteric Assessment of Quran Recitation using MFCC Miniature Features of Quranic Syllables

The use of technological speech recognition systems with a variety of approaches and techniques has grown rapidly in a variety of human-machine interaction applications. Further to this, a computerized assessment system to identify errors in reading the Qur'an can be developed to practice the advantages of technology that exist today. Based on Quranic syllable utterances, which contain Tajweed rules that generally consist of Makhraj (articulation process), Sifaat (letter features or pronunciation) and Harakat (pronunciation extension), this paper attempts to present the technological capabilities in realizing Quranic recitation assessment. The transformation of the digital signal of the Quranic voice with the identification of reading errors (based on the Law of Tajweed) is the main focus of this paper. This involves many stages in the process related to the representation of Quranic syllable-based Recitation Speech Signal (QRSS), feature extraction, non-phonetic transcription Quranic Recitation Acoustic Model (QRAM), and threshold classification processes. MFCC-Formants are used in a miniature state that are hybridized with three bands in representing QRSS combined vowels and consonants. A human-guided threshold classification approach is used to assess recitation based on Quranic syllables and threshold classification performance for the low, medium, and high band groups with performances of 87.27%, 86.86%and 86.33%, respectively. Keywords—Speech processing; MFCC-Formant; Quranic recitation assessment; human-guided threshold classification
Accounting for lease transactions: analysis of possible lobbying in the issuing of IFRS 16

Received in 9/16/2017. Ask to Revise on 11/14/2017. Resubmitted on 12/3/2017. Accepted on 12/11/2017 by Dr. Orleans Silva Martins (Editor). Published on 12/21/2017. Organization responsible for the journal: Abracicon Fábio Henrique Ferreira de Albuquerque Ph.D. in Economic and Business Sciences from Universidade de Extremadura and Professor at Instituto Superior de Contabilidade e Administração de Lisboa. Contact: Av. Miguel Bombarda, 20, Lisboa, Portugal, CEP: 1069-035. E-mail: fhalbuquerque@iscal.ipl. pt
3D printing nano-resolution organic electronic drug delivery devices

Development of biocompatible electronic interfaces and systems that can control drug release is a rapidly emerging multidisciplinary scientific niche. Various materials are used for bioelectronic applications, including inorganic electronic materials (e.g. metals and alloys) and organic electronic materials (e.g. graphene, carbon nanotubes, and conducting polymers). We focused here on conducting polymers for biomedical applications and therapeutics. We report 3D printing of conductive polymeric materials in various dimensions and scales (mesoscale, microscale and nanoscale) to be applied as organic bioelectronic neural interfaces and stimuli responsive drug delivery devices. Conductive polymers were 3D printed onto a 3D material (Polydimethylsiloxane PDMS acting as a soft conformal interface) using two-photon polymerization (TPP) via a direct laser writing (DLW) instrument (Nanoscribe), paving the way for the administration of drugs from flexible organic electronic devices. The research was carried out using a polymer frequently used in bioelectronics (polypyrrole, PPy) because it has previously been reported to be non-immunogenic with no significant inflammation and with a positive biocompatibility profile with CNS parenchyma in vivo. This technology has the potential to be applied in therapeutic devices in the future as neural interfaces and implantable or topical drug delivery systems.
The Epigenetic Mechanisms Underlying Thermomorphogenesis and Heat Stress Responses in Arabidopsis

Integration of temperature cues is crucial for plant survival and adaptation. Global warming is a prevalent issue, especially in modern agriculture, since the global rise in average temperature is expected to impact crop productivity worldwide. Hence, better understanding of the mechanisms by which plants respond to warmer temperatures is very important. This review focuses on the epigenetic mechanisms implicated in plant responses to high temperature and distinguishes the different epigenetic events that occur at warmer average temperatures, leading to thermomorphogenic responses, or subjected to extreme warm temperatures, leading to heat stress.