Miracle-dz/UniFAR-FTUs huggingface dataset:
Generation of a potential koi herpesvirus live vaccine by simultaneous deletion of the viral thymidine kinase and dUTPase genes.

Koi herpesvirus (KHV, Cyprinidherpesvirus 3) causes a fatal disease of koi and common carp. To obtain safe and efficacious live vaccines, we generated deletion mutants of KHV lacking the nonessential genes encoding two enzymes of nucleotide metabolism, thymidine kinase (TK, ORF55) and deoxyuridine-triphosphatase (DUT, ORF123). Since single-deletion mutants based on a KHV isolate from Israel (KHV-I) only exhibited partial attenuation (Fuchs W, Fichtner D, Bergmann SM, Mettenleiter TC. Arch Virol 2011;156 : 1059-1063), a corresponding double mutant was generated and tested in vivo, and shown to be almost avirulent but still protective. To overcome the low in vitro virus titres of KHV-I (≤105 p.f.u. ml-1), single and double TK and DUT deletions were also introduced into a cell culture-adapted KHV strain from Taiwan (KHV-T). The deletions did not affect in vitro virus replication, and all KHV-T mutants exhibited wild-type-like plaque sizes and titres exceeding 107 p.f. u. ml-1, as a prerequisite for economic vaccine production. Compared to wild-type and revertant viruses, the single-deletion mutants of KHV-T were significantly attenuated in vivo, and immersion of juvenile carp in water containing high doses of the double mutant caused almost no fatalities. Nevertheless, the deletion mutants induced similar levels of KHV-specific serum antibodies to the parental wild-type virus, and conferred solid protection against disease after challenge with wild-type KHV. For the convenient differentiation of DNA samples prepared from gill swabs of carp infected with wild-type and TK-deleted KHV we developed a triplex real-time PCR. Thus, KHV-TΔDUT/TK might be suitable as a genetic DIVA vaccine in the field.
SkinWire: Fabricating a Self-Contained On-Skin PCB for the Hand

Current wearable form factors often house electronics using an enclosure that is attached to the body. This form factor, while wearable, tends to protrude from the body and therefore can limit wearability. While emerging research in on-skin interfaces from the HCI and wearable communities have generated form factors with lower profiles, they often still require support by conventional electronics and associated form factors for the microprocessor, wireless communication, and battery units. In this work, we introduce SkinWire, a fabrication approach that extends the early work in on-skin interfaces to shift wearable devices from their traditional box-like forms to a fully self-contained on-skin form factor. The Skin Wire approach starts with the placement of electronic components into individual PCB islands, which are then distributed over the body surface. The islands are connected through a novel skin-wiring approach that deposits conformal multi-stranded metallic wires on thin silicon substrates through a sewing-based technique. The process affords on-skin interfaces with the needed wiring in limited surface areas. We exemplify the capacity of this approach by shifting an IMU-based hand gesture system - which traditionally come in bulky glove-based form factors - directly onto the skin. Inspired by the emerging body art trend of body wiring, the Skin Wire approach uses readily accessible materials and affords aesthetic customization. We evaluate fabrication parameters, and conduct a user study to uncover wearability concerns.
Entropy Correlation and Its Impacts on Data Aggregation in a Wireless Sensor Network

A correlation characteristic has significant potential advantages for the development of efficient communication protocols in wireless sensor networks (WSNs). To exploit the correlation in WSNs, the correlation model is required. However, most of the present correlation models are linear and distance-dependent. This paper proposes a general distance-independent entropy correlation model based on the relation between joint entropy and the number of members in a group. This relation is estimated using entropy of individual members and entropy correlation coefficients of member pairs. The proposed model is then applied to evaluate two data aggregation schemes in WSNs including data compression and representative schemes. In the data compression scheme, some main routing strategies are compared and evaluated to find the most appropriate strategy. In the representative scheme, with the desired distortion requirement, a method to calculate the number of representative nodes and the selection of these nodes are proposed. The practical validations showed the effectiveness of the proposed correlation model and data reduction schemes.
A comparative analysis of emerging scientific themes in business analytics

The purpose of this research is to investigate the emerging scientific themes in business analytics through the utilisation of burst detection, text-clustering and word occurrence analysis in top information systems journals in order to provide an insight about the future scientific trends of business analytics for scholars and practitioners in the field. Researchers have gathered a rich set of business analytics articles from top journals which are indexed in the well-known scientific database of web of science (WoS) core collection. The study provides clues, directions, and knowledge-based guidelines on the recent business analytics scientific trends through the utilisation of mentioned algorithms over paper abstracts, titles, and keywords. This study also highlights the most important areas of research and the future research directions that might be interesting to business analysts through an in-depth analytical discussion.
Retrosplenial and postsubicular head direction cells compared during visual landmark discrimination

Background: Visual landmarks are used by head direction (HD) cells to establish and help update the animal’s representation of head direction, for use in orientation and navigation. Two cortical regions that are connected to primary visual areas, postsubiculum (PoS) and retrosplenial cortex (RSC), possess HD cells: we investigated whether they differ in how they process visual landmarks. Methods: We compared PoS and RSC HD cell activity from tetrode-implanted rats exploring an arena in which correct HD orientation required discrimination of two opposing landmarks having high, moderate or low discriminability. Results: RSC HD cells had higher firing rates than PoS HD cells and slightly lower modulation by angular head velocity, and anticipated actual head direction by ~48 ms, indicating that RSC spiking leads PoS spiking. Otherwise, we saw no differences in landmark processing, in that HD cells in both regions showed equal responsiveness to and discrimination of the cues, with cells in both regions having unipolar directional tuning curves and showing better discrimination of the highly discriminable cues. There was a small spatial component to the signal in some cells, consistent with their role in interacting with the place cell navigation system, and there was also slight modulation by running speed. Neither region showed theta modulation of HD cell spiking. Conclusions: That the cells can immediately respond to subtle differences in spatial landmarks is consistent with rapid processing of visual snapshots or scenes; similarities in PoS and RSC responding may be due either to similar computations being performed on the visual inputs, or to rapid sharing of information between these regions. More generally, this two-cue HD cell paradigm may be a useful method for testing rapid spontaneous visual discrimination capabilities in other experimental settings.
Heuristics and metaheuristics for dynamic management of computing and cooling energy in cloud data centers

Data centers handle impressive high figures in terms of energy consumption, and the growing popularity of cloud applications is intensifying their computational demand. Moreover, the cooling needed to keep the servers within reliable thermal operating conditions also has an impact on the thermal distribution of the data room, thus affecting to servers' power leakage. Optimizing the energy consumption of these infrastructures is a major challenge to place data centers on a more scalable scenario. Thus, understanding the relationship between power, temperature, consolidation, and performance is crucial to enable an energy‐efficient management at the data center level. In this research, we propose novel power and thermal‐aware strategies and models to provide joint cooling and computing optimizations from a local perspective based on the global energy consumption of metaheuristic‐based optimizations. Our results show that the combined awareness from both metaheuristic and best fit decreasing algorithms allow us to describe the global energy into faster and lighter optimization strategies that may be used during runtime. This approach allows us to improve the energy efficiency of the data center, considering both computing and cooling infrastructures, in up to a 21.74% while maintaining quality of service.
Hand gesture recognition using DWT and F-ratio based feature descriptor

This study demonstrates the development of vision based static hand gesture recognition system using web camera in real-time applications. The vision based static hand gesture recognition system is developed using the following steps: preprocessing, feature extraction and classification. The preprocessing stage consists of illumination compensation, segmentation, filtering, hand region detection and image resize. This study proposes a discrete wavelet transform (DWT) and Fisher ratio ( F -ratio) based feature extraction technique to classify the hand gestures in an uncontrolled environment. This method is not only robust towards distortion and gesture vocabulary, but also invariant to translation and rotation of hand gestures. A linear support vector machine is used as a classifier to recognise the hand gestures. The performance of the proposed method is evaluated on two standard public datasets and one indigenously developed complex background dataset for recognition of hand gestures. All above three datasets are developed based on American Sign Language (ASL) hand alphabets. The experimental result is evaluated in terms of mean accuracy. Two possible real-time applications are conducted, one is for interpretation of ASL sign alphabets and another is for image browsing.
Fabrication and characterization of 3D‐printed elastic auricular scaffolds: A pilot study

Aesthetic reconstruction of the external ear is challenging due to the complex anatomical shape of the auricle. Recently, artificial scaffolds such as Medpor (Stryker, Kalamasoo, MI, USA) have become widely used in ear reconstruction. However, the Medpor scaffold is stiffer than the natural ear, which may lead to discomfort, and moreover has uniform design for every patient. In this study, we investigated whether three‐dimensional (3D)‐printed artificial polyurethane (PU) scaffolds are suitable for auricular reconstruction.
A New Fusion Rule of Multi-focus Image Fusion Based on Wavelet Transform

For fusing images taken at a range of focal depths, identifying the pixels or regions that are in focus is a major challenge. Wavelet analysis is growing in popularity for image fusion applications. Fusion rules for low-frequency sub-bands and high-frequency sub-bands have taken center stage in this research program. At present, conventional fusion rules are inadequate because they do not consider the relationships between low-frequency and high-frequency sub-band coefficients, often yielding incorrect coefficients, the fused low-frequency sub-bands reserve a large amount of information of the non-focusing region. This paper compares several conventional fusion rules and proposes a new fusion rule. Experimental comparisons of the proposed method with two conventional approaches indicate that the resulting algorithm reduces computation time and complexity while improving the quality of the output image.
Biomolecular Clusters Distribution up to Mega Dalton Region Using MALDI-Quadrupole Ion Trap Mass Spectrometer

We present the first report on complete cluster distributions of cytochrome c (molecular weight of 12.4 kDa) and bovine serum albumin ((BSA), molecular weight of 66.4 kDa) with mass-to-charge ratio (m/z) reaching 350,000 and 1,400,000, respectively, by matrix-assisted laser desorption/ionization (MALDI). Large cluster distributions of the analytes were measured by our homemade frequency-scanned quadrupole ion trap (QIT) mass spectrometer with a charge detector. To our knowledge, we report the highest m/z clusters of these two biomolecules. The quantitative results indicate that large clusters ions of cytochrome c and BSA follow the power law (r2 > 0.99) with cluster size distribution, which provides experimental evidence for the laser ablation studies of MALDI.
Optimization-Based Wi-Fi Radio Map Construction for Indoor Positioning Using Only Smart Phones

Fingerprinting-based Wi-Fi indoor positioning has great potential for positioning in GPS-denied areas. However, establishing a fingerprinting map (also called a radio map) prior to positioning (site survey) is normally a labor-intensive task. This paper proposes a method for easy site survey without need for any extra hardware. The user can conduct the site survey adopting only a smart phone. The collected inertial-based readings are processed using the pedestrian dead-reckoning algorithms to generate a raw trajectory. Then a factor graph optimization method is proposed to re-estimate the trajectory by adding constraints originated from collected Wi-Fi fingerprints and landmark positions. The proposed method is verified through an experiment in a mall. The mean positioning error is 1.10 m and the maximum error is 2.25 m. This level of positioning accuracy is considered sufficient for radio map generation purposes. A classical baseline algorithm, the k-Nearest Neighbor (kNN) algorithm, is adopted to test the positioning performance of the radio map (RM), which also validates the quality of the constructed RM from the proposed method.
A Survey on Gait Recognition

Recognizing people by their gait has become more and more popular nowadays due to the following reasons. First, gait recognition can work well remotely. Second, gait recognition can be done from low-resolution videos and with simple instrumentation. Third, gait recognition can be done without the cooperation of individuals. Fourth, gait recognition can work well while other features such as faces and fingerprints are hidden. Finally, gait features are typically difficult to be impersonated. Recent ubiquity of smartphones that capture gait patterns through accelerometers and gyroscope and advances in machine learning have opened new research directions and applications in gait recognition. A timely survey that addresses current advances is missing. In this article, we survey research works in gait recognition. In addition to recognition based on video, we address new modalities, such as recognition based on floor sensors, radars, and accelerometers; new approaches that include machine learning methods; and examine challenges and vulnerabilities in this field. In addition, we propose a set of future research directions. Our review reveals the current state-of-art and can be helpful to both experts and newcomers of gait recognition. Moreover, it lists future works and publicly available databases in gait recognition for researchers.
Fatigue in Chronic Respiratory Diseases: Theoretical Framework and Implications For Real-Life Performance and Rehabilitation

Fatigue is a primary disabling symptom in chronic respiratory diseases (CRD) with major clinical implications. However, fatigue is not yet sufficiently explored and is still poorly understood in CRD, making this symptom underdiagnosed and undertreated in these populations. Fatigue is a dynamic phenomenon, particularly in such evolving diseases punctuated by acute events which can, alone or in combination, modulate the degree of fatigue experienced by the patients. This review supports a comprehensive inter-disciplinary approach of CRD-related fatigue and emphasizes the need to consider both its performance and perceived components. Most studies in CRD evaluated perceived fatigue as a trait characteristic using multidimensional scales, providing precious information about its prevalence and clinical impact. However, these scales are not adapted to understand the complex dynamics of fatigue in real-life settings and should be augmented with ecological assessment of fatigue. The state level of fatigue must also be considered during physical tasks as severe fatigue can emerge rapidly during exercise. CRD patients exhibit alterations in both peripheral and central nervous systems and these abnormalities can be exacerbated during exercise. Laboratory tests are necessary to provide mechanistic insights into how and why fatigue develops during exercise in CRD. A better knowledge of the neurophysiological mechanisms underlying perceived and performance fatigability and their influence on real-life performance will enable the development of new individualized countermeasures. This review aims first to shed light on the terminology of fatigue and then critically considers the contemporary models of fatigue and their relevance in the particular context of CRD. This article then briefly reports the prevalence and clinical consequences of fatigue in CRD and discusses the strengths and weaknesses of various fatigue scales. This review also provides several arguments to select the ideal test of performance fatigability in CRD and to translate the mechanistic laboratory findings into the clinical practice and real-world performance. Finally, this article discusses the dose-response relationship to training and the feasibility and validity of using the fatigue produced during exercise training sessions in CRD to optimize exercise training efficiency. Methodological concerns, examples of applications in selected diseases and avenues for future research are also provided.
Finding Meaning With Creativity in the Past, Present, and Future

Being creative is considered a desirable trait, yet most empirical studies emphasize how to increase creativity rather than explore its possible benefits. A natural connection is how creativity can enhance life’s meaning. Many of the core concepts in work on the meaning of life, such as the needs for coherence, significance, and purpose or the desire for symbolic immortality, can be reached through creative activity. The synthesis of these two constructs—creativity and the meaning of life—is discussed with a temporal model encompassing past, present, and future pathways to creativity. The past pathway can help one understand and reflect on life. The present pathway can remind one of life’s joy and the many possible connections with humanity. Finally, the future pathway strives to ensure some type of legacy that may resonate with younger generations.
Functional Simple Sequence Repeat (SSR) Biomarkers for Specific Gene Groups of Oreochromis Niloticus

Selecting a superior strain of fish for cultivation, shortening the cultivation period, preventing environment deterioration, and reducing infectious disease transmission have become crucial factors for the aquaculture industry. Here we integrated bioinformatics and next-generation sequencing technologies to establish simple sequence repeat (SSR) marker selection database for Oreochromis niloticus (Nile tilapia). The designed system can facilitate fish farmers and biologists in effectively and efficiently performing marker-assisted selection. Genetic SSR biomarkers associated with the skeletal development system for Nile tilapias was experimentally verified in this study. In addition, a system for online comparison of two different Nile tilapia genomes was designed for the discovery of SSR variations. Based on Gene Ontology (GO) term features, a set of genes of interest and corresponding SSR biomarkers were retrieved and compared. Novel molecular biomarkers for a specific functional gene group can facilitate marker-assisted selection and breeding in the modern aquafarming industry.
Active site flexibility revealed in crystal structures of Parabacteroides merdae β‐glucuronidase from the human gut microbiome

β‐Glucuronidase (GUS) enzymes in the gastrointestinal tract are involved in maintaining mammalian‐microbial symbiosis and can play key roles in drug efficacy and toxicity. Parabacteroides merdae GUS was identified as an abundant mini‐Loop 2 (mL2) type GUS enzyme in the Human Microbiome Project gut metagenomic database. Here, we report the crystal structure of P. merdae GUS and highlight the differences between this enzyme and extant structures of gut microbial GUS proteins. We find that P. merdae GUS exhibits a distinct tetrameric quaternary structure and that the mL2 motif traces a unique path within the active site, which also includes two arginines distinctive to this GUS. We observe two states of the P. merdae GUS active site; a loop repositions itself by more than 50 Å to place a functionally‐relevant residue into the enzyme's catalytic site. Finally, we find that P. merdae GUS is able to bind to homo and heteropolymers of the polysaccharide alginic acid. Together, these data broaden our understanding of the structural and functional diversity in the GUS family of enzymes present in the human gut microbiome and point to specialization as an important feature of microbial GUS orthologs.
Uptake of elective laparoscopic colectomy for colon cancer in Canada from 2004/05 to 2014/15: a descriptive analysis.

BACKGROUND Evidence from randomized controlled trials published since 2004 shows that elective laparoscopic colectomy for colon cancer improves short-term postoperative outcomes with equivalent oncologic outcomes compared to open colectomy. The objective of this study was to examine the uptake of elective laparoscopic colectomy in Canada and compare its use among Canadian provinces. METHODS In this descriptive analysis, we identified from hospital discharge abstracts all patients in the Canadian provinces (except Quebec) who underwent elective colectomy for colon cancer between 2004/05 and 2014/15. We compared temporal changes in the proportion of patients who underwent laparoscopic colectomy or open colectomy among provinces using logistic regression. RESULTS Of 63 504 patients who underwent elective colectomy between 2004/05 and 2014/15, 19 691 (31.0%) underwent laparoscopic colectomy. The annual proportion of patients who underwent laparoscopic colectomy increased from 9.2% in 2004/05 to 51.5% in 2014/15 (mean annual percent increase 4.2%). There were significant differences between provinces in the overall proportion of patients who underwent laparoscopic colectomy (p < 0.001), ranging from 7.6% in Newfoundland and Labrador to 36.9% in Ontario. By 2014/15, most colectomy procedures were performed laparoscopically in 3 provinces; British Columbia (60.2%), Ontario (59.4%) and Alberta (53.1%). In addition to year and province, urban residence, younger age, female sex, fewer medical comorbidities, high surgeon volume, high hospital volume and right-sided tumours were significantly associated with increased likelihood of laparoscopic colectomy. INTERPRETATION Although the use of laparoscopic colectomy increased rapidly between 2004/05 and 2014/15 in Canada, substantial interprovincial variation exists. Further knowledge-translation strategies are needed to ensure equal access to laparoscopic colectomy for all Canadians.