Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the feasibility of using photo-identification studies to assist in investigations of short-finned pilot whale (Globicephala macrorhynchus) strandings along the US Southeast Coast

Pilot whales are an extremely social species, which is also associated with larger, more frequent strandings. Through intensive photo-identification efforts, the Duke University Marine Lab (DUML) has accumulated a catalog of over 1,700 individual pilot whales photographed off of Cape Hatteras, Jacksonville and Onslow Bay. The purpose of this study is to determine if two valuable research programs, photo-identification systems and marine mammal stranding procedures, can be used in union to contribute to a better understanding of marine mammal health and population dynamics. To identify this link, this research is comprised of three parts: 1) An overview of all recorded pilot whale strandings on the Southeast coast through statistical analysis of available stranding records; 2) Identification of possible overlaps in data by obtaining and matching photographs of stranded pilot whales to the Duke University Marine Lab’s catalog; and 3) Lastly, a review of best practices in the stranding and photo-identification protocols, in order to identify if this is a feasible and constructive data sharing initiative. Although no matches were made between the pictures of stranded pilot whales and DUML’s catalog, these data still offered many other important insights into this species’ tendencies and the systems we use to examine them.
Tactical Risk Assessment Method for Resilient Fuel Supply Chains for a Military Peacekeeping Operation

The article focuses on research on the functioning of liquid fuel supply chains, supplying troops carrying out peacekeeping and stabilisation operations in a foreign territory. Timely and complete supplies of fuels in war conditions determine the achievement of the assumed goals of a military operation. They often determine the health and life of soldiers. For this reason, the role of building the resilience of supply chains to disruptions, the type and frequency of which is entirely different from the undesirable events occurring in civil goods flows, is increasing. Therefore, the critical concept supporting building the resilience of fuel supply chains is risk management in these chains. The authors have developed a risk analysis method that integrates the Kaplan and Garrick approach and the fuzzy theory. The analysis identifies the existing disturbances and assigns them to the individual phases of the supply process. To illustrate the applicability of the proposed method, the authors analyse nine scenarios for the three most important stages of the procurement process in terms of building the resilience of the entire chain: Planning, delivery and storage. The fuzzy theory estimates the risk level for the analysed scenarios of adverse events. The proposed method is universal. It can be implemented to analyse the resistance of supply chains of other materials. It can also support the decision-making process for those responsible for planning, organisation and proper functioning of supply systems in all high-risk conditions, not only in the zone of war and stabilisation operations.
Supplementary Material for Partially View-aligned Clustering

In this supplementary material, we provide additional information including the network architecture, the training configuration, and implementation details. To investigate the effectiveness of the proposed differentiable aligning module, we conduct the experiments on the Pascal dataset to obtain the aligning results by Hungarian and our method. Furthermore, in the main paper, we report the performance comparison on the partially aligned data with the Hungarian algorithm performed on the PCA projected data. For a more complete comparison, in this material, we replace the PCA technology with auto-encoders (AEs) and report the results of the multi-view clustering baselines on the partially aligned data.
aDFS: An Almost Depth-First-Search Distributed Graph-Querying System

Graph processing is an invaluable tool for data analytics. In particular, pattern-matching queries enable ﬂexible graph exploration and analysis, similar to what SQL provides for relational databases. Graph queries focus on following connections in the data; they are a challenging workload because even seemingly trivial queries can easily produce billions of intermediate results and irregular data access patterns. In this paper, we introduce aDFS: A distributed graph-querying system that can process practically any query fully in memory, while maintaining bounded runtime memory consumption. To achieve this behavior, aDFS relies on (i) almost depth-ﬁrst (aDFS) graph exploration with some breadth-ﬁrst characteristics for performance, and (ii) non-blocking dispatching of intermediate results to remote edges. We evaluate aDFS against state-of-the-art graph-querying (Neo4J and GraphFrames for Apache Spark), graph-mining (G-Miner, Fractal, and Peregrine), as well as dataﬂow joins (BiGJoin), and show that aDFS signiﬁcantly outperforms prior work on a diverse selection of workloads.
Wearable Device-Based Smart Football Athlete Health Prediction Algorithm Based on Recurrent Neural Networks

For football players who participate in sports, the word “health” is extremely important. Athletes cannot create their own value in competitive competitions without a strong foundation. Scholars have paid a lot of attention to athlete health this year, and many analysis methods have been proposed, but there have been few studies using neural networks. As a result, this article proposes a novel wearable device-based smart football player health prediction algorithm based on recurrent neural networks. To begin, this article employs wearable sensors to collect health data from football players. The time step data are then fed into a recurrent neural network to extract deep features, followed by the health prediction results. The collected football player health dataset is used in this paper to conduct experiments. The simulation results prove the reliability and superiority of the proposed algorithm. Furthermore, the algorithm presented in this paper can serve as a foundation for the football team's and coaches' scientific training plans.
Anti-Flagellin Primary Antibody Responses FliC's Hypervariable D3 Domain Is Required for Robust

Bacterial flagellin is a well-known agonist of the innate immune system that induces proinflammatory responses through the TLR5 and Naip5/6 recognition pathways. Several clinical trials investigating flagellin fusion proteins have demonstrated promising results for inducing protective immunity toward influenza virus, which has been largely attributed to flagellin’s ability to activate TLR5. Our laboratory previously demonstrated that the Salmonella enterica serovar Typhimurium flagellin protein, FliC, induces Ab responses in mice through a third pathway that is independent of TLR5, Casp1/11, and MyD88. In this study, we further define the structural features of FliC that contribute to this unknown third pathway. By destroying the Naip5/6 and TLR5 recognition sites, we demonstrate that neither were required for the TLR5-, inflammasomeand MyD88-independent Ab responses toward FliC. In contrast, deletion of FliC’s D3 or D0/D1 domains eliminated primary anti-flagellin Ab responses. For optimal primary and secondary anti-flagellin Ab responses we show that TLR5, inflammasome recognition, and the D3 domain of FliC are essential for flagellin’s robust immunogenicity. Our data demonstrate that the D3 domain of FliC influences immunogenicity independent of the known innate recognition sites in the D0/D1 domains to augment Ab production. Our results suggest full-length FliC is critical for optimal immunogenicity and Ab responses in flagellin-based vaccines. ImmunoHorizons, 2019, 3: 422–432.
Comparison of Bone- and Tooth-Anchored, Bone-Anchored, and Surgically Assisted Bone-Anchored Rapid Palatal Expansion: a Pilot Retrospective CBCT Study

Introduction: The purpose of this retrospective pilot study is to evaluate and compare the transverse dental and skeletal changes in three different approaches to miniscrew-assisted rapid palatal expansion (MARPE) including boneand tooth-anchored (BTAME), bone-anchored (BAME), and surgically assisted bone-anchored maxillary expansion (SRBAME) maxillary expansion. The secondary purpose is to formulate new research questions and develop methods for future MARPE studies. Materials and Methods: Pre(T1) and post-expansion (T2) Cone Beam Computed Tomography (CBCT) radiographs from 12 patients treated with BAME (median age = 15.5, 95% CI 14.0-18.1), 7 patients treated with BTAME (median age = 19, 95% CI 14.8-26.9), and 5 patients treated with SRBAME (median age = 38, 95% CI 21.6-56.0) were included in the study. All skeletal, alveolar, and dental changes were standardized using suture opening at first molar for intergroup comparisons. There were seven linear and two angular measurements evaluated at the first premolar, second premolar, first molar, and second molar levels for intraand intergroup comparisons. Results: BTAME and BAME approaches both resulted in significant changes to transverse skeletal and alveolar transverse dimension with some dental tipping. Alveolar bone tipping at the first molar level in BAME was greater than in BTAME (p0.05) while it was significantly greater in the anterior than posterior in BAME (p Conclusions: Both BTAME and BAME result in significant transverse skeletal, alveolar, and dental expansion. BAME resulted in greater alveolar bone bending while BTAME resulted in greater dental tipping. Among the three groups, BTAME suture opening was closest to parallel from anterior to posterior. Contribution of skeletal expansion to intermolar width increase is more favorable in BAME than BTAME. Degree Type Thesis Degree Name MSOB (Master of Science in Oral Biology) Primary Advisor Dr. Hyeran Helen Jeon
Water sampling for environmental DNA surveys by using an unmanned aerial vehicle

Environmental DNA (eDNA) techniques utilizing DNA fragments from water have recently been developed to investigate the distribution and abundance/biomass of aquatic organisms. The eDNA technique is based on the analysis of DNA fragments in sampled water; thus, an unmanned aerial vehicle (UAV; drone) would be a useful way of collecting water for eDNA sampling, and may consequently allow us to extend eDNA surveys both spatially and temporally. Here, we developed a new method of water collection by using UAV with bleachable equipment, to avoid DNA contamination. To test the performance and contamination risk of UAV water sampling in eDNA surveys, we sampled water from a dam reservoir, detected eDNA from two fish species, and compared the water samples obtained by UAV with those obtained by boat. Additionally, we investigated contamination using blank samples. The results revealed that our UAV water sampling method performed similar to the boat sampling method. No positive signals were detected in the blank samples, including those used for UAV sampling, transportation, filtering, and PCR blanks. Our UAV method can be used to investigate species distributions using eDNA. Combinations of UAV technologies, including remote and thermal sensing, will enable efficient environmental monitoring in various waterbodies.
Decomposed (cid:179) Spatial and Temporal (cid:180) Convolution for Human Action Recognition in Videos

In this paper we study the effect of decomposed spatiotemporal convolutions for action recognition in videos. Our motivation emerges from the empirical observation that spatial convolution applied on solo frames of the video provide good performance in action recognition. In this research we empirically show the accuracy of factorized convolution on individual frames of video for action classification. We take 3D ResNet-18 as base line model for our experiment, factorize its 3D convolution to 2D (Spatial) and 1D (Temporal) convolution. We train the model from scratch using Kinetics video dataset. We then fine-tune the model on UCF-101 dataset and evaluate the performance. Our results show good accuracy similar to that of the state of the art algorithms on Kinetics and UCF-101 datasets.
Appendix of Prophet Attention

Fenglin Liu1, Xuancheng Ren2, Xian Wu3, Shen Ge3, Wei Fan3, Yuexian Zou1,4, Xu Sun2,5 1ADSPLAB, School of ECE, Peking University, Shenzhen, China 2MOE Key Laboratory of Computational Linguistics, School of EECS, Peking University 3Tencent, Beijing, China 4Peng Cheng Laboratory, Shenzhen, China 5Center for Data Science, Peking University {fenglinliu98, renxc, zouyx, xusun}@pku.edu. cn {kevinxwu, shenge, Davidwfan}@tencent.com
Composition and Niche-Specific Characteristics of Microbial Consortia Colonizing Marsberg Copper Mine in the Rhenish Massif

Abstract. The Kilianstollen Marsberg (Rhenish Massif, Germany) has been extensively mined for copper ores, dating from Early Medieval Period till 1945. The exposed organic-rich alum shale rocks influenced by the diverse mine drainages at an ambient temperature of 10 °C could naturally enrich biogeochemically distinct heavy metal resistant microbiota. This metagenomic study evaluates the microbially colonized subterranean rocks of the abandoned copper mine Kilianstollen to characterize the colonization patterns and biogeochemical pathways of individual microbial groups. Under the selective pressure of the heavy metal contaminated environment at illuminated sites, Chloroflexi (Ktedonobacteria) and Cyanobacteria (Oxyphotobacteria) build up whitish-greenish biofilms. In contrast, Proteobacteria, Firmicutes and Actinobacteria dominate rocks around the uncontaminated spring water streams. The metagenomic analysis revealed that the heavy metal resistant microbiome was evidently involved in redox cycling of transition metals (Cu, Zn, Co, Ni, Mn, Fe, Cd, Hg). No deposition of metals or minerals, though, was observed by transmission electron microscopy in Ktedonobacteria biofilms which may be indicative for the presence of different detoxification pathways. The underlying heavy metal resistance mechanisms, as revealed by analysis of metagenome-assembled genomes, were mainly attributed to transition metal efflux pumps, redox enzymes, volatilization of Hg0, methylated intermediates of As(III) and reactive oxygen species detoxification pathways.
Detection of Anomalies in Working Posture during Obstacle Avoidance Tasks using One-Class Support Vector Machine

: This study was conducted to evaluate working posture during obstacle avoidance tasks using a one-class support vector machine (SVM), and to compare the efficacy of this method in relation to traditional ergonomic evaluation methods. Eleven right-handed male participants performed reaching tasks in which they were required to move their right arm toward a predefined target position while avoiding obstacles. Working position, obstacle height/width, and obstacle presence varied among the experimental conditions. Working posture and subjective difficulty were assessed for each condition. The one-class SVM was applied to the quaternion of each body segment, which was determined based on measurements of working posture. Rates of postural anomalies were calculated for each experimental condition. The rates of postural anomalies for the right upper limb and head/neck increased as the width of the obstacle increased. Similarly, the subjective difficulty of work increased as obstacle width increased. Observational methods are unable to identify postural anomalies with regard to the right shoulder abduction angle and right lateral bending angle of the neck. However, our findings indicate that the proposed one-class SVM can detect postural anomalies in the right upper limb and head/neck for different obstacle widths.
Running title:LEVELS OF PHENYLPROPANOIDS AND IRIDOIDS IN GERVÃO Academy Section: Chemical Sciences

Herein we report for the first time the levels of phenylpropanoids and iridoids in extracts and infusions of V. minutiflora consumed in Brazil to treat urinary and infectious disorders. An in house validation study demonstrated good accuracy and precision to determine the bioactive compounds in V. minutiflora by HPLC-DAD. Phenylpropanoids varied in the extracts (leaves 139.70 to 221.20 mg g, flowers 106.43 to 227.22 mg g, stems 42.18 to 56.48 mg g). Verbascoside occurred in higher concentration in extracts of leaves (87.66 – 136.16) mg g and flowers (58.12 – 148.96) mg g than in stems (19.24 – 24.62) mg g. Iridoids in extracts were as follows: leaves (46.60 − 54.79) mg g, flowers (55.88 − 93.87) mg g and stems (40.05 to 61.74) mg g. High levels of iridoids (314.70 − 415.10) μg mL, phenylpropanoids (1996.39 − 2674.13) μg mL and verbascoside (1029.38 − 1456.42 μg mL) in infusions support the popular consume of V. minutiflora.
First Documentation of Life Cycle Completion of the Alien Rust Pathogen Melampsoridium hiratsukanum in the Eastern Alps Proves Its Successful Establishment in This Mountain Range

Melampsoridium hiratsukanum is an alien rust fungus which has spread pervasively throughout several European countries following introduction into North Europe at the end of the 20th century. The authenticity of several records of the Melampsoridium species infecting alder (Alnus spp.) in the northern hemisphere is questionable, due to the misidentification and confusion that surround many of the older reports. Given this complicated taxonomic history, and since a M. hiratsukanum-like rust is strongly impacting Alnus incana stands in the Alps, probably affecting the bank protection role of this species along rivers, the unambiguous identification of this pathogen was a pressing epidemiological and ecological issue. In this study, field surveys, light (LM) and scanning electron microscopy (SEM), and molecular characterization were put together in an attempt to solve the conundrum. Field monitoring data, LM and SEM analyses of key taxonomic traits (length of ostiolar cells of uredinium, uredinio-spore shape and size, spore echinulation, number and position of germ pores) and ITS-rDNA sequence-based identification, convergently and unambiguously connected the rust that is causing the current epidemic to the non-native M. hiratsukanum. We documented the completion of the M. hiratsukanum life cycle on its two taxonomically unrelated broadleaf/conifer hosts. This is the first report of M. hiratsukanum from naturally infected Larix decidua in Europe.
Facile fabrication of perovskite layers with large grains through a solvent exchange approach

Large-grained perovskite layers with fewer defects are beneficial to minimize carrier recombination at grain boundaries, thus boosting cell performance. Here, we present a facile solvent exchange strategy (SES) to yield large-grained perovskite films with high reproducibility. Upon employing a stoichiometric PbI2 : MAI : DMSO (3 : 2 : 2) precursor solution, we reduced the number of colloidal intermediates (PbI42−) which is correlated with the nucleation of seeds, resulting in a perovskite thin layer with large grain sizes up to 2 μm. The SES prepared CH3NH3PbI3 devices show significantly reduced grain boundaries corresponding to the decrease of recombination centers, which dramatically boosted the efficiency up to 17.2%.
An Experimental and Theoretical Study on the Aldol Condensation on Zirconium-Based Metal-Organic Framework

The aldol condensation of acetone in zirconium-based metal-organic framework functionalized by a sulfonic acid group (UiO-66-SO3H) has been theoretically investigated using the density functional theory. Acetone adsorbed on the UiO-66-SO3H with the adsorption energy of -17.4 kcal/mol. The catalyzed reaction has been proposed to be a two-step mechanism: the tautomerization of keto form to produce enol form of acetone, and the aldol condensation to produce diacetone alcohol. The activation energies were calculated to be 27.2 and 6.4 kcal/mol, respectively. For the experimental part, UiO-66-SO3H catalyst was synthesized and characterized by X-ray diffraction and IR spectroscopy. The catalytic reaction was carried out in a stirred batch reactor at different temperatures to optimize the reaction conditions. The obtained products were analyzed by 1H-NMR spectroscopy and chromatography techniques. This study demonstrated that UiO-66-SO3H can be used as a solid catalyst for the aldol condensation reaction.
Urinary Tract Infection among Adults Seeking Medicare at Kiambu Level 5 Hospital, Kenya: Prevalence, Diversity, Antimicrobial Susceptibility Profiles and Possible Risk Factors

Urinary tract infections are among the most prevalent extra-intestinal infections, with high prevalence globally. This cross-sectional study established prevalence of bacterial aetiology causing urinary tract infection (UTI) and their antimicrobial susceptibility profiles. A questionnaire was used to capture socio-demographic data and possible UTI risk factors among the 206 consented adults seeking medicare at Kiambu Level 5 Hospital. The collected midstream urine samples were subjected to dipstick analysis, microscopy and culture for UTI diagnosis. Results: The overall prevalence rate of UTIs was 27.6%, with women’s prevalence rate being significantly higher at 80.7% compared to men 19.2%. Pregnant women had UTI prevalence at 34% which was higher than other sets of participants. Women who did not frequently change their underpants daily had a higher UTI cases at 34.8%. Escherichia coli, Staphylococcus aureus and Klebsiella pneumoniae were the most prevalent bacterial pathogens at 38.5%, 21% and 19.3%, respectively. Antimicrobial sensitivity analysis revealed high resistances towards Sulfamethoxazole and Ampicillin at range between 50% 85%, suggesting that these drugs are no longer effective for UTI empirical treatment. The resistance patterns towards Cefotaxime, Cefepime and Ciprofloxacin were below 40%. However, more resistance patterns at a range between 14% 40% revealed towards Amoxicillin-clavulanic and Nitrofurantoin imply that these are drugs remain potent but there is the need to revise the current UTI management guidelines. In adHow to cite this paper: Wanja, F. , Ngugi, C. , Omwenga, E. , Maina, J. and Kiiru, J. (2021) Urinary Tract Infection among Adults Seeking Medicare at Kiambu Level 5 Hospital, Kenya: Prevalence, Diversity, Antimicrobial Susceptibility Profiles and Possible Risk Factors. Advances in Microbiology, 11, 360-383. https://doi.org/10.4236/aim.2021. 118028 Received: July 1, 2021 Accepted: July 29, 2021 Published: August 2, 2021 Copyright © 2021 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access
Dry vs Wet Cough Automatic Classiﬁcation using the COUGHVID Dataset

—Machine learning provides valuable tools for health care, such as helping detecting respiratory infections by analyzing audio recordings of coughs. The audio recordings present patterns that indicates whether the cough is dry or wet, which is useful to reveal infections like Covid-19. The database COUGHVID created by the Embedded Systems Lab has managed to gather a large collection of 20’000 coughs recordings from both healthy or Covid-19 ill patients, from which 10% have been assessed by medical experts to determine whether or not they were related to a Covid-19 condition. We present a model able to classify audio recordings between dry or wet. The model has been trained on audio features from the recordings labeled by the experts and reaches 0.66 testing accuracy. Results show that including metadata like the age, gender or respiratory symptoms determined by the experts could help improve the classiﬁcation.