Miracle-dz/UniFAR-FTUs huggingface dataset:
Insect diversity in the Saharo-Arabian region: Revealing a little-studied fauna by DNA barcoding

Although insects dominate the terrestrial fauna, sampling constraints and the poor taxonomic knowledge of many groups have limited assessments of their diversity. Passive sampling techniques and DNA-based species assignments now make it possible to overcome these barriers. For example, Malaise traps collect specimens with minimal intervention while the Barcode Index Number (BIN) system automates taxonomic assignments. The present study employs Malaise traps and DNA barcoding to extend understanding of insect diversity in one of the least known zoogeographic regions, the Saharo-Arabian. Insects were collected at four sites in three countries (Egypt, Pakistan, Saudi Arabia) by deploying Malaise traps. The collected specimens were analyzed by sequencing 658 bp of cytochrome oxidase I (DNA barcode) and assigning BINs on the Barcode of Life Data Systems. The year-long deployment of a Malaise trap in Pakistan and briefer placements at two Egyptian sites and at one in Saudi Arabia collected 53,092 specimens. They belonged to 17 insect orders with Diptera and Hymenoptera dominating the catch. Barcode sequences were recovered from 44,432 (84%) of the specimens, revealing the occurrence of 3,682 BINs belonging to 254 families. Many of these taxa were uncommon as 25% of the families and 50% of the BINs from Pakistan were only present in one sample. Family and BIN counts varied significantly through the year, but diversity indices did not. Although more than 10,000 specimens were analyzed from each nation, just 2% of BINs were shared by Pakistan and Saudi Arabia, 4% by Egypt and Pakistan, and 7% by Egypt and Saudi Arabia. The present study demonstrates how the BIN system can circumvent the barriers imposed by limited access to taxonomic specialists and by the fact that many insect species in the Saharo-Arabian region are undescribed.
Remediation of Polychlorinated Biphenyls (PCBs) in Contaminated Soils and Sediment: State of Knowledge and Perspectives

Polychlorinated biphenyls (PCBs) are one of the persistent organic pollutants (POPs) used worldwide between the 1930s and 1980s. Many PCBs can still be found in the environment such as in soils and sediments, even though their use has been heavily restricted. This review summarizes the most frequent remediation solutions including, phytoremediation, microbial degradation, dehalogenation by chemical reagent, and PCBs removal by activated carbon. New insights that emerged from recent studies of PCBs remediation including supercritical water oxidation, ultrasonic radiation, bimetallic systems, nanoscale zero-valent iron based reductive dehalogenation and biofilm covered activated carbon, electrokinetic remediation, and nZVI particles in combination with a second metal are overviewed. Some of these methods are still in the initial development stage thereby requiring further research attention. In addition, the advantages and disadvantages of each general treatment strategy and promising technology for PCBs remediation are discussed and compared. There is no well-developed single technology, although various possible technologies have been suggested. Therefore, the possibility of using combined technologies for PCB remediation is also here investigated. It is hoped that this present paper can provide a basic framework and a more profound prospect to select successful PCB remediation strategies or combined technologies.
Challenges of NTM Drug Development

Discovery and development of antibiotics active against the environmental opportunistic non-tuberculous mycobacteria (NTM) have been retarded by innate antibiotic-resistance of NTM cells and methodological challenges in the laboratory. The basis for the innate resistance of NTM cells is its lipid rich outer membrane that results in hydrophobic cells and the outer membrane’s impermeability, and the residence of NTM cells in phagocytic cells, and the slow growth and dormancy of NTM. Laboratory challenges include: the choice of species and strains for screening and measurement of anti-NTM activity, the high frequency colony switching between antibiotic-susceptible and resistant variants, the preference of NTM to adhere to surfaces and form biofilms, and the aggregation of NTM cells. Understanding these challenges can guide and inform our approaches to discovery and development of antibiotics with activity against NTM.
Effects of Training on Lateralization for Simulations of Cochlear Implants and Single-Sided Deafness

While cochlear implantation has benefitted many patients with single-sided deafness (SSD), there is great variability in cochlear implant (CI) outcomes and binaural performance remains poorer than that of normal-hearing (NH) listeners. Differences in sound quality across ears—temporal fine structure (TFS) information with acoustic hearing vs. coarse spectro-temporal envelope information with electric hearing—may limit integration of acoustic and electric patterns. Binaural performance may also be limited by inter-aural mismatch between the acoustic input frequency and the place of stimulation in the cochlea. SSD CI patients must learn to accommodate these differences between acoustic and electric stimulation to maximize binaural performance. It is possible that training may increase and/or accelerate accommodation and further improve binaural performance. In this study, we evaluated lateralization training in NH subjects listening to broad simulations of SSD CI signal processing. A 16-channel vocoder was used to simulate the coarse spectro-temporal cues available with electric hearing; the degree of inter-aural mismatch was varied by adjusting the simulated insertion depth (SID) to be 25 mm (SID25), 22 mm (SID22) and 19 mm (SID19) from the base of the cochlea. Lateralization was measured using headphones and head-related transfer functions (HRTFs). Baseline lateralization was measured for unprocessed speech (UN) delivered to the left ear to simulate SSD and for binaural performance with the acoustic ear combined with the 16-channel vocoders (UN+SID25, UN+SID22 and UN+SID19). After completing baseline measurements, subjects completed six lateralization training exercises with the UN+SID22 condition, after which performance was re-measured for all baseline conditions. Post-training performance was significantly better than baseline for all conditions (p < 0.05 in all cases), with no significant difference in training benefits among conditions. Given that there was no significant difference between the SSD and the SSD CI conditions before or after training, the results suggest that NH listeners were unable to integrate TFS and coarse spectro-temporal cues across ears for lateralization, and that inter-aural mismatch played a secondary role at best. While lateralization training may benefit SSD CI patients, the training may largely improve spectral analysis with the acoustic ear alone, rather than improve integration of acoustic and electric hearing.
Topology design of bankruptcy prediction neural networks using Particle swarm optimization and backpropagation

In this paper 1, the contribution of Particle Swarm (PSO) Optimization is studied to define the topology of artificial neural network. Moreover, we evolve the convergence of the PSO-PSO algorithm by presenting a new approach based on PSO and Backpropagation. Through this second algorithm, we studied the contribution of Backpropagation, with its strong ability to find local optimistic results, as particles initialization algorithm, to accelerate the convergence of the PSO to global minima. This hybrid model shows a high performance even in a context of missing data.
Internet of Things (IoT) as Assistive Technology: Potential Applications in Tertiary Education

The recent popularity of the Internet of Things (IoT) in the consumer space and Web of Things (WoT) work by the World Wide Web Consortium (W3C) has led to a Curtin University research project that has investigated the use of IoT by people with disabilities in the education space. Potential education-related IoT solutions raised in the research include the delivery of smartboard materials directly to the student to ensure compatibility with assistive technologies, the use of consumer-based IoT to provide captions and the monitoring of lecturer and student engagement in real-time to improve education delivery. While these technical possibilities are not new in their own right, the key points of interest from this research are that the students with disabilities, despite their IoT knowledge being limited to the emerging consumer space, have proposed these solutions as a way to support their learning. In addition, the fact such solutions are yet to be implemented in mainstream education settings despite the technical ability to do so raises concerns about the widening educational gap unless more effort is made by manufacturers to provide practical real-world IoT classroom solutions. While the use of IoT in these contexts may be considered an assistive technology in its own right, issues of privacy, security, and interoperability need to be addressed. As such, it is imperative that the W3C WoT work in this area continues to provide guidance and further academic research is needed.
Shipboard Power System Reconfiguration: A Self-Adaptation Exemplar

The Shipboard Power System (SPS) is the component responsible for granting energy to navigation, communication, and operational systems. The SPS Reconfiguration is the ability to react to electrical failure and to restore critical operations for granting vessel survivability. This work illustrate why SPS Reconfiguration software system may be implemented as a self-adaptive system. To illustrate this relation we exploit a systematic classification of SPS reconfiguration methods, by highlighting terms and attributes related to self-adaptive systems. In particular, the research method considers four types of self-adaptation systems with different degrees of autonomy and proactivity. The corresponding data analysis highlights a strong correlation between SPS Reconfiguration and Self-Adaptive systems, revealing most of the SPS reconfiguration techniques found in literature often belong to three of the four types of adaptation. The outcome of the paper is proposing SPS as an interesting benchmark for comparing self-adaptive approaches, also highlighting scenarios, tasks, norms goals and quality aspects with the support of the IEEE specifications.
In Vitro Uptake of Hydroxyapatite Nanoparticles and Their Effect on Osteogenic Differentiation of Human Mesenchymal Stem Cells

There have been many applications in biomedical fields based on hydroxyapatite nanoparticles (HA NPs) over the past decades. However, the biocompatibility of HANPs is affected by exposure dose, particle size, and the way of contact with cells. The objective of this study is to investigate the effect of HA NPs with different sizes on osteogenesis using human mesenchymal stem cells (hMSCs). Three different-sized HA NPs (~50, ~100, and ~150 nm, resp.) were synthesized to study the cytotoxicity, cellular uptake, and effect on osteogenic differentiation of hMSCs. The results clearly showed that each size of HA NPs had dose-dependent cytotoxicity on hMSCs. It was found that HA NPs could be uptaken into hMSCs. The osteogenic differentiation of hMSCs was evaluated through alkaline phosphatase (ALP) activity measurement, ALP staining, immunofluorescent staining for osteopontin (OPN), and real-time polymerase chain reaction (RT-PCR) examination. As expected, HA NPs of all sizes could promote the differentiation of hMSCs towards osteoblast lineage. Among the three sizes, smaller-sized HA NPs (~50 and ~100 nm) appeared to be more effective in stimulating osteogenic differentiation of hMSCs.
Hierarchical Regions of Interest

Mining crowd-sourced movement trajectories is a useful tool in urban computing. Common mobility patterns of the visitors or residents of a city can be exploited in applications such as disaster management, transportation planning and ad placement. In recommendation systems, individual behaviour is of special interest. To extract the visiting behaviour of individuals, the trajectories need to be semantically annotated. We describe how hierarchical regions of interest (ROIs) can be used for semantic annotation. By combining multiple layers of smaller and larger regions we can flexibly detect both visits to dense hotspots and trajectory segments visiting larger areas, such as an old town, a park or an island. Extending the annotation beyond common hotspots captures more information about the behaviour.
Efficient Privacy-Preserving Matrix Factorization for Recommendation via Fully Homomorphic Encryption

There are recommendation systems everywhere in our daily life. The collection of personal data of users by a recommender in the system may cause serious privacy issues. In this article, we propose the first privacy-preserving matrix factorization for recommendation using fully homomorphic encryption. Our protocol performs matrix factorization over encrypted users’ rating data and returns encrypted outputs so that the recommendation system learns nothing on rating values and resulting user/item profiles. Furthermore, the protocol provides a privacy-preserving method to optimize the tuning parameters that can be a business benefit for the recommendation service providers. To overcome the performance degradation caused by the use of fully homomorphic encryption, we introduce a novel data structure to perform computations over encrypted vectors, which are essential for matrix factorization, through secure two-party computation in part. Our experiments demonstrate the efficiency of our protocol.
Experiments and Comparisons of Power to Failure for SiGe-Based Low-Noise Amplifiers Under High-Power Microwave Pulses

This study demonstrates comparisons of power to failure for SiGe-based low-noise amplifiers by injecting high-power microwave pulses. A general equation was derived to calculate power to failure, which depends on pulse width and its duty cycle. Two types of silicon–germanium (SiGe) transistors were modeled, and their temperature distributions were simulated. The pulse thermal resistance, thermal capacitance, and breakdown temperature were calculated and determined. Results show that the power to failure of the two transistors depend on the number of slots, pulse thermal resistance, thermal capacitance, and breakdown temperature, although these transistors exhibit nearly similar structures. In addition, calculated and measured results show close correlations. A summary for calculating the power to failure of a type of SiGe transistor is provided.
Generalization in quasi-periodic environments

By and large the behavior of stochastic gradient is regarded as a challenging problem, and it is often presented in the framework of statistical machine learning. This paper offers a novel view on the analysis of on-line models of learning that arises when dealing with a generalized version of stochastic gradient that is based on dissipative dynamics. In order to face the complex evolution of these models, a systematic treatment is proposed which is based on energy balance equations that are derived by means of the Caldirola-Kanai (CK) Hamiltonian. According to these equations, learning can be regarded as an ordering process which corresponds with the decrement of the loss function. Finally, the main results established in this paper is that in the case of quasi-periodic environments, where the pattern novelty is progressively limited as time goes by, the system dynamics yields an asymptotically consistent solution in the weight space, that is the solution maps similar patterns to the same decision.
Design and Characterization of Inductors for Self-Powered IoT Edge Devices

This paper discusses the design, fabrication, and characterization of packaged planar inductors with magnetic material [nickel zinc (NiZn) ferrite]. Inductors are designed specifically for Internet of Things (IoT) applications based on power loss in an IoT architecture. Different spiral inductor geometries are demonstrated on a printed wiring board with varying thicknesses using a stencil printing process. The magnetic material can be applied to one or both sides of the inductor and, therefore, provides size reduction. This paper examines the role of varying dimensions on inductor performance along with model-to-hardware correlation. The fabrication process demonstrates inductance increase through a very simple procedure for applying a magnetic material on both sides of the inductor, while having flexibility to customize the geometry for minimal power loss in an IoT architecture. With NiZn ferrite material added to both sides of the inductor, the inductance increases between approximately 60% and 80% for the two substrate thicknesses studied, as compared to air-core inductors.
Entity-Level Sentiment Analysis of Issue Comments

Emotions and sentiment of software developers can largely influence the software productivity and quality. However, existing work on emotion mining and sentiment analysis is still in the early stage in software engineering in terms of accuracy, the size of datasets used and the specifcity of the analysis. In this work, we are concerned with conducting entity-level sentiment analysis. We frst build a manually labeled dataset containing 3,000 issue comments selected from 231,732 issue comments collected from 10 open source projects in GitHub. Then we design and develop SentiSW, an entitylevel sentiment analysis tool consisting of sentiment classifcation and entity recognition, which can classify issue comments into <sentiment, entity> tuples. We evaluate the sentiment classifcation using ten-fold cross validation, and it achieves 68.71% mean precision, 63.98% mean recall and 77.19% accuracy , which is signifcantly higher than existing tools. We evaluate the entity recognition by manually annotation and it achieves a 75.15% accuracy.
Relationship of Glove Arm Kinematics With Established Pitching Kinematic and Kinetic Variables Among Youth Baseball Pitchers

Background: While the kinematics of the pitching arm, trunk, and pelvis have been described and studied, glove arm kinematics remain an understudied portion of the pitching motion. Baseball pitchers seek to achieve maximum ball velocity in a fashion that does not place the arm at risk of injury. Purpose: To assess the relationship between glove arm shoulder horizontal abduction and elbow flexion and pitching arm kinematics and kinetics among youth pitchers to determine whether recommendations can be made toward a safer pitching motion. Study Design: Descriptive laboratory study. Methods: Thirty-three right-handed youth male baseball pitchers (mean ± SD: age, 13.6 ± 2.0 years; height, 169.4 ± 14.3 cm; weight, 63.5 ± 13.0 kg; experience, 7.3 ± 3.0 years) threw 3 fastballs to a catcher while kinematic data were collected with an electromagnetic tracking system. The Spearman rank-order test was used to identify relationships between glove arm horizontal abduction and glove arm elbow flexion and various kinematics and kinetics found at maximum shoulder external rotation (MER) and ball release for the fastest fastball delivered by each participant. Results: At MER, there were significant relationships found between a more flexed glove arm elbow and increased pitching arm elbow valgus force (rs [31] = –0.52, P = .002), increased pitching arm shoulder anterior force (rs = –0.39, P = .024), and decreased hip velocity (rs [31] = –0.45, P = .009). Additionally, there were significant relationships between greater glove arm horizontal abduction at MER and increased pitching arm humeral velocity (rs [31] = 0.52, P = .002) and increased trunk rotational velocity (rs [31] = 0.40, P = .022) at MER. Conclusion: A more extended glove arm elbow and more horizontally abducted glove arm shoulder at MER could prove to be more advantageous for performance and possibly be a safer motion for the baseball thrower. Clinical Relevance: The orthopaedic community can dictate safer biomechanics when communicating with pitchers, trainers, and pitching coaches.
The Roles of Thyroid and Thyroid Hormone in Pancreas: Physiology and Pathology

It is widely accepted that thyroid hormones (THs), secreted from the thyroid, play important roles in energy metabolism. It is also known that THs also alter the functioning of other endocrine glands; however, their effects on pancreatic function have not yet been reviewed. One of the main functions of the pancreas is insulin secretion, which is altered in diabetes. Diabetes, therefore, could be related to thyroid dysfunction. Earlier research on this subject focused on TH regulation of pancreas function (such as insulin secretion) or on insulin function through TH-mediated increase of energy metabolism. Afterwards, epidemiological investigations and animal test research found a link between autoimmune diseases, thyroid dysfunction, and pancreas pathology; however, the underlying mechanisms remain unknown. Furthermore, recent studies have shown that THs also play important roles in pancreas development and on islet pathology, both in diabetes and in pancreatic cancer. Therefore, an overview of the effects of thyroid and THs on pancreas physiology and pathology is presented. The topics contained in this review include a summary of the relationship between autoimmune thyroid dysfunction and autoimmune pancreas lesions and the effects of THs on pancreas development and pancreas pathology (diabetes and pancreatic cancer).
Video Time: Properties, Encoders and Evaluation

Time-aware encoding of frame sequences in a video is a fundamental problem in video understanding. While many attempted to model time in videos, an explicit study on quantifying video time is missing. To fill this lacuna, we aim to evaluate video time explicitly. We describe three properties of video time, namely a) temporal asymmetry, b)temporal continuity and c) temporal causality. Based on each we formulate a task able to quantify the associated property. This allows assessing the effectiveness of modern video encoders, like C3D and LSTM, in their ability to model time. Our analysis provides insights about existing encoders while also leading us to propose a new video time encoder, which is better suited for the video time recognition tasks than C3D and LSTM. We believe the proposed meta-analysis can provide a reasonable baseline to assess video time encoders on equal grounds on a set of temporal-aware tasks.