Miracle-dz/UniFAR-FTUs huggingface dataset:
BUTTERFLIES OF THE VLASINA REGION IN SOUTHEAST SERBIA (LEPIDOPTERA: PAPILIONOIDEA)

Although the Vlasina plateau has proved to be an interesting area hosting diverse and unique flora and fauna, itsbutterflies have not been thoroughly studied. Consolidating several known records and our field observations, a total of101 butterfly species were listed for this region. The area hosts a number of important species to be conserved underNatura 2000 and Emerald networks and a significant number of nationally important species. The most interesting recordis Colias caucasica, a butterfly not yet recorded in the neighboring region, and its finding is described here in more detail.
Seasonal observations on moulting and maturation in Stage V copepodites of Calanus finmarchicus from the Firth of Clyde

Stage V copepodites of Calarms finmarchicus collected from the Firth of Clyde during April–August 1978 and October 1979–January 1980 moulted to adults in the laboratory. The interval between capture and ecdysis was longer on average and less variable during the months July–November (when overwintering stocks build up in the Firth) than April–June. Overwintering Stage V copepodites moulted earlier in the laboratory than in the sea; this is not associated with differences in environmental factors known to affect developmental rate and may have been induced by stress associated with capture or handling. A similar induction of moulting is not evident in spring and summer generations.
The Human Microbiota as a Marker for Migrations of Individuals and Populations

In this review, we discuss evidence that the microbes that constitute the human microbiota coevolved with humans and maintain complex community and host interactions. Because these microbes are mostly vertically transmitted, they have evolved within each human group and provide a view of human ancestry. In particular, we discuss using Helicobacter pylori as a marker of ancestry and migrations. Other organisms with more mixed vertical and horizontal transmission are not suitable to trace migrations with any fidelity. Human mixing affects microbial phylogeographic signals, and lifestyles impact the human microbiome population structure. A decade after the human genome was sequenced, we are gaining insights into the population structure of the human microbiome. We also examine whether, rather than focus on the genetics of single microbial populations, a wider approach to the study of human ancestry based on the human microbiome is now possible.
Use of citizen advisory committees to direct deer management in Pennsylvania

Effective deer management must consider diverse stakeholder values. From 2006 to 2011, the Pennsylvania (USA) Game Commission implemented citizen advisory committees (CACs) to measure deer–human conflicts and tolerance for deer populations in each wildlife management unit. There was a general lack of public interest in participating in CACs. Key stakeholder groups were often absent and CACs exhibited a strong hunter bias. Although the CAC process seemed to benefit those involved, the scope was limited and likely did not represent the values and attitudes of the entire citizenry within the wildlife management unit. As a result of this CAC experience, the Pennsylvania Game Commission moved to a citizen survey in 2011 to ensure all interests are represented as the future success of deer management depends on greater understanding of the values and attitudes of every stakeholder. © The Wildlife Society, 2012
Two components of Northeast Atlantic herring within the same school during spawning: support for the existence of a metapopulation?

Johannessen, A. , Nottestad, L. , Ferno, A. , Langard, L. , and Skaret, G. 2009. Two components of Northeast Atlantic herring within the same school during spawning: support for the existence of a metapopulation? - ICES Journal of Marine Science, 66: 1740-1748.It has been hypothesized that some stocks of Atlantic herring are subject to genetic exchange and therefore should fit the definition of a metapopulation with subunits. Genetic exchange requires spatial overlap of individuals from different populations during spawning. We investigated a local herring population that is assumed to feed and spawn within the semi-enclosed marine ecosystem of Lindaspollene in west Norway, which is connected with the outer fjord only by a narrow sill. Acoustic recordings and gillnet samples demonstrated the mixed presence of two components within a single school throughout the spawning period 2005-2007. Members of the two components were of about the same size and in a similar stage of gonad development at all times, but the age composition was completely different. These observations represent the first documented case of different components being present in a spawning school and provide strong indications of regular interbreeding. Our data suggest that the two components represent autochthonous Lindas herring and allochthonous herring of coastal/oceanic origin, thereby supporting the metapopulation concept. Two alternative explanations, based on one migratory and one resident component of a single Lindas stock, are also discussed.
The choice of phenotypes for use of marker assisted selection in dairy cattle.

A granddaughter design with 10 grandsires was simulated to investigate different types of measurements of performance traits in marker assisted breeding evaluation (MA-BE). Genetic and phenotypic data were simulated for all grandsires, granddams and 500 sires. For each of the 100 replicates of the simulation the gametic relationship matrix was computed for one position and a MA-BE was performed to receive marker assisted breeding values as sum of the polygenic effect and animal's haplotypes effects. Spearman rank correlations were determined between marker assisted breeding values of the six input types and true breeding values. Correlations between de-regressed proofs (DRPV) and true breeding values (TBV) were highest (0.89), but correlations were also high between DRPV (0.86), daughter yield deviations (0.87) and TBV when weighted by the variance of the traits. Correlations were weaker for estimated breeding values weighted with the number of daughters.
Learning A Meta-Ensemble Technique For Skin Lesion Classification And Novel Class Detection

The frequency and fatality rates associated with skin Melanoma requires an accurate and efficient detection methodology to enable early medical diagnosis. Artificial Intelligence (AI) augmented detection methods aim at achieving this goal while reducing the costs and time involved in traditional methods. This work utilizes a two-level ensemble learning technique (trained with weighted losses) to improve accuracy over individual classification models. The ensemble technique alleviates over-fitting due to class imbalance in the dataset, achieving a Balanced Multi-class Accuracy (BMA) score of 0.591 without unknown class detection. The algorithm was extended by appending the proposed CS-KSU module collection to detect the presence of images belonging to novel classes during test time. The extended algorithm secured an Area Under the ROC Curve (AUC) score of 0.544 for the unknown class. Our algorithm’s performance is at par with the current state-of-the-art for this task1.
Nonverbal Vocalizations as Speech: Characterizing Natural-Environment Audio from Nonverbal Individuals with Autism

The study of nonverbal vocalizations, such as sighs, grunts, and monosyllabic sounds, has largely revolved around the social and affective implications of these sounds within typical speech. However, for individuals who do not use any traditional speech, including those with nonor minimally verbal (nv/mv) autism, these vocalizations contain important, individual-specific affective and communicative information. This paper outlines the methodology, analysis, and technology to investigate the production, perception, and meaning of nonverbal vocalizations from nv/mv individuals in natural environments. We are developing novel signal processing and machine learning methods that will help enable augmentative communication technology, and we are producing a nonverbal vocalization dataset for public release. We hope this work will expand the scientific understanding of these exceptional individuals’ language development and the field of communication more generally.
The Adoption of Building Information Modelling in Canada

Abstract: The First Annual BIM Survey was published in 2018 to understand the local adoption of Building Information Modelling (BIM) in the architecture, engineering, and construction (AEC) industries in the Greater Toronto Area. Technical analyses for the survey were also presented in the 2018 CSCE Conference in New Brunswick. Subsequently, the Second Annual BIM Survey was conducted in collaboration with the Residential Construction Council of Ontario, Canada BIM Council, BuildingSMART Canada, and local BIM chapters to engage AEC professionals in Canada. In this paper, sample results of the second survey are presented and benchmarked against those in the first survey. Cross-examinations of provinces and perspectives of BIM users and non-users are also discussed. This study serves as one of the milestones for BIM transition in Canada and aims to present a holistic view of the role that BIM plays in the future of the AEC industry.
Centroid and Inversion Charge Model for Long Channel Strained-Silicon GAA MOSFET with Quantum Effect

This paper presents a modelling approach for centroid and inversion charge of strained GAA MOSFET. Such analysis is essential to study the impact of the quantum effect on the device which involved with aggressive scaling of the radius of the channel and oxide layer thickness. In order to study the quantum effect in strained silicon GAA MOSFET, the Poisson-Boltzmann theorem and explicit modelling technique are used to conduct the analysis related to centroid and inversion charge. Quantum effects are integrated into the proposed model by introducing the quantum threshold and capacitance in term of centroid charge. The Bohm Quantum Model (BQP) is used to accommodate the quantum effect in the simulator. Our explicit model is in good agreement with the numerical simulator, for various strain level and centroid charge displacement. It is found that the inversion charge changed linearly with strain level. Besides, the doping level and radius of the device contributed to the changes of centroid charge displacement from the silicon-oxide interface to the center of the channel.
Rateless Code-Aided Transmission Scheme to Achieve Secrecy in a Delay-Constraint Environment

This paper analyses a secure transmission scheme using rateless codes (RC). As per the characteristic of the RC, receiver has to accumulate sufficient number of packets to reconstruct the entire source file. By utilizing the aforementioned characteristic, secure delivery can be achieved if the legitimate user accumulates required number of packets before the eavesdropper does. Thus, to expedite the decoding rate of the packets at the intended user, a two slot cooperative relaying is used. Besides, in this scheme, destination assists the source node and the source node assists the relay node in the first and the second slot respectively, to cooperatively send artificial noise without affecting the legitimate receiver. Quality of violation probability (QVP) which includes delay, reliability and secrecy is used as the performance metric, and its closed-form is derived. Both feedback-aided transmission (FT) and un-aided transmission (UT) are studied. Result shows that for FT, an increase in the total power reduces QVP, and by increasing the number of source packets intercept probability decays for both UT and FT.
Some quantitative studies on the benthos off Bombay

Distribution and abundance of benthic fauna in relation to environmental characteristics have been studied at twenty-two stations in May 1976 during the sixth cruise of R.V. Gaveshani. The study revealed that foraminifera and nematodes formed the dominant components of meiofauna at all depths, while polychaetes formed the bulk of macrobenthic biomass. The ratio of macro to meiofauna was 1:16,000 by number and 1:2 by wet weight. The ratio was numerically consistent at almost all stations inspite of variations in the ecological parameters. The sediment was largely muddy with varying proportions of silt and clay. It was rich in organic matter with an average value of 2.37%
Genetic variability and protein-protein interactions of puroindolines in relation to wheat grain texture and antimicrobial properties

The puroindoline genes, Pina-D1 and Pinb-D1, have been shown to be linked to grain hardness, an important trait in the end-use quality of wheat and hence in international usage and trade of wheat. Variations, in either or both genes, or lack of expression of either gene, result in a hard texture of common wheat, while the durum wheat that lacks both Pin genes is extremely hard. Depending on the type of mutation, a range of hardness observed. There has been a great interest to search for further genetic variations in these genes, firstly, to understand better the way these genes affect grain texture, and secondly, to introduce new variations into breeding programs in order to improve the end-use quality of wheat. Landraces of wheat, particularly from China (the secondary centre of origin of wheat), were analyzed and a new Pina-D1 allele was discovered, in addition to confirmation of several other reported alleles. Scanning electron microscopy analysis of various wheats with differences in their Pin alleles, showed more attachment between starch and protein matrix for those wheats either lacking Pins, or with potential truncation in either PIN, in comparison to the wheat with a single amino acid substitution in the Pin allele. Analysis of the Pinb-2 genes showed that these comprised a multigene family and were greatly diverse. Many new haplotypes were identified in hexaploid, tetraploid and dipoid wheats, including a new group designated Pinb-2v6. Synthetic peptides, designed based on the truncated tryptophan rich domain (TRD) of the putative PINB-2 proteins, comprising of only two Trps, showed antibacterial and antifungal activity, suggesting that the PINB-2 proteins could be of importance in seed defense, as suggested for the PINs. Many studies have suggested that the PIN proteins (PINA and PINB) were interdependent and interact to confer the grain softness trait. Examination of this aspect using the yeast two-hybrid system showed that PINA and PINB did interact physically, thus shedding some light on their possible function and supporting suggestions that they co-operatively bind to lipids. PINA was also able to interact with itself, which may be relevant to more number of Trps present at the TRD in comparison to PINB and GSP-1 which may have some association to its suggested ability to aggregate at the lipid membrane. The observed interactions of GSP-1 with PINA or PINB, suggest that the GSP-1 could be a minor factor influencing grain hardness.
Supportive Voice-Casting Robots using Bio-Estimated Emotion for Rehabilitation

We have developed a robot that voice-casting during the rehabilitation considering the emotion of the people. Firstly, we have discussed how to motivate rehabilitation by grasping the feelings of the patient and speaking from the results as it is called "supportive voice is important". As a method of grasping the patient's feelings, emotional analysis using biometric information was decided. Biological information is activity information of the body unconsciously issued by a person. Several methods for identifying emotion using such information has been proposed. In the research, we conducted emotional estimation using a pulse sensor to acquire the feelings of the person in motion, and designed and implemented a voice-casting robot that makes voice calls. As a result, it was possible to confirm the effectiveness of a voice-casting robot that performs supportive actions while using emotions.
Synthesis of Fault-Tolerant Reconfigurable Scan Networks

On-chip instrumentation is mandatory for efficient bring-up, test and diagnosis, post-silicon validation, as well as in-field calibration, maintenance, and fault tolerance. Reconfigurable scan networks (RSNs) provide a scalable and efficient scan-based access mechanism to such instruments. The correct operation of this access mechanism is crucial for all manufacturing, bring-up and debug tasks as well as for in-field operation, but it can be affected by faults and design errors.This work develops for the first time fault-tolerant RSNs such that the resulting scan network still provides access to as many instruments as possible in presence of a fault. The work contributes a model and an algorithm to compute scan paths in faulty RSNs, a metric to quantify its fault tolerance and a synthesis algorithm that is based on graph connectivity and selective hardening of control logic in the scan network. Experimental results demonstrate that fault-tolerant RSNs can be synthesized with only moderate hardware overhead.
Parasites mediate the relationship between host diversity and disturbance frequency

Patterns of community and population diversity are likely to be dependent on interactions between ecological variables. Here we address how two important ecological variables – extrinsic periodic mortality events (disturbances) and the presence of obligate-killing parasites – interact to affect the diversity of niche-specialist genotypes in laboratory populations of the bacterium Pseudomonas fluorescens. Consistent with previous studies, diversity was maximized at intermediate frequencies of disturbance in the absence of parasitic bacteriophages (phages). By contrast, no relationship was found between diversity and disturbance frequency in the presence of phage. The results can be explained in part by differential effects of phage on bacterial densities, and hence resource competition, under different disturbance regimes.
Pitfalls in Machine Learning-based Adversary Modeling for Hardware Systems

The concept of the adversary model has been widely applied in the context of cryptography. When designing a cryptographic scheme or protocol, the adversary model plays a crucial role in the formalization of the capabilities and limitations of potential attackers. These models further enable the designer to verify the security of the scheme or protocol under investigation. Although being well established for conventional cryptanalysis attacks, adversary models associated with attackers enjoying the advantages of machine learning techniques have not yet been developed thoroughly. In particular, when it comes to composed hardware, often being security-critical, the lack of such models has become increasingly noticeable in the face of advanced, machine learning-enabled attacks. This paper aims at exploring the adversary models from the machine learning perspective. In this regard, we provide examples of machine learning-based attacks against hardware primitives, e.g., obfuscation schemes and hardware root-of-trust, claimed to be infeasible. We demonstrate that this assumption becomes however invalid as inaccurate adversary models have been considered in the literature.
Oversampling Algorithm Based on Spatial Distribution of Data Sets for Imbalance Learning

Imbalance problem is widespread in machine learning. Most learning algorithms can’t get satisfied performance when they are applied on imbalance data sets, because they can be deteriorated by this problem easily. This paper proposed SDSMOTE method which captures the spatial distribution of imbalance data sets, and changes the tendency of learning algorithm by over sampling by oversampling according to the recognition difficulty. Experiments on 5 UCI data sets validate the effectiveness of this oversampling algorithm.
Integrated Optical Mode Converter With Vertical Coupling

We propose the design of an integrated optical mode converter consisting of the single-mode ring resonator, single-mode input access waveguide, and multimode output access waveguide. Access waveguides are designed under the ring forming the stack structure with vertical gap therefore device has vertical mode coupling. The higher-order mode in the multimode waveguide is phase-matched with the fundamental mode in the ring but all other modes are mismatched, the widths of the ring and single-mode waveguide are equal, therefore excitation of the fundamental mode in the single-mode waveguide leads to the inducing the higher-order mode in the multimode waveguide. We used finite difference time domain simulation of the device and found that straight access waveguides give the best performance of the mode conversion at the device output in comparison with the bent “pulley-coupling” scheme. The simulation shows high mode purity at the device output. Because of the resonant character of the spectrum, proposed device is WDM-compatible and can be used for mode division multiplexing systems.
Screening of Indonesian Plants for Antifungal and Free Radical Scavenging Activities

A total of 204 crude extracts of Indonesian plants (77 species from 43 families) have been screened for their fungicidal (Cladosporium cucumerinum, Candida albicans) and free radical scavenging [2,2-diphenyl-1-picrylhydrazyl (DPPH) radical] activities. Of the species investigated, 20 were active against Cladosporium cucumerinum, nine against Candida albicans and 24 exhibited radical scavenging properties.
NeuronFlow: a neuromorphic processor architecture for Live AI applications

Neuronflow is a neuromorphic, many core, data flow architecture that exploits brain-inspired concepts to deliver a scalable event-based processing engine for neuron networks in Live AI applications. Its design is inspired by brain biology, but not necessarily biologically plausible. The main design goal is the exploitation of sparsity to dramatically reduce latency and power consumption as required by sensor processing at the Edge.
Preliminary Identification of Speech Hoarseness from Cancer and Normal Speech

The problem of speech hoarseness already arise for long especially in any kind of customer service interaction, in education or audio medical studies. But this issue is not widely in cover or explore especially in terms tendency checking for variety of video, in gender, age, and between normal or hoarseness speech model. The current studies conducted initial experiments with audio speech signal contains of normal and hoarseness data from ‘Saarbrücken Voice Database’. This study is prevalence for investigating the difference between normal and hoarseness voice speech by implementing classification algorithm of K-Nearest Neighbor(KNN) and Gaussian Mixture Model(GMM) in order to find the best algorithm in identifying the different datasets of audio and the performance for different types of algorithm. For KNN, the classification accuracies achieved 70% for both combination of datasets while with GMM achieved higher accuracies for 90% from the overall combination. Through this preliminary studies can embarked more focus in identifying on hoarseness cases for education fields and not only to medical sector.