Miracle-dz/UniFAR-FTUs huggingface dataset:
Preference-Inspired Coevolutionary Algorithm Based on Differentiated Resource Allocation Strategy

Preference-inspired co-evolutionary algorithms (PICEAs) consider the target vectors as the preferences, and then use the domination relationship between the candidate solutions and target vectors to increase their selection pressure. However, the size of dominating objective space varies with the different positions of candidate solutions and it leads to the imbalance of the evolutionary ability of whole population. To solve this problem, this paper proposes a preference-inspired coevolutionary algorithm based on a differentiated allocation strategy (PICEAg-DS). First, it sets up an external archive to save the nondominated solutions and then extracts the convergence and diversity information from it. Second, it divides the objective space into several subspaces and designs a space distance operator to evaluate their optimization difficulty. Finally, it dynamically assigns the target vectors and guides more computational resource to the difficult to optimize subspaces, and thus drives the whole population evolution. To prove the advantages of differentiated resource allocation strategy, the PICEAg-DS is compared with two classic coevolutionary algorithms (PICEAg, CMOPSO) and two classic MOEAs based on resource allocation strategy (EAG-MOEAD, MOEAD-DRA). The experimental results show that PICEAg-DS performs better than the other algorithms on many WFG test problems. To further analysis the effectiveness of PICEAg-DS, compare it with two MOEAs based on domination relationship (NSGAII, SPEA2) and two MOEAs based on decomposition (RVEA, MOEA/D-M2M) on MOP and UF test suite. The experimental results show the PICEAg-DS has a better convergence than the other comparison algorithms, especially on 3-objective MOP6-7 and UF8-9.
A convolutional neural network for detecting sea turtles in drone imagery

Marine megafauna are difficult to observe and count because many species travel widely and spend large amounts of time submerged. As such, management programmes seeking to conserve these species are often hampered by limited information about population levels. Unoccupied aircraft systems (UAS, aka drones) provide a potentially useful technique for assessing marine animal populations, but a central challenge lies in analysing the vast amounts of data generated in the images or video acquired during each flight. Neural networks are emerging as a powerful tool for automating object detection across data domains and can be applied to UAS imagery to generate new population‐level insights. To explore the utility of these emerging technologies in a challenging field setting, we used neural networks to enumerate olive ridley turtles Lepidochelys olivacea in drone images acquired during a mass‐nesting event on the coast of Ostional, Costa Rica. Results revealed substantial promise for this approach; specifically, our model detected 8% more turtles than manual counts while effectively reducing the manual validation burden from 2,971,554 to 44,822 image windows. Our detection pipeline was trained on a relatively small set of turtle examples (N = 944), implying that this method can be easily bootstrapped for other applications, and is practical with real‐world UAS datasets. Our findings highlight the feasibility of combining UAS and neural networks to estimate population levels of diverse marine animals and suggest that the automation inherent in these techniques will soon permit monitoring over spatial and temporal scales that would previously have been impractical.
UnderstandingSouth Tangerang's Generation Z during 2019 Student Protest through Empathy Map Canvas

During Student Protest in September 23-24 2019, Indonesian Gen Z succeed to give a new looks for a student protest in Indonesia through various posters and slogans that influenced by various meme in social media and also how they held the protest itself. This phenomena is something that never been seen in Indonesian student activism before. In order to get understanding this phenomena, Empathy Map Canvas has been chosenas a tool to get better insight of Indonesian Gen Z perspective.This study aimed to see Indonesian Gen Z perspective in relation with politic and democracy. Quantitative study in the form of surveys and questionnaires that covered daily visual and audio experience and also their behavior were conducted with respondents students from various universities in South Tangerang that participated in the protest. In addition, qualitative study in the form of interview also conducted to the same group of respondents. This study confirm the intimate relation between of Indonesian Gen Z and social media, that in return influenced the way they communicate, think, and how to achieve their goal. At last, this study would provide insight for any politicians and political party that would like to get better understanding for Indonesian Gen Z.
Enhanced and High-Purity Enrichment of Circulating Tumor Cells Based on Immunomagnetic Nanospheres

Enrichment and purification of circulating tumor cells (CTCs) from peripheral blood is very critical for their detection and downstream analyses, in which many technologies have achieved good effects. However, efficient and high-purity enrichment of CTCs is still challenging because of their rarity and heterogeneity. Herein, anti-CD45 antibody-modified immunomagnetic nanospheres (IMNs (CD45)) and anti-EpCAM antibody and anti-EGFR antibody cocktail modified IMNs (IMNs (EpCAM & EGFR)) were employed to address the two challenges. The cocktail of anti-EpCAM antibody and anti-EGFR antibody enables capture of tumor cells more efficiently than a single antibody, offsetting the loss of CTCs with EpCAM-negative expression or undergoing epithelial to mesenchymal transition (EMT) potentially. Notably, using IMNs (CD45) to remove the vast majority of white blood cells (WBCs) and IMNs (EpCAM & EGFR) to capture tumor cells successively, our method exhibits excellent enrichment and purification capacity. The purity of t.
Incidence, pathogenicity and diversity of Alternaria spp. associated with alternaria leaf spot of canola (Brassica napus) in Australia

Studies were undertaken to determine Alternaria spp. associated with leaf spot symptoms on canola (Brassica napus) in two cropping seasons (2015, 2016) across southern Australia. Major allergen Alt a1 and plasma membrane ATPase genes were used to identify Alternaria spp. In 2015, 112 isolates of seven Alternaria spp. were obtained, with A. metachromatica predominating. In 2016, 251 isolates of 12 Alternaria spp. were obtained, with A. infectoria predominating. Alternaria spp. isolates were morphologically and phylogenetically identified and studies to determine their pathogenicity on both B. napus (cv. Thunder TT) and B. juncea (cv. Dune) confirmed 10 species (A. alternata, A. arborescens, A. brassicae, A. ethzedia, A. hordeicola, A. infectoria, A. japonica, A. malvae, A. metachromatica and A. tenuissima) as pathogenic on both Brassica species. Alternaria ethzedia, A. hordeicola and A. malvae were recorded for the first time in Australia on any host and the record of A. arborescens was the first for New South Wales (NSW) and South Australia (SA). Other first records included A. infectoria on B. napus in NSW; A. japonica on B. napus in NSW and Western Australia (WA); A. metachromatica on any host in NSW, Victoria (VIC), WA and SA; and A. tenuissima on B. napus in NSW, SA and WA. It is evident that alternaria leaf spot on canola across southern Australia is not solely caused by A. brassicae, but that a range of other Alternaria spp. are also involved to varying degrees, depending upon the year and the geographic locality.
Content validity evidences in the motor coordination test with ball

Abstract The main objective of this study was to establish content validity evidences in the Motor Coordination Test with Ball (MCTB). Four Ph.D. professors and former sports coaches with academic experience in the motor coordination area took part of the validation process as experts. The experts assessed four motor tasks and graded using the Likert scale from one to five for criteria of clarity of language, practice relevance, and theoretical relevance. The content validity coefficient (CVC) has been used to determine the CVCc of each task and the CVCt for the instrument as a whole, adopting as a cutoff CVCc . 70 and CVCt . 80. The results showed good agreement among experts concerning “clarity of language” (CVC= .89), “practice relevance” (CVC= .81), and theoretical relevance (CVC= .86). For “practice relevance” of images and videos of task execution, there has been observed CVCt of . 86 and CVCt of . 95, respectively. When requested the order of relevance of coordination pressures, the agreement among experts presented the existence of at least four coordination pressures in each one of the tasks and, out of these, at least two had a higher relevance. After the calculation of the CVC, ecological validity was determined for the MCTB, accrediting it as an instrument for the assessment of motor coordination with ball in the context of sports games.
The Phylogeny of Lampreys: an Assessment based on the gene order and nucleotide sequence for the mitochondrial genomes of Geotria australis and Mordacia mordax.

Lampreys are jawless fish whose earliest ancestor is believed to have diverged from other jawless fishes at least 500 million years ago. The 38 contemporary members of the group are commonly allocated to three families, that is, Petromyzontidae (34 species found in temperate latitudes of the Northern Hemisphere), Mordaciidae (3 species found in temperate latitudes of the Southern Hemisphere) and Geotriidae (one species found in temperate latitudes of the Southern Hemisphere). Whilst recent molecular studies suggest that lampreys are more closely related to another group of extant jawless fish, that is, hagfishes, than they are to jawed vertebrates, the interrelationships of the three families of lampreys has yet to be resolved. In this study, 15 776 nucleotides for the mitochondrial genome of Geotria australis (Geotriidae) and three separate fragments of 4134, 1616 and 1294 bp in length, totalling 7044 bp for Mordacia mordax (Mordaciidae) were sequenced. Analyses of the genomes revealed characteristics consistent with other animal mitochondrial genomes. Maximum parsimony analyses of individual and concatenated protein-coding genes at both the nucleotide and amino acid level, for the Southern Hemisphere lamprey species G. australis and M. mordax, in combination with published sequence data from the Northern Hemisphere lamprey species, Petromyzon marinus and Lampetra fluviatilis, resolved the three-taxon statement regarding the relationships of the Petromyzontidae, Mordaciidae and Geotriidae. The outgroup taxa included two gnathostomes (Mustelus manazo and Oncorhynchus mykiss) and two hagfishes (Myxine glutinosa and Eptatretus burgeri). The results demonstrated that lampreys are a monophyletic group, the Petromyzontiformes, and that the Petromyzontidae, Mordaciidae and Geotriidae constitute three further monophyletic groups. Furthermore, the Petromyzontidae and Geotriidae were more closely related than either was to the Mordaciidae, which was the most basal oflamprey families.
Broadband Balun-LNA Employing Local Feedback gm-Boosting Technique and Balanced Loads for Low-Power Low-Voltage Applications

A new low-voltage and low-power noise-cancelling method that employs the local feedback <inline-formula> <tex-math notation="LaTeX">$g_{m}$ </tex-math></inline-formula>-boosting and balanced loads is proposed by developing a design for a low-noise and low-power balun-low-noise amplifier (LNA) for low-power broadband applications. A common-gate (CG) – common-source (CS) balun-LNA with a modified current-bleeding (CBLD) technique has low noise performance and differential balanced output but consumes more power. Because local feedback boosts the overall <inline-formula> <tex-math notation="LaTeX">$g_{m}$ </tex-math></inline-formula> of the CG stage using the amount of loop gain, the current consumption and supply voltage requirements can be mitigated. In addition, the cross-coupled cascode stage acts as a differential current balancer to improve the gain and phase mismatches at the differential output. Implemented in a 65-nm CMOS technology, the balun-LNA achieves a noise figure of 2.3 - 3 dB, a maximum voltage gain of 27.5 dB and a <inline-formula> <tex-math notation="LaTeX">$S_{11}$ </tex-math></inline-formula> of less −10 dB over the frequency range of 50 MHz to 1.3 GHz. The measured OIP3 and OIP2 are 25.3 dBm and 45.3 dBm, respectively. It consumes 5.7 mA from a nominal supply voltage of 1 V while the active die area is 0.046 mm<sup>2</sup>.
The complete mitochondrial genome characterization of Paratrypauchen microcephalus (Gobiiformes: Oxudercidae) and phylogenetic consideration

Abstract The complete mitochondrial genome of Paratrypauchen microcephalus (Gobiiformes: Oxudercidae) was completely sequenced by high throughput sequencing method. The complete mitochondrial genome was 16,552 bp in length, consisted of 13 protein-coding genes, 22 tRNA genes, two rRNA genes, a putative control region (CR), and an origin of replication on the light-strand (OL). The base composition values for the mitochondrial genome were 29.1%, 27.6%, 15.7%, and 27.6% for A, C, G, and T, respectively. The gene arrangement is identical to those in typical fishes. Phylogenetic tree based on 13 protein-coding genes shows that P. microcephalus has a close phylogenetic relationship with genus Trypauchen and belongs to Oxudercidae.
Collective Remote Attestation at the Internet of Things Scale: State-of-the-Art and Future Challenges

In recent years, the booming of Internet of Things (IoT) has populated the world with billions of smart devices that implement novel services and applications. The potential for cyberattacks on IoT systems have called for new solutions from the research community. Remote attestation is a widely used technique that allows a verifier to identify software compromise on a remote platform (called prover). Traditional challenge-response remote attestation protocols between the verifier and a single prover face a severe scalability challenge when they are applied to large scale IoT systems. To tackle this issue, recently researchers have started developing attestation schemes, which we refer to as Collective Remote Attestation (CRA) schemes, that are capable of remotely performing attestation of large networks of IoT devices. In this paper, after providing the reader with a background on remote attestation, we survey and analyze existing CRA schemes. We present an analysis of their advantages and disadvantages, as well as of their effectiveness against a reference attacker model. We focus our attention on CRA schemes’ characteristics and adversarial mitigation capabilities. We finally highlight open research issues and give possible directions for mitigating both the limitations of existing schemes, and new emerging challenges. We believe this work can help guiding the design of current and future proposals for CRA.
Harnessing the Commonwealth Advantage in Global Value Chains

This paper examines the participation of 43 Commonwealth countries in global value chains (GVCs). It shows that Commonwealth member countries' participation in GVCs increased between 1995–2015, but that it was primarily with non-Commonwealth countries. It finds that three main regional clusters connect Commonwealth value chains in Africa, Asia-Pacific and Europe, and deep regional trade agreement membership impacts on GVC participation. It also finds that while open economies, such as Singapore, tend to import value-added inputs from the G20 countries, smaller Commonwealth countries were relatively more reliant on other Commonwealth members for inputs for domestic industries. It recommends that targeted measures and an enabling business environment are required, and that additional support for developing countries will facilitate participation at the lower end of the value chain.
Melatonin chelates iron and binds directly with phenylhydrazine to provide protection against phenylhydrazine induced oxidative damage in red blood cells along with its antioxidant mechanisms: an in vitro study

Oxidative stress is an important causative factor for a number of diseases. Phenylhydrazine (PHZ) is a widely accepted model for studying hemolytic anemia by induction of oxidative stress. In the present study, goat red blood cells (RBCs) were incubated in vitro with PHZ (1mM) to generate oxidative stress. To test whether melatonin exhibits protective effects on PHZ induced RBC damage and to explore its potential molecular mechanisms, different concentrations of melatonin (5, 10, 20 and 40 nmoles/ml) were also included. PHZ caused altered profiles on biomarkers of oxidative stress and antioxidative as well as glucose metabolic enzymes in RBCs. These alterations indicated a development of oxidative stress. Melatonin at a concentration of 40 nmoles/ml provided optimal protection against all alterations induced by PHZ. The important cellular membrane proteins, including spectrin and actin, were also damaged by PHZ and this led to RBC deformation similar to that of observed in severe β-thalassaemia; the RBC deformation was also prevented by melatonin. Binding profiles of melatonin with PHZ and ferrous iron indicated favorable binding of melatonin with both of them, respectively. Thus, in addition to the direct antioxidant and free radical scavenging capability, melatonin also inhibited iron overloading by chelating iron and binding with the PHZ. This action of melatonin further reduces free radical generation. Based on the results, melatonin may provide therapeutic relevance to ß-thalassemia and other hemolytic RBC disorders involving oxidative stress.
Integral Equation Methods With Multiple Scattering and Gaussian Beams in Inhomogeneous Background Media for Solving Nonlinear Inverse Scattering Problems

I develop inverse scattering methods for velocity reconstruction in the subsurface, based on multiple scattering theory, Gaussian beams and nonlinear Born approximation. This method is based on a new version of the distorted Born iterative inverse scattering method. It directly uses an explicit representation of the data sensitivity function in terms of Green functions, rather than the indirect optimization approach based on the adjoint state method. I propose three direct scattering methods for forward modeling, namely, Gaussian beam integral equation propagators, nonlinear Born approximation, and multiple scattering. First, I apply a sensitivity kernel incorporating the Gaussian beam summation-based integral equation method and compute the background medium Green’s function in an inhomogeneous medium. Then I extend an approximate solution of the Lippmann–Schwinger equation, referred to as nonlinear Born approximation to inverse scattering problem. I apply the nonlinear Born approximation to forward modeling at each iteration. Furthermore, I combine the Gaussian beams with the multiple scattering theory for nonlinear scattering problems. I obtain the inversion results using the proposed approaches, which shows the capability for inverse scattering imaging. I have carried out several numerical experiments that involve reconstructing the resampled Marmousi and Society of Exploration Geophysicists (SEG)/European Association of Geoscientists and Engineers (EAGE) salt models from its smoothed version.
A novel patch-matching 2D denoising method for fault diagnosis of roller bearings

The vibration signal of roller bearings contains important information, but the strong background noise makes fault diagnosis difficult. In this paper, inspired by the idea of a block-matching 3D algorithm, using local and nonlocal correlation of vibration signal, a patch-matching 2D (PM2D) denoising method is proposed for the first time to suppress noise in vibration signals. The proposed denoising method constructs similarity matrices of component modules, which are used for threshold processing to determine the coefficients of the 2D discrete cosine transform, so as to achieve optimal denoising performance. Then, empirical mode decomposition and envelope analysis are employed to perform fault diagnosis. The proposed PM2D denoising method and fault diagnosis strategies are applied to both simulated and measured signals. A comparison study shows the superiority of the proposed method over the other existing denoising methods.
Scalable Scheduling Policies with Performance Guarantees for Cloud Applications

Scalable Scheduling Policies with Performance Guarantees for Cloud Applications Konstantinos Psychas We study three models of job scheduling in a distributed server system. For each of them we suggest scheduling algorithms that are computationally efficient and provably achieve a performance objective related to the model. For this we consider jobs to be an abstraction of executable programs that request specific resources e.g. memory, CPU. Resources need to be reserved in one of the servers for the duration the programs run, which is unknown. The first model considers queue-based scheduling algorithms, in which jobs belong to a finite set of types and each type has a separate queue. The scheduling objective under this formulation is to keep the size of all queues bounded, which translates to bounded queuing delay. The two families of algorithms for this model can achieve the objective for the maximum theoretical workload. Most importantly they follow vastly different paradigms and are both viable alternatives depending on what other trade-offs the scheduling has to achieve. The second model considers that resource requirements of jobs come from an unknown distribution. Jobs are queued and the objective is again to keep the number of jobs in the queue bounded and consequently the queuing delay. In this harder formulation there is no previous characterization of the maximum workload that can achieve the objective. We provide such a characterization and algorithms that achieve at least 2/3 of that maximum. Lastly, we consider a model without queues in which jobs are admitted or rejected on arrival, with the goal to maximize the total utility of the jobs that run. Algorithms of this model were proven to achieve at least 1/2 of the maximum, but further analysis suggests that this limit can be as high as 1− e−1. In all models we made simplifying assumptions that allow us to prove the desired properties of the system, but despite the theoretical nature of this work, we also discuss how the algorithms can be applied and tailored to the needs of different cloud applications. We hope they will eventually inspire improvements to existing cloud infrastructure management deployments.