Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of imbalanced land-use/land-cover data using variational semi-supervised learning

Classification of Land Use/Land Cover (LULC) data is a typical task in remote-sensing domain. However, because the classes distribution in LULC data is naturally imbalance, it is difficult to do the classification. In this paper, we employ Variational Semi-Supervised Learning (VSSL) to solve imbalance problem in LULC of Jakarta City. This VSSL exploits the use of semi-supervised learning on deep learning model. Therefore, it is suitable for classifying data with abundant unlabeled like LULC. The result shows that VSSL achieves 80.17% of overall accuracy, outperforming other algorithms in comparison.
Understanding the Drivers and Outcomes of Healthcare Organizational Privacy Responses

This research adopts a grounded theory approach to examine the drivers, safeguards and operational outcomes of organizational information privacy responses in the healthcare context. Semi-structured interviews with key healthcare stakeholders were conducted. The findings are sobering. First, privacy safeguards are driven by legal compliance, competitive advantages, available resources and best practices. However, organizations have to balance conflicting risks associated with these drivers. Second, this study identifies the operational and behavioral outcomes which results in major balance issues. Third, the adoption of a privacy impact assessment (PIA) allows the integration of a risk management approach to effectively assess the different types of privacy risks. The findings provide evidence for: (1) a gap between privacy responses and their outcomes on healthcare practice and delivery; (2) the importance of the privacy impact assessment as a risk management tool; and (3) the challenging context of the healthcare environment of how privacy responses are unfolding.
An Approach for Maintaining Models of an E-commerce Collaboration

To keep an overview on complex e-commerce collaborations several models are used to describe them. When models overlap in describing a collaboration, the overlapping information should not contradict. Models are of different nature and maintained by different people. Therefore, keeping model-overlap contradiction-free is challenging. In this paper we propose a novel approach for maintaining models representing an E-Commerce collaboration. Applying this approach supports avoiding contradictions in models during evolution of E-Commerce collaborations.
Short-term effects of temperature on the abundance and diversity of magnetotactic cocci

Temperature is one of the most important climate factors that can regulate the activity and growth of organisms. However, it is so far unclear how temperature influences the abundance and community composition of magnetotactic bacteria (MTB) that mineralize intracellular magnetite and/or greigite magnetosomes and play significant roles in the global iron cycling and sediment magnetization. To address this specific problem, in this study we have assessed the impact of temperature on freshwater magnetotactic cocci through laboratory microcosm simulations. Microcosms containing MTB were exposed to four constant temperatures ranging from 9°C to 37°C. After 10 days and 28 days of incubation, no significant differences in abundance were detected in microcosms at 9°C, 15°C, and 26°C (Student's t‐test, P > 0.05); however, microcosms exposed to 37°C exhibited a significant decrease of magnetotactic cocci abundance (P < 0.05). Dendrogram analysis of community‐amplified ribosomal DNA restriction analysis (community ARDRA) banding patterns distinguished the 37°C samples from samples at lower temperatures regardless of incubation periods. Furthermore, clone library analysis revealed that most of the operational taxonomic units (OTUs) detected in samples from 9°C to 26°C were absent from the 37°C microcosms, whereas six OTUs were exclusively detected in the 37°C samples. Community compositions from four incubation temperatures were further compared using statistical phylogenetic methods (UniFrac and LIBSHUFF), which revealed that the 37°C samples harbored phylogenetically distinct MTB communities compared to those found in 9°C, 15°C, and 26°C samples. Taken together, our results indicate that elevated temperature can influence the abundance and diversity of dominant members of magnetotactic cocci. This linkage further infers that the abundance and diversity of MTB (e.g., based on the fossil magnetosomes) may be useful in reconstruction of paleotemperature.
Body Condition Peaks at Intermediate Parasite Loads in the Common Bully Gobiomorphus cotidianus

Most ecologists and conservationists perceive parasitic infections as deleterious for the hosts. Their effects, however, depend on many factors including host body condition, parasite load and the life cycle of the parasite. More research into how multiple parasite taxa affect host body condition is required and will help us to better understand host-parasite coevolution. We used body condition indices, based on mass-length relationships, to test the effects that abundances and biomasses of six parasite taxa (five trematodes, Apatemon sp., Tylodelphys sp., Stegodexamene anguillae, Telogaster opisthorchis, Coitocaecum parvum, and the nematode Eustrongylides sp.) with different modes of transmission have on the body condition of their intermediate or final fish host, the common bully Gobiomorphus cotidianus in New Zealand. We used two alternative body condition methods, the Scaled Mass Index (SMI) and Fulton’s condition factor. General linear and hierarchical partitioning models consistently showed that fish body condition varied strongly across three lakes and seasons, and that most parasites did not have an effect on the two body condition indices. However, fish body condition showed a highly significant humpbacked relationship with the total abundance of all six parasite taxa, mostly driven by Apatemon sp. and S. anguillae, indicating that the effects of these parasites can range from positive to negative as abundance increases. Such a response was also evident in models including total parasite biomass. Our methodological comparison supports the SMI as the most robust mass-length method to examine the effects of parasitic infections on fish body condition, and suggests that linear, negative relationships between host condition and parasite load should not be assumed.
Reconciling neural fields to self-organization

Despite being successfully used in the design of various biologically-inspired applications, the paradigm of dynamic neural fields (DNF) does not seem to have been exploited at its full potential yet. Partly because of the difficulties concerning a comprehensive theoretical study of them, essential aspects as learning mechanisms have rarely been addressed in the literature. In the current paper, we first show that classical DNF equations fail to offer reliable support for self-organization, unveiling some behavioural issues that prevent the fields to achieve this goal. Then, as an alternative to these, we propose a new DNF equation capable of deploying indeed a self-organizing mechanism based on neural fields.
Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification

We present the Explicit Kernel Rewards Regression (EKRR) approach, as an extension of Kernel Rewards Regression (KRR), for Op- timal Policy Identification in Reinforcement Learning. The method uses the Structural Risk Minimisation paradigm to achieve a high generalisa- tion capability. This explicit version of KRR offers at least two important advantages. On the one hand, finding a near-optimal policy is done by a quadratic program, hence no Policy Iteration techniques are necessary. And on the other hand, the approach allows for the usage of further con- straints and certain regularisation techniques as e.g. in Ridge Regression and Support Vector Machines.
Importance of the antenniform legs, but not vision, for homing by the neotropical whip spider Paraphrynus laevifrons

ABSTRACT Amblypygids, or whip spiders, are nocturnal, predatory arthropods that display a robust ability to navigate to their home refuge. Prior field observations and displacement studies in amblypygids demonstrated an ability to home from distances as far away as 10 m. In the current study, micro-transmitters were used to take morning position fixes of individual Paraphrynus laevifrons following an experimental displacement of 10 m from their home refuge. The intention was to assess the relative importance of vision compared with sensory input acquired from the antenniform legs for navigation as well as other aspects of their spatial behavior. Displaced individuals were randomly assigned to three treatment groups: (i) control individuals; (ii) vision-deprived individuals, VD; and (iii) individuals with sensory input from the tips of their antenniform legs compromised, AD. Control and VD subjects were generally successful in returning home, and the direction of their movement on the first night following displacement was homeward oriented. By contrast, AD subjects experienced a complete loss of navigational ability, and movement on the first night indicated no hint of homeward orientation. The data strongly support the hypothesis that sensory input from the tips of the antenniform legs is necessary for successful homing in amblypygids following displacement to an unfamiliar location, and we hypothesize an essential role of olfaction for this navigational ability. Summary: Tropical amblypygids inhabit structurally complex habitats, yet navigate home in the dark after a night hunting prey; olfaction appears to be important for navigation.
Integrative microRNA-mRNA and protein-protein interaction analysis in pancreatic neuroendocrine tumors.

OBJECTIVE Pancreatic neuroendocrine tumors are relatively rare pancreatic neoplasms over the world. Investigations of the molecular biology of PNETs are insufficient for nowadays. We aimed to explore the expression of microRNA and messenger RNA and regulatory processes underlying pancreatic neuroendocrine tumors. MATERIALS AND METHODS The messenger RNA and microRNA expression profile of GSE43796 were downloaded, including 6 samples with pancreatic neuroendocrine tumors and 5 healthy samples. First, the Limma package was utilized to distinguish the differentially expressed messenger RNA and microRNA separately. Then we used microRNA Walk databases to predict the target genes of the differentially expressed microRNAs (DE-microRNAs), and selected differentially expressed target genes whose expression was reversely correlated with microRNAs. Gene Ontology classification and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to explore the functions and pathways of target genes. In addition, we constructed a regulatory miRNAs-target genes network and a protein-protein interaction network. RESULTS There were 28 differentially expressed microRNAs and 859 differentially expressed messenger RNAs, including 253 potential target genes. These target genes mainly enriched in ABC transporters pathway. In this network, hsa-miR-7-2-3p demonstrated the highest connectivities whereas KLF12 was the mRNAs with the highest connectivities. CXCL12 was identified as the hub of the protein-protein interaction sub-network. CONCLUSIONS The genes involved in ABC transporters and Type II diabetes mellitus pathway, KLF12 and CXCL12 may play an important role in the progression of pancreatic neuroendocrine tumors. However, more experimental studies are required.
Prenatal Residential Proximity to Agricultural Pesticide Use and IQ in 7-Year-Old Children

Background: Residential proximity to agricultural pesticide use has been associated with neural tube defects and autism, but more subtle outcomes such as cognition have not been studied. Objectives: We evaluated the relationship between prenatal residential proximity to agricultural use of potentially neurotoxic pesticides and neurodevelopment in 7-year-old children. Methods: Participants included mothers and children (n=283) living in the agricultural Salinas Valley of California enrolled in the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) study. We estimated agricultural pesticide use within 1 km of maternal residences during pregnancy using a geographic information system, residential location, and California’s comprehensive agricultural Pesticide Use Report data. We used regression models to evaluate prenatal residential proximity to agricultural use of five potentially neurotoxic pesticide groups (organophosphates, carbamates, pyrethroids, neonicotinoids, and manganese fungicides) and five individual organophosphates (acephate, chlorpyrifos, diazinon, malathion, and oxydemeton-methyl) and cognition in 7-year-old children. All models included prenatal urinary dialkyl phosphate metabolite concentrations. Results: We observed a decrease of 2.2 points [95% confidence interval (CI): −3.9, −0.5] in Full-Scale IQ and 2.9 points (95% CI: −4.4, −1.3) in Verbal Comprehension for each standard deviation increase in toxicity-weighted use of organophosphate pesticides. In separate models, we observed similar decrements in Full-Scale IQ with each standard deviation increase of use for two organophosphates (acephate and oxydemeton-methyl) and three neurotoxic pesticide groups (pyrethroids, neonicotinoids, and manganese fungicides). Conclusions: This study identified potential relationships between maternal residential proximity to agricultural use of neurotoxic pesticides and poorer neurodevelopment in children. https://doi.org/10.1289/EHP504
Trio, a novel high fecundity allele: I. Transcriptome analysis of granulosa cells from carriers and noncarriers of a major gene for bovine ovulation rate†

Abstract A major gene for bovine ovulation rate has been mapped to a 1.2 Mb region of chromosome 10. Screening of coding regions of positional candidate genes within this region failed to reveal a causative polymorphism, leading to the hypothesis that the phenotype results from differences in candidate gene expression rather than alteration of gene structure. This study tested differences in expression of positional candidate genes in granulosa cells between carriers and noncarriers of the high fecundity allele, as well as characterizing differences in the transcriptomic profile between genotypes. Five carriers and five noncarriers, female descendants of “Trio,” a carrier of the high fecundity allele were initially used in an RNA-seq analysis of gene expression. Four of ten samples were contaminated with theca cells, so that six samples were used in the final analysis (three of each genotype). Of 14 973 genes expressed, 143 were differentially expressed (false discovery rate P < 0.05) in carriers versus noncarriers. Among the positional candidate genes, SMAD6 was 6.6-fold overexpressed in the carriers compared to noncarriers (P < 5 × 10-5). This result was replicated in an independent group of 12 females (7 carriers and 5 noncarriers) using quantitative real-time PCR; SMAD6 was 9.3-fold overexpressed in carriers versus noncarriers (P = 1.17 × 10-6). Association of overexpression of SMAD6, an inhibitor of the BMP/SMAD signaling pathway, with high ovulation rate corresponds well with disabling mutations in ligands (BMP15 and GDF9) and a receptor (BMPR1B) of this pathway that cause increased ovulation rate in sheep. Summary Sentence Carriers of an allele for high ovulation rate exhibit a six-fold overexpression of the positional candidate gene SMAD6 compared to noncarriers, strongly implicating SMAD6 as the gene responsible for the high ovulation rate phenotype.
Experiments with Neural Networks for Small and Large Scale Authorship Verification

We propose two models for a special case of authorship verification problem. The task is to investigate whether the two documents of a given pair are written by the same author. We consider the authorship verification problem for both small and large scale datasets. The underlying small-scale problem has two main challenges: First, the authors of the documents are unknown to us because no previous writing samples are available. Second, the two documents are short (a few hundred to a few thousand words) and may differ considerably in the genre and/or topic. To solve it we propose transformation encoder to transform one document of the pair into the other. This document transformation generates a loss which is used as a recognizable feature to verify if the authors of the pair are identical. For the large scale problem where various authors are engaged and more examples are available with larger length, a parallel recurrent neural network is proposed. It compares the language models of the two documents. We evaluate our methods on various types of datasets including Authorship Identification datasets of PAN competition, Amazon reviews, and machine learning articles. Experiments show that both methods achieve stable and competitive performance compared to the baselines.
A beacon in the cytoplasm: Tracking translation of single mRNAs

Translation is carefully regulated to control protein levels and allow quick responses to changes in the environment. Certain questions about translation in vivo have been unattainable until now. In this issue, Pichon et al. (2016. J. Cell Biol. http://dx.doi.org/10.1083/jcb.201605024) describe a new technique to allow real-time monitoring of translation on single mRNAs.
An elliptical-shaped density-based classification algorithm for detection of entangled clusters

We present a density-based clustering method producing a covering of the dataset by ellipsoidal structures in order to detect possibly entangled clusters. We first introduce an unconstrained version of the algorithm which does not require any assumption on the number of clusters. Then a constrained version using a priori knowledge to improve the bare clustering is discussed. We evaluate the performance of our algorithm and several other well-known clustering methods using existing cluster validity techniques on randomly-generated bi-dimensional gaussian mixtures. Our simulation results show that both versions of our algorithm compare well with the reference algorithms according to the used metrics, foreseeing future improvements of our method.
Identification of Candidate Genes Responsible for Age-related Macular Degeneration using Microarray Data

A DNA microarray can measure the expression of thousands of genes simultaneously, and this enables us to study the molecular pathways underlying Age-related Macular Degeneration. Previous studies have not determined which genes are responsible for the process of AMD. The authors address this deficiency by applying modern data mining and machine learning feature selection algorithms to the AMD microarray dataset. In this paper four methods are utilized to perform feature selection: Naïve Bayes, Random Forest, Random Lasso, and Ensemble Feature Selection. Functional Annotation of 20 final selected genes suggests that most of them are responsible for signal transduction in an individual cell or between cells. The top seven genes, five protein-coding genes and two non-coding RNAs, are explored from their signaling pathways, functional interactions and associations with retinal pigment epithelium cells. The authors conclude that Pten/PI3K/Akt pathway, NF-kappaB pathway, JNK cascade, Non-canonical Wnt Pathway, and two biological processes of cilia are likely to play important roles in AMD pathogenesis.
An evaluation on the accuracy of the minimum width transistor area models in ranking the layout area of FPGA architectures

This work provides an evaluation on the accuracy of the minimum width transistor area models in ranking the actual layout area of FPGA architectures. Both the original VPR area model and the new COFFE area model are compared against the actual layouts with up to 3 metal layers for the various FPGA building blocks. We found that both models have significant variations with respect to the accuracy of their predictions across the building blocks. In particular, the original VPR model overestimates the layout area of larger buffers and full adders by as much as 34% while underestimate the layout area of smaller buffers and multiplexers by as much as 59% for an overall prediction error variation of 93%. The newer COFFE model also significantly overestimates the layout area of full adders by 13% and underestimates the layout area of multiplexers by a maximum of 58% for a prediction error variation of 71%. Such variations are particularly significant considering sensitivity analyses are not routinely performed in FPGA architectural studies. Our results suggest that such analyses are extremely important in studies that employing the minimum width area models so the tolerance of the architectural conclusions against the prediction error variations can be quantified. Furthermore, an open source version of the layouts of the actual FPGA building blocks should be created, so their actual layout area can be used to achieve a highly accurate ranking of the implementation area of FPGA architectures built upon these layouts.
Allee Effects May Slow the Spread of Parasites in a Coastal Marine Ecosystem

Allee effects are thought to mediate the dynamics of population colonization, particularly for invasive species. However, Allee effects acting on parasites have rarely been considered in the analogous process of infectious disease establishment and spread. We studied the colonization of uninfected wild juvenile Pacific salmon populations by ectoparasitic salmon lice (Lepeophtheirus salmonis) over a 4-year period. In a data set of 68,376 fish, we observed 85 occurrences of precopular pair formation among 1,259 preadult female and 613 adult male lice. The probability of pair formation was dependent on the local abundance of lice, but this mate limitation is likely offset somewhat by mate-searching dispersal of males among host fish. A mathematical model of macroparasite population dynamics that incorporates the empirical results suggests a high likelihood of a demographic Allee effect, which can cause the colonizing parasite populations to die out. These results may provide the first empirical evidence for Allee effects in a macroparasite. Furthermore, the data give a rare detailed view of Allee effects in colonization dynamics and suggest that Allee effects may dampen the spread of parasites in a coastal marine ecosystem.
Modelling of the failure behaviour of windscreens and component tests

Windscreens from laminated safety glass (glass/PVB interlayer/glass) are widely used in automotive structures and have an important contribution to the stiffness of the vehicle. The stiffness of the laminated safety glass is dominantly given by the two layers of glass while the PVB interlayer serves to fix glass splinters to avoid serious injuries of the passengers in a collision. A finite element model for modelling the failure behaviour of laminated glass windscreens is presented. A special element structure with three layers (shell/volume/shell) has been used to model the laminated glass windscreen. A fracture criterion for brittle fracture based on the maximum principal stress (σ I ≥ σ c) was applied to model the fracture behaviour of glass. The PVB interlayer was modelled with both a linear elastic and a hyperelastic material law without damage. The critical fracture stress of glass was determined by fitting the failure force measured from static bending tests on laminated glass windscreens. The transferability of the fracture criterion and the corresponding parameter was checked by simulating two different loading cases of the component tests.