Partial Classifications Research Articles

Phylogenetic analysis of Dengue virus and insect-specific Flavivirus in Aedes aegypti from Gresik, Indonesia 2019

Abstract. Hakim RN, Damayanti M, Fauziyah S, Sucipto TH. 2024. Phylogenetic analysis of Dengue virus and insect-specific Flavivirus in Aedes aegypti from Gresik, Indonesia 2019. Biodiversitas 25: 2340-2347. The spread of several Flaviviruses, such as Dengue virus and insect-specific Flavivirus, is periodically detected in Indonesia, including Surabaya, which is an endemic area. Gresik, as one of Surabaya's satellite cities, has high traffic mobility between regions, increasing the possibility of viral transmission. In this study, we identified Flaviviruses from Aedes aegypti mosquito isolates from Gresik collected in 2019. We also revealed the possibility of virus transmission from Surabaya to Gresik. The mosquito samples were collected using mosquito trap method. The Flavivirus Partial Nonstructural Protein 5 (NS5) -encoding gene region was isolated via the nested reverse transcription-polymerase chain reaction method. Sequence alignment and phylogenetic analysis were carried out to determine the kinship of Gresik strain virus isolates with the GenBank database. The results revealed that six out of 29 isolated samples (Sample from Duduk Sampeyan (47 and 43), Mengare (212 and 31), Kedamean (58), and Manyar (38)) exhibited a 220 bp DNA band, which corresponds to the NS5 gene. Further analysis using basic local alignment search tool - nucleotide and phylogenetic methods revealed that two sample sequences (38 and 212) are closely related to DENV-1 genotype 1, while the other four (31, 43, 47, and 58) are associated with Insect-Spesific Flavivirus (ISF). The similarity in NS5 partial sequence and genotype classifications of the dengue virus suggests the potential transmission of the virus from Surabaya to Gresik. We hypothesize that this phenomenon is closely linked to the population mobility between the two areas.

Alternative metrics for characterizing longer-term clinical outcomes in difficult-to-treat depression: II. Sensitivity to treatment effects.

Characteristics of difficult-to-treat depression (DTD), including infrequent symptom remission and poor durability of benefit, compel reconsideration of the outcome metrics historically used to gauge the effectiveness of antidepressant interventions. Self-report and clinician assessments of depression symptom severity were obtained regularly over a 2-year period in a difficult-to-treat depression registry sample receiving treatment as usual (TAU), with or without vagus nerve stimulation (VNS). Alternative outcome metrics for characterizing symptom change were compared in effect size and discriminating power in distinguishing the vagus nerve stimulation + treatment as usual and treatment as usual treatment groups. We expected metrics based on remission status to produce weaker between-group separation than those based on the classifications of partial response or response and metrics that integrate information over time to produce greater separation than those based on single endpoint assessment. Metrics based on remission status had smaller effect size and poorer discrimination in separating the treatment groups than metrics based on partial response or response classifications. Metrics that integrated information over the 2-year observation period had stronger performance characteristics than those based on symptom scores at single endpoint assessment. For both the clinician-rated and self-report depression ratings, the metrics with the strongest performance characteristics were the median percentage change in symptom scores over the observation period and the proportion of the observation period in partial response or better. In difficult-to-treat depression, integrative symptom severity-based and time-based measures are sensitive and informative outcomes for assessing between-group treatment effects, while metrics based on remission status are not.

MT-MAG: Accurate and interpretable machine learning for complete or partial taxonomic assignments of metagenomeassembled genomes.

We propose MT-MAG, a novel machine learning-based software tool for the complete or partial hierarchically-structured taxonomic classification of metagenome-assembled genomes (MAGs). MT-MAG is alignment-free, with k-mer frequencies being the only feature used to distinguish a DNA sequence from another (herein k = 7). MT-MAG is capable of classifying large and diverse metagenomic datasets: a total of 245.68 Gbp in the training sets, and 9.6 Gbp in the test sets analyzed in this study. In addition to complete classifications, MT-MAG offers a "partial classification" option, whereby a classification at a higher taxonomic level is provided for MAGs that cannot be classified to the Species level. MT-MAG outputs complete or partial classification paths, and interpretable numerical classification confidences of its classifications, at all taxonomic ranks. To assess the performance of MT-MAG, we define a "weighted classification accuracy," with a weighting scheme reflecting the fact that partial classifications at different ranks are not equally informative. For the two benchmarking datasets analyzed (genomes from human gut microbiome species, and bacterial and archaeal genomes assembled from cow rumen metagenomic sequences), MT-MAG achieves an average of 87.32% in weighted classification accuracy. At the Species level, MT-MAG outperforms DeepMicrobes, the only other comparable software tool, by an average of 34.79% in weighted classification accuracy. In addition, MT-MAG is able to completely classify an average of 67.70% of the sequences at the Species level, compared with DeepMicrobes which only classifies 47.45%. Moreover, MT-MAG provides additional information for sequences that it could not classify at the Species level, resulting in the partial or complete classification of 95.13%, of the genomes in the datasets analyzed. Lastly, unlike other taxonomic assignment tools (e.g., GDTB-Tk), MT-MAG is an alignment-free and genetic marker-free tool, able to provide additional bioinformatics analysis to confirm existing or tentative taxonomic assignments.

GenCo: A Generative Learning Model for Heterogeneous Text Classification Based on Collaborative Partial Classifications

The use of generative learning models in natural language processing (NLP) has significantly contributed to the advancement of natural language applications, such as sentimental analysis, topic modeling, text classification, chatbots, and spam filtering. With a large amount of text generated each day from different sources, such as web-pages, blogs, emails, social media, and articles, one of the most common tasks in NLP is the classification of a text corpus. This is important in many institutions for planning, decision-making, and creating archives of their projects. Many algorithms exist to automate text classification tasks but the most intriguing of them is that which also learns these tasks automatically. In this study, we present a new model to infer and learn from data using probabilistic logic and apply it to text classification. This model, called GenCo, is a multi-input single-output (MISO) learning model that uses a collaboration of partial classifications to generate the desired output. It provides a heterogeneity measure to explain its classification results and enables a reduction in the curse of dimensionality in text classification. Experiments with the model were carried out on the Twitter US Airline dataset, the Conference Paper dataset, and the SMS Spam dataset, outperforming baseline models with 98.40%, 89.90%, and 99.26% accuracy, respectively.

Working diagnosis: The medical labour process and the classification of suffering.

Medical sociologists argue that diagnosis is a critical component of medicine and that diagnosis is most obviously exercised by doctors. This scholarship, however, largely ignores other medical workers. I extend the concept of working diagnosis to help solve this problem. These are partial and preliminary medical classifications of suffering that are imposed between informal experiences of illness and formal classifications of disease. In a complex division of medical labour where doctoring is a minority practice, working diagnoses are critical forces that shape, and are shaped by, the relational conditions of medical production. To illustrate the analytical promise of this concept, I sharpen it through an ethnography of ambulance work in California. Working diagnoses in this case are officially referred to as 'primary impressions'. I show how these impressions are deeply embedded in the relations of paramedical production. Three are specifically highlighted: the relations between ambulance crews and their patients, the relations between ambulance crews and their nurse and police counterparts and the relations between ambulance crews and their managers. I work towards a simple but rarely stated conclusion: medical sociologists should focus more heavily on how diagnostic processes influence labour processes and vice versa.

Evaluation of an automated Presidio anonymisation model for unstructured radiation oncology electronic medical records in an Australian setting

BackgroundElectronic medical records (EMRs) contain valuable information for clinical research, however, the presence of personally identifying information (PII) restricts their use. Anonymisation of PII from EMRs enables clinical information to be shared for research purposes. Since there is limited research relating to the anonymisation of Australian EMRs, the performance of Microsoft Presidio with customisation on clinical documents from an Australian radiation oncology information system (OIS) was evaluated. MethodsA random sample of 300 unstructured free-text clinical documents were extracted from the Prince of Wales Cancer Centre OIS on patients diagnosed with cancer of the head and neck between 2000 and 2017. Anonymisation of clinical text was performed using Microsoft Presidio, implemented in Python programming language. Each clinical document was manually compared pre- and post-anonymisation for the identification and redaction of 13 PII. Model performance was evaluated using three classification criteria; correct, partial, and missed classification, to determine recall, precision, and F1-score. These three metrics were performed under relaxed conditions, where partial classifications were considered correct, and under strict conditions, where only correct classifications were considered correct. ResultsA total of 8,713 PII were identified, of which 7,026 (81%) were classified as correct, 850 (10%) as partial, and 837 (9%) as missed. There were 245 instances of incorrect classifications. Evaluation of the model demonstrated an average precision of 0.8921, recall (strict) of 0.8064, F1-score (strict) of 0.8471, recall (relaxed) of 0.9039, and F1-score (relaxed) of 0.8980. ConclusionThis is the first example of an open-source anonymisation model to be customised and tested on clinical documents from an Australian radiation oncology EMR. These findings support the use of Presidio for the safe use and sharing of cancer data within Australia for certain PII, however, additional checks are required to ensure person names are successfully anonymised.

Sukuk Market and Economic Welfare Nexus: A Partial Equilibrium Approach

Due to its distinctive features and investment quality, sukuk as an Islamic alternative to bond financing, have known last decades a worldwide interest and a rapid widespread, particularly after the 2007-2008 global financial crisis. Despite the global market prevalence of sukuk, the literature on the sukuk – economic wealth nexus still inexistant. In this study, we develop a basic model that captures the welfare effects of sukuk markets. The main finding shows the importance of a well-developed sukuk market in hedging interest rate and inflation risks effectively and, thereby improving investor welfare.Keywords: Sukuk, Economic welfare, Partial equilibriumJEL Classifications: D53 G15 D60DOI: https://doi.org/10.32479/ijefi.11507

Wronskian indices and rational conformal field theories

The classification scheme for rational conformal field theories, given by the Mathur-Mukhi-Sen (MMS) program, identifies a rational conformal field theory by two numbers: (n, l). n is the number of characters of the rational conformal field theory. The characters form linearly independent solutions to a modular linear differential equation (which is also labelled by (n, l)); the Wronskian index l is a non-negative integer associated to the structure of zeroes of the Wronskian.In this paper, we compute the (n, l) values for three classes of well-known CFTs viz. the WZW CFTs, the Virasoro minimal models and the mathcal{N} = 1 super-Virasoro minimal models. For the latter two, we obtain exact formulae for the Wronskian indices. For WZW CFTs, we get exact formulae for small ranks (upto 2) and all levels and for all ranks and small levels (upto 2) and for the rest we compute using a computer program. We find that any WZW CFT at level 1 has a vanishing Wronskian index as does the {hat{mathbf{A}}}_{mathbf{1}} CFT at all levels. We find intriguing coincidences such as: (i) for the same level CFTs with {hat{mathbf{A}}}_{mathbf{2}} and {hat{mathbf{G}}}_{mathbf{2}} have the same (n, l) values, (ii) for the same level CFTs with {hat{mathbf{B}}}_{mathbf{r}} and {hat{mathbf{D}}}_{mathbf{r}} have the same (n, l) values for all r ≥ 5.Classifying all rational conformal field theories for a given (n, l) is one of the aims of the MMS program. We can use our computations to provide partial classifications. For the famous (2, 0) case, our partial classification turns out to be the full classification (achieved by MMS three decades ago). For the (3, 0) case, our partial classification includes two infinite series of CFTs as well as fifteen “discrete” CFTs; except three all others have Kac-Moody symmetry.

Polar actions on Damek-Ricci spaces

A proper isometric Lie group action on a Riemannian manifold is called polar if there exists a closed connected submanifold which meets all orbits orthogonally. In this article we study polar actions on Damek-Ricci spaces. We prove criteria for isometric actions on Damek-Ricci spaces to be polar, find examples and give some partial classifications of polar actions on Damek-Ricci spaces. In particular, we show that non-trivial polar actions exist on all Damek-Ricci spaces.

On the classification of exceptional scattered polynomials

Let f(X)∈Fqr[X] be a q-polynomial. If the Fq-subspace U={(xqt,f(x))|x∈Fqn} defines a maximum scattered linear set, then we call f(X) a scattered polynomial of index t. The asymptotic behavior of scattered polynomials of index t is an interesting open problem. In this sense, exceptional scattered polynomials of index t are those for which U is a maximum scattered linear set in PG(1,qmr) for infinitely many m. The classifications of exceptional scattered monic polynomials of index 0 (for q>5) and of index 1 were obtained in [1]. In this paper we complete the classifications of exceptional scattered monic polynomials of index 0 for q≤4. Also, some partial classifications are obtained for arbitrary t. As a consequence, the classification of exceptional scattered monic polynomials of index 2 is given.

A Century of Swine Influenza: Is It Really Just about the Pigs?

Influenza viruses (IV) are one of the major threats to human and animal health worldwide due to the variety of species they affect. Pigs play an important role in IV ecology as the “mixing vessel,” since they can be infected by swine, avian and human IV, allowing the appearance of new subtypes. Human viruses originated in swine are known as IV of swine origin or swine influenza virus (SwIV) variants. In this study, we identified knowledge tendencies of SwIV and assessed potential bias in the literature caused by these variants. We identified the most mentioned SwIV variants and manually reviewed the literature to determine the number of publications applying the whole influenza nomenclature, a partial nomenclature, only the subtype or mixed terminology, along with the proportion of articles in which the GenBank ID number was available. We observed that the 2009 H1N1 human pandemic created an important bias in SwIV research driven by an increase in human publications on the IV of swine origin. H1N1 is the most studied subtype for swine and humans, followed by H3N2. We found differences between the nomenclatures applied, where partial classifications were slightly more common. Finally, from all the publications, only 25% stated the GenBank ID of the sequence studied. This review represents the most complete exploration of trends in SwIV knowledge to date and will serve as a guidance for future search strategies in SwIV research.

Evaluation System for Online Terminological Databases

This paper attempts to create an extensive classification and evaluation system to offer objective viewpoints for the comprehension, description, classification, evaluation and review of central online termbases of larger organisations. Such a comprehensive classification already exists for lexicographical genres, i.e. printed and online dictionaries, but it is still missing for online termbases. The research is based on previous international and Hungarian literature, the study of several online examples, of existing partial classifications and our previous research. The experimental categorisation with a schematic version in the appendix offers a contribution to a deeper comprehension, the possibility of a thorough description and more attentive evaluation, and ultimately, a growing awareness of the use of online termbases. Providing a new insight may also inspire the development of these beneficial tools which facilitate communication in the field of specialised languages.

Classification of symmetry-protected phases for interacting fermions in two dimensions

Recently, it has been shown that two-dimensional bosonic symmetry-protected topological(SPT) phases with on-site unitary symmetry $G$ can be completely classified by the group cohomology class $H^3(G, \mathrm{U}(1))$. Later, group super-cohomology class was proposed as a partial classification for SPT phases of interacting fermions. In this work, we revisit this problem based on the mathematical framework of $G$-extension of unitary braided tensor category(UBTC) theory. We first reproduce the partial classifications given by group super-cohomology, then we show that with an additional $H^1(G, \mathbb{Z}_2)$ structure, a complete classification of SPT phases for two-dimensional interacting fermion systems for a total symmetry group $G\times\mathbb{Z}_2^f$ can be achieved. We also discuss the classification of interacting fermionic SPT phases protected by time-reversal symmetry.

Towards a Complete Classification of Symmetry-Protected Topological Phases for Interacting Fermions in Three Dimensions and a General Group Supercohomology Theory

Classification and construction of symmetry protected topological (SPT) phases in interacting boson and fermion systems have become a fascinating theoretical direction in recent years. It has been shown that the (generalized) group cohomology theory or cobordism theory can give rise to a complete classification of SPT phases in interacting boson/spin systems. Nevertheless, the construction and classification of SPT phases in interacting fermion systems are much more complicated, especially in 3D. In this work, we revisit this problem based on the equivalent class of fermionic symmetric local unitary (FSLU) transformations. We construct very general fixed point SPT wavefunctions for interacting fermion systems. We naturally reproduce the partial classifications given by special group super-cohomology theory, and we show that with an additional $\tilde{B}H^2(G_b, \mathbb Z_2)$ (the so-called obstruction free subgroup of $H^2(G_b, \mathbb Z_2)$) structure, a complete classification of SPT phases for three-dimensional interacting fermion systems with a total symmetry group $G_f=G_b\times \mathbb Z_2^f$ can be obtained for unitary symmetry group $G_b$. We also discuss the procedure of deriving a general group super-cohomology theory in arbitrary dimensions.

Economic Growth, Inequality and Poverty in the EU

A country’s poverty rate is influenced by numerous factors, including economic growth and the distribution of its effects. This article aims to classify European Union (EU) member states in terms of their ability to handle the economic challenges of the past decade. A country’s ability to negotiate global challenges in conjunction with their respective social and economic growth, as well as that of the EU, represents a key classification attribute. In this article, classification is based on an analysis of changes in economic growth, inequality and poverty across all 28 EU member states. The classification emerges from monitoring trends in economic growth and inequality, and their interconnections with poverty across the different countries. In order to analyse these interactions, this investigates uses the Bourguignon model (Poverty-Growth-Inequality Triangle–PGI) and the Growth Incidence Curve. The article reveals that economic growth is connected with a decrease in poverty. However, as inequalities in income increase, poverty also increases. Nevertheless, rates of development differ across countries. Four broad categories of country sharing similar attributes are defined, and an additional, special category assigned to Greece owing to its distinctive attributes. These partial classifications facilitated the complex classification of the EU member states, by which different development tendencies across the countries in the period 2005–2015 might be deciphered. By analysing the relationships between gross domestic product, income distribution and poverty rates, and by developing a system by which to classify countries, essential information regarding individual countries’ economic and social development is revealed, with implications for their distinctive challenges in reducing inequality and poverty. The article also highlights considerable diversity in countries’ relative abilities to handle a range of unfavourable global trends, such as the recent global financial crisis. In general, countries with strong economies are better able to weather challenges such as inequality and poverty during a period of crisis.

Lie point symmetries and ODEs passing the Painlevé test

The Lie point symmetries of ordinary differential equations (ODEs) that are candidates for having the Painlevé property are explored for ODEs of order n = 2,…, 5. Among the 6 ODEs identifying the Painlevé transcendents only PIII, PV and PVI have nontrivial symmetry algebras and that only for very special values of the parameters. In those cases the transcendents can be expressed in terms of simpler functions, i.e. elementary functions, solutions of linear equations, elliptic functions or Painlevé transcendents occurring at lower order. For higher order or higher degree ODEs that pass the Painlevé test only very partial classifications have been published. We consider many examples that exist in the literature and show how their symmetry groups help to identify those that may define genuinely new transcendents.

Strongly 2-Hopf hypersurfaces in complex projective and hyperbolic planes

We give a geometric characterization of certain hypersurfaces of cohomogeneity one in the complex projective and hyperbolic planes. We also obtain some partial classifications of austere hypersurfaces and of Levi-flat hypersurfaces with constant mean curvature in these spaces.

QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms.

In this work, we introduce QUEST (QUantile Estimation after Supervised Training), an adaptive classification algorithm for Wireless Sensor Networks (WSNs) that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting raw sensor data puts high demands on the battery, reducing network life time. By merely transmitting partial results or classifications based on the sampled data, the amount of traffic on the network can be significantly reduced. Such classifications can be made by learning based algorithms using sampled data. An important issue, however, is the training phase of these learning based algorithms. Training a deployed sensor network requires a lot of communication and an impractical amount of human involvement. QUEST is a hybrid algorithm that combines supervised learning in a controlled environment with unsupervised learning on the location of deployment. Using the SITEX02 dataset, we demonstrate that the presented solution works with a performance penalty of less than 10% in 90% of the tests. Under some circumstances, it even outperforms a network of classifiers completely trained with supervised learning. As a result, the need for on-site supervised learning and communication for training is completely eliminated by our solution.

Impacto da produtividade leiteira e qualidade morfológica das vacas leiteiras na rentabilidade económica das explorações

The economic situation of Azores dairy farms is experiencing difficulties due to the liberalization of milk production in Europe. The Azorean cattle raising has to adjust to this changes and the enhancement of knowledge regarding productivity and profitability factors seems to be the priority. This paper presents a multiple linear regression model which relates farm incomes to the technical-economic, productive and morphological, in 2010, of 91 farms of the island of San Miguel. Based on the developed procedure, a strong correlation was observed and a significant effect milk production between 305 days and the final score resulting from the partial primary descriptive classifications of characters of primiparas (r=0.748). The same is true in the production of fat (r=0.673) and protein (r=0.731) in the same period. The multiple linear regression model with a R2 = 0,736 shows that milk sales, feeding, salary and rent expenses, and animal density, all by area unity, have a significant effect in dairy farms profitability. The conclusions pointed that for an increase of milk sales per hectare it is necessary to improve the morphological quality of dairy cows, to enhance milk production, protein and fat.

PRINCIPLES OF GEOMORPHIC PROCESSES CLASSIFICATION

Seven different principles of geomorphic processes classification are discussed. These principles are the following: by genesis, by environmental conditions, by place of action, by spacial distribution, by the type of lithodinamic flows, by chronological criteria, by morphological results. The multiplicity of principles does not perplex the developing of partial classifications designed for concrete research aims.