Unbalanced Ones Research Articles

LABORATORY PLATFORM FOR DEMONSTRATING THE SYMMETRICAL COMPONENTS ȚUGULEA POWER THEORY APPLIED ON GRID MODELS WITH NEUTRAL CONDUCTOR

In the context of the ever-increasing complexity of modern power systems, optimizing consumers’ performance to improve electrical energy quality becomes paramount. This article thoroughly examines the power transfer effects in the context of distorting and non-symmetrical regimes in three-phase, four-wire power systems, focusing on heavily nonlinear and unbalanced consumer influence across the grid. Particular emphasis is placed on the impact of these regimes on the parasitic active and reactive powers affecting linear and balanced consumers due to distorting and unbalanced ones. An essential aspect of this analysis is including the neutral conductor in the experimental circuit, enhancing relevance and a more profound understanding of consumer interactions in modern networks. Quantitative aspects of the phenomena involved are assessed from the perspective offered by SCPT (introduced by Andrei Ţugulea), allowing us to identify the source of non-symmetry and residual powers through comprehensive power balance equations for the active and reactive powers.

Nutritional Diagnosis of Potato Crops Using the Multivariate Method

The compositional nutrient diagnosis (CND) method considers the multiple relationships among nutrients and has been proposed to evaluate the nutritional status of plants in place of the univariate and bivariate methods. As it is mathematically based and considers the interactions among all nutrients at the same time, it avoids the errors and trends observed in the calculations of other methods estimating nutritional status, enabling a greater relationship with productivity. The objective of this study was to obtain the CND norms for high-yielding populations of potato crops. For this, 587 samples were used from 21 experimental areas in the state of São Paulo, Brazil to correlate the leaf nutrient contents and the yields of potato crops. Crops with yields higher than 48,993.24 kg ha−1 were considered to have high yields, and the Mahalanobis distance separated the balanced samples from the nutritionally unbalanced ones. Thus, the CND-ilr method generated the norms and classified the 587 samples as nutritionally balanced with a high yield (5% of the total), nutritionally unbalanced with a low yield (92%), nutritionally unbalanced with a high yield (0.3%), or nutritionally balanced with a low yield (2.7%), with accuracy, sensitivity, specificity, NPV, and PPV scores of 96.9, 97.1, 93.6, 64.4, and 99.6%, respectively.

Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network.

Microbes have dense linkages with human diseases. Balanced microorganisms protect human body against physiological disorders while unbalanced ones may cause diseases. Thus, identification of potential associations between microbes and diseases can contribute to the diagnosis and therapy of various complex diseases. Biological experiments for microbe-disease association (MDA) prediction are expensive, time-consuming, and labor-intensive. We developed a computational MDA prediction method called GPUDMDA by combining graph attention autoencoder, positive-unlabeled learning, and deep neural network. First, GPUDMDA computes disease similarity and microbe similarity matrices by integrating their functional similarity and Gaussian association profile kernel similarity, respectively. Next, it learns the feature representation of each microbe-disease pair using graph attention autoencoder based on the obtained disease similarity and microbe similarity matrices. Third, it selects a few reliable negative MDAs based on positive-unlabeled learning. Finally, it takes the learned MDA features and the selected negative MDAs as inputs and designed a deep neural network to predict potential MDAs. GPUDMDA was compared with four state-of-the-art MDA identification models (i.e., MNNMDA, GATMDA, LRLSHMDA, and NTSHMDA) on the HMDAD and Disbiome databases under five-fold cross validations on microbes, diseases, and microbe-disease pairs. Under the three five-fold cross validations, GPUDMDA computed the best AUCs of 0.7121, 0.9454, and 0.9501 on the HMDAD database and 0.8372, 0.8908, and 0.8948 on the Disbiome database, respectively, outperforming the other four MDA prediction methods. Asthma is the most common chronic respiratory condition and affects ~339 million people worldwide. Inflammatory bowel disease is a class of globally chronic intestinal disease widely existed in the gut and gastrointestinal tract and extraintestinal organs of patients. Particularly, inflammatory bowel disease severely affects the growth and development of children. We used the proposed GPUDMDA method and found that Enterobacter hormaechei had potential associations with both asthma and inflammatory bowel disease and need further biological experimental validation. The proposed GPUDMDA demonstrated the powerful MDA prediction ability. We anticipate that GPUDMDA helps screen the therapeutic clues for microbe-related diseases.

Characterizing onboard noise in ships: Insights from statistical, machine learning and advanced noise index analyses

Understanding the specific characteristics of onboard noise can significantly benefit human activity in different kinds of ships. Here, the perceived noise can significantly change from space to space in terms of both levels and frequency content, depending on location onboard in respect to the primary sources and on propagation paths. Moreover, secondary sources as ventilation systems contribute to generate a complex soundscape for each ship. In this work, noise spectra reported in the literature were collected and analyzed to obtain an overview of the noise characteristics in different spaces onboard military and commercial vessels, i.e. accommodation, navigation bridge, and other workspaces. A prevalence of high noise levels in the different spaces that can be over the commonly accepted limits was found, characterized by higher levels at low and high frequencies. Different noise indexes not yet adopted in this sector were tested on the data to derive more information about onboard noise annoyance. Supervised and unsupervised machine learning algorithms were also applied to qualitatively classify and study the collected spectra. The analysis shows the presence of different spectral typologies, i.e. balanced spectral shapes (quasi-linear decay of the noise level per octave band with no dominant frequency components) or unbalanced ones.

Antibiotic Prescription for Dental Procedures in Type 1 Diabetic Children.

The aim is to optimize the benefit and minimize the risk of antibiotics in dental treatments performed in diabetic children. A cross-sectional approach was conducted on 155 type 1 diabetic children (72 controlled and 83 uncontrolled). The types of dental acts held for the study were pulpotomies, pulpectomies, pediatric crowns, scaling, and extraction. For the balanced diabetic patients, no antibiotics were prescribed except for infected teeth. In the unbalanced diabetic group, for the acts causing bleeding, prophylactic antibiotics were administered. In presence of dental infection, antibiotics were administered for at least 5 days. The analysis of data was carried out using Statistical Package for the Social Sciences Computer Software (SPSS 21.0, Inc., Chicago, Illinois, USA). A probability value of <0.05 was regarded as statistically significant. Around 126 acts in the balanced group and 145 in the unbalanced ones were performed. In balanced diabetic children, 125 successes and one failure were noted. In the unbalanced group, 142 successes and three failures were recorded. The comparison between variables did not show any statistical significance (p-value = 0.382). This study demonstrated that working with diabetic young patients is possible and safe as long as some measures are considered. It is crucial to identify the dental acts that necessitate antibiotics administration and to differentiate between balanced and unbalanced diabetic children for the same dental procedure. Nassif N, Noueiri B. Antibiotic Prescription for Dental Procedures in Type 1 Diabetic Children. Int J Clin Pediatr Dent 2023;16(1):60-63.

Fundamental Limits of Stochastic Shared-Cache Networks

The work establishes the exact performance limits of stochastic coded caching when users share a bounded number of cache states, and when the association between users and caches, is random. Under the premise that more balanced user-to-cache associations perform better than unbalanced ones, our work provides a statistical analysis of the average performance of such networks, identifying in closed form, the exact optimal average delivery time. To insightfully capture this delay, we derive easy-to-compute closed-form analytical bounds that prove tight in the limit of a large number Λ of cache states. In the scenario where delivery involves K users, we conclude that the multiplicative performance deterioration due to randomness - as compared to the well-known deterministic uniform case - can be unbounded and can scale as Θ([log Λ]/[log log Λ]) at K = Θ(Λ ), and that this scaling vanishes when K = Ω(Λ log Λ ). To alleviate this adverse effect of cache-load imbalance, we consider various load-balancing methods, and show that employing proximity-bounded load balancing with an ability to choose from h neighboring caches, the aforementioned scaling reduces to Θ([log(Λ/h)]/[log log(Λ/h)]) at K=Θ(Λ ), while when the proximity constraint is removed, the scaling is of a much slower order Θ(log log Λ ). The above analysis is extensively validated numerically.

Distributed Prescribed-Time Interval Bipartite Consensus of Multi-Agent Systems on Directed Graphs: Theory and Experiment

This work deals with the analysis and protocol design problems of the prescribed-time interval bipartite consensus of multi-agent systems on signed and directed graphs. A new distributed protocol with hybrid constant and time-varying feedbacks of local signed error is proposed, whose consensus time period is independent of the specific topology among agents and initial states of all agents. By introducing a series of well-structured Lyapunov functions, the technical difficulties arising from the asymmetrical Laplacian matrices of directed graphs are circumvented. The effectiveness of this prescribed-time protocol for multi-agent systems on signed digraphs with a spanning tree is proven both on structurally balanced digraphs and structurally unbalanced ones with a positive root subgraph. An illustrative simulation example and a prescribed-time bipartite formation experiment on a swarm of nano-quadcopters are implemented to show the validity and practicability of these proposed protocols.

Noninvasive Passive Measurement of Multiphase Currents in IoT

The feasibility and the diversity of cantilever-based current sensing mechanism, which mainly comprised a cantilever with a permanent magnet on its free end, are verified for desirable applications of wireless sensor network (WSN) in Internet of Things (IoT). In the noninvasive multiphase current measurement, the applied current induced magnetic force is passively converted into a cantilever vibration via the magnet. The cantilever vibration can be further converted to an output voltage as a function of the applied current via diverse detecting units, enabling the diversity of cantilever-based current sensing mechanisms. In this article, cantilever-based methodology is verified to be applicable to multiphase current measurements, with considering decoupling and reconstructing in case of unbalanced ones. As a typical demonstration, three-phase four-wire ac current is passively measured via the positive piezoelectric effect of the piezoelectric detecting unit. Since the measurement of current is physically the noninvasive passive measurement of the gradient of the superimposed magnetic field, the cantilever-based current sensing methodology is applicable to a wide range of diverse current measurements of WSN in various IoT use cases.

Analysis of the embryos genetic characteristics and methodologies of human translocations research

Aim. Assessment of the embryos genetic characteristics from translocation carriers and analysis of the translocation research methodology. Methods. The chromosome structure was analyzed using classical cytogenetics methods, GTG, FISH. Preimplantation genetic testing to identify structural rearrangements of the embryos chromosomes was performed on trophectoderm cells using NGS and FISH methods. Results. The proportion of translocation carriers in the sample of patients with reproductive disorders (n = 6156) was 1.1 %, with 0.4 % – for Robertson translations and 0.8 % for reciprocal ones. 5-day-old embryos with balanced reciprocal translocations are 3-4 times less than with unbalanced ones. Euploid embryos with balanced variants from translocation carriers-mothers and -fathers, amounted to 14.3 % and 12.5 %. Aneuploid embryos with unbalanced translocations accounted for 59.2 % of mothers and 63.2 % of fathers of all received embryos, 80.6 % and 77.8 % of unbalanced ones. Conclusions. Understanding the prevalence of segmental karyotype disorders among the population and modern research methods allows to optimize reproductive care for patients.&#x0D; Keywords: reciprocal translocations, embryos, PGT-SR, NGS, FISH.

A Corpus-based Study of Question Tags in Asian Englishes with Reference to American and British English

This study investigated question tags in world Englishes from a comparative perspective. A corpus analysis was conducted with the GloWbe to identify the forms and communicative functions of the commonly used question tags in inner-circle and outer-circle English-speaking countries. It revealed that the three most frequent positive tags are do you?, are you?, and would you?, and negative-positive balanced tags are more frequent than unbalanced ones. An in-depth analysis of the concordance lines indicates that unbalanced tags are primarily used for euphemistic, ironic, and confrontational effects. English speakers in the inner-circle countries tend to use would you? tags in imperative and argumentative situations while those in the outer-circle countries use them more often to make a request for confirmation and express encouragement in phatic communion. Furthermore, inner-circle speakers exhibit a tendency to use do you? and are you? tags to posit a proposition that presupposes the listener’s agreement, whereas in the outer-circle countries their usage contexts are preferentially associated with emphasis, oxymoron, and sarcasm.

Scale-invariant topology and bursty branching of evolutionary trees emerge from niche construction

Phylogenetic trees describe both the evolutionary process and community diversity. Recent work has established that they exhibit scale-invariant topology, which quantifies the fact that their branching lies in between the two extreme cases of balanced binary trees and maximally unbalanced ones. In addition, the backbones of phylogenetic trees exhibit bursts of diversification on all timescales. Here, we present a simple, coarse-grained statistical model of niche construction coupled to speciation. Finite-size scaling analysis of the dynamics shows that the resultant phylogenetic tree topology is scale-invariant due to a singularity arising from large niche construction fluctuations that follow extinction events. The same model recapitulates the bursty pattern of diversification in time. These results show how dynamical scaling laws of phylogenetic trees on long timescales can reflect the indelible imprint of the interplay between ecological and evolutionary processes.

Symmetry and Balance as Factors of Aesthetic Appreciation: Ethel Puffer’s (1903) “Studies in Symmetry” Revised

Symmetry and balance are basic concepts in art theory for the composition of pictures. It is assumed that well-balanced pictures are preferred to unbalanced ones. One of the first experimental studies to test this assumption was conducted more than a century ago by Ethel Puffer. By applying a production method, she found little evidence for the hypothesis that balance is favorable for the aesthetical appreciation of pictures. Instead, she observed that other construction principles competing with balance, such as bilateral symmetry and closeness, were applied. The aim of the present study was to repeat some of Puffer’s experiments with modern methods and to examine whether her results are replicable. In two experiments, we also found little to no evidence for balance. Moreover, as in Puffer’s study, participants used closeness and bilateral symmetry as principles. However, compared to that study, the relative frequency of use of these principles was quite different.

Unsupervised feature selection algorithm for multiclass cancer classification of gene expression RNA-Seq data

This paper presents a Grouping Genetic Algorithm (GGA) to solve a maximally diverse grouping problem. It has been applied for the classification of an unbalanced database of 801 samples of gene expression RNA-Seq data in 5 types of cancer. The samples are composed by 20,531 genes. GGA extracts several groups of genes that achieve high accuracy in multiple classification. Accuracy has been evaluated by an Extreme Learning Machine algorithm and was found to be slightly higher in balanced databases than in unbalanced ones. The final classification decision has been made through a weighted majority vote system between the groups of features. The proposed algorithm finally selects 49 genes to classify samples with an average accuracy of 98.81% and a standard deviation of 0.0174.

The evolution of structural balance in time-varying signed networks

Signed networks are ubiquitous in the real world. Most of them are temporal and the nodes and edges are varying over time, which makes the changing of network structure, including the clustering, the structural balance and so forth. In this work, we focus on the evolution of structural balance defined as the ratio of balanced triangles in the temporal signed networks. Firstly, it is shown that the balanced triangles tend to be formed during a relatively short time, while the formation of unbalanced ones takes a longer time. In addition, the real world networks exhibit strong structural balance in the early stage of the network generated and then it decreases to a stable state. As a result, we find that the unbalanced triangles are prone to be balanced as time goes, which is accordance with structural balance theory.

Complex karyotype in de novo acute myeloid leukemia: typical and atypical subtypes differ molecularly and clinically.

Complex karyotype (CK) with ≥3 abnormalities is detected in 10-12% of patients with acute myeloid leukemia (AML) and associated with poor prognosis. The most common unbalanced abnormalities found in CK result in loss of material from the 5q, 7q and/or 17p chromosome arms. The presence of 5q, 7q and/or 17p abnormalities denotes typical CK and their absence denotes atypical CK. Since molecular features of CK-AML are not well-characterized, we investigated mutational status of 81 leukemia/cancer-associated genes in 160 clinically well-characterized patients. They included 136 patients with ≥3 exclusively unbalanced chromosome abnormalities, 96 of whom had a typical CK and 40 atypical CK, and 24 patients with ≥1 balanced abnormality in addition to ≥2 unbalanced ones. Patients with atypical CK-AML differed from those with typical CK-AML: they carried TP53 mutations less often (P<0.001) and more often PHF6 (P=0.008), FLT3-TKD (P=0.02), MED12 (P=0.02) and NPM1 (P=0.02) mutations. They were younger (P=0.007), had higher WBC (P=0.001) and percentages of marrow (P<0.001) and blood (P=0.006) blasts, higher complete remission rates (P=0.02) and longer overall survival (P<0.001), thus indicating that atypical and typical CK-AMLs constitute distinct disease subtypes. We also identified smaller patient subsets within both typical and atypical CK-AML that differed molecularly and clinically.

Imbalanced Learning Techniques for Improving the Performance of Statistical Models in Automated Essay Scoring

The problem of class imbalance occurs in many application domains, as in the case of essays. The imbalance of the number or samples among the classes presents a problem for predictive algorithms, both for classification or for regression. In this paper, we present imbalanced learning techniques for improving the performance of statistical models in automated essay grading. We analyze the performance of different types of statistical algorithms using machine learning and classification techniques, combined with different balancing methods. The results indicated a significant improvement of accuracy and average error when the algorithms were applied in a balanced corpus, comparing with the unbalanced ones.

Bi-level hybrid local search approach for three-dimensional loading problem with balancing constraints

This paper presents a bi-level hybrid local search (BHLS) algorithm for the three-dimensional loading problem with balancing constraints (3DLP-B), where several rectangular boxes with even densities but different sizes are loaded into a single cubic bin to meet the requirements of the space or capacity utilization and the balance of the center of gravity. The proposed algorithm hybridizes a novel framed-layout procedure in which the concept of the core block and its generation strategy are introduced. Once the block-loading sequence has been determined, we can load one block at a time by the designed construction heuristic. Then, the double-search is introduced; its external search procedure generates a list of compact packing patterns while its internal search procedure is used to search the core-block frames and their best distribution locations. The approach is extensively tested on weakly to strongly heterogeneous benchmark data. The results show that it has better performance in improving space utilization rate and balanced condition of the placement than existed techniques: the overall averages from 79.85% to 86.45% were obtained for the balanced cases and relatively high space-usage rate of 89.44% was achieved for the unbalanced ones.

Crop yields and soil organic carbon dynamics in a long-term fertilization experiment in an extremely arid region of northern Xinjiang, China

A long-term fertilization experiment was set up in northern Xinjiang, China to evaluate the dynamics of crop production and soil organic carbon (SOC) from 1990 to 2012 with seven fertilization treatments. The seven treatments included an unfertilized control (CK) and six different combinations of phosphorus (P), potassium (K), nitrogen (N), straw (S) and animal manure (M). The balanced fertilization treatments had significantly (P<0.05) higher average yields than the unbalanced ones. The treatment with 2/3 N from potassium sulfate (NPK) and 1/3 N from farmyard manure (NPKM) had a higher average yield than the other treatments. The average yields (over the 23 years) in the treatments of NPK, and urea, calcium superphosphate (NP) did not differ significantly (P>0.05) but were higher than that in the treatment with urea and potassium sulfate (NK; P<0.05). The results also show that the highest increases in SOC (P<0.05) occurred in NPKM with a potential increase of 1.2 t C/(hm2•a). The increase in SOC was only 0.31, 0.30 and 0.12 t C/(hm2•a) for NPKS (9/10 N from NPK and 1/10 N from straw), NPK and NP, respectively; and the SOC in the NP, NK and CK treatments were approaching equilibrium and so did not rise or fall significantly over the 23-year experiment. A complete NPK plus manure fertilization program is recommended for this extremely arid region to maximize both yields and carbon sequestration.

Accurate power sharing for parallel DGs in microgrid with various-type loads

Microgrids are nowadays used to produce electric energy with more efficiency and advantage. However, the use of microgrids presents some challenges. One of the main problems of the microgrids widely used in electrical power systems is the control of voltage, frequency and load sharing balance among inverter- based distributed generators (DGs) in islanded mode. Droop method performance degrades when the feeder impedances of two DGs are different and thereby, further modification is required. In this article, a new method based on virtual impedance and compensating voltage is proposed and simulation results show that this method combined with droop control results in balanced power sharing with negligible voltage and frequency drop. Simulation results have been extracted from the Simulink, MATLAB and showed that the proposed method has a good performance in equal load sharing between two DGs with different feeder impedances; both in equal and different droop gains, and with different loads such as nonlinear or unbalanced ones.

Evidence of structural balance in spatial ecological networks

Despite recent advances in applying networks to study ecological systems, most of the network datasets are built attending only to a single type of interaction between nodes, which can be an oversimplification. In the present work, we built ecological networks that had positive and negative links for multiple plant communities based on the local spatial association between species. Then, we evaluated whether those networks were in balance, a hypothesis commonly formulated for real signed graphs but never tested in systems other than social networks. Specifically, we quantified the global and the local structural balance in the networks. We found that plant community networks were more balanced than expected by chance, and that this pattern was due to a large number of balanced triads to the detriment of unbalanced ones. Furthermore, this pattern was consistent among all of the types of the plant communities examined, which suggests that configurations that promote structural balance might be common in ecological signed networks. We also found that almost all networks had some unbalanced components, which might be responsible for the adaptation of the system. Mechanisms behind these structure and possible applications for community ecology are discussed. Our results encourage testing structural balance in other ecological networks to confirm if it is a widespread architecture of natural systems.