Important Instances Research Articles

Developing Model-Agnostic Meta-Learning Enabled Lightbgm Model Asthma Level Prediction in Smart Healthcare Modeling

Millions of people across the world suffer from the chronic respiratory condition known as asthma. Predicting the severity of asthma based on a variety of personal and environmental characteristics might yield useful information for preventative measures. LightGBM model is a gradient-boosted model with the potential for great accuracy, but it requires careful hyperparameter adjustment to reach its full potential. Common tuning techniques have a hard time generalizing to new data distributions. The dataset was used, and its many subsets were used to represent various demographics and geographic areas. LightGBM was configured with hyperparameters, trained on a sample dataset, and then verified for each job. To quickly adjust to new tasks, the MAML method sought to find the optimal values for its hyperparameters. After the meta-training step was complete, the generalizability of the hyperparameters was tested on new data. After including MAML for hyperparameter adjustment, the Light- GBM model showed a gain of 7% in accuracy, coming in at 98.5%. Predictions of severe asthma had a crucially high 97.8 percent degree of accuracy. The model’s recall rate for severe asthma levels was 97.4%, demonstrating its capacity to reliably detect and anticipate important instances. An F1-score of 97.1%, a metric that averages the accuracy and recall of a model, is indicative of good overall performance.. For gradient-boosted model applications like asthma level prediction, MAML provides a viable path for hyperparameter adjustment. Although there are obstacles to be overcome, this method has the potential to greatly improve the flexibility and precision of predictive healthcare models. More effective implementations and a wider range of applications can be explored in future studies.

Clinical Features of Actinomycosis in Older Adults: A 10-Year Experience of a Single Institute in Beijing, China.

Actinomycosis is a rare infectious disease with non-specific clinical presentations often resulting in delayed diagnosis, especially in older adults. Diagnosing and treating actinomycetal infections in this population can be particularly challenging due to the lack of comprehensive case series studies focusing specifically on actinomycosis in older adults. The existing literature mainly consists of case reports, highlighting the need for more extensive research in this area. This study aimed to provide a profile of actinomycosis in older adults to guide future research efforts. Elderly patients aged 60 years and older who satisfied the inclusion criteria for actinomycosis at Peking Union Medical College Hospital from January 2014 to May 2024 underwent a retrospective analysis. The research centered on describing the clinical features and diagnostic techniques, distinguishing between different conditions, and treating clinically important instances of actinomycosis within this specific age bracket. This study involved 22 patients, with a balanced gender distribution of 11 males and 11 females, aged between 60 and 84 years, and a median age of 67 years. The disease predominantly affected the thoracic region (n=17), followed by the abdominal-pelvic (n=2) and orocervicofacial (n=2) regions, along with one case involving soft tissue (n=1). Microbiological methods confirmed the diagnosis in 17 cases (77%), while histopathological examination was employed in the remaining five cases (23%). General symptoms, such as fever and weight loss, were reported by 64% of the patients, whereas 32% exhibited symptoms localized to the infection site. Only one patient (4%) did not present any symptoms. The median duration from the onset of initial symptoms to diagnosis was 120 days (IQR 34.5-240). Nine patients were successfully treated with antibiotics, with only one patient experiencing a relapse during the follow-up period. Infections caused by actinomycetes are infrequent among the elderly and often exhibit non-specific clinical symptoms and imaging results. Among the various types of actinomycetal infections in this demographic, pulmonary actinomycosis is the most prevalent. Recognizing the wide-ranging capacity of actinomycetes to induce infections beyond our present knowledge is essential. It is important for healthcare practitioners to deepen their knowledge of actinomycosis to prevent delays in both diagnosis and treatment.

PairK: Pairwise k-mer alignment for quantifying protein motif conservation in disordered regions.

Protein-protein interactions are often mediated by a modular peptide recognition domain binding to a short linear motif (SLiM) in the disordered region of another protein. The ability to predict domain-SLiM interactions would allow researchers to map protein interaction networks, predict the effects of perturbations to those networks, and develop biologically meaningful hypotheses. Unfortunately, sequence database searches for SLiMs generally yield mostly biologically irrelevant motif matches or false positives. To improve the prediction of novel SLiM interactions, researchers employ filters to discriminate between biologically relevant and improbable motif matches. One promising criterion for identifying biologically relevant SLiMs is the sequence conservation of the motif, exploiting the fact that functional motifs are more likely to be conserved than spurious motif matches. However, the difficulty of aligning disordered regions has significantly hampered the utility of this approach. We present PairK (pairwise k-mer alignment), an MSA-free method to quantify motif conservation in disordered regions. PairK outperforms both standard MSA-based conservation scores and a modern LLM-based conservation score predictor on the task of identifying biologically important motif instances. PairK can quantify conservation over wider phylogenetic distances than MSAs, indicating that SLiMs may be more conserved than is implied by MSA-based metrics. PairK is available as open-source code at https://github.com/jacksonh1/pairk.

PRIMORDIAL INCEST, THE INTRUSION OF ISRAILIYAAT AND THE QUESTION OF EVOLUTION

The early Muslim attitude towards Israiliyaat was overwhelmingly negative because of the prohibitions on taking knowledge from the Judeo-Christian tradition. But over time a steady import of Israiliyaat literature made its way into Quranic exegesis. The Quran was revealed to correct and rectify the mistakes documented in the Bible (Q 16:64). The Quran was not revealed to be explained in the light of those fabrications. In this paper three important instances are discussed, and it is shown how the inclusion of Israiliyaat distorts the Quranic meaning and undermines the non-contradictory nature of the Quran. One of the cases i.e Adam’s children committing incest is analyzed in detail. While neither the Quran nor Hadith support this view, it is still used as the primary explanation for the progression of the human race. This paper discusses how the dismissal of this bizarre view is necessary as it goes against the Quran. But its dismissal brings in another significant question. If there were just two humans on earth, and incest is out of the question, then how did human lineage move forward? Thus, it becomes a necessity in such a scenario to assume that there were other humans along with Adam and Eve on earth. And this is Muslim Evolutionism as espoused by Iqbal, Abdus Sabbur Shahin, Adnan Ibrahim, Israr Ahmed and others. This view is proved to be more Quranic in spirit and is in line with rationality and demonstrable scientific evidence. This paper demonstrates how biblical fabrications in Tafsir literature obscure Quranic narratives and their elimination will bring about a better understanding of the Quranic view of the origin of life.

Coordination in social learning: expanding the narrative on the evolution of social norms

A shared narrative in the literature on the evolution of cooperation maintains that social learning evolves early to allow for the transmission of cumulative culture. Social norms, whilst present at the outset, only rise to prominence later on, mainly to stabilise cooperation against the threat of defection. In contrast, I argue that once we consider insights from social epistemology, an expansion of this narrative presents itself: An interesting kind of social norm — an epistemic coordination norm — was operative in early and important instances of specialised social learning. I show how there’s a need for such norms in two key social learning strategies and explain how this need is constituted. In assessor-teaching (e.g. Castro et al., 2019b, 2021), epistemic coordination norms allow agents to coordinate around the content of social learning, i.e., what is to be known and how this is to be done. These norms also allow agents to coordinate around the form of cultural learning in what’s sometimes called strategic social learning (Laland, 2004; Hoppitt & Laland, 2013; Heyes, 2018, Chap. 5) and elsewhere. Broadly speaking, this concerns how cultural learning is organised within the social group. The upshot is that the evolution of social learning and social norms are intertwined in important and underappreciated ways from early on. The above matters as it informs our views about the evolution of social norms more generally. Truly social norms emerged to coordinate a plurality of complex behaviours and interactions, amongst them specialised social learning. I substantiate this view by contrasting it with Jonathan Birch’s views on the evolution of norms. What results is a general but cohesive narrative on the early evolution of social norms.

Handling class imbalance and overlap with a Hesitation-based instance selection method

Class imbalance is a common problem in machine learning, particularly in classification tasks. When the distribution of instances across known classes is biased or skewed, this issue leads to poor predictive performance. This is especially true for the minority class, which is often of greater importance in problems. However, class imbalance is not the only factor that can decrease performance. Overlapping problems and borderline instances can also degrade classification performance. Conventional imbalanced learning methods often balance the distribution between classes, for example, by oversampling the minority class or under sampling the majority class. However, these methods may not adequately address the difficulties caused by overlapping and borderline instances. The present paper expands on the classification of imbalanced datasets by addressing the issue of how boundary instances should be sampled to handle class imbalance and control class overlap. The designed Hesitation degree-based instance weighting method can identify the impact of instances on classifier performance while reducing the skewness of the dataset and alleviating the possibility of class overlap. Additionally, by integrating a chaotic evolutionary algorithm with the designed classifier, the most important instances can be selected. Statistical results show that the proposed method outperforms state-of-the-art methods in terms of reduction rate, error rate, and G-mean.

Progress in Lewis-Acid-Templated Diels-Alder Reactions.

The synthesis of natural products with complicated architectures often requires the use of segments with functional groups that can be structurally transformed with the desired stereogenic centers. Bicyclic 𝛾-lactones have great potential as a suitable segment for natural product synthesis. However, the stereoselective construction of such functionalized bicyclic 𝛾-lactones is not as straightforward as one might expect. The template-mediated Diels-Alder reaction is one of the most powerful and versatile methods for providing bicyclic 𝛾-lactones with high regioselectivity and stereoselectivity. In this reaction, the diene is linked to the dienophile by a temporary tether, allowing the reaction to proceed efficiently, yielding a product that can be used for natural product synthesis. This review describes some important instances of the template-mediated Diels-Alder reaction and its application to the synthesis of biologically active compounds.

Carbapenem-resistant Escherichia coli exhibit diverse spatiotemporal epidemiological characteristics across the globe

Carbapenem-resistant Escherichia coli (CREC) poses a severe global public health risk. This study reveals the worldwide geographic spreading patterns and spatiotemporal distribution characteristics of resistance genes in 7918 CREC isolates belonging to 497 sequence types (ST) and originating from 75 countries. In the last decade, there has been a transition in the prevailing STs from highly virulent ST131 and ST38 to higher antibiotic-resistant ST410 and ST167. The rise of multi-drug resistant strains of CREC carrying plasmids with extended-spectrum beta-lactamase (ESBL) resistance genes could be attributed to three important instances of host-switching events. The spread of CREC was associated with the changing trends in blaNDM-5, blaKPC-2, and blaOXA-48, as well as the plasmids IncFI, IncFII, and IncI. There were intercontinental geographic transfers of major CREC strains. Various crucial transmission hubs and patterns have been identified for ST131 in the United Kingdom, Italy, the United States, and China, ST167 in India, France, Egypt, and the United States, and ST410 in Thailand, Israel, the United Kingdom, France, and the United States. This work is valuable in managing CREC infections and preventing CREC occurrence and transmission inside healthcare settings and among diverse hosts.

Recent developments in thiochromene chemistry.

Thiochromenes are versatile sulfur-containing heterocyclic compounds that have received considerable interest in drug discovery because of their ability to act as crucial building blocks for synthesizing bioactive compounds. In particular, these scaffolds have found utility in the design of anticancer, anti-HIV, antioxidant, and antimicrobial agents, among others. Despite their pharmacological potential, the synthesis of these scaffolds is less explored in contrast to their oxygen-containing counterparts. This review classifies the synthetic processes into Michael addition, cycloaddition, ring-opening, coupling, cyclization and Diels-Alder reactions, and others. Reaction mechanisms, circumstances, and important instances are thoroughly discussed in each area. For instance, chiral catalysts and substrates like mercaptobenzaldehyde and cinnamaldehyde are used in Michael addition processes to achieve excellent enantioselectivity. In cycloaddition reactions, readily available substrates such as thioisatins and alkynes achieve regioselectivity and product production. Thiochromenes are also synthesized by ring-opening reactions with epoxides or aziridines. These reactions demonstrate the importance of catalysts and solvents in reaction control, particularly palladium catalysts for aryl halides and thiol coupling processes. Another major class discussed is cyclization reactions with alkynyl thiols and alkynes under regulated temperature and pressure conditions to efficiently synthesize thiochromenes. With the use of chiral substrates and catalysts, Diels-Alder processes increase yields and selectivity and enhance the variety of thiochromene compounds. This review emphasizes the versatility of thiochromenes in drug discovery and consolidates the existing literature on thiochromenes, scrutinizing the gaps and opportunities for synthesizing novel thiochromene-containing lead molecules.

Support vector machine with eagle loss function

SVM utilizes the hinge loss function and maximum margin to find the separating hyperplane. In SVM, only the boundary instances/support vectors confine the separating hyperplane, making it susceptible to noisy samples near the decision boundary. This work proposes a novel noise-robust eagle loss function and presents Eagle-SVM based on the proposed loss function. The formulation of the eagle loss function was motivated by examining the state-of-the-art loss assignment policy. It allocates the loss value as per instance significance. The more important instances are assigned higher loss values, whereas those corresponding to outliers and noise are assigned lower loss values. The experiments were conducted on the benchmark datasets downloaded from the UCI repository to compare the performance of the proposed variant of SVM with hinge loss SVM, pinball loss SVM, ϵ-pinball loss SVM, SVM-CL, relabel SVM, 2medianSVM and 2meanSVM. The experimental results demonstrate that the eagle loss SVM outperforms all the state-of-the-art variants of SVM and is robust due to the incorporation of the novel loss assignment policy.

Constitutional Retconning: History in Judicial Reasoning and Changes in Constitutional Meaning

Retroactive continuity or “retconning” describes a situation where the established history or continuity of a narrative is adjusted or reinterpreted to align with new developments in the story. The concept was popularized in reference to comic books and television shows. This article develops and applies a novel concept, constitutional retconning, to examine how the courts have relied on retconning as an interpretive tool when redefining the meaning or scope of constitutional provisions. I explore the implications of constitutional retconning by analyzing three important instances where the courts have established a reimagining of history or new understandings of historical facts. Because retconning concerns historically established narratives about the constitution, constitutional retconning can have profound implications for changes in constitutional meaning and our understanding of the development of the constitution.

Typology and Characterization: Reading Portraits of Identity in Mk. 1:35 and 6:46

Abstract The discovery of Jesus’ identity as the Messiah is often understood to be the central driving force of the first half of Mark’s narrative (1:14–8:30). However, from the perspective of narrative continuity, it is not always clear how each of the micro-narratives within the larger narrative unit support this purpose. Particularly puzzling in this regard is the two instances where the author briefly describes Jesus going away to pray privately by himself (1:35; 6:46). While these two verses have often been overlooked by scholars when considering Mark’s narrative purpose, this essay considers these two micro-narratives as important instances of indirect characterization, arguing that they develop layers of narrative typology in order to characterize Jesus as a key figure within Israel’s prophetic tradition.

Factors and Consequences of Polygamy in Afghanistan

The aim of this paper is to investigate factors that cause the men in Afghanistan to turn to polygamy and show its familial, social and economic consequences. 
 Polygamy is one of the axial discussions in Islamic sociology and a doctrinal belief in its social aspect. Continually Muslim intellectuals have been studying and describing the theme of polygamy and its preconditions, from different points of views in its all aspects. If we look into the preconditions that Islam has put, we find out that the holy religion of Islam allows the polygamy in the case that man can provide justice including moral justice such as having good relation based on bilateral respect with all wives, economic justice such as distributing wealth‌ fairly among his spouses. The research shows that main factors of polygamy in Afghanistan are piety, tribal rivalry, need of social immunity, abortion of the first wife, being sonless, illness of the wife, unawareness of the husband from his responsibilities, richness, social power and position and differences among spouses. Polygamy has positive consequences as it prevents the man from adultery, obscene actions and when the first wife is abortive, it paves the way for the man to have children from another wife. There are also negative consequences for polygamy; the important instances are increase of family disputes among wives, vagrancy of their children, spread of enmity among families, problem of not following justice and finally it causes heavenly punishment for the man. This paper suggests that polygamy should be enacted only in the case when the legal and religious conditions are provided by the man.

A non-isothermal phase-field hydraulic fracture modeling in saturated porous media with convection-dominated heat transport

This research aims to extend the isothermal continuum mechanical modeling framework of hydraulic fracturing in porous materials to account for the non-isothermal processes. Whereas the theory of porous media is used for the macroscopic material description, the phase-field method is utilized for modeling the crack initiation and propagation. We proceed in this study from a two-phase porous material consisting of thermomechanically interacting pore fluid and solid matrix. The heat exchange between the fluid in the crack and the surrounding porous environment through the diffusive fracture edges is carefully studied, and new formulations here are proposed. Besides, temperature-dependent solid and fluid material parameters are taken into account, which is of particular importance in connection with fluid viscosity and its effect on post-cracking pressure behavior. This continuum mechanical treatment results in strongly coupled partial differential equations of the mass, the momentum, and the energy balance of the thermally non-equilibrated constituents. Using the finite element method, two-dimensional initial-boundary-value problems are presented to show, on the one hand, the stability and robustness of the applied numerical algorithm in solving the emerged strongly coupled problem in the convection-dominated heat transport state. On the other hand, they show the capability of the modeling scheme in predicting important instances related to hydraulic fracturing and the role of the temperature field in this process. Additionally, they show the importance of using stabilization techniques, such as adding an artificial thermo-diffusivity term, to mitigate temperature fluctuations at high flow velocity.

Effects of changing thermal conductivity on photothermal excitation in non-local semiconductor material subjected to moisture diffusion and laser pulses

A novel model is presented in this study for the situation of wave interference in a non-local stimulated semiconductor medium, including thermal, plasma, and elastic waves. Moisture diffusion in one dimension (1D) has been included in the governing equations by varying the non-local medium's thermal conductivity under the impact of laser pulse according to the non-Gaussian temporal profile. The dimensionless model was characterized by linear transformations. Analytical solutions were obtained by applying Laplace transforms to a description of the governing equations based on the photo-thermoelasticity theory based on moisture diffusivity and variable thermal conductivity. When applying certain of the circumstances (thermal ramp type and non-Gaussian plasma shock), linear solutions are achieved in the time domain using various numerical techniques based on inverse Laplace transforms. Some of the physical variables being studied are visually shown via numerical simulation. The present investigation has produced numerous important concrete instances. Using graphs and theoretical descriptions, several contrasts are drawn, while certain physical factors, such as relaxation durations, changing thermal conductivity, non-local parameters, and reference moisture values, are in play.

Practical exponential stability of switched homogeneous positive nonlinear systems with stable and unstable modes

In this article, we primarily investigate practical exponential stability of switched homogeneous positive nonlinear systems (SHPNSs) that have partial unstable modes and perturbation. First of all, the max-separable Lyapunov function (MSLF) technique and a special pre-setting switching sequence are used to define a number of significant stability conditions that ensure the state trajectories of the system converge to a confined region in continuous-time and discrete-time domains. In addition, the key results include several earlier findings as special situations and can be directly applied to general switched systems, not necessarily positive. Finally, two important instances are provided to further illustrate the validity of the theoretical findings.

(Invited) Nonlinear Schrödinger equation: Autonomous and nonautonomous soliton

This article contains a brief review of the autonomous and nonautonomous solitons supported by autonomous and nonautonomous nonlinear Schrödinger equations. Majority of the results reported here are theoretical. However, few important instances of experimental achievements have also been cited. The present review is expected to be useful and interesting to readers and young researchers.

Threshold optimization and random undersampling for imbalanced credit card data

Output thresholding is well-suited for addressing class imbalance, since the technique does not increase dataset size, run the risk of discarding important instances, or modify an existing learner. Through the use of the Credit Card Fraud Detection Dataset, this study proposes a threshold optimization approach that factors in the constraint True Positive Rate (TPR) ≥ True Negative Rate (TNR). Our findings indicate that an increase of the Area Under the Precision–Recall Curve (AUPRC) score is associated with an improvement in threshold-based classification scores, while an increase of positive class prior probability causes optimal thresholds to increase. In addition, we discovered that best overall results for the selection of an optimal threshold are obtained without the use of Random Undersampling (RUS). Furthermore, with the exception of AUPRC, we established that the default threshold yields good performance scores at a balanced class ratio. Our evaluation of four threshold optimization techniques, eight threshold-dependent metrics, and two threshold-agnostic metrics defines the uniqueness of this research.

Transcriptome differential display of a drought‐tolerant early flowering spineless mutant of safflower (Carthamus tinctorius) and identification of candidate genes

AbstractOne of the best candidates to face the increasing environmental stresses is safflower (Carthamus tinctorius L.) with natural tolerance to multiple abiotic stresses including drought. In the present study, transcriptome profile of a spineless drought‐tolerant mutant of safflower with early flowering was compared to its spiny wild type. In differential RNA‐Seq analyses more than 400 differentially expressed genes (DEGs) were identified in spineless drought‐tolerant mutant. The expression of 8 top DEGs, mostly related to the contrasting traits, was confirmed by real‐time quantitative reverse transcription PCR. Transcription factors (TFs) followed by protein kinases had the highest frequency among the identified DEGs. TF families involved in the regulation of cell cycle, development, and environmental responses were prevalent in DEGs of spineless drought‐tolerant mutant, including NAC, bHLH, MYB, HD‐ZIP, and ERF. Three Kyoto Encyclopedia of Genes and Genomes pathways with direct or indirect role in cell/tissue development and metabolic processes were enriched for DEGs. Our results suggest that phenotypic differences between the two contrasting genotypes can be governed via regulation of hormone signal transduction/or cell cycle and stress‐related pathways. Several candidate genes for spine formation, early flowering, and drought tolerance were introduced, important instances are ZHD8 and TBL21 (candidates for spininess), three novel transcripts, respectively, encoding a CCT type protein, a MADS‐box TF and a CCA1 (candidates for early flowering), and CAT2, ZAT10, and CAMTA (candidates for drought response). These findings facilitate the isolation of key genes controlling drought‐tolerance, spininess, and early flowering in safflower and can be applied for developing value‐added varieties through genome‐based breeding programs.

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