Continuous Search Research Articles

High-throughput screening of ancient forest plant extracts shows cytotoxicity towards triple-negative breast cancer

According to the World Health Organization, women's breast cancer is among the most common cancers with 7.8 million diagnosed cases during 2016–2020 and encompasses 15 % of all female cancer-related mortalities. These mortality events from triple-negative breast cancer are a significant health issue worldwide calling for a continuous search of bioactive compounds for better cancer treatments. Historically, plants are important sources for identifying such new bioactive chemicals for treatments. Here we use high-throughput screening and mass spectrometry analyses of extracts from 100 plant species collected in Chinese ancient forests to detect novel bioactive breast cancer phytochemicals. First, to study the effects on viability of the plant extracts, we used a MTT and CCK-8 cytotoxicity assay employing triple-negative breast cancer (TNBC) MDA-MB-231 and normal epithelial MCF-10A cell lines and cell cycle arrest to estimate apoptosis using flow cytometry for the most potent three speices. Based on these analyses, the final most potent extracts were from the Amur honeysuckle (Lonicera maackii) wood/root bark and Nigaki (Picrasma quassioides) wood/root bark. Then, 5 × 106 MDA-MB-231 cells were injected subcutaneously into the right hind leg of nude mice and a tumour was allowed to grow before treatment for seven days. Subsequently, the four exposed groups received gavage extracts from Amur honeysuckle and Nigaki (Amur honeysuckle wood distilled water, Amur honeysuckle root bark ethanol, Nigaki wood ethanol or Nigaki root bark distilled water/ethanol (1:1) extracts) in phosphate-buffered saline (PBS), while the control group received only PBS. The tumour weight of treated nude mice was reduced significantly by 60.5 % within 2 weeks, while on average killing 70 % of the MDA-MB-231 breast cancer cells after 48 h treatment (MTT test). In addition, screening of target genes using the Swiss Target Prediction, STITCH, STRING and NCBI-gene database showed that the four plant extracts possess desirable activity towards several known breast cancer genes. This reflects that the extracts may kill MBD-MB-231 breast cancer cells. This is the first screening of plant extracts with high efficiency in 2 decades, showing promising results for future development of novel cancer treatments.

The anticancer and antibacterial potential of bioactive secondary metabolites derived From bacterial endophytes in association with Artemisia absinthium

The continuous search for secondary metabolites in microorganisms isolated from untapped reservoirs is an effective prospective approach to drug discovery. In this study, an in-depth analysis was conducted to investigate the diversity of culturable bacterial endophytes present in the medicinal plant A. absinthium, as well as the antibacterial and anticancer potential of their bioactive secondary metabolites. The endophytic bacteria recovered from A. absinthium, were characterized via the implementation of suitable biochemical and molecular analyses. Agar well diffusion and broth microdilution were used to screen antibacterial activity. SEM was performed to assess the impact of the extracted metabolite on MRSA strain cell morphology. Apoptosis and cytotoxicity assays were used to evaluate anticancer activity against MCF7 and A549. The FTIR, GC–MS were used to detect bioactive compounds in the active solvent fraction. Of the various endophytic bacteria studied, P. aeruginosa SD01 showed discernible activity against both bacterial pathogens and malignancies. The crude ethyl acetate extract of P. aeruginosa SD01 showed MICs of 32 and 128 µg/mL for S. aureus and MRSA, respectively. SEM examination demonstrated MRSA bacterial cell lysis, hole development, and intracellular leaking. This study revealed that the crude bioactive secondary metabolite SD01 has potent anticancer activity. In this study, 2-aminoacetophenone, 1,2-apyrazine-1,4-dione, phenazine and 2-phenyl-4-cyanopyridine were the major bioactive secondary metabolites. In conclusion, our findings indicate that the bacteria recovered from A. absinthium plants and in particular, P. aeruginosa SD01 is a remarkable source of untapped therapeutic, i.e., antimicrobial and anticancer compounds.

The Cruel Optimism of International Prison Regulation: Prison Ontologies and Carceral Harms

This article examines the development of international human rights standards and oversight mechanisms directed at addressing the negative effects of imprisonment. We identify this as the rules-based prison-regulation project, widely endorsed by international organizations and legal scholars. However, with a focus on the United Nations Standard Minimum Rules for the Treatment of Prisoners, we argue that this project has inherent limitations, as it is based on (a) a reductive understanding of carceral harms and (b) a rule-centric ontology of prisons. By challenging these foundations, we explore whether the project exemplifies “cruel optimism” (Berlant, 2011), where the pursuit of improved prison regulation could inadvertently hinder societal flourishing. We argue that the continuous search for new and better prison standards may perpetuate rather than alleviate the problems associated with imprisonment unless accompanied by explicit strategies for countering prison growth and dramatically reducing prisoner numbers, for building the democratic power of prisoners and communities targeted by imprisonment, and continual linkages between prison conditions and the wider political-economic institution of imprisonment. We conclude that engaging with prisons as sites of relational power in practice must underlie any quest to reduce the harms of imprisonment.

Clinical experience in rehabilitation of patients with Fuchs corneal dystrophy and cataract by ultrasonic phacoemulsification and descemetorhexis

BACKGROUND: The potential for peripheral corneal endothelial capabilities is a novel, poorly understood direction. The comprehensive development of various modifications of endothelial keratoplasty goes hand in hand with a lack of donor material. This explains the continuous search for safe tissue-preserving techniques.
 AIM: The aim of this study is to evaluate the clinical and functional results of treatment of patients with Fuchs corneal dystrophy and cataract using a combination of cataract ultrasound phacoemulsification and descemetorhexis.
 MATERIALS AND METHODS: The study included 3 patients (3 eyes), 3 women aged 65 to 78 (on average 73.6 7.5 years). The follow-up period in the postoperative period was 36 months. The inclusion criteria were: patient complaints about glare, blurred vision and cloudy vision in the morning; the location of the guttae in the central 5 mm zone, central corneal stromal edema less than 610 microns, the inability to count endothelial cells in the center, endothelial cells density on the periphery in the upper quadrant more than 1400 cells/mm2. All patients underwent phacoemulsification of cataract with IOL implantation and subsequent descemetorhexis in the 4 mm zone.
 RESULTS: At 1 month an increase in the central corneal thickness and a slight increase in uncorrected visual acuity (UCVA) and in best corrected visual acuity (BCVA). By the 3rd month, positive dynamics was present: an increase in UCVA and BCVA in all cases, a decrease in the central corneal thickness (559 20 m), resorption of stromal edema, increase in corneal transparency, possibility to calculate the endothelial cells density in the center (866 46 cells/mm2). At 36 months, the BCVA was 0.6, 0.4 and 0.5, respectively.
 CONCLUSIONS: Restoration of corneal transparency was achieved in 100% of cases (3 out of 3). An analysis of the clinical results of the descemetorhexis + phacoemulsification + IOL operation demonstrated an increase in visual acuity, an increase in corneal transparency and a decrease in stromal edema in patients with initial Fuchs corneal dystrophy and cataract. The possibility of not using donor material for the treatment of Fuchs corneal dystrophy is a promising trend. Further accumulation of material is required.

Evaluation of Antimicrobial Activity by Marine Nocardiopsis dassonvillei against Foodborne Listeria monocytogenes and Shiga Toxin-Producing Escherichia coli.

The emergence of multidrug-resistant pathogens creates public health challenges, prompting a continuous search for effective novel antimicrobials. This study aimed to isolate marine actinomycetes from South Africa, evaluate their in vitro antimicrobial activity against Listeria monocytogenes and Shiga toxin-producing Escherichia coli, and characterize their mechanisms of action. Marine actinomycetes were isolated and identified by 16S rRNA sequencing. Gas chromatography-mass spectrometry (GC-MS) was used to identify the chemical constituents of bioactive actinomycetes' secondary metabolites. Antibacterial activity of the secondary metabolites was assessed by the broth microdilution method, and their mode of actions were predicted using computational docking. While five strains showed antibacterial activity during primary screening, only Nocardiopsis dassonvillei strain SOD(B)ST2SA2 exhibited activity during secondary screening for antibacterial activity. GC-MS identified five major bioactive compounds: 1-octadecene, diethyl phthalate, pentadecanoic acid, 6-octadecenoic acid, and trifluoroacetoxy hexadecane. SOD(B)ST2SA2's extract demonstrated minimum inhibitory concentration and minimum bactericidal concentration, ranging from 0.78-25 mg/mL and 3.13 to > 25 mg/mL, respectively. Diethyl phthalate displayed the lowest bacterial protein-binding energies (kcal/mol): -7.2, dihydrofolate reductase; -6.0, DNA gyrase B; and -5.8, D-alanine:D-alanine ligase. Thus, marine N. dassonvillei SOD(B)ST2SA2 is a potentially good source of antibacterial compounds that can be used to control STEC and Listeria monocytogenes.

THE DEGREE OF AWARENESS OF THE POPULATION OF THE KARAGANDA REGION ON THE INCIDENCE AND PREVENTION OF COLORECTAL CANCER: A LITERATURE REVIEW

Relevance: Colorectal cancer (CRC) is the leading cancer in yearly morbidity and mortality. WHO forecasts that 2030 CRC incidence will exceed 2.2 million cases yearly, and mortality will increase to 1.1 million yearly. More than 3,000 new cases of colorectal cancer are detected annually in Kazakhstan. In disease control, it is necessary to develop preventive measures as much as possible. Preventive measures play a crucial role in reducing mortality from this disease. One of the most critical issues is the lack of public awareness about the disease.
 The study analyzes the global experience in preventing colorectal cancer to develop measures to raise public awareness.
 Methods: A continuous search was performed in the PubMed, CrossRe, Scopus, and Cochrane databases for 2013-2023 for the keywords “colorectal cancer,” “risk factors,” “public awareness,” “medical literacy,” “morbidity,” and “prevention.” In total, more than 75 scientific articles and 500 abstracts were reviewed.
 Results: The problem is aggravated by the fact that among patients with an oncological diagnosis, patients with colorectal cancer, or patients with a confirmed diagnosis of the disease, there is insufficient information about this disease, and they neglect preventive measures. Firstly, we insist that the population is not fully aware of the responsibility for their health (this is influenced by a false sense of shame and insufficient awareness of the disease), and secondly, primary prevention is essential. Accordingly, it is necessary to increase the effectiveness of screening programs, improve awareness, and organize full-fledged assistance from the state in disease control.
 Conclusion: Colorectal cancer is an urgent disease that occupies an essential place in Kazakhstan’s list of oncological diseases. Due to the increased awareness of the population about this disease and the correct solution to prevention issues, it will be possible to reduce the incidence among patients. In this regard, it is necessary to widely disseminate information about the disease among the population and increase patients’ responsibility for their health.

What Can Biologic Aging Tell Us About the Effects of Mental Stress on Vascular Health.

Cardiovascular disease is often a disease of aging. Considerable advances in our understanding of the biological mechanisms of aging have been made; yet, cardiovascular disease remains the leading cause of death in the United States urging a continued search for novel risk factors to target for preventing and treating disease. Mental stress (MS) is emerging as an important risk factor, and while progress has been made in understanding the link between MS and cardiovascular disease, the precise mechanisms of a putative causal relationship require greater clarification. In the current review, we (1) summarize our current understanding of the pathological effects of MS on vascular health; (2) describe important aspects of the pathobiology of vascular aging including inflammation, oxidative stress, mitochondrial dysfunction as well as novel processes such as genomic instability, epigenetic alterations, and nutrient signal pathways; (3) highlight similarities in the downstream biologic effects of aging and MS on vascular health with an emphasis on cellular and molecular processes that could be used to develop novel prognostic markers and treatment strategies for cardiovascular disease; (4) discuss lifestyle and pharmacological methods that target indicators of aging whose role could be translated into approaches managing the effects of MS; and (5) outline important future steps that should be considered in this area of research including the need for prospective clinical trials and for creating greater collaboration between preclinical aging researchers and clinical investigators managing MS.

Impacts and Regulations of Healthcare Solid Waste Management during the COVID-19 Pandemic: A Systematic Review

In a pandemic context, it is essential to intensify precautions related to healthcare solid waste, known as HCSW, ensuring the continuous search for safer management and handling protocols of these materials. In this sense, the aim of this paper is to conduct a comprehensive review of the literature about the management of healthcare waste during the COVID-19 pandemic. The current investigation was underpinned by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) framework, selected to ensure the comprehensive and transparent presentation of the systematic review. In pursuit of this objective, three distinct keyword combinations were employed, namely, “solid waste management”, “medical waste”, and “COVID-19 pandemic”. Consequently, a total of 76 documents were incorporated into the analysis. The results of this analysis indicate that the amount and treatment of hospital solid waste were significantly affected by the pandemic, bringing impacts on social, economic, and environmental aspects. Recent studies have focused on mitigating these impacts by pursuing “green” solutions, such as implementing sustainable strategies, preserving biodiversity, adopting an eco-conscious lifestyle, improving healthcare infrastructure, raising public awareness, and changing HCSW management policies. In addition, alternative technologies have been explored for the adequate treatment of these wastes, as well as the replacement of harmful materials by safer substances. However, more scientific research on this topic is still needed, especially in the Brazilian context, in order to contribute to the development of strategies that minimize the impacts of the pandemic on both society and the environment.

Exploring the structural, elastic, phonon, optoelectronics, and thermoelectric properties of tetragonal complex metal hydride X2MgH4 (X=K, Rb, and Cs) compounds for hydrogen storage applications

Hydrogen storage is of great interest to researchers due to its renewable and clean energy properties. Therefore, there is a continuous search for innovative compounds that can provide hydrogen storage conditions. A first-principles study of X2MgH4 (X = K, Rb, and Cs) compounds has been carried out to investigate their physical properties using the Generalized Gradient Approximation (GGA) with the SIESTA package. The elastic, optical, structural, electronic, phonon, and thermoelectric properties of X2MgH4 (X = K, Rb, and Cs) compounds with tetragonal crystal structures have been investigated. The electronic properties of X2MgH4 (X = K, Rb, and Cs) compounds are insulators. All three compounds fulfil the Born stability condition. The gravimetric hydrogen storage capacities of X2MgH4 (X = K, Rb, and Cs) compounds are 3.8, 2.02, and 1.37 wt%, respectively. X2MgH4 (X = K, Rb, and Cs) crystals are dynamically stable. The thermoelectric and optical properties of X2MgH4 (X = K, Rb, and Cs) compounds are also discussed.

A Mini-Review on Marine Bioactive Compounds as a Source of Antiviral Drug Lead

Abstract: Currently, pathogens or some microorganisms that are dangerous to human society cause plenty of diseases. All these diseases are spreading because of the limited available treatment options. Some pathogens species are very dangerous to humankind, particularly viral pathogens. These viral pathogens (viruses) have become resistant and immune to many of the medications, thus requiring more and more drug molecules or treatments to be discovered. Many new drugs or treatments are discovered and under clinical trials, and many are being tested. Presently, researchers are in continuous search of newer drugs or molecules using synthetic chemistry or exploring natural resources. However, synthesizing a drug molecule is time-consuming and requires more workforce and much more costly equipment. To tackle this challenge, the use of computational approaches provided complementary information that may also help in the discovery of new molecules. Recently, the fragment molecular orbit based density-functional tight-binding method (DFTB) of drug discovery of drug-like lead is rapid and accurate as compared to conventional computational approaches. Natural resources from land and water can become a choice as an alternative option to discover new entities. The marine environment provides us with a broad spectrum of chemically diverse antiviral compounds isolated from many marine organisms such as bacteria, fungi, sponges, algae, etc. Now, the natural marine molecule as an antiviral agent harrows a new way to modern medicine.

THE DEGREE OF AWARENESS OF THE POPULATION
 OF THE KARAGANDA REGION
 ON THE INCIDENCE AND PREVENTION
 OF COLORECTAL CANCER:
 A LITERATURE REVIEW

Relevance: Colorectal cancer (CRC) is the leading cancer in yearly morbidity and mortality. WHO forecasts that 2030 CRC incidence will
 exceed 2.2 million cases yearly, and mortality will increase to 1.1 million yearly. More than 3,000 new cases of colorectal cancer are detected
 annually in Kazakhstan. In disease control, it is necessary to develop preventive measures as much as possible. Preventive measures play a crucial
 role in reducing mortality from this disease. One of the most critical issues is the lack of public awareness about the disease.
 The study analyzes the global experience in preventing colorectal cancer to develop measures to raise public awareness.
 Methods: A continuous search was performed in the PubMed, CrossRe, Scopus, and Cochrane databases for 2013-2023 for the keywords
 “colorectal cancer,” “risk factors,” “public awareness,” “medical literacy,” “morbidity,” and “prevention.” In total, more than 75 scientific
 articles and 500 abstracts were reviewed.
 Results: The problem is aggravated by the fact that among patients with an oncological diagnosis, patients with colorectal cancer, or patients
 with a confirmed diagnosis of the disease, there is insufficient information about this disease, and they neglect preventive measures. Firstly,
 we insist that the population is not fully aware of the responsibility for their health (this is influenced by a false sense of shame and insufficient
 awareness of the disease), and secondly, primary prevention is essential. Accordingly, it is necessary to increase the effectiveness of screening
 programs, improve awareness, and organize full-fledged assistance from the state in disease control.
 Conclusion: Colorectal cancer is an urgent disease that occupies an essential place in Kazakhstan’s list of oncological diseases. Due to the
 increased awareness of the population about this disease and the correct solution to prevention issues, it will be possible to reduce the incidence
 among patients. In this regard, it is necessary to widely disseminate information about the disease among the population and increase patients’
 responsibility for their health.

A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery

Material properties share an intrinsic relationship with their structural attributes, making inverse design approaches crucial for discovering new materials with desired functionalities. Reinforcement Learning (RL) approaches are emerging as powerful inverse design tools, often functioning in discrete action spaces. This constrains their application in materials design problems, which involve continuous search spaces. Here, we introduce an RL-based framework CASTING (Continuous Action Space Tree Search for inverse design), that employs a decision tree-based Monte Carlo Tree Search (MCTS) algorithm with continuous space adaptation through modified policies and sampling. Using representative examples like Silver (Ag) for metals, Carbon (C) for covalent systems, and multicomponent systems such as graphane, boron nitride, and complex correlated oxides, we showcase its accuracy, convergence speed, and scalability in materials discovery and design. Furthermore, with the inverse design of super-hard Carbon phases, we demonstrate CASTING’s utility in discovering metastable phases tailored to user-defined target properties and preferences.

An Improved Binary Quadratic Interpolation Optimization for 0-1 Knapsack Problems

This paper presents a new binary optimization technique for solving the 0–1 knapsack problem. This algorithm is based on converting the continuous search space of the recently proposed quadratic interpolation optimization (QIO) into discrete search space using various V-shaped and S-shaped transfer functions; this algorithm is abbreviated as BQIO. To further improve its performance, it is effectively integrated with a uniform crossover operator and a swap operator to explore the discrete binary search space more effectively. This improved variant is called BIQIO. Both BQIO and BIQIO are assessed using 20 well-known knapsack instances and compared to four recently published metaheuristic algorithms to reveal their effectiveness. The comparison among algorithms is based on three performance metrics: the mean fitness value, Friedman mean rank and computational cost. The first two metrics are used to observe the accuracy of the results, while the last metric is employed to show the efficiency of each algorithm. The results of this comparison reveal the superiority of BIQIO over the classical BQIO and four rival optimizers.

Phenol Glucosides as Potential Inhibitors of SGLT1 for Enhanced Diabetes Mellitus Treatment in Patients with Declining Renal Function

Diabetes mellitus poses a significant global health challenge, necessitating the continual search for innovative therapeutic strategies. While sodium-glucose cotransporter 2 (SGLT2) inhibitors have shown promise in diabetes management, their efficacy diminishes in patients with declining renal function. This study aims to evaluate the potential of phenol glucosides as inhibitors for the sodium-glucose transport protein 1 (SGLT1), a key player in glucose uptake. We identified phlorizin as a representative phenol glucoside for experimental validation. The SGLT1 protein structure (PDB ID 7wmv) was analyzed through Ramachandran plot, ERRAT score, and ProSAweb Z-score, confirming its high-quality 3D conformation. A ligand-based virtual screening approach yielded 400 compounds that matched well with our pharmacophore models, including 10 compounds from virtual libraries. Notably, two compounds stood out for their high matching scores. Molecular docking simulations revealed strong binding affinities with SGLT1, especially for the compound CHEMBL2303983 with a binding energy of -11.2 kcal/mol. ADMET analysis was conducted to evaluate the drug-likeness & safety profile of such high-affinity compounds. The compounds exhibited variable water solubility and moderate lipophilicity but were generally compliant with most drug-likeness rules. However, certain challenges such as low GI absorption and inability to cross the blood-brain barrier were identified. No PAINS or Brenk alerts were raised, suggesting a low likelihood of assay interference or toxicity. In conclusion, our in-silico approach has identified promising candidates among phenol glucosides for inhibition of SGLT1, albeit with challenges in solubility and pharmacokinetics that require further optimization. The study opens new avenues for the synthesis and experimental verification of novel SGLT1 inhibitors.

ATL-DAS: Automatic Topology Learning for Differentiable Architecture Search

Differentiable architecture search (DARTS) provides a fast solution to Neural Architecture Search (NAS) by using gradient descent over a continuous search space. Despite its high search speed, DARTS suffers from several problems such as ambiguous topology selection, operation co-adaptation, incomplete NAS pipeline, and large memory consumption. To address these problems, we first introduce topology parameters into the search space to explicitly model the network topology, which ensures the searched network architecture is well-defined. Next, we propose two sampling strategies to sample independent child networks for training and evaluation, which solve the co-adaptation problem while making the NAS pipeline complete. Finally, we use hard pruning to avoid invalid computations, which greatly reduces memory consumption. The proposed Automatic Topology Learning for Differentiable Architecture Search (ATL-DAS) algorithm performs favorably against the state-of-the-art approaches on CIFAR10 and CIFAR100 with error rates of 2.49% and 16.8%, respectively. Moreover, the architectures searched perform well across various visual tasks, including ImageNet classification, COCO object detection, and Composition-1K image matting, highlighting the potential of ATL-DAS for real-world applications.

Role of transfer functions in PSO to select diagnostic attributes for chronic disease prediction: An experimental study

Particle Swarm Optimization (PSO) is a classic and popularly used meta-heuristic algorithm in many real-life optimization problems due to its less computational complexity and simplicity. The binary version of PSO, known as BPSO, is used to solve binary optimization problems, such as feature selection. Like other meta-heuristic optimization techniques designed on the continuous search space, PSO uses the transfer functions (TFs) to map the candidate solutions to the discrete search space in BPSO, and these TFs play a vital role to get the desired results. Over the years, many forms of TFs have been introduced in the literature, most of which fall under one of the five families - Linear, S-shaped, V-shaped, U-shaped, and Time-varying Mirrored S-shaped TFs. The goal of this study is to determine an appropriate setup constituting a TF and a classifier for feature selection from different types of clinical data. In this study, the impacts of the five TF families have been investigated, considering one from each family for the selection of attributes/features, while predicting disease using diagnosis or medical reports. The classification tasks are carried out using four standard classifiers: Support Vector Machine, Decision Tree, K-Nearest Neighbors, and Gaussian Naive Bayes. For experimental purposes, we have used four publicly available datasets namely, the UCI Heart Disease dataset, Wisconsin Breast Cancer dataset, UCI Chronic Kidney Disease dataset, and PIMA Indians Diabetes dataset. After an exhaustive set of experiments, we have obtained 96.72%, 99.82%, 100.00%, and 84.41% disease prediction scores in the best case for Heart disease, Breast Cancer, Chronic Kidney disease, and Diabetes, respectively. The obtained results are comparable to several state-of-the-art methods considered here for comparison. The present study helps in selecting a suitable BPSO setup (i.e., a TF and a classifier) to select important diagnostic attributes useful to design a computer-aided decision support system for the said diseases.

A Lévy Flight-Inspired Random Walk Algorithm for Continuous Fitness Landscape Analysis

Heuristic algorithms are effective methods for solving complex optimization problems. The optimal algorithm selection for a specific optimization problem is a challenging task. Fitness landscape analysis (FLA) is used to understand the optimization problem's characteristics and help select the optimal algorithm. A random walk algorithm is an essential technique for FLA in continuous search space. However, most currently proposed random walk algorithms suffer from unbalanced sampling points. This article proposes a Lévy flight-based random walk (LRW) algorithm to address this problem. The Lévy flight is used to generate the proposed random walk algorithm's variable step size and direction. Some tests show that the proposed LRW algorithm performs better in the uniformity of sampling points. Besides, the authors analyze the fitness landscape of the CEC2017 benchmark functions using the proposed LRW algorithm. The experimental results indicate that the proposed LRW algorithm can better obtain the structural features of the landscape and has better stability than several other RW algorithms.

Sustainable Modern Environment Responses on Bawean Architecture

The continuous search for sustainable architectural practices in the vernacular model paves the way for alternative approaches to modern diversity. In particular, the growing demand for habitation leads to loss of local identity architecture. This phenomenon or dilemma of “cultural aridity” occurred in many areas of Indonesia with settlements linked to history. The purpose of this article is to explore Bawean architectural identity located in the north-java island. With a focus on an examination of the original design of Bawean architecture into modern development design. Through, mapping and inventory of identity, assess the perspectives of the occupants of houses and those who are involved in the construction to get a better understanding of public knowledge, experience, and responses. The results show that the concept of Bawean architecture, mainly granaries is applied to modern architectural design with the advantage of wind flow to maintain storage humidity. However, a better understanding of this adaptation needs more investigation with the future study of an energy simulation analysis to develop a strategy for energy-efficient buildings. This article contributes to the emerging literature on developing granary design toward sustainably minimizing the environmental impacts of household electricity utilization.

Intersecting Pathways: Examining Hildegard Peplau's and Rosemarie Parse's Nursing Theories through a Comparative Lens

Background: Nursing theories are organized bodies of knowledge providing a way to define nursing as a unique discipline that is separate from other disciplines. As a profession, nursing is committed to recognizing its own unparalleled body of knowledge vital to nursing practice and science. Nursing is a science based on the theory of what nursing is, what nurses do, and why. Aim: This paper aims to elucidate the practical application of Hildegard Peplau's and Rosemarie Parse's nursing theories, individually and in synthesis, in modern nursing practice. Key points: These include a) Hildegard Peplau's Theory of Interpersonal Relations emphasizes the nurse-patient relationship, therapeutic communication, and the continuous search for improvement in patients, even those facing mental health challenges. b) Rosemarie Parse's Theory of Human Becoming underscores the uniqueness of each patient's lived experiences, the significance of "meaning" in health experiences, "rhythmicity" in patterns, and the potential for "transcendence" and growth. c) Integrating Peplau's and Parse's theories promotes holistic patient-centered care, compassionate and empathetic nursing, enhanced communication skills, patient autonomy, cultural competence, continuity of care, and a deep respect for human dignity. d) By embracing both theories, nurses can provide comprehensive, compassionate, and patient-centered care that respects each patient's individuality and capacity for growth. Conclusion: The synthesis of Hildegard Peplau's and Rosemarie Parse's nursing theories offers nurses a comprehensive framework for modern nursing practice. It guides nurses in providing high-quality, patient-centered care that preserves human dignity and recognizes the uniqueness of each patient. Drawing from multiple theoretical perspectives enhances nursing practice and ensures the well-being of patients in today's evolving healthcare landscape.

TA-DARTS: Temperature Annealing of Discrete Operator Distribution for Effective Differential Architecture Search

In the realm of machine learning, the optimization of hyperparameters and the design of neural architectures entail laborious and time-intensive endeavors. To address these challenges, considerable research effort has been directed towards Automated Machine Learning (AutoML), with a focus on enhancing these inherent inefficiencies. A pivotal facet of this pursuit is Neural Architecture Search (NAS), a domain dedicated to the automated formulation of neural network architectures. Given the pronounced impact of network architecture on neural network performance, NAS techniques strive to identify architectures that can manifest optimal performance outcomes. A prominent algorithm in this area is Differentiable Architecture Search (DARTS), which transforms discrete search spaces into continuous counterparts using gradient-based methodologies, thereby surpassing prior NAS methodologies. Notwithstanding DARTS’ achievements, a discrepancy between discrete and continuously encoded architectures persists. To ameliorate this disparity, we propose TA-DARTS in this study—a temperature annealing technique applied to the Softmax function, utilized for encoding the continuous search space. By leveraging temperature values, architectural weights are judiciously adjusted to alleviate biases in the search process or to align resulting architectures more closely with discrete values. Our findings exhibit advancements over the original DARTS methodology, evidenced by a 0.07%p enhancement in validation accuracy and a 0.16%p improvement in test accuracy on the CIFAR-100 dataset. Through systematic experimentation on benchmark datasets, we establish the superiority of TA-DARTS over the original mixed operator, thereby underscoring its efficacy in automating neural architecture design.