Conventional Means Research Articles

Analyzing The Influence of Social Media Posts on Government Policy Adoption in Papua City

In recent years, the use of social media has been very high among millennials and the middle class in Papua. This represents a new communication channel, especially in underdeveloped areas, where the political relations between citizens and the government are mostly conducted through conventional means such as demonstrations, dialogues, public hearings, submitting open letters to the government, putting up banners, and open complaint boxes. This article aims to analyze the role of social media in the process of public policy-making in the Province of Papua. The use of social media is very high among the millennial generation in Papua to respond to local government policies. However, its influence on policy change is still limited. Only traffic management policies have changed in response to criticisms on social media. This descriptive qualitative research was conducted through interviews and document analysis. The results show that social media plays a role in voicing public aspirations but has not yet influenced policy decision-making. There is a need for political will from the Papua Local Government to integrate citizens' aspirations into public policies. Further research could formulate a model of the relationship between citizens and the government through social media for more participatory public policies.

Multimode Rayleigh wave dispersion spectrum inversion using Wasserstein distance coupled with Bayesian optimization

We develop a new automatic framework for the nondestructive multichannel analysis of surface waves that combines multimode dispersion spectrum matching and a finite-element method (FEM)-based inversion to enhance the accuracy of subsurface profiling in site investigation activities. This framework eliminates the need for manual identification of the Rayleigh wave energy component and multimode assignment, reducing dependence on operator experience and judgment. The dispersion spectrum is generated through an FEM model that simulates 2D seismic wave propagation, taking into account the actual acquisition layout and lateral variations in the subsurface. We introduce the Wasserstein distance (WD) for evaluating the difference between the observed and simulated spectra and incorporate Bayesian optimization for efficiently inverting S-wave velocity profiles. The effectiveness of our framework is demonstrated through synthetic data examples, and the superiority of the WD-based objective function is illustrated by comparing it with the conventional mean square error-based objective function. Subsequently, we conduct a field test on a reclaimed landfill to validate our framework. This test confirms the ability of the framework to retrieve multimode Rayleigh waves and demonstrates its effectiveness in providing high-resolution S-wave profiles of the shallow subsurface.

Conventional vs Augmented Reality-Guided Lateral Calcaneal Lengthening Simulated in a Foot Bone Model.

Acquired adult flatfoot deformity (AAFD) results in a loss of the medial longitudinal arch of the foot and dysfunction of the posteromedial soft tissues. Hintermann osteotomy (H-O) is often used to treat stage II AAFD. The procedure is challenging because of variations in the subtalar facets and limited intraoperative visibility. We aimed to assess the impact of augmented reality (AR) guidance on surgical accuracy and the facet violation rate. Sixty AR-guided and 60 conventional osteotomies were performed on foot bone models. For AR osteotomies, the ideal osteotomy plane was uploaded to a Microsoft HoloLens 1 headset and carried out in strict accordance with the superimposed holographic plane. The conventional osteotomies were performed relying solely on the anatomy of the calcaneal lateral column. The rate and severity of facet joint violation was measured, as well as accuracy of entry and exit points. The results were compared across AR-guided and conventional osteotomies, and between experienced and inexperienced surgeons. Experienced surgeons showed significantly greater accuracy for the osteotomy entry point using AR, with the mean deviation of 1.6 ± 0.9 mm (95% CI 1.26, 1.93) compared to 2.3 ± 1.3 mm (95% CI 1.87, 2.79) in the conventional method (P = .035). The inexperienced had improved accuracy, although not statistically significant (P = .064), with the mean deviation of 2.0 ± 1.5 mm (95% CI 1.47, 2.55) using AR compared with 2.7 ± 1.6 mm (95% CI 2.18, 3.32) in the conventional method. AR helped the experienced surgeons avoid full violation of the posterior facet (P = .011). Inexperienced surgeons had a higher rate of middle and posterior facet injury with both methods (P = .005 and .021). Application of AR guidance during H-O was associated with improved accuracy for experienced surgeons, demonstrated by a better accuracy of the osteotomy entry point. More crucially, AR guidance prevented full violation of the posterior facet in the experienced group. Further research is needed to address limitations and test this technology on cadaver feet. Ultimately, the use of AR in surgery has the potential to improve patient and surgeon safety while minimizing radiation exposure. Subtalar facet injury during lateral column lengthening osteotomy represents a real problem in clinical orthopaedic practice. Because of limited intraoperative visibility and variable anatomy, it is hard to resolve this issue with conventional means. This study suggests the potential of augmented reality to improve the osteotomy accuracy.

Reducing the carbon footprint of the textile sector: an overview of impacts and solutions

The clothing, footwear, and household textiles sectors play a significant role, providing employment opportunities on a global scale. However, they are also associated with a considerable consumption of natural resources, leading to high levels of water pollution and emissions of greenhouse gases, contributing to climate change. The carbon footprint (CF) of textiles depends generally on fabric types and production processes. Natural fibers such as cotton, wool, and silk, generally have a lower CF when compared to synthetic fabrics such as polyester and nylon, requiring more energy and chemicals during production. In addition, fabrics manufactured through eco-friendly methods, such as closed-loop systems and sustainable production processes, have a significantly lower CF than those produced using conventional means. Accordingly, there is a perceived need for comprehensive studies that investigate the environmental and climate implications of the textile sector. Considering these concerns, a study was undertaken on the topic, encompassing a literature review and data collection so as to present an overview of the environmental impacts and CF associated with the textile sector. The results from the research show that the resource consumption associated with the textile sector, particularly its CF, demands urgent action in order to reduce its impacts. Also, actionable measures are needed so as to reduce the CF of the textile industry. These are described in the paper, along with the obstacles that need to be overcome so as not only to reduce the CF of this sector, but also to pursue the objectives outlined in the sustainable development goals.

Quantile Optimization via Multiple-Timescale Local Search for Black-Box Functions

Black-Box Quantile Optimization via Finite-Difference-Based Gradient Approximation Risk management necessitates consideration of metrics such as quantiles to supplement conventional mean performance measures. In “Quantile Optimization via Multiple-Timescale Local Search for Black-Box Functions,” J. Hu, M. Song, and M. C. Fu consider the problem where the goal is to optimize the quantile of a black-box output. They introduce two new iterative multitimescale stochastic approximation algorithms utilizing finite-difference-based gradient estimators. The first algorithm requires 2d + 1 samples of the black-box function per iteration, where d is the number of decision variables. The second employs a simultaneous-perturbation-based gradient estimator that uses only three samples per iteration, irrespective of the number of decision variables. The authors prove strong local convergence for both algorithms and analyze their finite-time convergence rates through a novel fixed-point argument. These algorithms perform well across a varied set of benchmark problems.

Effectiveness of Bottle Size Variation on the Growth of Dendrobium Striaenopsis Orchid Plantlets

The production of Dendrobium striaenopsis orchid cultivation in Indonesia has many obstacles including limited seed provision, low seed quality and cultivation techniques that have not been done well, while orchid enthusiasts always increase every year. Propagation of orchid plants by conventional means requires a long time to obtain a large number of plant saplings, therefore alternative cultivation using tissue culture techniques is needed. In vitro tissue culture techniques are widely used as a fast and efficient way to produce D. striaenopsis orchid plants, but not infrequently there are factors that affect the production of orchids, one of which is bottle size. The purpose of this study is to determine the effect of the effectiveness of bottle size variations on the growth of D. striaenopsis plantlets after comparing the difference in bottle volume and knowing the optimum size of bottles used for D. striaenopsis plantlet growth. The study was conducted from May to August 2023 in the Laboratory CV. Candi Orchid, Semarang City. The method used was the observation and experimental method after which it was continued with the One Way Anova test and further test T. In this study using Vacin and Went medium with a size of 60 ml by providing treatment variations in bottle sizes of 250 ml, 500 ml and 750 ml with 4 repeats. The result of this study is that a 750 ml bottle used in the tissue culture technique of D. striaenopsis Orchid is effective in use even though the growth of plantlets does not occur a significant difference, this is due to environmental factors, namely light intensity and duration of irradiation

Algorithm-Based Data Generation (ADG) Engine for Dual-Mode User Behavioral Data Analytics

The increasing significance of data analytics in modern information analysis is underpinned by vast amounts of user data. However, it is only feasible to amass sufficient data for various tasks in specific data-gathering contexts that either have limited security information or are associated with older applications. There are numerous scenarios where a domain is too new, too specialized, too secure, or data are too sparsely available to adequately support data analytics endeavors. In such cases, synthetic data generation becomes necessary to facilitate further analysis. To address this challenge, we have developed an Algorithm-based Data Generation (ADG) Engine that enables data generation without the need for initial data, relying instead on user behavior patterns, including both normal and abnormal behavior. The ADG Engine uses a structured database system to keep track of users across different types of activity. It then uses all of this information to make the generated data as real as possible. Our efforts are particularly focused on data analytics, achieved by generating abnormalities within the data and allowing users to customize the generation of normal and abnormal data ratios. In situations where obtaining additional data through conventional means would be impractical or impossible, especially in the case of specific characteristics like anomaly percentages, algorithmically generated datasets provide a viable alternative. In this paper, we introduce the ADG Engine, which can create coherent datasets for multiple users engaged in different activities and across various platforms, entirely from scratch. The ADG Engine incorporates normal and abnormal ratios within each data platform through the application of core algorithms for time-based and numeric-based anomaly generation. The resulting abnormal percentage is compared against the expected values and ranges from 0.13 to 0.17 abnormal data instances in each column. Along with the normal/abnormal ratio, the results strongly suggest that the ADG Engine has successfully completed its primary task.

Cybercrimes: An Emerging Category of Offenses within the Frame of the International Criminal Court Jurisdiction

In our interconnected society, crime persists, demanding joint efforts by national and international authorities to detect, prevent, and prosecute criminal activities. Jurisprudential evolution mandates lawmakers to possess a comprehensive legal vision, adapting laws to changing social contexts and emerging criminal methods, especially in technology, including computer technology and Artificial Intelligence (AI). This article comments on the escalating vulnerability of sovereign states and their economies to cyber-attacks. The radical evolution of computer systems has led to new modes of aggression, targeting not only traditional legal assets but also individuals familiar with advanced technology. The emergence of "cyberwarfare" prompts inquiries into potential categorizations within international legal frameworks. Recent global conflicts highlight the potential classification of cyber-attacks on critical infrastructure as war crimes or acts of aggression, urging the International Criminal Court (ICC) to consider incorporating cybercrimes into its core interests. While normative references may lack in existing conventions, the Martens Clause emphasizes treating attacks using technology as equivalent to conventional means. Article 51 of the United Nations Charter implies that cyber weapons could be deemed equivalent to conventional weapons under international law. The article stresses the importance of education and advanced training for legal personnel skilled in identifying cybercrime perpetrators, challenging the ICC to recruit or train individuals with the necessary legal and technical expertise for effective cybersecurity responses. The article briefly explores challenges in conceptualizing and categorizing cybercrimes within existing legal frameworks. The intersection of law and technology necessitates harmonious collaboration between legal and technical experts, acknowledging the intricate web of cyberspace and the implications of cyber threats on global stability and security. In conclusion, the article advocates a fundamental shift in the approach to justice, recognizing the ICC's imperative evolution in addressing cybercrimes. Integrating cybercrimes into the ICC's purview aligns with international law principles, emphasizing the equivalence of cyber weapons to conventional arms. Collaboration between legal and technical experts is essential in navigating the complexities of cybercrimes, ensuring accountability, and upholding justice in the digital age. The article concludes by highlighting the proactive role of the ICC in shaping the future of global justice amid emerging cyber threats.

Custom-form iron trifluoride Li-batteries using material extrusion and electrolyte exchanged ionogels

Custom-form factor batteries fabricated in non-conventional shapes can maximize the overall energy density of the systems they power, particularly when used in conjunction with energy dense materials (e.g., Li metal anodes and conversion cathodes). Additive manufacturing (AM), and specifically material extrusion (ME), have been shown as effective methods for producing custom-form cell components, particularly electrodes. However, the AM of several promising energy dense materials (conversion electrodes such as iron trifluoride) have yet to be demonstrated or optimized. Furthermore, the integration of multiple AM produced cell components, such as electrodes and separators, along with a custom package remains largely unexplored. In this work, iron trifluoride (FeF3) and ionogel (IG) separators are conformally printed using ME onto non-planar surfaces to enable the fabrication of custom-form Li-FeF3 batteries. To demonstrate printing on non-planar surfaces, cathodes and separators were deposited onto cylindrical rods using a 5-axis ME printer. ME printed FeF3 was shown to have performance commensurate with FeF3 cast using conventional means, both in coin cell and cylindrical rod formats, with capacities exceeding 700 mAh/g on the first cycle and ranging between 600 and 400 mAh/g over the next 50 cycles. Additionally, a ME process for printing polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) based IGs directly onto FeF3 is developed and enabled using an electrolyte exchange process. In coin cells, this process is shown to produce cells with similar capacity to cells built with Celgard separators out to 50 cycles, with the exception that cycling instabilities are observed during cycles 8–20. When using printed and exchanged IGs in a custom cylindrical cell package, 6 stable high-capacity cycles are achieved. Overall, this work demonstrates approaches for producing high-energy-density Li-FeF3 cells in coin and cylindrical rod formats, which are translatable to customized, arbitrary geometries compatible with ME printing and electrolyte exchange.

Review of PEDELECS as an alternative to conventional means of urban transportation

Sustainable transportation solutions are more crucial than ever because of the pressing need to increase resource efficiency while lowering greenhouse gas emissions. The most recent advancements in the e-cycle sector have made a significant contribution to this goal and have attracted the interest of numerous businesses that offer mobility services. This paper discusses the main topics surrounding pedal electric cycles (PEDELECS) with an accent on a niche application, namely e-cargo cycles. The paper highlights not just the defining characteristics of these categories, but also other relevant aspects such as barriers to market penetration, general legislation, benefits for specific applications, as well as the significance of incentives, local infrastructure, and urban policies. Based on the available literature, it can be concluded that PEDELECS have a considerable potential to contribute to sustainability goals in urban areas due to their numerous benefits (functionality without emissions, less space occupied on roads, ability to access destinations with increased precision, ability to travel in car-restricted areas, lower costs compared to conventional vehicles, added health benefits to the users, versatility etc.). However, there are also significant challenges and barriers that must be overcome before they can see widespread adoption.

An innovative environmental regulation tool for regional air pollution based on DEA-RFR

Environmental regulation tools are one of the conventional means for pollution control in various countries. For large-scale urbanization regions, reasonable pre-allocation of pollutant emission amount for each area is an effective regulation to improve air quality. Treating pollutant emission quota as a resource element, a comprehensive input-output model has been established based on Data Envelopment Analysis (DEA) method, to evaluate the rationality of pollutant emission allocation and provide adjustment scheme, thus developing an environmental regulation tool. The index system includes factors of economy, environment, energy consumption, demographic and land-use as input indicators, regional GDP and environmental air quality index as output indicators. The regulation tool is applied to the current air pollutant emission management in Henan Province, China. The results show that 7 cities need to further adjust the allocation scheme, among which, Anyang, Xinxiang, Nanyang and Shangqiu are suggested to reduce the emission allocation quotas; Puyang and Zhumadian are suggested to increase the emission allocation quotas; Pingdingshan shall seek optimization paths through collaborative improvement. Further, to verify the effectiveness of the tool, by joint using Random Forest Regression (RFR), a DEA efficiency reassessment is conducted on the obtained new allocation scheme of Nanyang City. The results show that the efficiency of the new allocation scheme has reached optimal. This study provides a practical and effective regulation tool for regional management of pollutant emission, to balance economic growth and environmental protection.

Tattva, vrata, caryā: On the Relationship of View and Practice in the First Chapter of Padmavajra’s Guhyasiddhi

The religious worldview of the mantranaya (esoteric Mahāyāna or Vajrayāna) can arguably be seen as rooted in the perspective that reality (tattva) is to be self-experienced (svasamvedya) through contemplative practices, serving as both their means (upāya) and expression (caryā). The tantric path-model of Padmavajra’s Guhyasiddhi, an exegetical text in the Guhyasamāja tradition, supposedly enables individuals to rapidly realize reality, a state also referred to as mahāmudrā or other, within a single lifetime. This path-model describes a transformation leading to the revelation of ultimate realization leaving behind conventional means. These two levels correspond to two stages, the stage of arising (utpattikrama), serving as the foundation for the stage of the arisen (utpannakrama). While the first stage is like a supporting framework giving rise to the correct view, in the second stage, the practitioner cultivates the view that has arisen. The practices of the latter stage eventually become inseparable from the view itself, meaning they are practical expressions of the view exemplified in doctrines like unmattavrata and other forms of observances integral to the mahāmudrā doctrine. Thus, contemplative practices and the established worldview mutually inform each other in a reciprocal relationship. Simultaneously, this system of practice and view continues to influence and shape religious practices and rituals as they are transmitted, e.g., through teacher–disciple lineages (guruparaṃparā). In this paper, I will explore this relationship through the critical edition and annotated translation of Guhyasiddhi’s first chapter by Padmavajra (ca. late 8th and early 9th century), in which a clear exposition of the relationship in question is presented. My analysis of it, thus connecting the work to more general Buddhist concepts, follows a two-level framework, that is, the well-known two-fold system of conventional/implicit (a) and definitive/explicit (b), which can be seen as equivalent to utpatti- (a) and utpannakrama (b). The efficiency of promoted practices accords with the practitioner’s correct assessment of tattva which, following Padmavajra, is the basis for engagement in tantric practices per se. The first part provides the analysis, given in 1.1–1.5, of Padmavajra‘s system and is based on the second part, the annotated translation (2.1) and critical edition (2.2) of Padma-vajra’s Guhyasiddhi chapter one.

INTERCONNECTION RESULTANT EFFECT OF TWO INSTRUCTIONAL STRATEGIES, MENTAL ABILITY AND GENDER, ON LEARNERS’ ACHIEVEMENT IN ABSTRACT CONCEPTS IN BIOLOGY

This study looked at how students' success in grasping abstract concepts in biology was affected by cognitive capacity, Gender, and two different teaching philosophies (project and Inquiry)—a quasi-experimental paradigm known as the pretest-posttest control group design was employed in the study. 120 SSII Biology students were split into treatment and control groups. The students came from six coeducational schools in two Local Government Areas in Kwara State. The tests were the Biology Students Mental Ability Test (r=0.87), the test measuring understanding of abstract concepts in biology (r=0.86), and instructional manuals on inquiry and project techniques. At the 0.05 significance level, three research questions and three hypotheses were examined. The collected data were analyzed using a covariance study, which found that there was a significant 3-way interconnection (interaction effect) between treatment, mental capacity, and gender and learners' accomplishment in abstract ideas in biology (F2,107) = 5.757, P> 0.05). Low mental ability female students (x ̅=24.00) had a lower mean score in project strategy than low mental ability male students ((x) ̅=24.43). In the inquiry strategy, low mental ability male students' mean score (x ̅ = 22.33) was superior to that of low mental ability female students (x ̅ = 20.75); in contrast, the conventional Strategy's mean score (x ̅ = 14.33) for low mental ability male students was superior to that of high mental ability female students (x ̅ = 13.47). The study's conclusions led to the recommendation that project and inquiry methodologies be used to raise students' mental ability and achievement in abstract concepts in biology, among others.

A multi-objective Grey Wolf–Cuckoo Search algorithm applied to spatial truss design optimization

A novel hybrid algorithm called Multi-Objective Hybrid Grey Wolf Cuckoo Search (MOGWOCS) is developed for spatial truss designs in this study. A new simple yet efficient mechanism to select the best candidates is proposed. Furthermore, harmonic averaging is employed to be a replacement for conventional arithmetic mean for higher effectiveness. Additionally, the Lévy flight in Cuckoo Search (CS) is utilized to increase efficiency in early searching and also reduce local entrapment possibility. For verification purposes, MOGWOCS is first performed on some mathematical functions and 11 CEC2020 mechanical problems. It is then examined on four large-scale truss design problems, in two of which multi-objective optimization is studied for the first time. To demonstrate the superiority of the proposed approach, five up-to-date algorithms, and various indicators are included for validation. It is found that MOGWOCS is able to produce solutions with higher optimality in terms of diversity and accuracy.

LanTERN: A Fluorescent Sensor That Specifically Responds to Lanthanides.

Lanthanides, a series of 15 f-block elements, are crucial in modern technology, and their purification by conventional chemical means comes at a significant environmental cost. Synthetic biology offers promising solutions. However, progress in developing synthetic biology approaches is bottlenecked because it is challenging to measure lanthanide binding with current biochemical tools. Here we introduce LanTERN, a lanthanide-responsive fluorescent protein. LanTERN was designed based on GCaMP, a genetically encoded calcium indicator that couples the ion binding of four EF hand motifs to increased GFP fluorescence. We engineered eight mutations across the parent construct's four EF hand motifs to switch specificity from calcium to lanthanides. The resulting protein, LanTERN, directly converts the binding of 10 measured lanthanides to 14-fold or greater increased fluorescence. LanTERN development opens new avenues for creating improved lanthanide-binding proteins and biosensing systems.

Targeting Compact and Ordered Emitters by Supramolecular Dynamic Interactions for High-performance Organic Ambient Phosphorescence.

Purely organic room-temperature phosphorescence (RTP) materials have received intense attention due to their fascinating optical properties and advanced optoelectronic applications. The promotion of intersystem crossing (ISC) and minimalization of nonradiative dissipation under ambient conditions are key prerequisites for realizing high-performance organic RTP; However, the ISC process is generally inefficient for organic fluorogens and the populated triplet excitons are always too susceptible to be well stabilized by conventional means. Particularly, organizing organic fluorophores into compact and ordered entities by supramolecular dynamic interactions has proven to be a newly-emerged strategy to boost the ISC process greatly and suppress the non-radiative relaxations immensely, facilitating the population and stabilization of triplet excitons to access high-performance organic RTP. Consequently, well-defined organic emitters enable robust RTP emission even in the solution state, thus greatly extending the applications. Here, this review is focused on a timely and brief introduction to recent progress in tailoring ordered high-performance RTP emitters by supramolecular dynamic interactions. Their typical preparation strategies, optoelectronic properties, and applications are thoroughly summarized. In the summary section, key challenges and perspectives of this field are highlighted to suggest potential directions for future study.

Stage 2 Registered Report: Anomalous perception in a Ganzfeld condition - A meta-analysis of more than 40 years investigation.

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means). The technique used for eliciting an effect is the Ganzfeld condition (a form of sensory homogenization that eliminates distracting peripheral noise). The database consists of studies published between January 1974 and December 2020 inclusive. The overall effect size estimated both with a frequentist and a Bayesian random-effect model, were in close agreement yielding an effect size of approximately .08 (.04 -.12). This result passed four publication bias tests and seems not contaminated by questionable research practices. Trend analysis carried out with a cumulative meta-analysis and a meta-regression model with year of publication as a covariate, did not indicate sign of decline of this effect size. The moderators' analyses show that the selected participants' effect size was almost three-times that obtained by non-selected participants and that tasks that simulate telepathic communication show a two-fold effect size for tasks requiring the participants to guess a target. The Stage 1 Registered Report can be accessed here: https://doi.org/10.12688/f1000research.24868.3.

Groups of Non-Conventional Means Referring to Time in Literary Texts.

The paper is an extensive analysis of literary texts spanning different eras, genres, and languages (including the epic of Gilgamesh, Russian works by A. P. Chekhov, S. Dovlatov, G. G. Demidov, as well as English works by W. Shakespeare, R. P. Warren, W. Faulkner, K. Vonnegut). Through this analysis, the author identified a common poetic feature shared by these works: the utilization of both conventional and non-conventional means to convey the passage of time. The objective of the study was to examine and categorize these non-conventional means according to their respective referential spheres, as well as to elucidate their functions within literary texts. Four main groups were identified, encompassing references to food, human physiology, events or objects in the characters’ living spaces, and processes in nature. The study reveals that non-conventional methods of conveying time in literature are considered archaic; however, they are still widely employed to personalize characters’ perception of time and highlight its psychological aspect. The temporality of these methods is generally reinforced through the use of adverbs, prepositions, or grammatical structures that indicate time. In conclusion, it is established that due to the directional nature of time, its fluidity, and the inevitability of approaching death, authors strive to find ways to capture and define time, giving it tangible forms, and in doing so, the past becomes alive once more.

Asurluların Siyasal Yaşamında Veliahtlık Anlayışı

Assyrians had a monarchical structure in which a king, who came to power through inheritance from a specific family, held absolute authority. At times, this form of governance manifested as a theocratic monarchy, where every political action found its legitimacy on religious grounds. Regarding succession, it is evident that practices were carried out with divine approval and request as guiding principles. The heir in question could be any of the king's natural children, but children born to kings from their second wives or slaves could not ascend to the throne through conventional means. Periodically, kings appointed their children as administrators in various cities, including Babylon, to gain experience in state affairs. The permanence of the designated heir's position and their ascension to the throne upon the king's death were not guaranteed.Additionally, historical records reveal instances where kings changed the crown prince for various reasons. These changes might be attributed to the inadequacy of the crown prince or could result from the influence of queens, as the mother of the chosen crown prince held a significant position within the Assyrian hierarchy. In this study, which is based on cuneiform texts and modern works, the objective is to comprehensively examine the role of the heir apparent in the Assyrian state system, providing insights through periodic examples. Additionally, it seeks to unveil the complex relationships between heirs, kings, queens, and other princes.

Predictive Analysis in Nephrology: Evaluating Machine Learning Models for Chronic Kidney Disease Prediction

Abstract: In the realm of healthcare, early detection and accurate diagnosis are critical for effective treatment, especially for diseases that are often undiagnosed until later stages. This research presents an Automated Classification System focused on Chronic Kidney Disease (CKD), a prevalent condition frequently undetected in its early stages. Leveraging advanced machine learning techniques, the study aims to overcome the traditional reliance on doctors' intuition and experience by providing a data-driven approach for CKD diagnosis. Utilizing a comprehensive dataset, the research explores various data pre-processing methods, including innovative approaches for handling missing values and data integrity, which surpass the conventional mean and mode-based imputation methods prevalent in existing literature. Through exploratory data analysis and the application of diverse machine learning algorithms, the study seeks to identify the most effective model for predicting CKD risk. The findings of this research have significant implications for enhancing clinical decisions, offering a path towards more accessible, efficient, and accurate diagnosis of Chronic Kidney Disease, ultimately contributing to improved patient outcomes and healthcare practices