Traditional Structure Research Articles

IDENTIFIKASI FAKTOR DAN TANTANGAN DI SEKTOR PERUNGGASAN UNTUK MENINGKATKAN KELINCAHAN BISNIS DI AGROINDUSTRI INDONESIA: TINJAUAN LITERATUR

The poultry industry in Indonesia, especially the poultry sector, plays a crucial role in ensuring national food security by providing essential animal protein sources. Therefore, business agility is highly necessary to address fluctuating demand issues that can change unpredictably. Many industries in this sector have faced setbacks due to unforeseen shifts in demand. However, in implementing business agility, numerous factors need consideration, such as traditional organizational structures, bureaucratic processes that impede change, and a corporate culture resistant to transformation. This research aims to identify various challenges faced by companies in achieving business agility through a literature review using Publish or Perish software and manual searches on Google Scholar, resulting in the selection and analysis of 23 relevant journals. The findings from the literature review indicate that effective supply chain management, innovative management leadership, technological automation, adaptability to unforeseen events, investment in employee development, and a deep understanding of customer needs are key factors influencing business agility in the poultry industry in Indonesia.

Research on the Functions and Obstacles of Rural Social Organizations in Rural Governance from the Perspective of Structural Functionalism

Since the reform and opening up, with the transformation of the national governance model, my country's rural social structure has undergone earth-shaking changes. The multi-center governance subject structure has gradually replaced the traditional single governance subject structure and has become the main model for the management of rural social public affairs in my country. As an important subject in governance activities, rural social organizations play a key role in promoting farmers' collective actions and nurturing grassroots democracy. As an important part of the rural social structure, rural social organizations not only have their structure and functions rooted in the transformation of the social structure, but their changes and development also play an important role in the transformation of the social structure. From the perspective of structural functionalism, analyzing the role and function of rural social organizations in the rural social structure has positive theoretical value and practical significance for achieving the effective fit of the structure and function of rural social organizations and building a benign management order in rural society under the background of the rural revitalization strategy.

Integrating 19F Distance Restraints for Accurate Protein Structure Determination by Magic Angle Spinning NMR Spectroscopy.

Traditional protein structure determination by magic angle spinning (MAS) solid-state NMR spectroscopy primarily relies on interatomic distances up to 8 Å, extracted from 13C-, 15N-, and 1H-based dipolar-based correlation experiments. Here, we show that 19F fast (60 kHz) MAS NMR spectroscopy can supply additional, longer distances. Using 4F-Trp,U-13C,15N crystalline Oscillatoria agardhii agglutinin (OAA), we demonstrate that judiciously designed 2D and 3D 19F-based dipolar correlation experiments such as (H)CF, (H)CHF, and FF can yield interatomic distances in the 8-16 Å range. Incorporation of fluorine-based restraints into structure calculation improved the precision of Trp side chain conformations as well as regions in the protein around the fluorine containing residues, with notable improvements observed for residues in proximity to the Trp pairs (W10/W17 and W77/W84) in the carbohydrate-binding loops, which lacked sufficient long-range 13C-13C distance restraints. Our work highlights the use of fluorine and 19F fast MAS NMR spectroscopy as a powerful structural biology tool.

The reality of poetic structure in modern African literature written in Arabic language Analytical descriptive study

This research ends with an explanation of the poetic structure of African poetry written in Arabic. The aim of the study is related to knowing the new poetic structure of African poetry, which can only be achieved after knowing the poetic structure of the Arabs. It is known that ancient Arabic poetic structure proceeds from the initial introductions to the basic purpose of the poem, as mentioned by critics, and we find a multiplicity of themes within it. As for new poetry, it has its own structure which differs. of the traditional structure in terms of linguistic aspect, forms and themes. African literature written in Arabic knew these literary facts, and African poets paid attention in their poetic productions to the new poetic structure which differs from the vertical structure of poetry. Using poetic models, we were able to explain the poetic structure of old and new African poetry written in Arabic.

Selective IR wavelengths multichannel filter based on the one-dimensional topological photonic crystals comprising hyperbolic metamaterial

In this research article, we have theoretically introduced a one-dimensional topological photonic crystal (1D TPC) design to provide a better stability due to imperfections and fluctuations in geometry compared to the traditional PC structures. The considered structure is designed by the combination of two different PCs, i.e., PC1 and PC2. PC1 consists of two layers of silicon (Si) and magnesium fluoride (MgF2), while PC2 contains a multilayer stack of MgF2 and hyperbolic metamaterial (HMM). Interestingly, the HMM layer is introduced as a composite of a dielectric material of indium arsenide (InAs), and nanocomposite of Ag nanoparticles inside a hosting medium of Y2O3. The foundations of our theoretical framework are based on Effective Medium Theory (EMT), the Transfer Matrix Method (TMM), and the Maxwell-Garnett model. Our research primarily focuses on utilizing our design as a pass/stop band filter for near-infrared (NIR) applications. Notably, this proposed design exhibits significant stability in the face of imperfections and variations. Our numerical findings highlight the influence of several geometric parameters including the refractive index of hosting medium for Ag nanoparticles, thicknesses, and filling fraction on the characteristics of the resulting filter. Remarkably, the results also reveal the emergence of multiple resonance peaks that maintain high stability against geometric tolerances. We believe our work presents a finite photonic crystal (PC) whose wave localization properties are resilient to random geometric imperfections, making it suitable for NIR filtering applications.

A Review of Seismic Optimization Design of Building Structures with Uniform Response

Earthquakes threaten human survival with powerful destructive power, and the performance of buildings in earthquakes is crucial. The seismic design of traditional building structures has the limitations of non-uniform response to displacement and acceleration, which can easily lead to partial damage to the building, unreasonable structure and difficulty in post-earthquake repair, which seriously affects the comfort and safety of the building. It is emphasized that improving the seismic safety of buildings is not only an inevitable requirement to ensure the safety of people's lives, but also to meet people's needs for continuous improvement of building comfort. The review shows that it is of great practical significance to study the seismic optimization design method of building structures with uniform response, which provides an important reference direction for the future design of building structures.

Construction of cellulose 3D network composite membrane supported by hydroxylated boron nitride with high surface charge density to achieve high-efficiency osmotic energy harvesting

Ion selectivity and mechanical persistence are critical properties of membranes to harvest osmotic energy. Two-dimensional nanofluidic membranes have been studied to enhance those properties, whereas they are usually constrained due to unsatisfactory mass transfer performances. Herein, a ternary three-dimensional membrane (T-CNF/PVDF/BN-OH composite membrane, abbreviated as CPBN) with distinct mechanical strength and high surface charge density (−2.65 mC·m−2) for sustainable osmotic energy harvesting is designed. In CPBN, negatively charged TEMPO-oxidized cellulose acts as a scaffold and constructs a 3D network structure together with the hydroxylated boron nitride (BN-OH) via a self-assembly process. The affluent nano-constrained ion channels effectively enhance the controllability and effectiveness of ion transport. The abundant ionized carboxyl groups extremely facilitate the selective transportation of the cations, while the BN-OH also assist this process, promoting the one-way transmission of cations in the channel. Additionally, the participation of PVDF polymer forms a network interlock structure, which significantly improves mechanical performances and stability in water. The membrane demonstrates a high power density (10.6 W/m2), measured in minimal testing areas, and an average power density around 1 W/m2 in larger areas, with an energy conversion efficiency of up to 30.7 %. This study provides a promising exploration of replacing traditional two-dimensional layered structure with three-dimensional network structure of cellulose for osmotic energy harvesting.

Opportunities for the use of artificial intelligence in supply chain management

Aim. To evaluate the potential of generative artificial intelligence technology in the context of supply chain management.Objectives. To analyze how artificial intelligence is changing traditional management practices and structures in supply chain management; to identify fundamental shifts brought about by AI, including automation, data-driven decision making, and human empowerment; to examine current statistics on the effectiveness of artificial intelligence in management processes and conclude the potential, promise of this technology in the logistics industry; to provide strategic insight and practicalMethods. The research combines qualitative and quantitative methods to provide a deeper understanding of the problems considered. Based on these methods, an array of relevant statistical data and expert opinions in the field of generative artificial intelligence has been studied.Results. In today’s business environment, supply chains face a number of challenges: globalization, market volatility, changing customer expectations, and force majeure (natural disasters, pandemics, or wars). To meet these challenges and strengthen their market position, companies are increasingly turning to new technologies and innovations. These technologies have the potential to revolutionize the approach to supply chain management, increasing transparency, efficiency and responsiveness. All emerging technologies, from artificial intelligence and blockchain to the Internet of Things (IoT) and robotics, potentially offer opportunities to streamline operations, improve decision-making, and enhance supply chain collaboration.Conclusions. In this article, the authors have shown how artificial intelligence is changing traditional governance structures in supply chain management. Current statistical data on the effectiveness of artificial intelligence in management processes are analyzed, and a conclusion is made about the potential and prospects of this technology in the logistics sphere. Strategic understanding is formed and practical recommendations for organizations seeking to implement new tools of generative artificial intelligence are given.

Thermo-hydraulic performance evaluation of lattice structures with triply periodic minimal surfaces for latent heat storage devices

Triply periodic minimal surface (TPMS) structures exhibit significant potential in latent heat storage (LHS) applications. In this study, numerical investigations were conducted to study the thermal storage performance of four TPMS lattice types: Primitive, IWP, FRD, and Gyroid lattices, used as metallic skeletons in LHS devices. The volumes of both the TPMS skeletons and the phase change material (PCM) were kept constant, with PCM embedded either inside or outside the lattices. The melting process of PCM, the heat storage energy density, and the power density of the LHS units for different configurations were examined. Additionally, a performance evaluation coefficient was introduced to assess the heat transfer and flow characteristics of heat transfer fluid (HTF) flowing on both sides of the lattices. The results indicated that when using Primitive and FRD lattices, embedding the PCM within the internal space of the lattices resulted in a 20 % and 9.8 % higher energy storage compared to embedding it outside the lattices. The internal space of IWP and Gyroid lattices was more suitable for HTF flow channels, resulting in performance evaluation coefficients (PECs) that improved by 27.7 % and 86.3 %, respectively, when HTF flowed through the internal channels of these lattices. Moreover, the Gyroid lattice exhibited the most balanced overall heat transfer performance due to its minimal flow resistance, whereas the FRD lattice had the lowest flow performance due to its complex structure. Therefore, the Primitive and Gyroid lattices could be considered as new heat transfer structures for LHS devices, while the FRD lattice was more suitable for replacing traditional fin structures in heat sink devices.

A Deep Learning-Based Two-Branch Generative Adversarial Network for Image De-Raining

Raindrops can scatter and absorb light, causing images to become blurry or distorted. To improve image quality by reducing the impact of raindrops, this paper proposes a novel generative adversarial network for image de-raining. The network comprises two parts: a generative network and an adversarial network. The generative network performs image de-raining. The adversarial network determines whether the input image is rain-free or de-rained. The generative network comprises two branches: the A branch, which follows a traditional convolutional network structure, and the U branch, which utilizes a U-Net architecture. The A branch includes a multi-scale module for extracting information at different scales and a residual attention module to reduce redundant information interference. The U branch contains an encoder module designed to address the loss of details and local information caused by conventional down-sampling. To improve the performance of the generative network in image de-raining, this paper employs a relative discriminator incorporating a mean squared error loss. This discriminator better measures the differences between rainy and rain-free images while effectively preventing the occurrence of gradient vanishing. Finally, this study performs visual and quantitative comparisons of the proposed method and existing methods on three established rain image datasets. In the quantitative experiments, the proposed method outperforms existing methods regarding PSNR, SSIM, and VIF metrics. Specifically, our method achieves an average PSNR, SSIM, and VIF of approximately 5%, 3%, and 4% higher than the MFAA-GAN method, respectively. These results indicate that the de-rained images generated via the proposed method are closer to rain-free images.

Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits

Blueberries, as one of the more economically rewarding fruits in the fruit industry, play a significant role in fruit detection during their growing season, which is crucial for orchard farmers’ later harvesting and yield prediction. Due to the small size and dense growth of blueberry fruits, manual detection is both time-consuming and labor-intensive. We found that there are few studies utilizing drones for blueberry fruit detection. By employing UAV remote sensing technology and deep learning techniques for detection, substantial human, material, and financial resources can be saved. Therefore, this study collected and constructed a UAV remote sensing target detection dataset for blueberry canopy fruits in a real blueberry orchard environment, which can be used for research on remote sensing target detection of blueberries. To improve the detection accuracy of blueberry fruits, we proposed the PAC3 module, which incorporates location information encoding during the feature extraction process, allowing it to focus on the location information of the targets and thereby reducing the chances of missing blueberry fruits. We adopted a fast convolutional structure instead of the traditional convolutional structure, reducing the model’s parameter count and computational complexity. We proposed the PF-YOLO model and conducted experimental comparisons with several excellent models, achieving improvements in mAP of 5.5%, 6.8%, 2.5%, 2.1%, 5.7%, 2.9%, 1.5%, and 3.4% compared to Yolov5s, Yolov5l, Yolov5s-p6, Yolov5l-p6, Tph-Yolov5, Yolov8n, Yolov8s, and Yolov9c, respectively. We also introduced a non-maximal suppression algorithm, Cluster-NMF, which accelerates inference speed through matrix parallel computation and merges multiple high-quality target detection frames to generate an optimal detection frame, enhancing the efficiency of blueberry canopy fruit detection without compromising inference speed.

China’s Belt and Road Initiative and its Implications on the Global Power Dynamics

This work explores the multifaceted impact of the Belt and Road Initiative (BRI) initiated by China on global power dynamics, economic landscapes, and diplomatic alliances. Beginning with an overview of the BRI's historical context and objectives, the essay delves into its theoretical framework, employing Organski's power transition theory to analyze economic, geopolitical, strategic, and cultural dimensions. The literature review integrates insights from scholars such as Layne, Modelski, Thompson, Huntington, and Nye, providing a nuanced understanding of the BRI's placement within broader historical patterns. The essay then examines the economic impact of the BRI on participating countries, emphasizing infrastructure development, trade facilitation, and technology transfer. A shift in the global economic center of gravity towards Asia is explored, challenging traditional economic power structures. Geopolitical implications and evolving power dynamics are analyzed, highlighting the strategic positioning of China and the formation of new alliances. Global responses to the BRI, particularly from major powers like the United States, Russia, and the European Union, are discussed, reflecting varying perspectives on China's growing influence. The work also addresses challenges and criticisms related to debt sustainability, environmental concerns, transparency, and governance. In conclusion, the paper reflects on the transformative effects of the BRI, emphasizing its role in shaping a multipolar world and challenging existing norms of hegemony.

‘Pirates’, ports, politics: The Gulf (khalīj) & international society’s expansion

Abstract This paper examines how Britain, through ‘gunboat diplomacy’ campaigns against so-called Arab pirates, overran the pre-existing Gulf suzerain system and became the predominant power in its waters. By filling a gap in the classical English School ‘international society’ expansion thesis, this article describes how and when political and ideational shifts in the Gulf allowed sovereignty to manifest into its present dynastic form. It argues British imposition of rules, norms, and institutions through a series of nineteenth-century Anglo-Arab treaties against Arab ‘pirates’ broke traditional conditions of divisible sheikhly authority to embed a new telos of sovereign indivisibility, facilitating indirect colonisation. Colonialism as an overlooked primary institution in the classical international society expansion story reinforced political inequality to create dynasticism to simplify colonial statecraft. The 1836 Restrictive Line was a central institution introduced by Britain to manage the transition from divisible to indivisible authority. Drawing from colonial archives, the paper argues that British control over cross-coastal movements through a Restrictive Line reinforced domestic sovereignty of British treaty signatories while weakening agency of maritime sheikhs outside the Anglo-Arab treaties framework. This unsettled traditional structures, transforming maritime tribal confederacies from participation to compliance and reconfiguring Gulf coastal security imperatives for treaty-signatory sheikhs from sea to desert.

Aging Retardation of Lead-Acid Batteries by Adjusting Charge Controller Threshold Values in Off-grid Photovoltaic System

Hybrid systems or coupled power plants with energy storage are becoming more and more popular due to the rising need for energy. Researchers have been conducting several experiments to assure longer-lasting battery use due to the increasing widespread use of energy storage and the depletion of resources such as silicon and precious metals. In this study, a simulation study is carried out in PVSyst software on lead-acid batteries, which have a low cycle and a very traditional electrochemical structure. The simulation is realized by scaling Spain’s consumption curve in 2023, taken from the European Network of Transmission System Operators for Electricity (ENTSO-E), together with lead acid batteries and off-grid photovoltaic (PV) modules. After the off-grid system design is created and consumption data is imported, it is aimed to extend battery life by changing the charge-discharge threshold values of the charge controllers. Threshold values are in two categories, high and low, and seventeen different cases are simulated. According to the results of the simulation, the state of charge (SOC) levels of the batteries decreases significantly due to radiation and cloudiness in the winter months and remain high in the spring and summer months. When charge controllers are set to high thresholds levels, they cause gassing currents that rise to an average of 20 amps, while battery life extends up to 5.3 years. When low threshold values are used, negligible levels of oxygen and hydrogen gasses are formed in the battery, but battery life decreases to 4.1 years.

Catalysts of connection. The role of digital information and communication technology in fostering neighbourhood social cohesion: A systematic review of empirical findings

Neighbourhood social cohesion is associated with a range of beneficial outcomes for residents. However, it is commonly hypothesised that neighbourhood relations face potential disruptions from digital information and communication technologies (DICT) as they are assumed to alter traditional community structures previously grounded in physical proximity. We systematically review 52 empirical studies on the relationship between DICT and neighbourhood social cohesion to determine in what ways DICT hinder or promote neighbourhood social cohesion. We found that DICT promote social cohesion by catalysing local social capital, but not for everyone and not in every neighbourhood. We propose the theoretical concept of ‘catalysts of connection’ to explain how technological affordances and online content interact with collective and individual social capital to develop various domains of social cohesion. Based on these results and our theoretical concept, we conclude that DICT exacerbate socio-spatial inequality in cities as neighbourhoods with low social capital are less likely to reap the benefits of the digital age. We provide paths for future investigations on the intersection of urban research and media and communication studies.

Participatory Surveillance and Candidacy: A Discourse Analysis of Views on Self-Testing for Proteinuria in Pregnancy.

Actively involving people in self-monitoring and management during their pregnancy is an emerging clinical and social practice. Self-monitoring of blood pressure and self-testing for proteinuria, key diagnostic tests for pre-eclampsia, are becoming commonplace in hypertensive pregnancies. While evidence exists on the acceptability and feasibility of self-monitoring blood pressure, evidence for self-testing for proteinuria in pregnancy is thin, with little knowledge of how it might affect the traditional structures of maternity care. As part of a diagnostic accuracy study on self-testing for proteinuria, pregnant people and healthcare professionals were recruited to a qualitative study to understand their experiences of, and attitudes to, self-testing. Multiple qualitative methods were used, including interviews, focus groups, and free text postcards. A discourse analysis was conducted to understand how self-testing might inform and reshape routine antenatal care. Analysis revealed a tension between the empowering concept of participatory surveillance, which pregnant people and healthcare professionals were broadly positive about, and the adjudications made by healthcare professionals about the candidacy, or suitability, of certain pregnant people to self-test. Candidacy is a framework for understanding what influences access to healthcare for socially disadvantaged groups, including professional judgments that impact access to interventions. While participatory surveillance was felt to have the potential to empower pregnant people in antenatal care, the loss of the traditional clinical gaze was disquieting for some, and pregnant people and healthcare professionals were reluctant to cede professional responsibility.

A novel cellular structure with center-symmetric cell walls for morphing applications

Cellular structures are potential candidates for the supporting framework of flexible morphing skins. Unlike traditional zero Poisson’s ratio (ZPR) cellular structures with axisymmetric cell walls, this paper proposes a novel cellular structure with center-symmetric cell walls. The in-plane mechanical properties of this novel structure are explored through theoretical analysis and substantiated by both finite element simulations and experimental tests. Compared to the classic accordion honeycomb structure, the elastic modulus in the x-direction of the novel structure is reduced by an average of 58%, the strain amplification rate is increased by 122%, and the in-plane stiffness anisotropy is improved by 200%. These findings suggest that the proposed structure offers far superior stiffness anisotropy and large deformation potential, making it more suitable for morphing applications than the traditional ZPR cellular structures.

Rethinking Field School Delivery and Addressing Our Biases

Abstract Field schools are foundational training for archaeologists and the corresponding methods for instruction are largely consistent within the discipline. The expectation is that at some point early in their careers students will enroll in a field school. To participate, students must pay summer tuition, dedicate a minimum of four weeks (usually longer) to full-time fieldwork, and in many cases travel to remote locations. The reality is that for many students such expectations make field school participation an impossibility—and ultimately make archaeology a nonviable career option for students from historically underrepresented backgrounds. Offering local field opportunities within the context of a regular school year alleviates those problems. A recent field school in north Idaho demonstrated how traditional field school structure excludes many students and how archaeologists can adjust instruction to make field training more accessible to students.

Sunflower pith inspired dual-gradient cellular polyurethane architecture with amplified mechanical functions

Artificial cellular materials with various mechanical functions are attracting increasing attentions from aerospace, transportation, and industrialization. However, many artificial cellular materials, despite of the hierarchically ordered structures and even unique performance to some, still lag behind many natural ones in amplification of mechanical functions owing to the limitations in intrinsic mechanical performance and sophisticated structural design. Herein, inspired with lightweight and high strength of sunflower piths, we proposed a dual-gradient structure consisting of pore size gradient and wall thickness gradient to engineer cellular architectures with desirable mechanical performance by harnessing vat photopolymerization 3D printing of double crosslinking networks polyurethane elastomer. The double-gradient cellular polyurethane architecture displays more exceptional capability in load-bearing and energy absorption compared with non– and single gradient structures. Besides, the specific compressive strength and energy absorption of the dual-gradient cellular architectures are 4 times higher than those of traditional mechanical metamaterial structures such as octet-truss lattice, gyroid lattice, and porous structure prepared with the same material. Potential mechanisms such as dual-gradient cellular structures to obtain selective flexural deformation behaviour increasing their energy absorption and dissipation capacity are fully elucidated. As the potential paradigms, we demonstrated the mechanical functions of biomimetic mechanical cellular architectures for efficient impact protection and noise isolation, which offered a promising perspective toward developing soft metamaterials with excellent mechanical functions for potential soft machines and engineering applications.

Adaptive hierarchical interval type-2 fuzzy control for trajectory tracking of an underactuated AUV with uncertain dynamics

In this study, an adaptive hierarchical interval type-2 fuzzy control (AHIT2FC) scheme is presented for three-dimensional (3D) trajectory tracking control of an underactuated autonomous underwater vehicle (AUV), which has only three independent control inputs and is subject to partially parametric uncertainty and unknown external disturbances. To decrease reliance on hydrodynamic parameters, an interval type-2 fuzzy logic system (IT2FLS) is utilized, which exhibits superior capabilities in handling high levels of uncertainties prevalent in the underwater environment as compared to a type-1 fuzzy logic system. However, the traditional fuzzy system structure encounters the “curse of dimensionality” issue, which results in high computational complexity and imposes a significant burden on the limited computing resources underwater. The proposed AHIT2FC framework, based on a hierarchical structure, can substantially enhance computational speed while ensuring excellent control performance. Subsequently, Lyapunov’s theory is adopted to guarantee that all the tracking errors in the closed-loop system are semiglobally uniformly bounded (SGUB). Finally, comparative simulation results demonstrate the effectiveness and superiority of the proposed AHIT2FC scheme.