Harmonious Balance Research Articles

Enhancing Livestock Detection: An Efficient Model Based on YOLOv8

Maintaining a harmonious balance between grassland ecology and local economic development necessitates effective management of livestock resources. Traditional approaches have proven inefficient, highlighting an urgent need for intelligent solutions. Accurate identification of livestock targets is pivotal for precise livestock farming management. However, the You Only Look Once version 8 (YOLOv8) model exhibits limitations in accuracy when confronted with complex backgrounds and densely clustered targets. To address these challenges, this study proposes an optimized CCS-YOLOv8 (Comprehensive Contextual Sensing YOLOv8) model. First, we curated a comprehensive livestock detection dataset encompassing the Qinghai region. Second, the YOLOv8n model underwent three key enhancements: (1) incorporating a Convolutional Block Attention Module (CBAM) to accentuate salient image information, thereby boosting feature representational power; (2) integrating a Content-Aware ReAssembly of FEatures (CARAFE) operator to mitigate irrelevant interference, improving the integrity and accuracy of feature extraction; and (3) introducing a dedicated small object detection layer to capture finer livestock details, enhancing the recognition of smaller targets. Experimental results on our dataset demonstrate the CCS-YOLOv8 model’s superior performance, achieving 84.1% precision, 82.2% recall, 84.4% mAP@0.5, 60.3% mAP@0.75, 53.6% mAP@0.5:0.95, and 83.1% F1-score. These metrics reflect substantial improvements of 1.1%, 7.9%, 5.8%, 6.6%, 4.8%, and 4.7%, respectively, over the baseline model. Compared to mainstream object detection models, CCS-YOLOv8 strikes an optimal balance between accuracy and real-time processing capability. Its robustness is further validated on the VisDrone2019 dataset. The CCS-YOLOv8 model enables rapid and accurate identification of livestock age groups and species, effectively overcoming the challenges posed by complex grassland backgrounds and densely clustered targets. It offers a novel strategy for precise livestock population management and overgrazing prevention, aligning seamlessly with the demands of modern precision livestock farming. Moreover, it promotes local environmental conservation and fosters sustainable development within the livestock industry.

Preface

Welcome to the proceedings of the The 10th International Seminar on Tropical Animal Production (ISTAP X) organized by Faculty of Animal Science, Universitas Gadjah Mada. In the midst of escalating concerns about the environmental impacts of animal production and the imperative to ensure global food security, this symposium serves as a crucial platform for scholars, researchers, policymakers, and industry professionals to converge and deliberate on pressing issues. The title of our symposium, “Sustainable Animal Productivity and Environmental Footprint Toward Global Halal and Food Security,” encapsulates the multifaceted challenges we face today. As the world’s population burgeons and economies expand, the demand for animal products escalates, placing immense pressure on our environment and resources. Yet, this surge in production comes at a cost—degradation of ecosystems, deforestation, habitat loss, and a myriad of environmental woes. Concurrently, the burgeoning demand for halal food, driven by the expanding Muslim population, necessitates innovative approaches to ensure the sustainability and integrity of supply chains. The backdrop against which this symposium unfolds is one characterized by urgency and complexity. Traditional agricultural practices, marked by inefficiencies and resource-intensive methods, are no longer tenable in the face of escalating global challenges. The need of the hour is a paradigm shift towards sustainable animal production systems that reconcile productivity with environmental stewardship. Throughout this symposium, esteemed experts from diverse disciplines will engage in rigorous discourse, sharing insights, methodologies, and innovative solutions aimed at fostering sustainable animal productivity while mitigating environmental footprints. By fostering interdisciplinary collaboration and knowledge exchange, we aspire to chart a path towards a more sustainable, resilient, and equitable future for animal production systems worldwide. The contributions contained within these proceedings represent the culmination of rigorous research, thought-provoking insights, and practical applications. We extend our deepest gratitude to all the authors, presenters, attendees, and organizers whose collective efforts have made this symposium a resounding success. As we embark on this intellectual journey, let us remain steadfast in our commitment to forge a harmonious balance between the imperatives of productivity, environmental sustainability, halal integrity, and global food security. List of Committee of ISTAP X 2023 is available in this Pdf.

Adaptasi Sosial Orang Melayu dalam Bermukim di Bantaran Sungai

Malay is one ethnic that lives on riverbank of Kapuas. Settlements on riverbanks consist of physical elements such as buildings, river flow patterns, and their inhabitants, as well as non-physical elements in the form of rules and local wisdom. Rivers are environmental elements that shape settlement patterns in Mendawai and Bansir villages. Riverbanks are a place for social and cultural activities that illustrate a harmonious balance between humans and the natural environment. Natural conditions and physical/non-physical elements make residents in both villages adapt to current needs. This research explores forms of social adaptation in the settlement of Malay people on riverbanks. The method used in this research is a descriptive and qualitative approach, which describes the existing conditions of two Kampung, Mendawai and Bansir, in the Bansir Laut Subdistrict using the adaptation strategy theory. Data was collected by field observation, literature study, and digital tracing. The results of this research illustrate the social adaptation of the people in Mendawai and Bansir villages according to the environmental conditions on the riverbanks. The village circulation route of both Kampung is maintained with Gertak and Steher as essential elements of the environment, which is experiencing changes as a manifestation form of the social adaptation of the Malay people on the banks of the Kapuas River.

An Enhanced Tree-Seed Algorithm for Function Optimization and Production Optimization.

As the fields of engineering, energy, and geology become increasingly complex, decision makers face escalating challenges that require skilled solutions to meet practical production needs. Evolutionary algorithms, inspired by biological evolution, have emerged as powerful methods for tackling intricate optimization problems without relying on gradient data. Among these, the tree-seed algorithm (TSA) distinguishes itself due to its unique mechanism and efficient searching capabilities. However, an imbalance between its exploitation and exploration phases can lead it to be stuck in local optima, impeding the discovery of globally optimal solutions. This study introduces an improved TSA that incorporates water-cycling and quantum rotation-gate mechanisms. These enhancements assist the algorithm in escaping local peaks and achieving a more harmonious balance between its exploitation and exploration phases. Comparative experimental evaluations, using the CEC 2017 benchmarks and a well-known metaheuristic algorithm, demonstrate the upgraded algorithm's faster convergence rate and enhanced ability to locate global optima. Additionally, its application in optimizing reservoir production models underscores its superior performance compared to competing methods, further validating its real-world optimization capabilities.

Application of multi-objective artificial gorilla troops optimization algorithm in intelligent evacuation path planning for building fires

In the event of a sudden incident in large buildings, optimizing personnel evacuation paths has a direct and significant impact on overall evacuation efficiency. To address personnel evacuation scenarios caused by building fires in complex environments, this study presents a path planning approach based on the Multi-Objective Gorilla Optimization (MIGTO) algorithm. The objective function comprises path risk, congestion cost, and path length. However, traditional GTO algorithms face limitations in addressing such problems, including slow convergence, premature convergence, and susceptibility to local optima. To address the aforementioned challenges, this study introduces variable updates to the spiral position during the algorithm development phase to improve search efficiency. The nonlinear parameters are adjusted to achieve a harmonious balance between global and local search capabilities. In addition, the alert perturbation mechanism is implemented before each optimization iteration, which improves the algorithm's ability to overcome local optima. Furthermore, a compound chaotic mapping is introduced to increase the diversity of the population. Experimental results demonstrate the outstanding performance of the MIGTO algorithm in various grid map path planning scenarios. Whether faced with complex obstacles, multiple exits, or multiple fire sources, the path inferiority indices of MIGTO in path planning are significantly superior to other algorithms. The MIGTO algorithm is not only suitable for dynamic planning of fire evacuation paths, but can also be used in the Pathfinder evacuation simulation software, where it outperforms the software's built-in algorithms.

Impact of reduced sucrose content on processed cheese: Sensory, textural, and storage stability analysis

The present study examines the impact of varying sucrose concentrations (12%, 6%, and 0%) on the sensory qualities and storage stability of processed cheese. Our findings reveal that sucrose is crucial for enhancing color depth, modulating flavor, and improving texture. Specifically, higher sucrose levels impart a caramel color, increase sweetness, and maintain a harmonious balance between salty and sour tastes, thereby mitigating the intensification of unwanted flavors (P < 0.05). Furthermore, sucrose acts as a structural element that bolsters viscoelastic properties and prolongs storage stability; increased sucrose content slows flavor degradation and preserves textural consistency over time. While reductions in sucrose do not significantly compromise the texture of fresh samples (P > 0.05), they necessitate adjustments in flavor profiles. This research highlights the essential role of sucrose in processed cheese and sets the stage for further studies on sugar reduction strategies and the potential use of alternative fillers, marking a significant step forward in the development of processed cheese products.

Beyond the basics: mapping the inflation response to fiscal deficit in India with smooth transition autoregressive model

PurposeIndia’s historical fiscal performance has featured elevated deficit levels. Driven by the imperative need for fiscal stimulus measures in response to the crisis, efforts toward fiscal consolidation from 2003 to 2008 were reversed in 2008–2009 due to the financial crisis. These stimulus actions are believed to have wielded a notable influence on inflation dynamics. Presumably, a high inflation rate hinders growth and inflicts severe welfare costs. Accordingly, the principal objective of this paper is to scrutinise the threshold effects of fiscal deficit on inflation within the context of the Indian economy.Design/methodology/approachWe employed the Smooth Transition Autoregressive (STAR) Model, a robust tool for capturing non-linear relationships, to discern the specific threshold level of fiscal deficit. Our analysis encompasses annual data spanning from 1971 to 2020. Additionally, we have leveraged the Toda-Yamamoto causality test to establish the existence and direction of a causal connection between fiscal deficit and inflation in the Indian economy.FindingsOur analysis pinpointed a critical threshold level of 3.40% for fiscal deficit, a value beyond which inflation dynamics in India undergo a marked transition, signifying the presence of significant non-linear effects. Moreover, the results derived from the Toda-Yamamoto causality test offer substantiating evidence of a causal relationship originating from the fiscal deficit and leading to inflation within the Indian economic framework.Research limitations/implicationsThe findings of our study carry significant implications, particularly for the formulation and execution of both fiscal and monetary policies. Understanding the threshold effects of fiscal deficit on inflation in India provides policymakers with valuable insights into achieving a harmonious balance between these two critical economic variables.Originality/valueTo the best of our knowledge, this study is the first of its kind to empirically investigate threshold effects of fiscal deficit on inflation in India from a non-linear perspective using the Smooth Transition Autoregression (STAR) model.

Organic Farming vs. Integrated Nutrient Management: A Comparative Review of Agricultural Productivity and Sustainability

In an era where sustainable agriculture is crucial for global food security and environmental preservation, organic farming and Integrated Nutrient Management (INM) have emerged as leading practices. This review paper offers a comprehensive comparison of these two approaches, focusing on their impact on agricultural productivity and sustainability. Organic farming, with its emphasis on reducing the use of chemical fertilizers, pesticides, growth hormones, and feed additives, aligns closely with the principles of sustainability. It enhances food quality, promotes soil health, and mitigates adverse environmental effects by encouraging natural recovery cycles. However, organic farming's limitations, such as lower yields and a more labour-intensive approach have prompted interest in innovative solutions that blend organic practices with modern technologies. Integrated Nutrient Management (INM) presents a compelling alternative. By combining organic, inorganic, and biological nutrient sources, INM seeks to optimize nutrient use efficiency and maintain soil health. This approach offers a flexible nutrient management strategy, balancing organic and inorganic inputs to maintain crop productivity while reducing environmental impact. Studies have shown that INM can improve soil properties, such as bulk density, porosity, and water-holding capacity, leading to enhanced crop yields and lower greenhouse gas emissions. The paper explores how INM's integrated approach not only stabilizes crop production but also supports the growth of soil microbes, providing a source of energy and organic carbon. By using a combination of specific microorganisms, organic matter, and minimal doses of inorganic fertilizers, INM can achieve a harmonious balance that reduces environmental pollution and ensures long-term soil fertility. Ultimately, this review underscores the potential of combining organic and INM practices to create a sustainable and productive agricultural system. Through a comparative analysis, the paper aims to guide researchers, policymakers, and farmers towards adopting strategies that foster agricultural sustainability without compromising productivity.

Spectral Superresolution Using Transformer with Convolutional Spectral Self-Attention

Hyperspectral images (HSI) find extensive application across numerous domains of study. Spectral superresolution (SSR) refers to reconstructing HSIs from readily available RGB images using the mapping relationships between RGB images and HSIs. In recent years, convolutional neural networks (CNNs) have become widely adopted in SSR research, primarily because of their exceptional ability to extract features. However, most current CNN-based algorithms are weak in terms of extracting the spectral features of HSIs. While certain algorithms can reconstruct HSIs through the fusion of spectral and spatial data, their practical effectiveness is hindered by their substantial computational complexity. In light of these challenges, we propose a lightweight network, Transformer with convolutional spectral self-attention (TCSSA), for SSR. TCSSA comprises a CNN-Transformer encoder and a CNN-Transformer decoder, in which the convolutional spectral self-attention blocks (CSSABs) are the basic modules. Multiple cascaded encoding and decoding modules within TCSSA facilitate the efficient extraction of spatial and spectral contextual information from HSIs. The convolutional spectral self-attention (CSSA) as the basic unit of CSSAB combines CNN with self-attention in the transformer, effectively extracting both spatial local features and global spectral features from HSIs. Experimental validation of TCSSA’s effectiveness is performed on three distinct datasets: GF5 for remote sensing images along with CAVE and NTIRE2022 for natural images. The experimental results demonstrate that the proposed method achieves a harmonious balance between reconstruction performance and computational complexity.

Synergistic Catalytic Performance of Pt-Au Bimetallic Catalysts on High-Crystallinity ZSM-23 Zeolite for Hexadecane Hydroisomerization: Metal-Acid Balance and Enhanced Isomerization Selectivity.

Highly crystalline ZSM-23 zeolite, exhibiting a distinctive dumbbell morphology, was synthesized via a hydrothermal method. Bifunctional catalysts, comprising single metals (Pt or Au) and bimetals (Pt-Au), were successfully prepared by using a positional precipitation method. The hydroisomerization of hexadecane served as a model reaction to assess the catalytic performance arising from the synergistic effects of bimetallic active sites. In comparison to single-metal catalysts, 0.3Au0.7Pt/ZSM-23 demonstrated increased n-C16 conversion, while 0.5Au0.5Pt/ZSM-23 exhibited enhanced i-C16 selectivity, achieving the highest i-C16 yield. The bimetallic catalyst not only finely tuned the metal site activity through bimetallic synergy but also achieved a superior balance between metal and acid catalysis, resulting in improved catalytic performance in the n-C16 hydroisomerization. The Pt-Au bimetallic catalyst approached the ideal requirements for a hydroisomerization catalyst, achieving a harmonious balance of metal and acid catalysis.

Application of energy scheduling algorithm based on energy consumption prediction in smart home energy scheduling

To effectively optimize household energy management, enhance user comfort, and ensure the stability of the power grid, this paper directs its focus towards household equipment and presents inter-household and indoor energy scheduling algorithms. Grounded in a two-dimensional dynamic device priority framework and predictive device operation modeling, this study demonstrates that the utilization of scheduling algorithms can avert grid overload scenarios during periods of low electricity prices. This results in more consistent hourly electricity consumption and a substantial peak-to-average ratio reduction of up to 44.86 %. Additionally, the application of the continuous wavelet neural network algorithm proves to be proficient in accurately forecasting home device operations. When the time was 17.5 h, the actual energy consumption of the water heater was 7.12 kWh, which was 0.78 kWh more than the predicted energy consumption. Utilizing scheduling algorithms, as opposed to not employing them, led to notable reductions in electricity expenses, demonstrating a cost savings rate of 15.32 % on the third day. Additionally, it facilitated decreased usage of the power grid. When the time was 18 o'clock, the power consumption of the grid using scheduling algorithms was 0.24 kWh, which was 0.25 kWh lower than that without scheduling algorithms. Following the implementation of the scheduling algorithm, minimal deviation in device startup times was observed during periods of high comfort, with offsets ranging from 0 h. The research methods employed demonstrate efficacy in orchestrating energy distribution among households and indoor spaces, thereby striking a harmonious balance between energy conservation and user comfort.

Toward Sustainable Global Product Development Performance: Exploring the Criticality of Organizational Factors and the Moderating Influence of Global Innovation Culture

In today’s dynamic and global landscape, innovation and globalization are intricately linked drivers that propel modern businesses forward, serving as indispensable pillars upon which organizations heavily rely to maintain their competitive edge. Leveraging innovation within the context of global product development (GPD) practices is imperative for organizations seeking to survive and effectively compete in the rapidly evolving marketplace. While preceding studies have primarily focused on the importance of individual and organizational capabilities, policies, and cultural factors in driving product development (PD) performance, they often overlook their interconnectedness within a global context. To address this gap, this study delves into the relationship between organizational factors and global product development performance (GPDP) while examining the moderating influence of global innovation culture (GIC). These organizational factors encompass technological innovation capabilities (TICs), team creativity (TC), dynamic capabilities (DCA), and competitive advantage (CA). Our hypothesis suggests a positive impact of these factors on GPD performance. Employing a structural equation modeling (SEM) approach through SMART-PLS 3, we analyzed data collected from 480 questionnaire forms distributed among registered global product development (GPD) organizations operating in China. The empirical findings underscore the significant influence of organizational factors on GPD performance, highlighting the critical role of global innovation culture in shaping these relationships. These insights shed light on the importance of establishing a harmonious balance between organizational culture and various factors to enhance interaction among organizational elements and optimize global product development performance. Ultimately, these efforts can lead to improvements in the overall effectiveness and sustained global product development.

EXPLORING CONSCIOUSNESS THROUGH THE QUR'AN: A PHILOSOPHICAL INQUIRY

This paper delves into the concept of consciousness as explored through the Qur'an, presenting a comprehensive philosophical inquiry into Islamic perspectives on the mind, self-awareness, and the nature of human understanding. Employing a hermeneutic approach to interpret Qur'anic verses, the study highlights the unique contributions of Islamic thought to the global discourse on consciousness. By juxtaposing Qur'anic teachings with contemporary philosophical and scientific theories of consciousness, this inquiry sheds light on the interplay between divine wisdom and human intellect in understanding the essence of consciousness. The research adopts a multidisciplinary methodology, integrating insights from Islamic theology, philosophy, psychology, and cognitive science to explore the Qur'anic conceptualization of consciousness. The analysis reveals that the Qur'an offers profound insights into the nature of consciousness, emphasizing its multifaceted dimensions, including self-awareness, perception, intentionality, and the soul's journey. Furthermore, the paper discusses the implications of the Qur'anic perspective on consciousness for ethical behavior, personal identity, and the pursuit of knowledge. It argues that the Qur'an advocates for a holistic understanding of consciousness that encompasses both physical and spiritual dimensions, encouraging a harmonious balance between material and transcendental aspects of human existence. The study concludes that exploring consciousness through the Qur'an enriches the philosophical inquiry into the nature of the mind and provides valuable ethical and spiritual insights. This interdisciplinary exploration contributes to bridging the gap between religious wisdom and contemporary scientific understanding, offering a nuanced perspective on one of human existence's most profound and complex phenomena.

Strengthening Fe1.4Co0.8Ni0.8Cr high-entropy alloy composites via in-situ synthesis of TiC: Perspective from experiments and first principles calculations

Achieving a harmonious balance between strength and plasticity is a long-standing problem in single-phase face-centered-cubic (fcc) high-entropy alloys (HEAs). Herein, in-situ TiC ceramic particle reinforced fcc-structured Fe1.4Co0.8Ni0.8Cr HEAs is designed and investigated by combining the experiments and first-principate calculations. The results show that the y (TiC)–Fe1.4Co0.8Ni0.8Cr (y = 0, 2.5, 5.0, 7.5 and 10.0 %, y: volume fraction) composites consist of fcc phase with submicron/micron TiC after the co-addition of Ti and C element, and the formation of TiC facilitates to refine the microstructure of the composites. Such microstructural evolutions significantly enhance the mechanical performances of the composites. Particularly, the 7.5 % (TiC)–Fe1.4Co0.8Ni0.8Cr composite exhibits a high yield strength of ∼562.7 ± 7.7 MPa and tensile strength of ∼971.3 ± 5.4 MPa, which are respectively increased by 169.0 % and 88.3 % as compared with the Fe1.4Co0.8Ni0.8Cr based alloy, yet with the fracture elongation decreases to 35.9 ± 0.3 %. The increment in yield strength is mainly driven from the combined effect of the grain refinement strengthening, dislocation strengthening and precipitation strengthening. Density functional theory (DFT) results reveal that the increase of C–Ti bonds and the formation of covalent bonds in the 7.5 % (TiC)–Fe1.4Co0.8Ni0.8Cr composite lead to relatively higher strength and lower ductility, which are well agreed with the experimental results.

Examining Patterns and Trends of Change in Greater Yola, Adamawa State, Nigeria: A 10 Years Spatio-Temporal Investigation

This research paper explores the dynamics of land cover and land use in Greater Yola, Adamawa State, Nigeria, spanning the years 2013 to 2023. Through comprehensive analysis, including remote sensing techniques and spatial modeling, the study examines the temporal trends and implications of urbanization on ecosystem diversity and resilience within the region. The findings reveal a significant trend of rapid urbanization, characterized by the expansion of built-up areas at the expense of natural vegetation, which poses challenges to ecosystem integrity. Furthermore, the analysis highlights the implications of these changes for ecosystem diversity, including the loss of natural habitats and fragmentation of ecosystems, threatening biodiversity and essential ecosystem services. The study underscores the critical need for a balanced approach to urban development and environmental conservation to achieve sustainable development goals. Recommendations are provided to guide policymakers and stakeholders in fostering ecosystem conservation, promoting sustainable land use practices, and mitigating the adverse impacts of urbanization on ecosystem health. By implementing these recommendations, Greater Yola can strive towards achieving a harmonious balance between urban growth and environmental stewardship, ensuring the long-term sustainability of ecosystems and the well-being of its residents.

Selective hydrodeoxygenation of 5-hydromethylfurfural to 2,5-dimethylfuran over PtFe/C catalyst

2,5-dimethylfuran (DMF), a promising biomass-derived fuel, is synthesized via the hydrodeoxygenation of 5-hydroxymethylfurfural (HMF). This study focuses on the inherent activity of a 5Pt5Fe/C catalyst for HMF hydrodeoxygenation to DMF. The catalyst exhibited exceptional performance, achieving a remarkable DMF yield of 99.6 %. It displayed specific selectivity for C = O bond hydrogenation and CO bond cleavage in diverse substrates, producing high yield of 2-methylfuran from furfural and furfury alcohol, and high yield of toluene from benzaldehyde, benzyl alcohol. In-depth characterizations unveiled valuable insights into the 5Pt5Fe/C catalyst's properties, emphasizing a harmonious balance between metal and acid sites due to the interactive synergy between Pt and Fe species, enhancing hydrodeoxygenation activity. Additionally, the catalyst demonstrated satisfactory stability, maintaining a commendable DMF yield over five reaction cycles despite observed changes.

Examining Urban-Rural Public Service Equalization and Common Prosperity in China: A Data-Driven Study on Regional Disparity

Achieving equal access to basic public services between urban and rural areas in China has become an important pathway to eliminating inequality, improving national welfare, and ultimately achieving common prosperity. Through data analysis and a data-driven approach, it is possible to better guide future policy formulation and implementation to help China achieve its goal of inclusive growth. This research endeavors to examine the interrelations between the discrepancies in basic public services provision in urban and rural areas, establishing a comprehensive evaluation indicator framework, while delving into the intricate dynamics between such service equalization and the attainment of common prosperity. Moreover, it aims to uncover the varying degrees of regional disparities witnessed during the journey to common prosperity in different parts of China, thereby providing valuable insights and references for nations and regions striving to enhance social equality. This study focused on the 31 provincial-level administrative regions of China(excluding the regions of Hong Kong, Macau, and Taiwan) The research methodology entails employing the entropy weight method to determine the weights of evaluation indicators, supplemented by a coupling coordination model to analyze the level of harmonization between urban and rural areas. Furthermore, the Dagum Gini coefficient method and kernel density estimation were utilized for an in-depth exploration of the distribution and disparities observed in regional coordination. The findings of this study reveal that between 2012 and 2021, the disparities in the equalization of basic public services between China’s urban and rural areas witnessed a progressive widening, despite modest improvements in the overall level of common prosperity. The prevailing pattern observed can be summarized as “high coupling, low coordination”. Notably, these disparities are particularly conspicuous in the western regions of the country. Additionally, this research identifies the imbalanced development of basic public service equalization between urban and rural areas as the primary cause for the observed low level of coordination. This study emphasized the intrinsic nexus and coordinated interplay existing between the equalization of urban and rural public services and the achievement of common prosperity. To foster enhanced coordination between urban and rural areas, it is imperative to prioritize the implementation of policies that promote the amalgamation of urban and rural realms, while concurrently striking a harmonious balance in the pursuit of multi-dimensional objectives. Furthermore, region-specific policies need to be formulated, with particular attention to addressing the disparities in coordination and the polarization issues prevalent in the western regions, ensuring the effectiveness and precision of these measures.

Animal behaviour and welfare research: A One Health perspective

Animal behaviour and welfare research are part of a wider endeavour to optimize the health and wellbeing of humans, animals and ecosystems. As such, it is part of the One Health research agenda. This article applies ethical principles described by the One Health High Level Expert Panel to animal behaviour and welfare research. These principles entail that animal behaviour and welfare research should be valued equitably alongside other research in transdisciplinary and multisectoral collaboration. It should include and promote a multiplicity of marginalized voices, including those of animals, and it should apply and describe a harmonious balance between human—animal-environment interactions. Lastly, it should describe how humans need to change behaviour, adopt sustainable solutions and recognize the importance of animal welfare and the integrity of the whole ecosystem.

A one-two punch strategy for diabetic wound management based on an antibiotic-hybrid biomineralized iron sulfide nanoparticle

Bacterial infection and immune imbalance are the primary culprits behind chronic wounds in individuals with diabetes, impeding the progression of damaged tissues towards normal healing. To achieve a harmonious balance between pro- and anti-inflammation within these infected areas, herein, we propose a one-two punch strategy for on-demand therapy of diabetes-infected wounds, utilizing an azithromycin (AZM)-hybrid nanocomposite termed GOx@FexSy/AZM. During the infective stage, the nanocomposite facilitates the production of ROS, coupled with the burst release of AZM and H2S gas, effectively dismantling biofilms and achieving rapid sterilization. Subsequently, the hyperinflammatory response induced by antibiosis is significantly mitigated through the synergistic action of tissue H2S and the prolonged half-life of AZM. These components inhibit the activity of pro-inflammatory transcription factors (AP-1 and NF-κB) within macrophages, thereby promoting the polarization of macrophages towards a reparative M2 phenotype and facilitating tissue remodeling. By catering to the diverse requirements of wound healing at different stages, this nanocomposite accelerates a sensible transition from inflammation to the reparative phase. In summary, this one-two punch strategy gives an instructive instance for procedural treatment of diabetes wound infection. Statement of significanceThe treatment of diabetic wound infection presents two major challenges: the diminished antibacterial efficacy arising from biofilm formation and bacterial resistance, as well as the inadequate transition of the wound microenvironment from pro-inflammatory to anti-inflammatory states after bacterial clearance. In this work, a biomineralized iron sulfide nanocomposite was prepared to mediate cascade catalytic (ROS storm) / antibiotic (AZM) / gas (H2S) triple-synergetic antibacterial therapy during the initial stage of bacterial infection, achieving the goal of rapid bactericidal effect; Subsequently, the residual H2S and long half-life AZM would inhibit the key pro-inflammatory transcription factors and promote the macrophages polarization to reparative M2, which effectively mediated tissue repair after hyperinflammatory reactions, leading to orderly treatment of hyperglycemic infected wounds.

Ginsenoside CK Alleviates DSS-Induced IBD in Mice by Regulating Tryptophan Metabolism and Activating Aryl Hydrocarbon Receptor via Gut Microbiota Modulation.

Dysbiosis of gut microbiota is believed to be associated with inflammatory bowel disease (IBD). Ginsenoside compound K (CK), the main metabolite of Panax ginseng ginsenoside, has proven effective as an anti-inflammatory agent in IBD. However, the mechanisms by which CK modulates gut microbiota to ameliorate IBD remain poorly understood. Herein, CK demonstrated the potential to suppress the release of proinflammatory cytokines by gut microbiota modulation. Notably, supplementation with CK promoted the restoration of a harmonious balance in gut microbiota, primarily by enhancing the populations of Lactobacillus and Akkermansia. Furthermore, CK considerably elevated the concentrations of tryptophan metabolites derived from Lactobacillus that could activate the aryl hydrocarbon receptor. Overall, the promising alleviative efficacy of CK primarily stemmed from the promotion of Lactobacillus growth and production of tryptophan metabolites, suggesting that CK should be regarded as a prospective prebiotic agent for IBD in the future.