Special Strategies Research Articles

A Geometric Distortion Solution Specifically for Historical Observations and its Implementation

Geometric distortion (GD) critically constrains the precision of astrometry. Using well-established methods to correct GD requires calibration observations, which can only be obtained using a special dithering strategy during the observation period. Unfortunately, this special observation mode is not often used, especially for historical observations before those GD correction methods were presented. As a result, some telescopes have no GD calibration observations for a long period, making it impossible to accurately determine the GD effect. This limits the value of the telescope observations in certain astrometric scenarios, such as using historical observations of moving targets in the solar system to improve their orbits. We investigated a method for handling GD that does not rely on the calibration observations. With this advantage, it can be used to solve the GD models of telescopes which were intractable in the past. The method was implemented in Python and released on GitHub. It was then applied to solve GD in the observations taken with the 1 m and 2.4 m telescopes at Yunnan Observatory. The resulting GD models were compared with those obtained using well-established methods to demonstrate the accuracy. Furthermore, the method was applied in the reduction of observations for two targets, the moon of Jupiter (Himalia) and binary GSC 2038-0293, to show its effectiveness. After GD correction, the astrometric results for both targets show improvements. Notably, the mean residual between the observed and computed position (O − C) for binary GSC 2038-0293 decreased from 36 to 5 mas.

Embedding a Circular Economy through Local Government in Gippsland: A Case Study, Utilising Smart Specialisation Methodology

AbstractIn 2017, the ageing Hazelwood coal-fired power station in Gippsland (Australia), finally—and abruptly, closed. The Latrobe Valley Authority (LVA), funded by the Victorian State Government was then established to assist redundant workers and develop a long-term approach to transitioning towards a more sustainable regional economy and socially cohesive community. To enable this, the LVA adopted and implemented a methodology made popular in the European Union of the ‘Smart Specialisation Strategy’ (S3), bringing together practitioners from government, business, research and education, and the wider local community (known as the ‘quadruple helix’) to co-design a shared vision for the region’s future prosperity. With Australia declaring its commitment to and the Victorian government developing policy support for a Circular Economy (CE), the LVA funded a research project in 2022 to facilitate a ‘place-based’ approach to implementing a CE business model across Gippsland. Based on interviews and workshops conducted in the period 2022–23 with key regional stakeholders, as well as on the analysis of secondary sources, this paper provides an overview of the experience utilising the S3 methodology to explore the implementation of CE in a regional setting, historically dominated by natural resource-based industries, that is now undergoing multiple economic transitions, including cessation of coal-fired power generation, oil and gas extraction and native timber harvesting. Significant barriers identified include: poor understanding of broader opportunities embedded in systemic notions of S3 and CE, siloed structure of local government authorities (both within or between councils), difficulty in promoting alignment and cooperation at all levels between a diverse range of stakeholders, lack of policy coordination and support for business innovation, together with the absence of financial incentives or regulatory mechanisms to change behaviour from a linear to CE. Despite improved intentions in policy settings around intentionality of CE practices and other initiatives being progressed simultaneously with this work, CE in Gippsland (and Victoria more broadly) and its implementation continue to be narrowly focussed on recycling and waste management, where there are clear pressures in stock-piling of waste and limitations on landfill expansion. Regional approaches to implementation of circular economy are limited in Australia, with the exception of exemplars such as Geelong, Barwon South West, and Bega. However, there are currently no examples of utilising S3 methodology to implement CE in a regional setting. Here we identify current barriers and provide recommendations on how to overcome these with the engagement of a diverse range of stakeholders across Gippsland from agribusiness, regional planning, local governments, small and medium enterprises, utilising S3 methodology, to enable systemic changes towards CE models to be implemented region-wide. This study documents the journey so far for Gippsland, where the transition from traditional extractive industry provides the opportunity to embed more sustainable practices moving forward.

A unified multimodal classification framework based on deep metric learning

Multimodal classification algorithms play an essential role in multimodal machine learning, aiming to categorize distinct data points by analyzing data characteristics from multiple modalities. Extensive research has been conducted on distilling multimodal attributes and devising specialized fusion strategies for targeted classification tasks. Nevertheless, current algorithms mainly concentrate on a specific classification task and process data about the corresponding modalities. To address these limitations, we propose a unified multimodal classification framework proficient in handling diverse multimodal classification tasks and processing data from disparate modalities. UMCF is task-independent, and its unimodal feature extraction module can be adaptively substituted to accommodate data from diverse modalities. Moreover, we construct the multimodal learning scheme based on deep metric learning to mine latent characteristics within multimodal data. Specifically, we design the metric-based triplet learning to extract the intra-modal relationships within each modality and the contrastive pairwise learning to capture the inter-modal relationships across various modalities. Extensive experiments on two multimodal classification tasks, fake news detection and sentiment analysis, demonstrate that UMCF can extract multimodal data features and achieve superior classification performance than task-specific benchmarks. UMCF outperforms the best fake news detection baselines by 2.3% on average regarding F1 scores.

One style does not fit all: the relationship of mediator behavioral adaptivity to mediator empowerment, efficacy, and satisfaction

Purpose Prior research on the situated model of mediation has suggested that mediators’ abilities to be more flexible and adaptive in responding to potential derailers in mediation situations lead to better outcomes. The purpose if this paper is to build on this theory and research by developing a new scale of mediator behavioral adaptivity and investigating the hypothesized effects of mediator adaptivity on their sense of efficacy, empowerment and satisfaction when mediating. Design/methodology/approach The paper presents findings from two survey studies with currently active, experienced mediators. Findings The findings offer a new scale for the study of effective mediation – the mediator behavioral adaptivity scale – and offer support for the hypothesis that mediators reporting an ability to use more diverse behavioral tactics and strategies (both standard and specialized strategies) report higher levels of satisfaction with mediation outcomes as well as more self-efficacy and empowerment during mediations. Research limitations/implications These studies are both self-report and correlational and so should be supplemented by subsequent research using experimental methods and more objective measures of mediation outcomes. Originality/value The program of research extended in this paper offers a new integrative model of adaptive mediation, which aims to provide evidence-based guidelines for using different types of mediation strategies in categorically different conflict situations. The model can ultimately help the field transcend discussions of preferred or best mediation styles and focus instead on how distinct strategies offer different degrees of fit for different types of mediation challenges.

Enhanced reinforcement learning-based two-way transmit-receive directional antennas neighbor discovery in wireless ad hoc networks

The utilization of directional antennas for neighbor discovery in wireless ad hoc networks brings notable benefits, such as extended transmission range, reduced transmission interference, and enhanced antenna gain. However, when nodes use directional antennas for neighbor discovery, the communication range is limited, resulting in a lack of knowledge of potential neighbors. Hence, it is necessary to design a special antenna direction switching strategy for neighbor discovery based on directional antennas. Traditional methods of switching antenna directions are often random or follow predefined sequences, overlooking the historical knowledge of sector exploration for antenna directions. In contrast, existing machine learning approaches aim to leverage observed historical knowledge to adjust antenna directions for faster neighbor discovery. Nonetheless, the latency of neighbor discovery is still high because the node cannot fully utilize the observed historical knowledge (i.e., only using the knowledge observed by the node in transmission mode, ignoring the knowledge observed by the node in reception mode). Meanwhile, the corresponding reward and penalty mechanisms are still not detailed enough (i.e., these reward and penalty mechanisms only consider the sectors of discovered and undiscovered neighboring nodes, ignoring the scenario of sectors that have been rewarded). In this paper, the neighbor discovery process is modeled as a reinforcement learning-based learning automaton. We propose an enhanced reinforcement learning-based two-way transmit-receive directional antennas neighbor discovery algorithm, called ERTTND. The algorithm consists of a two-way transmit-receive reinforcement learning mechanism (TTRL) and an enhanced reward-and-penalty mechanism (ERAP). This algorithm leverages insights from nodes in transmission and reception modes to refine their tactical decisions. Then, through an enriched reward-and-penalty framework, nodes optimize their strategies, thus expediting neighbor discovery based on directional antennas in wireless ad hoc networks. Simulation results demonstrate that compared to existing representative algorithms, the proposed ERTTND algorithm can achieve over 30% savings in terms of average discovery delay and energy consumption.

A platform for the early selection of non-competitive antibody-fragments from yeast surface display libraries.

In this work, we report the development of a platform for the early selection of non-competitive antibody-fragments against cell surface receptors that do not compete for binding of their natural ligand. For the isolation of such subtype of blocking antibody-fragments, we applied special fluorescence-activated cell sorting strategies for antibody fragments isolation from yeast surface display libraries. Given that most of the monoclonal antibodies approved on the market are blocking ligand-receptor interactions often leading to resistance and/or side effects, targeting allosteric sites represents a promising mechanism of action to open new avenues for treatment. To directly identify these antibody-fragments during library screening, we employed immune libraries targeting the epidermal growth factor receptor as proof of concept. Incorporating a labeled orthosteric ligand during library sorting enables the early selection of non-competitive binders and introduces an additional criterion to refine the selection of candidates exhibiting noteworthy properties. Furthermore, after sequencing, more candidates were identified compared to classical sorting based solely on target binding. Hence, this platform can significantly improve the drug discovery process by the early selection of more candidates with desired properties.

Problem Identification of Dyspraxia Students in Primary School

This research aims to describe the problem identification of dyspraxic students in primary schools. In identifying the problems of students with dyspraxia in elementary school, it provides knowledge related to learning obstacles in elementary school. The type of research conducted is a qualitative case study at SDIT Muhammadiyah Al Kautsar. The data sources in this study are classes that have children with special needs, class teachers and Counselling Guidance (BK) teachers. Data collection in this study was through observations and interviews with class teachers and Counselling Guidance teachers at SDIT Muhammadiyah Al Kautsar. The results of this study indicate that SDIT Muhammadiyah Al Kautsar has carried out activities to identify the problems of students with dyspraxia and provide solutions to students with dyspraxia. In addition, the results of this study are that SDIT Muhammadiyah Al Kautsar has identified students by adjusting the curriculum, mapping of children with dyspraxia, and providing evaluations or solutions in learning obstacles for students with dyspraxia. In problem identification activities, students with dyspraxia need special handling from class teachers and Counselling Guidance teachers with the aim that students are able to learn well to achieve differentiated learning objectives. In addition, in this identification it is necessary to specifically handle and provide good training starting from writing for children with dyspraxia, special assistance strategy activities, activities up and down stairs, fine motor assistance, and making appropriate LKPD.

Cellulose dissolution strategy modulates hierarchical porous structure of biomass derived carbon for supercapacitors

The vast majority of biomass derived carbon is prepared using a top-down process, however, this process lacks the freedom to design the microstructure of the derived carbon. To address this shortcoming, this study proposes a special bottom-up preparation strategy based on cellulose dissolution and breaks away from the constraints of the top-down preparation process. Research shows that this special preparation strategy can regulate the microscopic pore structure of derived carbon for application in supercapacitors. The target sample not only possesses excellent specific capacitance (512 F g−1 at 1 A g−1) and rate performance (71.1 % capacitance retention at 20 A g−1) in the three-electrode system, but also exhibits outstanding energy density (37.7 Wh kg−1 at 750 W kg−1) and cycle stability (capacity loss is 5.8 % after 5000 cycles) in the symmetric full capacitor. These exciting results herald the potential of the special preparation strategy proposed in this study to prepare high-quality biomass derived carbon suitable for supercapacitors.

Special Survival Strategy of First-Instar Scorpions Revealed by Synchronous Molting Behavior from Social Facilitation of Maternal Care and Reciprocal Aggregation.

Ecdysis is a well-known developmental feature among arthropods. Because the aggregate and synchronous molting of first-instar scorpions is markedly different from the common independent molting behavior of older scorpions and most arthropods, knowledge on the biological benefits of the unusual behavior of first-instar scorpions remain limited. Before the molting of newborn scorpions, their mothers exhibited a remarkable ability to efficiently locate the fallen offspring and help them climb onto their back, which was supported by strong maternal behavior because they climbed more swiftly than the 7-day postpartum scorpions. Most newborn scorpions molted and survived on the mother's back, with a survival rate of approximately 100%, and most newborn scorpions survived via aggregate molting behavior on sand in the absence of mothers (89.83% ± 1.91%). The important role of the mother scorpion was further highlighted in mothers with one to five first-instar scorpions. While all first-instar scorpions individually or reciprocally molted and survived on the mother's back, only 52.00% ± 7.14% to 79.20% ± 4.24% of newborn scorpions isolated from the mother could individually or reciprocally molt and survive on the sand, and the aggregated states of first-instar scorpions strengthened as their numbers on sand increased before molting. These results highlight collaborative molting as an evolutionary driving force for newborn scorpions. Taken together, both maternal care and collaborative aggregate molting behavior enhanced the survival of first-instar scorpions before and after molting, and these benefits for first-instar scorpions play essential and evolutionary roles in scorpion survival.

Genome-Wide Identification and Expression Analysis of the Cyclic Nucleotide-Gated Channel Gene Family in Zoysia japonica under Salt Stress.

Salt stress severely inhibits plant growth. Understanding the mechanism of plant salt tolerance is highly important to improving plant salt tolerance. Previous studies have shown that nonselective cyclic nucleotide-gated ion channels (CNGCs) play an important role in plant salt tolerance. However, current research on CNGCs mainly focuses on CNGCs in glycophytic plants, and research on CNGCs in halophytes that exhibit special salt tolerance strategies is still scarce. This study used the halophilic plant Zoysia japonica, an excellent warm-season turfgrass, as the experimental material. Through bioinformatics analysis, 18 members of the CNGC family were identified in Zoysia japonica; they were designated ZjCNGC1 through ZjCNGC18 according to their scaffold-level chromosomal positions. ZjCNGCs are divided into four groups (I-IV), with the same groups having differentiated protein-conserved domains and gene structures. ZjCNGCs are unevenly distributed on 16 scaffold-level chromosomes. Compared with other species, the ZjCNGCs in Group III exhibit obvious gene expansion, mainly due to duplication of gene segments. The collinearity between ZjCNGCs, OsCNGCs, and SjCNGCs suggests that CNGCs are evolutionarily conserved among gramineous plants. However, the Group III ZjCNGCs are only partially collinear with OsCNGCs and SjCNGCs, implying that the expansion of Group III ZjCNGC genes may have been an independent event occurring in Zoysia japonica. Protein interaction prediction revealed that ZjCNGCs, calcium-dependent protein kinase, H+-ATPase, outwardly rectifying potassium channel protein, and polyubiquitin 3 interact with ZjCNGCs. Multiple stress response regulatory elements, including those involved in salt stress, are present on the ZjCNGC promoter. The qPCR results revealed differences in the expression patterns of ZjCNGCs in different parts of the plant. Under salt stress conditions, the expression of ZjCNGCs was significantly upregulated in roots and leaves, with ZjCNGC8 and ZjCNGC13 showing the greatest increase in expression in the roots. These results collectively suggest that ZjCNGCs play an important role in salt tolerance and that their expansion into Group III may be a special mechanism underlying the salt tolerance of Zoysia japonica.

Effectiveness of supplementary antimicrobial procedures in disinfecting lateral canals as evaluated by a novel ex vivo analytical approach

This ex vivo study devised an analytical ex vivo method for infection/disinfection of simulated lateral canals located in the middle and apical segments of the root. The antibacterial effects of supplementary approaches were tested in this model. Extracted mandibular premolars had their main root canals enlarged and then two lateral canals (100 μm in diameter) were created in the root, one in the apical and the other in the middle portion. Micro-computed tomography was used for specimen selection and to confirm the quality of the simulated ramifications. The specimens were contaminated with a mixed bacterial culture from subgingival bacterial biofilm added to pure Enterococcus faecalis strain ATCC 29212 grown overnight, using special strategies to facilitate culture medium penetration within the lateral canals. The following procedures were tested for disinfection: NaOCl/passive ultrasonic irrigation (PUI), NaOCl/XP-endo Finisher, ozonated water/continuous ultrasonic irrigation (CUI), and NaOCl/conventional irrigation with 30-G needles (control). Bacteriological samples were taken from the main canal before (S1) and after (S2) each supplementary protocol, and also from each lateral canal after treatment (S3). DNA extracted from the samples was subjected to quantitative real-time polymerase chain reaction. All S1 main canal samples were positive for bacterial presence. Bacterial counts in the main root canal substantially decreased by 99.2% after PUI, 99.1% after ozone/CUI, 99% after XP-endo Finisher, and 96% in the control group (P < 0.01 for all groups). There were no significant differences between groups (P > 0.05). The same was observed when comparing the effects of the supplementary approaches in the apical and middle lateral canals (P > 0.05). Only a few lateral canals showed no detectable bacteria. The method proposed here proved effective for ex vivo infection/disinfection studies. All supplementary approaches induced a substantial bacterial reduction in the main canal, with no significant differences between them. However, in terms of lateral canal disinfection, none of the tested approaches showed significant effects when compared to the control group.

Multilevel Governance and Smart Specialisation Strategy: The case of the Swifts Creek district in Gippsland

Multilevel Governance and Smart Specialisation Strategy: The case of the Swifts Creek district in Gippsland

A special coupling strategy: Cu2MoS4 as a large-sized co-catalyst for promoting photocatalytic hydrogen production performance

The photocatalytic hydrogen production performance of semiconductor materials can be improved by co-catalyst modification. In most of the studies, the size of the co-catalyst is relatively small compared to the primary catalyst. However, in this study, we employed a novel strategy by synthesizing a relatively large-sized Cu2MoS4 as the co-catalyst and in situ loading smaller-sized Zn0.5Cd0.5S onto Cu2MoS4, verifying that Cu2MoS4 enhances the photocatalytic hydrogen production efficiency of Zn0.5Cd0.5S. It can be observed by scanning electron microscopy (SEM) that the lateral size of 2D Cu2MoS4 is at least 50 times larger than the Zn0.5Cd0.5S nanoparticle particle size. In addition, Density Functional Theory (DFT) calculations have demonstrated that the active site for hydrogen production in the composite is located in Cu2MoS4. The large-sized of Cu2MoS4 not only provides more active sites but also broadens the electron transport channel, which is conducive to promoting the transfer of photogenerated electrons from Zn0.5Cd0.5S. This work enriches the study of large-sized materials as co-catalyst and provides a strategy for the construction of composite catalysts.

Employment imbalances in EU regions: technological dependence or high-tech trade centrality?

ABSTRACT We analyse the role of technological dependence and interregional trade centrality in explaining a region’s employment performance. We first identify the core–periphery technological structure of European Union (EU) regions, clustering them based on their high-tech trade relations (trade blocks) and technological and economic indicators (place-based regional groups). We show that EU regions have a fractal structure: blocks at the core and periphery of the high-tech trade network are divided into core and peripheral subgroups, which differ significantly in terms of innovation and employment performance. Next, the econometric analysis shows that buyer centrality is the main component of employment growth (especially in services), but within trade blocks it has to be combined with low technological dependence on more innovative regions (especially in manufacturing). Cohesion policies should pay attention to the fractal structure of regional inequalities, and Smart Specialisation strategies should consider that unrelated diversification towards activities intensive in the use of high-tech inputs may be more conducive to employment growth.

Match-based solution of general parametric eigenvalue problems

We describe a novel algorithm for solving general parametric (nonlinear) eigenvalue problems. Our method has two steps: first, high-accuracy solutions of non-parametric versions of the problem are gathered at some values of the parameters; these are then combined to obtain global approximations of the parametric eigenvalues. To gather the non-parametric data, we use non-intrusive contour-integration-based methods, which, however, cannot track eigenvalues that migrate into/out of the contour as the parameter changes. Special strategies are described for performing the combination-over-parameter step despite having only partial information on such migrating eigenvalues. Moreover, we dedicate a special focus to the approximation of eigenvalues that undergo bifurcations. Finally, we propose an adaptive strategy that allows one to effectively apply our method even without any a priori information on the behavior of the sought-after eigenvalues. Numerical tests are performed, showing that our algorithm can achieve remarkably high approximation accuracy.

Psychological Preconditions of Conflict Proneness of Personality and Mental Health: The Role of Self-Regulation, Emotional Intelligence and Mutual Understanding in The Context of Interpersonal Relations

This study aims at the investigation of psychological preconditions of conflict proneness in personality and mental health, with a specific focus on the roles of self-regulation, emotional intelligence, and mutual understanding. The research was oriented towards the application of qualitative methodology, particularly the analysis of transcripts of interview sessions. The findings showed that psychological preconditions of conflict proneness exist in professional, educational, and personal settings. Self-regulation, mutual understanding, and emotional intelligence were found to be important qualities which help to avoid conflicts. They contribute to increased motivation for conflict-less communication and interaction, cooperation, flexibility, improvement of active listening and problem solving, increased patience, formation of stress management skills, constructive feedback, reflective thinking, and building resilience. The special attention was paid towards the development of special strategies aimed at overcoming conflict proneness. The research findings demonstrated that the strategies include formation of communication skills, development of emotional intelligence and conflict management skills, improvement of active listening, building of stress management, development of team building activities, definition of responsibilities, creation of supporting environment, organization of immediate feedback, establishment of open communication, promotion of respect, creation of rituals, and encouragement of empathy. The outcomes can be used for the development of curriculum on the formation of conflict resolution skills.

Cone-Traced Supersampling With Subpixel Edge Reconstruction.

While signed distance fields (SDFs) in theory offer infinite level of detail, they are typically rendered using the sphere tracing algorithm at finite resolutions, which causes the common rasterized image synthesis problem of aliasing. Most existing optimized antialiasing solutions rely on polygon mesh representations; SDF-based geometry can only be directly antialiased with the computationally expensive supersampling or with post-processing filters that may produce undesirable blurriness and ghosting. In this work, we present cone-traced supersampling (CTSS), an efficient and robust spatial antialiasing solution that naturally complements the sphere tracing algorithm, does not require casting additional rays per pixel or offline pre-filtering, and can be easily implemented in existing real-time SDF renderers. CTSS performs supersampling along the traced ray near surfaces with partial visibility - object contours - identified by evaluating cone intersections within a pixel's view frustum. We further introduce subpixel edge reconstruction (SER), a technique that extends CTSS to locate and resolve complex pixels with geometric edges in relatively flat regions, which are otherwise undetected by cone intersections. Our combined solution relies on a specialized sampling strategy to minimize the number of shading computations and correlates sample visibility to aggregate the samples. With comparable antialiasing quality at significantly lower computational cost, CTSS is a reliable practical alternative to conventional supersampling.

Skin picking disorder in elderly: a case report

The clinical importance of skin picking disorder (SPD) in the elderly is quite high, this importance stems from physical health complications, psychological effects, social isolation, treatment difficulties, and the need for specialized treatment strategies. Effective management of this disorder requires a multidisciplinary approach and age-specific treatment strategies. Such an approach could significantly improve the overall health and quality of life of older individuals. In this study, a 69-year-old male patient who applied to the psychiatry outpatient clinic with SPD complaints was discussed in the light of literature information.

Thriving or Striving: Comparing Intra-Uterine Growth Restricted, Low Birth Weight and Normal Birth Weight Piglets within the First 24 Hours.

This observational study explored the early-life challenges of intra-uterine growth restricted (IUGR), low birth body weight (LBW), and normal birth body weight (NBW) piglets. The aim was to understand the impact of birth weight and intra-uterine growth restriction phenotype on neonatal survival and behavior. Based on weight and phenotype, piglets were classified as IUGR (n = 32), LBW (n = 34), and NBW (n = 29) immediately after birth. The piglets were litter- and sex-matched. Vitality scores were assigned based on motor activity and breathing and complemented with an assessment of umbilical cord condition, rectal temperature, crown-rump length (CRL), time to reach the udder, time to suckle, colostrum intake, and weight gain over 24 h. Beyond the lower birth weight, reduced CRL, and higher mortality rate, IUGR piglets faced several other challenges compared with LBW and NBW piglets. Growth-impaired piglets often struggled to engage in early feeding behaviors and displayed consistently lower rectal temperatures at 1, 3 and 24 h after birth. IUGR piglets showed inadequate colostrum intake and weight loss, which were also observed for LBW counterparts. In contrast, no significant differences were observed in vitality scores and umbilical cord conditions across the groups. In conclusion, our findings underscore the impact of intra-uterine growth restriction on neonatal piglets, emphasizing the need for specialized care strategies to improve survival and health outcomes in IUGR.

Spatial distribution and determinants of exclusive breastfeeding practice among mothers of children under 24 months of age in Ethiopia: spatial and multilevel analysis

BackgroundBreast milk is the first, highly valuable, and solely natural food recommended for infants in their first six months of life, which is critical for children's overall growth and development. Evidence suggests that exclusive breastfeeding differs by geographic area in Ethiopia. However, little is known regarding the geographic distribution of exclusive breastfeeding practice. Hence, this study aimed to assess exclusive breastfeeding practice, its geographic variation and associated factors among Ethiopian mothers.MethodThe study used the 2019 Ethiopian mini demographic and health survey data. All living children born 0–23 months before the survey were included. Global Moran’s I statistics on Arc-GIS and Getis Ord Gi* statistics was used to visualize the spatial pattern and hotspot and cold spot areas, respectively. Kulldorff SaTScan was used to show purely significant spatial clusters. The associated factors were identified using a multilevel mixed-effects logistic regression model. Statistically significant factors were reported using the AOR with a 95% CI and a p-value of < 5%.ResultThe coverage of exclusive breastfeeding practice in Ethiopia was 56.05% (95% CI: 53.95%, 58.10%). The spatial pattern was non-random across the country’s regions. Somalia, Gambela, Benshangul Gumuz, Dire Dawa, and Harari regions had low clustering of exclusive breastfeeding practices, whereas Amhara, Eastern SNNPR, and Central and Northern Oromia regions had high clustering. Children born through caesarean delivery [AOR = 0.36; 95% CI: 0.21, 0.63], initiated breastfeeding within the first 1 h [AOR = 0.55; 95% CI: 0.34, 0.90], after 1–24 h of delivery [AOR = 0.36; 95% CI: 0.24, 0.54], after a day [AOR = 0.04; 95% CI: 0.02, 0.08], and women residing in the pastoralist region [AOR = 0.22; 95% CI: 0.12, 0.39] or city administrations [AOR = 0.49; 95% CI: 0.27, 0.89] had lower odds of exclusive breastfeeding practice.ConclusionExclusive breastfeeding practice in Ethiopia remained low. The practice had a spatial variation across the country. Caesarean section delivery, late breastfeeding initiation, and region were statistically significant variables. Therefore, promoting timely initiation of breastfeeding and improving the utilization of maternal health services and designing special intervention strategy for women residing in city administrations and pastoralist regions of the country may increase the coverage of exclusive breastfeeding practice.