Occupation Of States Research Articles

Interference of longitudinal and transversal fragmentations in the Josephson tunneling dynamics of Bose-Einstein condensates

Abstract The dynamics of bosons in Josephson junctions have drawn much attention where the bosons are initially condensed. When interacting bosons tunnel back and forth along the junction, depletion and eventually fragmentation develop. Here, we pose the question how do fragmented bosons tunnel in a bosonic Josephson junction? To this end, we exploit the transverse degree-of-freedom of the junction to encode initial fragmentation to the bosonic cloud. We analyze the survival probability along the junction, fluctuations of particle positions across the junction, and the occupancy of the lowest single-particle states. The dynamics found is rich and includes the speed up of the
collapse of density oscillations and slow down of the revival process. It is found that a fully fragmented state significantly accelerates the revival process compared to the conventional Bose-Einstein condensate. To explain the underlying many-body mechanism, we show that the initial fragmentation in the transverse direction interferes with the development of fragmentation in time along the junction. The dynamics of occupation in the first excited single-particle state defines whether interference of fragmentations occurs in the junction. The interference mechanism is a purely many-body effect that does not occur in the mean-field dynamics. All in all, we show that the interference of longitudinal and transversal fragmentations leads to new rules for macroscopic tunneling phenomena of interacting bosons in traps.

Occupational health and safety management systems – analysis of selected requirements for evaluation of occupational health and safety performance

The publication undertakes the problems of occupational health and safety in the aspect of requirements for occupational health and safety management systems. The aim of the work was analysis of selected aspects of evaluation of occupational health and safety performance according to the ISO 45001:2018 standard. Performance evaluation and improvement are one of the basic requirements, that determine the suitability, adequacy, effectiveness and efficiency of management systems. The essential element of the study was the development of assumptions for evaluation of occupational health and safety performance, which include the analysis of occupational health and safety state and the evaluation of occupational health and safety management systems.

Abundance-mediated species interactions.

Species interactions shape biodiversity patterns, community assemblage, and the dynamics of wildlife populations. Ecological theory posits that the strength of interspecific interactions is fundamentally underpinned by the population sizes of the involved species. Nonetheless, prevalent approaches for modeling species interactions predominantly center around occupancy states. Here, we use simulations to illuminate the inadequacies of modeling species interactions solely as a function of occupancy, as is common practice in ecology. We demonstrate erroneous inference into species interactions due to error in parameter estimates when considering species occupancy alone. To address this critical issue, we propose, develop, and demonstrate an abundance-mediated interaction framework designed explicitly for modeling species interactions involving two or more species from detection/non-detection data. We present Markov chain Monte Carlo (MCMC) samplers tailored for diverse ecological scenarios, including intraguild predation, disease- or predator-mediated competition, and trophic cascades. Illustrating the practical implications of our approach, we compare inference from modeling the interactions in a three-species network involving coyotes (Canis latrans), fishers (Pekania pennanti), and American marten (Martes americana) in North America as a function of occupancy states and as a function of abundance. When modeling interactions as a function of abundance rather than occupancy, we uncover previously unidentified interactions. Our study emphasizes that accounting for abundance-mediated interactions rather than simple co-occurrence patterns can fundamentally alter our comprehension of system dynamics. Through an empirical case study and comprehensive simulations, we demonstrate the importance of accounting for abundance when modeling species interactions, and we present a statistical framework equipped with MCMC samplers to achieve this paradigm shift in ecological research.

Smart Meeting Room Access Control and Management Via IOT

In Most Meeting Room Scheduling or Management System, The Availability of Meeting Rooms Are Mainly Based on Pre-Determined Schedules. However, Since the Meeting Duration Is Not Always Exact as It Is Scheduled, There Are Some Situations That A Meeting Room Is Underutilized. Therefore, In This Paper, We Present A Smart Meeting Room Scheduling and Management System Which Detect Occupancy Status of Meeting Rooms in Real Time and Integrate This Information into The Scheduling Application to Support Meetings and Increase Room Utilization. Occupancy Data Is Sent to A Central Application Server by UDP Over Ip Protocols. On This Server, A Web Application Is Developed and Hosted to Not Only Allow People Book Rooms for Their Meetings, But Also Check the Utilization of These Rooms Based on Predefined Policies. The System Also Supports Meetings by Providing Real-Time Availability of Meeting Rooms to Users.

Fusion algorithms on identifying vacant parking spots using vision-based approach

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>In densely populated cities, parking space scarcity results in issues like traffic congestion and difficulty finding parking spots. Recent advancements in computer vision have introduced methods to address parking lot management challenges. The availability of public image datasets and rapid growth in deep learning technology has led to vision-based parking management studies, offering advantages over sensor-based systems in comprehensive area coverage, cost reduction, and additional functionalities. This study presents an innovative fusion algorithm that integrates object detection with occupancy state algorithms to accurately identify vacant parking spaces. The employment of the YOLOv7 framework for vehicle instance segmentation, combined with three occupancy algorithms Euclidean distance (ED), intersection over reference (IoR), and intersection over union (IoU) are compared to determine the occupancy state of observed areas. The proposed method is evaluated using the CNRPark-EXT dataset, and its performance is compared with state-of-the-art methods. As a result, the proposed approach demonstrates robustness under varying conditions. It outperforms existing methods in terms of system evaluation performance, achieving accuracies of 98.88%, 97.99%, and 90.04% for ED, IoR, and IoU, respectively. This fusion detection method enhances adaptability and addresses occlusions, emphasizing YOLOv7’s advantages and accurate shape approximation for slot annotation. This study contributes valuable insights for effective parking management systems and has potential usage in the real-world implementation of intelligent transportation systems.</p></div></div></div>

New regime of the Coulomb blockade in quantum dots

We consider how the absence of thermalization affects the classical Coulomb blockade regime in quantum dots. By solving the quantum kinetic equation in the experimentally accessible regime when the dot has two relevant occupation states, we calculate the current–voltage characteristics for arbitrary coupling to the leads. If the couplings are strongly asymmetric, the Coulomb staircase is practically reduced to the first step, which is independent of the charging energy, when the Fermi energy is comparatively small, while the standard thermalized results are recovered in the opposite case. When the couplings are of the same order, the absence of thermalization has a new, striking signature—a robust additional peak in the differential conductance.

Mechanised Safety Verification for a Distributed Autonomous Railway Control System

We present a distributed railway interlocking (IXL) method based on trains communicating with switch boxes deployed along the railway network for switching points and monitoring the occupancy states of track elements. The method does not require any centralised IXL components. A distributed architecture is proposed that carefully separates the overall business logic and automated train operation from the safety-critical automated train protection and distributed IXL logic. This architecture is also suitable for autonomous trains traversing the railway network. The safety of the IXL logic is formally proven, using the Isabelle/HOL proof assistant. Experiments confirm that this proof-based approach is superior to model checking approaches, since the model checking effort grows exponentially with the size of the railway network. In contrast to this, the mathematical safety proof is performed once and for all railway networks fulfilling a realistic well-formedness condition. For a concrete network, only the well-formedness of the network and its initial train placements has to be verified, whereas the safety of the dynamic behaviour is a consequence of the network-independent safety proof.

Formation of the national concept of transitive justice

The scientific article is devoted to researching the concept of transit justice and clarifying its significance for Ukraine. The concept of transitive justice is very relevant, which is connected with the spread of internal and interstate conflicts. It is noted that the national model of transitive justice is relatively new for domestic legal practice, therefore the understanding of its essence and the development of mechanisms is still at the initial stage. It is emphasized that transitive justice involves a set of measures aimed at overcoming the consequences of war and occupation and developing mechanisms that will prevent the recurrence of conflicts in the future. The concept of transitive justice is used by states that are transitioning from a state of conflict and occupation to a state of peace, it does not contain universal formulas for all states. Attention is focused on the fact that under modern conditions in Ukraine, the directions of transitive justice are implemented situationally, unsystematically and do not have proper legal consolidation. The international experience of the implementation of the mentioned concept, taking into account the Ukrainian realities, should be defined as useful. Recognition of the supremacy of international law and the tendency to increase the role of non-judicial mechanisms in the justice system will provide an opportunity to use non-judicial mechanisms in order to strengthen sustainable peace. Implementation of the principles of transitive justice affects the development of the legal system of Ukraine and should ensure its stabilization, creation of conditions for its modernization and sustainable development. At the same time, it is stated that it is necessary to carry out a lot of work to establish the reasons for which the war is taking place, to find out what happened directly during the armed conflict. It should be understood that the end of the war is not just the return of the occupied territories under the jurisdiction of Ukraine, but the beginning of a difficult path to resolve the consequences of the conflict and search for a compromise. It is emphasized that there is a real need to implement the model of transitive justice, as an important tool for resolving the military conflict and the main direction of state legal policy, in the conditions of Russia’s armed aggression against Ukraine.

Development and Application of IoT-Based Emotional Lighting System: Focusing on Emotion Analysis Using Instant Message Data

ABSTRACT Research on human-centric lighting (HCL) is actively being conducted to provide an optimal lighting environment that takes into account the physical and mental states of humans, as well as energy savings and improvements in convenience. This study is a proof-of-concept study that proposes and implements the concept of an IoT-based emotional lighting system using instant message (IM) data. The system we propose performs emotion analysis based on IM data to automatically control the lighting environment of the home according to the emotional state of the occupants when they return home. The lighting system was programmed using Node-RED to extract only the necessary data for emotion analysis from IM data, translate it into English, and perform emotion analysis in IBM Cloud’s Natural Language Understanding (NLU) to adjust the color of the lighting according to the emotional state of the occupants. Based on previous studies that demonstrated the effect of color on emotion regulation, this study selected lighting colors that are appropriate for the emotional state of occupants. The operability of the system was then tested through its implementation in a mock-up studio. Our proposed emotional lighting system, which utilizes IM data, enhances convenience by minimizing the need for occupants to manually intervene. Furthermore, this system can be effortlessly implemented in any personal space and offers scalability due to its seamless integration with other smart devices.

SentinelGuard Pro: Deploying Cutting‐Edge FusionNet for Unerring Detection and Enforcement of Wrong Parking Incidents

ABSTRACTWrong parking incidents pose a pervasive challenge in urban environments, disrupting the smooth flow of traffic, compromising safety and contributing to various logistical issues. Unauthorized parking occurs when vehicles are parked in locations not designated for such purposes, leading to a myriad of problems for both authorities and the general public. This research introduces a pioneering approach to confront the persistent challenge of unauthorized parking incidents in urban environments. The study focuses on harnessing the advanced capabilities of the FusionNet model to enhance the accuracy of license plate detection. This paper introduces the YOLO v8 Model, a deep learning architecture designed to enhance urban parking management by accurately detecting vehicles parked in unauthorized slots. The objective is to enhance parking management efficiency by accurately detecting vehicles and their occupancy status in designated parking areas. The methodology begins with data collection and preprocessing of images of parking spaces, followed by the training of YOLO v8 to identify vehicles and parking spaces in real time. Leveraging a diverse dataset encompassing various parking scenarios, including instances of unauthorized parking, the model achieves an accuracy of 98.50% in identifying vehicles outside designated areas. This model segments characters from detected license plates, enabling the accurate extraction of alphanumeric information associated with each vehicle. The integrated system provides timely identification of parking violations and facilitates effective enforcement actions through captured license plate data. Results demonstrate the model's effectiveness in real‐world scenarios, showcasing its potential for improving urban safety and efficiency. The implementation of FusionNet in the Python programming language, the proposed solution aims to streamline parking management, improve compliance with parking regulations and enhance overall urban mobility., with robust precision 96.17%, specificity 97.42% and sensitivity 96.19%, surpassing other MobileNet, CNN, ANN, DNN and EfficientNet models.

Importing Atomic Rare‐Earth Sites to Activate Lattice Oxygen of Spinel Oxides for Electrocatalytic Oxygen Evolution

AbstractSpinel oxides have emerged as highly active catalysts for the oxygen evolution reaction (OER). Owing to covalency competition, the OER process on spinel oxides often follows an arduous adsorbate evolution mechanism (AEM) pathway. Herein, we propose a novel rare‐earth sites substitution strategy to tune the lattice oxygen redox of spinel oxides and bypass the AEM scaling relationship limitation. Taking NiCo2O4 as a model, the incorporation of Ce into the octahedral site induces the formation of Ce−O−M (M=Ni, Co) bridge, which triggers charge redistribution within NiCo2O4. The developed Ce−NiCo2O4 exhibits remarkable OER activity with a low overpotential, satisfactory electrochemical stability, and good practicability in anion‐exchange membrane water electrolyzer. Theoretical analyses reveal that OER on Ce−NiCo2O4 surface follows a more favorable lattice oxygen mechanism (LOM) pathway and non‐concerted proton‐electron transfers compared to pure NiCo2O4, as also verified by pH‐dependent behavior and in situ Raman analysis. The 18O‐labeled electrochemical mass spectrometry provides direct evidence that the oxygen released during the OER originates from the lattice oxygen of Ce−NiCo2O4. We discover that electron delocalization of Ce 4f states triggers charge redistribution in NiCo2O4 through the Ce−O−M bridge, favoring antibonding state occupation of Ni−O bonding in [Ce−O−Ni] unit site, thereby activating lattice oxygen redox of NiCo2O4 in OER. This work provides a new perspective for designing highly active spinel oxides for OER and offers significant insights into the rare‐earth‐enhanced LOM mechanism.

Importing Atomic Rare-Earth Sites to Activate Lattice Oxygen of Spinel Oxides for Electrocatalytic Oxygen Evolution.

Spinel oxides have emerged as highly active catalysts for the oxygen evolution reaction (OER). Owing to covalency competition, the OER process on spinel oxides often follows an arduous adsorbate evolution mechanism (AEM) pathway. Herein, we propose a novel rare-earth sites substitution strategy to tune the lattice oxygen redox of spinel oxides and bypass the AEM scaling relationship limitation. Taking NiCo2O4 as a model, the incorporation of Ce into the octahedral site induces the formation of Ce-O-M (M=Ni, Co) bridge, which triggers charge redistribution within NiCo2O4. The developed Ce-NiCo2O4 exhibits remarkable OER activity with a low overpotential, satisfactory electrochemical stability, and good practicability in anion-exchange membrane water electrolyzer. Theoretical analyses reveal that OER on Ce-NiCo2O4 surface follows a more favorable lattice oxygen mechanism (LOM) pathway and non-concerted proton-electron transfers compared to pure NiCo2O4, as also verified by pH-dependent behavior and in situ Raman analysis. The 18O-labeled electrochemical mass spectrometry provides direct evidence that the oxygen released during the OER originates from the lattice oxygen of Ce-NiCo2O4. We discover that electron delocalization of Ce 4f states triggers charge redistribution in NiCo2O4 through the Ce-O-M bridge, favoring antibonding state occupation of Ni-O bonding in [Ce-O-Ni] unit site, thereby activating lattice oxygen redox of NiCo2O4 in OER. This work provides a new perspective for designing highly active spinel oxides for OER and offers significant insights into the rare-earth-enhanced LOM mechanism.

Dynamics of AKAP/Calmodulin complex is largely driven by ionic occupancy state

AKAP79/150 is a scaffold protein found in dendritic spines and other neuronal compartments. It localizes and regulates phosphorylation by protein kinase A and C and is, in turn regulated by Ca2+, mediated by Calmodulin (CaM). Thus, the interaction of AKAP79/150 with CaM is of biological interest. A 2017 study used a peptide cross linking coupled to mass spectrometry (XLMS) to identify the CaM binding site on AKAP79/150 and subsequently solved an X-ray crystallography structure of CaM in complex with a short helical AKAP79/150 peptide. The XRD structure revealed an unusual mixed ionic occupancy state of CaM as bound to the AKAP79/150 peptide. In this molecular dynamics-based study, we have explored the motional modes of the CaM-AKAP helix complex under three ionic occupancy conditions. Our results indicate that the dynamics of this CaM backbone is largely dominated by the ionic occupancy state. We find that binding of the AKAP79/150 peptide to CaM is not preferentially stabilized in energetic terms in the Ca2+ state as compared to apo. However, the Mg2+ state is destabilized energetically as compared to the apo state. In addition, in the Ca2+ state, the AKAP79/150 peptide appears to be preferentially stabilized by additional hydrogen bonds. Our simulations suggest that further structural biology studies should be carried out, with a focus on driving the system equilibrium to full Ca2+ occupancy. NMR studies may be able to capture conformational states which are not seen in crystals.

Flotillin-2 dampens T cell antigen-sensitivity and functionality.

T cell receptor (TCR) engagement triggers T cell responses, yet how TCR-mediated activation is regulated at the plasma membrane remains unclear. Here, we report that deleting the membrane scaffolding protein Flotillin-2 (Flot2) increases T cell antigen-sensitivity, resulting in enhanced TCR signaling and effector function to weak TCR stimulation. T cell-specific Flot2-deficient mice exhibited reduced tumor growth and enhanced immunity to infection. Flot2-null CD4+ T cells exhibited increased T helper 1 polarization, proliferation, Nur77 induction, and phosphorylation of ZAP70 and ERK1/2 upon weak TCR stimulation, indicating a sensitized TCR-triggering threshold. Single cell-RNA sequencing suggested that Flot2-null CD4+ T cells follow a similar route of activation as wild-type CD4+ T cells but exhibit higher occupancy of a discrete activation state under weak TCR stimulation. Given prior reports that TCR clustering influences sensitivity of T cells to stimuli, we evaluated TCR distribution with super-resolution microscopy. Flot2 ablation increased the number of surface TCR nanoclusters on naïve CD4+ T cells. Collectively, we posit that Flot2 modulates T cell functionality to weak TCR stimulation, at least in part, by regulating surface TCR clustering. Our findings have implications for improving T cell reactivity in diseases with poor antigenicity, such as cancer and chronic infections.

Predictive Factors of State Licensure Board Disciplinary Actions in Occupational Therapy.

One primary function of occupational therapy state licensure boards (SLBs) is the discipline of ethical misconduct by licensed occupational therapy practitioners. However, SLB sanctioning is poorly understood by practitioners, regulators, and the public. To identify predictors of occupational therapy practitioner sanctioning outcomes in the United States. Retrospective study; all public final consent orders and database entries provided online by SLBs were analyzed. Supervised gradient boosting machine learning, logistic regression, and contingency tables were used to generate odds ratios for variables associated with each sanctioning outcome. Multinomial testing was used to identify attribute overrepresentation among cases and national practitioner distributions. A total of 2,400 cases were analyzed across 47 states and Washington, DC. None. Numerous complaint and respondent attribute variables were collected from final consent orders and database entries. Complaint reason, practice setting, and complaint source had the highest influence on predicting sanction outcome; geographic region, number of complaints in a given case, and length of investigation in months were secondarily influential. Being male or a certified occupational therapy assistant was associated with higher odds of severe sanctioning outcomes. Disciplinary actions against occupational therapy practitioners were determined by numerous contextual factors; however, the most influential factors were complaint reason, practice setting, and complaint source. These results provide direction for exploring factors that predict sanctioning outcomes in the United States and also provide occupational therapy practitioners and SLBs a basis of applied outcomes that may improve implementation and education regarding clinical practice ethics. Plain-Language Summary: Occupational therapy state licensure boards (SLBs) are responsible for disciplining licensed occupational therapy practitioners for ethical misconduct. SLB sanctioning is poorly understood by practitioners, regulators, and the public. In this study, we identify the factors that predict the sanctioning outcomes of occupational therapy practitioners. The results may help state regulators, educators, and national associations more effectively act in a way that protects the public faith in occupational therapy services by providing contextualized information on practitioner behaviors that result in specific sanctioning outcomes. The study findings also provide occupational therapy practitioners and SLBs a basis of applied outcomes that may improve the implementation of and education regarding clinical practice ethics.

Exploring Co2TiRE (RE = Nd and Tb) as a promising shape memory alloy using DFT methods

Our study employs self-consistent ab-initio calculations using highly precise spin-polarized density functional theory with both GGA and GGA+U approaches, coupled with the Boltzmann transport scheme. This comprehensive approach investigated the structural stability, magneto-electronic behavior, thermophysical characteristics, and thermoelectric transport properties of Co2TiRE (RE = Nd, Tb) Heusler alloys. Through structural optimizations, we confirm that these materials exhibit ferromagnetic behavior. Analysis of band occupation and density of states using GGA and GGA+U methods reveals that both compounds are metallic in both spin configurations. We evaluated key transport properties such as the Seebeck coefficient, electrical and thermal conductivity and the figure of merit to understand their potential in thermoelectric applications. Conservative estimates of the Seebeck coefficient and the figure of merit suggest promising applications in thermoelectric energy harvesting technologies. Additionally, we provide a comprehensive analysis of the thermophysical behavior, including the Debye temperature, thermal expansion, and specific heat, to assess the alloys thermodynamic stability across varying temperature and pressure conditions.

Scrutinizing the electronic structure, magnetic, mechanical, thermodynamic, optical and thermoelectric properties of lead-free hafnium based Hf2VP (P = Si, Sn) full Heusler alloys

The study of energy harvesting and thermoelectric materials has drawn more attention in the last several years. The great thermal stability of these materials is advantageous for thermoelectric devices, in addition to their structural capacity for showcasing and incorporating diverse novel concepts to augment the thermoelectric figure of merit. In the current study, we have predicted the physical properties of Hf2VP (P = Si, Sn) Heuslers using density functional theory in conjunction with the Boltzmann transport scheme. The strength and ductility of these materials are ascertained by simulating elastic characteristics The exchange correlation potential is handled via the modified Becke–Johnson potential (mBJ) and the generalized gradient approximation of Perdew, Burke, and Ernzerhof (GGA-PBE). Near the Fermi level, the band profiles for Hf2VSi and Hf2VSn Heuslers were found to be n-type indirect band-gap respectively. The thermodynamic stability of these materials is approved by the formation and cohesive energy. The relationships between different transport parameters are predicted using the band occupation and density of states in the post DFT treatment. Slack’s equation has identified the most significant lattice component of heat conductivity with great precision. These materials are likely to find use in the design of memory devices and future thermoelectric and energy harvesting materials due to their half-metallic nature and efficient thermoelectric parameters, such as electrical conductivity, Seebeck coefficient, thermal conductivity, power factor, and ZT.

Ramsey interferometry of nuclear spins in diamond using stimulated Raman adiabatic passage

Abstract We report the first experimental demonstration of stimulated Raman adiabatic passage (STIRAP) in nuclear-spin transitions of 14N within nitrogenvacancy (NV) color centers in diamond. It is shown that the STIRAP technique suppresses the occupation of the intermediate state, which is a crucial factor for improvements in quantum sensing technology. Building on that advantage, we develop and implement a generalized version of the Ramsey interferometric scheme, employing half-STIRAP pulses to perform the necessary quantum-state manipulation with high fidelity. The enhanced robustness of the STIRAP-based Ramsey scheme to variations in the pulse parameters is experimentally demonstrated, showing good agreement with theoretical predictions. Our results pave the way for improving the long-term stability of diamond-based sensors, such as gyroscopes and frequency standards.

Fundamental Laws and Quantum Dynamics

Background: Recently, we obtained a unitary theory of quantum mechanics and general relativity, where a quantum particle is a continuous distribution of matter in the two conjugate spaces of the coordinates and momentum, quantized by the equality of the mass parameter describing the relativistic dynamics of the matter, with the mass as an integral of the matter density. However, in this framework, we have not explicitly revealed the connection between our new theory and the fundamental laws of quantum mechanics. Methods: We analyzed in detail the three fundamental laws of quantum mechanics, explicitly describing experimental data: 1) Planck’s law of the blackbody electromagnetic radiation of a system of electrically charged harmonic oscillators, 2) Einstein’s law of the photon energy proportionality with the photon frequency, and 3) de Broglie’s law of the quantum particle as an oscillator in space. Results: We reobtained the two dynamical equations, in the conjugate spaces of the coordinates and momentum, as functions of the Lagrangian system, unlike the Schrödinger equation, depending on the Hamiltonian. Conclusion: According to the fundamental laws of quantum mechanics, a quantum particle is a continuous distribution of matter with an intrinsic mass, unlike the conventional quantum mechanics for the state occupation probabilities of punctual entities moving with the light velocity and getting an apparent mass only by collisions with some bosons pervading the whole universe. According to these laws, we obtained a quantum theory in agreement with common sense, classical logic, and general relativity.

Theory-driven design of local spin-state modulation at atomically dispersed iron sites for enhanced CO2 electroreduction

Herein, density functional theory (DFT) was used to guide the systematic design of highly efficient single-atom electrocatalysts to improve the kinetics of the CO2 reduction reaction (CO2RR). We present a novel class of catalysts that exhibit magnetic-proximity-induced exchange splitting (spin polarization). The design of these catalysts involved the precise modulation of d-shell energy levels at metallic sites and the subsequent alteration of the atomic/molecular orbitals of the adsorbed intermediates. To validate the effectiveness of our design strategy, we introduced neighboring nitrogen (N) doping near the Fe-N4 coordination environment, demonstrating the successful manipulation of the local spin state of the active sites. The results of the theoretical calculations align with the experimental results, with remarkable selectivity exceeding 90 % at low potentials (<-0.5 V vs. RHE) and sustained electrocatalytic activity for over 24 h. In situ characterization further revealed that a modulated local spin state led to a decrease in the occupation of the Fe 3d spin-down electronic states below the Fermi level. Concurrently, electrons migrated to the frontier antibonding orbitals of *COOH. This dual effect resulted in a lower reaction energy (ΔG), representing a thermodynamic benefit, and accelerated proton transfer to *COOH, representing a kinetic benefit, collectively enhancing the electrocatalytic process.