Differential Power Research Articles

Collaborative ethnography and a call for pluralism and dialogic knowledge in health equity debates and global cancer research culture.

Scholars in medical anthropology note that, despite more than 25 years of anthropological studies on cancer, much of this scholarship remains marginal in mainstream public health approaches. This paper examines social practices, biases, and unnoticed assumptions in mainstream global health research culture that prevents anthropology from having a more influential role in cancer research and policy agendas. It focuses on the day-to-day, ordinary, micro academic practices in which differential power distribution exacerbates inequity within the field, ignoring the role played by approaches with disciplinarian, epistemological and geopolitical peripheries. Inspired by a Bourdieusian epistemic reflexivity, this autoethnography systematized and analyzed through decolonial lenses some deterrents within real-world-research practices, including as the corpus own studies on cancer and inequalities studies that were based on collaborative ethnography (2013-2024). Six categories account for such deterrents in the global field: 1) Public health mainstream-centrism and the lack of recognition of anthropological knowledge principles; 2) Restrictive conception of ethics; 3) Similis Simili Gaudet biases - to be inclined to select what is alike; 4) Ethnocentric and naïve assumptions in relation to the road from evidence to practice; 5) Unconsidered dimensions of collaborations: Strengthening citizenship; 6) The moral economy of (only) professional trajectories interests and hidden priorities. It concludes by noting that anthropology has a lot to provide in the search for a genuinely democratic, plural, and decentralized knowledge in global cancer equity debates strengthening paradigms of dialogue, still so fragile and invisible in the field of cancer and public health in general.

An Improved Photovoltaic Differential Power Processing System Using Bidirectional Boost-Type Converters With Synchronous Switching

An Improved Photovoltaic Differential Power Processing System Using Bidirectional Boost-Type Converters With Synchronous Switching

Cross-cultural adaptation, reliability and validity of the persian version of the functional assessment scale for acute hamstring injuries

BackgroundThe Functional Assessment Scale for Acute Hamstring Injuries (FASH) which measure symptom’s severity and impact on physical activity and sports ability in individuals with acute hamstring muscle injury, is not available in Persian. The aim of this study was to translate and cross-culturally adapt the FASH questionnaire to Persian and to assess the psychometric properties of the translated version.MethodsThe Persian-translation and cross-cultural adaptation processes were based on World Health Organization method. A total of 160 participants compromising of four groups: (1) acute hamstring injury (N = 40), (2) other lower extremity injury (N = 40), (3) risk of acute injury (N = 40), and (4) healthy control (N = 40) were recruited to complete the Persian version of FASH (FASH-P) questionnaire twice with an interval of 48–60 h. The Short Form Health Survey (SF-36) and Lower Extremity Functional Scale (LEFS) were used to assess the criterion validity. Test-retest reliability, internal consistency, criterion validity, Dimensionality and floor/ceiling effects were evaluated to assess the FASH-P psychometric properties.ResultsThe FASH questionnaire were translated to Persian without any major problems. The FASH-P showed excellent power of differentiation because the scores were significantly different among the four groups. Regarding psychometric performances, excellent test–retest reliability (Intraclass correlation coefficient of 0.997) and a high level of internal consistency (Cronbach’s alpha of 0.966) were observed. The FASH-P total score was significantly correlated with SF-36 and LEFS questionnaires representing an excellent criterion validity. No floor or ceiling effect were found for total score in Hamstring muscle injury group.ConclusionsDue to the excellent psychometric performance, the FASH-P can be used as a reliable and valid tool for evaluating the severity of symptoms and sports ability in Persian-speaking patients with hamstring muscle injury.

Switched-Capacitor-Based Hybrid Resonant Bidirectional Buck–Boost Converter for Improving Energy Harvesting in Photovoltaic Systems

Photovoltaic (PV) modules are often connected in series to achieve the desired voltage level in practical applications. A common issue with this setup is module mismatch, which can be either permanent or temporary and is caused by various factors. The differential power processing (DPP) concept has emerged as a prominent solution to address this problem. However, a significant drawback of current DPP topologies is their reduced performance under certain conditions, particularly in cases of permanent mismatch. As a result, applications involving the DPP concept for permanent mismatches remain underexplored. In this context, the goal of this work is to develop and implement a novel DPP topology capable of increasing energy harvesting in PV systems under permanent mismatch. The proposed hybrid architecture combines features from both bidirectional buck–boost (BBB) and resonant switched capacitor (ReSC) converters. The ReSC converter operates under soft-switching conditions, minimizing undesirable losses. Key advantages of the proposed converter include fewer switches, lower voltage stress, and soft-switching operation, making it suitable for PV systems with mismatched modules. Experimental tests showed an energy harvesting improvement under the assessed conditions.

Enhancing Long-Term Robustness of Inter-Space Laser Links in Space Gravitational Wave Detection: An Adaptive Weight Optimization Method for Multi-Attitude Sensors Data Fusion

The stable and high-precision acquisition of attitude data is crucial for sustaining the long-term robustness of laser links to detect gravitational waves in space. We introduce an effective method that utilizes an adaptive weight optimization approach for the fusion of attitude data obtained from charge-coupled device (CCD) spot-positioning-based attitude measurements, differential power sensing (DPS), and differential wavefront sensing (DWS). This approach aims to obtain more robust and lower-noise-level attitude data. A system is designed based on the Michelson interferometer for link simulations; validation experiments are also conducted. The experimental results demonstrate that the fused data exhibit higher robustness. Even in the case of a single sensor failure, valid attitude data can still be obtained. Additionally, the fused data have lower noise levels, with root mean square errors of 9.5%, 37.4%, and 93.4% for the single CCD, DPS, and DWS noise errors, respectively.

Differential pressure power generation in UGS: Operational optimization model and its implications for carbon emission reduction

Underground Gas Storage (UGS) is an important facility for natural gas peak adjustment and ensuring the balance between energy supply and demand. The daily gas injection and production capacity of large UGS can reach several hundred million or even billions of cubic meters, and the energy consumed by the injection and production equipment is not to be underestimated, which also contains a large amount of pressure energy that can be utilized for power generation. In this context, the optimization of low-carbon operation of UGS is of great practical significance in engineering. In this study, an innovative UGS system operation optimization method is proposed to integrate a natural gas differential pressure generator set in the UGS system. Considering the complex interconnections among multiple storage areas, multiple wells and wellsites, and the hydro-thermodynamic constraints during the operation of injection and production pipeline network, and with the objective of minimizing the carbon emission, the UGS integrated with Differential Pressure Power Generation System (UGSIDPPGS) is established. In order to solve this complex model, this paper designs an optimization solution framework based on variational assignment, which effectively avoids the problem of falling into inferior solutions during the solution process. The optimization model is applied to the case study of a large-scale depleted gas reservoir in China, and the optimal operation schemes under three scenarios are successfully obtained. The results show that the UGSIDPPGS optimization model, not only effectively utilizes the pressure energy, generates up to 56.908 × 106 kW h per month, and reduces the CO2 emission by 56,738 tons, but also achieves the low-carbon and economic operation of the UGS. In conclusion, the operation strategy proposed in this study is of great value for optimizing the operation of UGS, and provides practical guidance and suggestions for the low carbon and environmental protection of UGS and the utilization of new energy sources.

Seeing the Whole Together Through Relational Mapping: A Method for Engaging in Complex Systems Change

Complex global challenges cut across organizational and sectoral boundaries, increasing calls for holistic responses. Seeing the whole across diverse stakeholders is challenging for participants in complex systems, yet doing so is essential for engaging effectively in systems change. A promising new method known as relational mapping, based on relational coordination theory, has been used to facilitate complex systems change. Here, we propose that relational mapping can be applied to help participants (1) see the whole in relation to the parts, (2) share their explicit and tacit knowledge, (3) engage in dialogue across distinct perspectives supported by the map as a boundary object, (4) reduce the impact of power differences, and (5) prepare to co-design interventions from multiple perspectives. This paper presents an illustrative case of relational mapping in the context of public administration in a South Carolina community engaging in complex systems change. Our analysis suggests a set of boundary conditions for the success of relational mapping, including the willingness of participants to seek integrative solutions to a conflict or problem and facilitation that is attentive to differential power and status among stakeholders. We conclude that relational mapping is a powerful, theoretically grounded method that enables the visual assessment of multi-level stakeholder relationships, preparing participants to engage in complex systems change and then present a template for use of relational mapping more broadly.

Research and clearance analysis on of steam twin-screw expander employed in indutrial waste heat recovery

In actual factories, screw expanders frequently operate under partial loads.To address the lack of theoretical research and the risks of errors in engineering design associated with steam pressure differential power generation under these conditions,a simulation of the twin-screw expander's working process was developed. The rotor profile was designed, geometric variables such as rotor mesh clearance were calculated, and models for leakage and heat transfer were established. A suction pressure correction model was proposed for the suction process under partial loads, along with correction parameters to simplify simulations.Experimental results demonstrate that the twin-screw expander operates stably under highly fluctuating conditions, demonstrating excellent variable load performance.As the load decreases, the loss of suction pressure reduces the expander's pressure differential, leading to lower leakage and improved efficiency. When the load is reduced from 100 % to 65 %, the volumetric efficiency increases from 78.87 % to 84.76 %, and the isentropic efficiency rises from 66.81 % to 74.25 %.Compared to experimental data, the flow calculation error of the suction pressure correction model presented in this study is controlled within 3 %.This model addresses performance calculations under partial loads, ensuring that theoretical models better align with real-world applications and supporting accurate selection of twin-screw expanders.This model enables appropriate selection of expanders to reduce pressure losses and enhance economic efficiency.

Area-Time-Efficient Secure Comb Scalar Multiplication Architecture Based on Recoding

With the development of mobile communication, digital signatures with low latency, low area, and high security are in increasing demand. Elliptic curve cryptography (ECC) is widely used because of its security and lightweight. Elliptic curve scalar multiplication (ECSM) is the basic arithmetic in ECC. Based on this background information, we propose our own research objectives. In this paper, a low-latency and low-area ECSM architecture based on the comb algorithm is proposed. The detailed methodology is as follows. The recoding-k algorithm and randomization-Z algorithm are used to improve security, which can resist sample power analysis (SPA) and differential power analysis (DPA). A low-area multi-functional architecture for comb is proposed, which takes into account different stages of the comb algorithm. Based on this, the data dependency is considered and the comb architecture is optimized to achieve a uniform and efficient execution pattern. The interleaved modular multiplication algorithm and modified binary inverse algorithm are used to achieve short clock cycle delay and high frequency while taking into account the need for a low area. The proposed architecture has been implemented on Xilinx Virtex-7 series FPGA to perform ECSM on 256-bits prime field GF(p). In the hardware architecture with only 7351 slices of resource usage, a single ECSM only takes 0.74 ms, resulting in an area-time product (ATP) of 5.41. The implementation results show that our design can compete with the existing state-of-the-art engineering in terms of performance and has higher security. Our design is suitable for computing scenarios where security and computing speed are required. The implementation of the overall architecture is of great significance and inspiration to the research community.

B-350 The application of MALDI-TOF imaging to biomarker discovery in a mouse model of papillomavirus associated tumorigenesis

Abstract Background Human papillomavirus (HPV) can cause infection and dysplasia in cutaneous epithelium of immunodeficient patients. An animal model has been developed to study HPV-associated tumorigenesis using Nude mouse (Foxn1nu) and mouse papillomavirus (MmuPV1). This study applies MALDI-TOF imaging to compare the expression pattern of small molecules between viral-infected dysplastic mouse skin and mock-infected control tissue. Three sets of molecules showing distinct patterns are identified in correlation with the upregulation of an enzyme in related biosynthetic pathway. Methods Nude mice were wounded on tail and inoculated with MmPV1 suspension (1×109 viral DNA genomes per infected site) or PBS 24 hours later for treatment and control group, respectively. Tail skins were harvested 4 weeks post-infection and processed for cryosectioning. Tissue sections were analyzed using timsTOF flex (Bruker) under negative ion mode with 9-aminoacridine as the matrix. Viral infection (MmuPV1-L1 antigen) and enzyme expression (3'-phosphoadenosine 5'-phosphosulfate synthetase 1, PAPSS1) were assessed by immunofluorescence on adjacent sections. Results Three peaks demonstrated distinct distribution patterns in mouse skin. One peak at m/Z = 465 was identified as cholesterol sulfate (CS) by tandem MS and comparing with the standard. CS was enriched in keratinocytes, hair follicles, and blood vessels in normal skins, and it increased in dysplastic skins with enhanced angiogenesis. The combined peaks at m/Z = 327 & 329 were tentatively identified as docosahexaenoic acid (DHA) and docosapentaenoic acid (DPA). These long chain polyunsaturated fatty acids (LC-PUFAs) were present in the dermis as foci partially co-localized with CS, and they also increased in virus-infected skins. The peak at m/Z = 426 may represent a combination of ADP and APS. Although these two isobars cannot be separated by tandem MS, APS was revealed by the presence of sulfur isotopes at expected natural abundance (34S and 32S). They were present at a low level in the epidermis of normal skins but significantly increased after virus infection. APS and ADP were closely associated with the proliferating cells, and the signal intensity also increased with the degree of tissue dysplasia. As a single factor, APS & ADP demonstrated a fair differential power for MmuPV1-induced dysplastic skin and normal control (AUC of ROC curve = 0.75). The bifunctional enzyme PAPSS1 catalyzes the conversion of ATP to 3’-phosphonato-5’-adenyl sulfate (PAPS) via APS as an intermediate. Interestingly, immunofluorescence showed the expression of PAPSS1 also increased significantly with the severity of tissue dysplasia and MmuPV1 infection. Conclusions MALDI-TOF imaging reveals three sets of molecules with distinct patterns in mouse skin, and their levels are increased during MmuPV1-induced epithelium dysplasia. As a precursor of the common sulfate donor (PAPS), increased APS and ADP in the epidermis of virus-infected skins indicate an upregulation of sulfation pathway and adenine metabolism. This finding is supported by enhanced expression of enzyme PAPSS1 and an increased sulfation reaction product, CS. In addition, DHA and DPA are also increased in the dermis of virus-infected skins, implying a disturbance in LC-PUFA metabolism. This study demonstrates combined use of MALDI-TOF imaging and immunostaining in the search of novel biomarkers of HPV-associated tumorigenesis.

State‐of‐the‐Art 3DES Pipelined Cryptographic Engine Design Against Side‐Channel Attacks

ABSTRACTIn this paper, a high‐speed, low‐latency, and high‐security hardware‐implemented triple data encryption standard (3DES) cryptographic algorithm is proposed for securing data privacy. In order to achieve a high throughput for the 3DES architecture, the whole circuit is optimized with a 24‐stage pipelined design at first. For breaking the correlation between the processed data and power dissipation of the 3DES circuit against differential power analysis (DPA) attacks, two pseudo‐random number generators (PRNGs) are embedded to randomly alter the number of pipelined stages and data substitution locations within the 3DES circuit, respectively. Under such a circumstance, the proposed 3DES circuit is able to achieve high performance and strong robustness against DPA attacks without causing much overhead. As shown in the results, under the synthesis of SMIC 14‐nm process design kits (PDK), the clock frequency, area, power dissipation, and throughput of the proposed 3DES circuit, respectively, are achieved as 1.2 GHz, 26,435 m2, 21.05 mW, and 64 Gbps. Furthermore, when DPA attacks are executed on the proposed 3DES circuit, the corresponding secret key cannot be revealed even if 2 million plaintexts are enabled. In contrast, only 40,000 plaintexts are adequate to disclose the secret key of a regular pipelined 3DES circuit.

Differential Power Processing Based Control Framework for Multiple Battery Energy Storage Systems in DC Microgrids

Differential Power Processing Based Control Framework for Multiple Battery Energy Storage Systems in DC Microgrids

Application of Machine Learning Techniques for Countering Side-Channel Attacks in Cryptographic Systems

The use of machine learning algorithms in order to, not only, detect the adversarial intend behind side-channel attacks on cryptographic systems, but also to resist Differential Power Analysis (DPA) attacks. In particular, with the help of the DPA Challenge Dataset containing power traces of AES encryption operations, we propose a detailed step-by-step approach that includes data acquisition, preprocessing, feature extraction, and model assessment. The pre-processing includes noise reduction, normalization and segmental processing of the collected data for which basic statistical and frequency domain analysis can be used for extraction of relevant features. Support Vector Machines (SVMs) are then trained and tested in order to classify and in turn predict attack scenarios as per the subsequently derived features. As the outcome of the result pages show, the SVM model successfully classifies attack and non-attack traces at a rate of 88% on the validation set, which underlines the usage of machine learning to boost cryptographic security. Investigation of the feature relevance demonstrates that frequency-domain features, namely FFT coefficients are most impactful. The findings of this research prove that machine learning can be useful in preventing side-channel attacks apart from providing valuable information on enhancing the understanding of different defenses in cryptographic systems as well as future development of this domain.

Epistemic Injustices Online

AbstractIn typical instances of epistemic injustice, the victims and perpetrators are distinct across social groups – as marginally or dominantly situated. When epistemic injustice happens, the dominantly situated typically rely on prejudicial stereotypes to prevent the marginally situated from participating in epistemic activities. This is a manifestation/ exercise of their social power. However, with anonymity on the internet, a marginally situated person can effectively pose as a dominantly situated person and vice versa. When this happens, we cannot always tell who is behind a post. Consequently, relying on differential power relations, as in typical cases of epistemic injustice, might be ineffective online. In this paper, I argue for three ways that anonymity might complicate instances of epistemic injustice online.

The Emergence of New Sporothrix brasiliensis Genotypes in Current Epidemic of Sporotrichosis in Southeastern Brazil.

Zoonotic sporotrichosis caused by Sporothrix brasiliensis has become the main subcutaneous mycosis in Brazil. Minas Gerais (MG) is located in southeast Brazil and since 2015 has experienced an epidemic of zoonotic sporotrichosis. This study aimed to reconstruct the epidemiological scenario of sporotrichosis from S. brasiliensis in recent epizooty in the Metropolitan Region of Belo Horizonte (MRBH), MG. A total of 95 Sporothrix spp. isolates (Sporothirx brasiliensis n = 74, S. schenckii n = 11 and S. globosa n = 10) were subjected to Amplified Fragment Length Polymorphism (AFLP) genotyping and mating-type analysis to determine genetic diversity and population structure. Of these, 46 S. brasiliensis isolates were recovered from animals (cats n = 41 and dogs n = 5) from MRBH. Our study describes the high interspecific differentiation power of AFLP-based genotyping between the main phylogenetic Sporothrix groups. S. brasiliensis presents high genetic variability and pronounced population structure with geographically focused outbreaks in Brazil. The genetic groups include older genotypes from the prolonged epidemic in Southeast (Rio de Janeiro and São Paulo), South (Rio Grande do Sul), Northeast (Pernambuco) and new genotypes from the MRBH. Furthermore, we provide evidence of heterothallism mating strategy in pathogenic Sporothrix species. Genotypes originating in Rio de Janeiro and Pernambuco carry the predominant MAT1-2 idiomorph as opposed to genotypes from Rio Grande do Sul, which have the MAT1-1 idiomorph. We observed an overwhelming occurrence of MAT1-1 among MRBH isolates. Our study provides clear evidence of the predominance of a genetic group profile circulating in animals in Minas Gerais, independent of that disseminated from Rio de Janeiro. Our data can help us understand the genetic population processes that drive the evolution of this fungus in Minas Gerais and contribute to future mitigation actions for this ongoing epidemic.

Attributing spatially stratified heterogeneity in biodiversity of urban–rural interlaced zones based on the OPGD model

Urban–rural interlaced zones are characterized by the interpenetration of urban and rural elements, drastic changes in construction, relatively weak planning and management, and anthropogenic activities that constantly impact the ecological background. However, the ecological barriers and hinterland spaces of the city center provide important ecological functions. In this study, we selected forest birds as indicator species of the urban ecological environment and explored the spatial stratification and heterogeneity effects of environmental substrates and anthropogenic activities on bird diversity (species richness, abundance, Shannon–Wiener index, and Simpson index) in urban–rural interlaced zones using the optimal parameter geographic detector model to characterize the changes in ecological functions in these zones. The results of this study are as follows:(1) The bird diversity index in Minhang District, Shanghai, showed an obvious urban-rural gradient divergence with the transition of urban zone- rural-urban interface - rural zone.An agglomerative spatial differentiation pattern was observed more in the southeast but less in the northwest, with a high degree of spatial distribution concentrations and evident imbalance characteristics.(2) The spatially stratified heterogeneity in bird diversity in urban–rural interlaced zones was because of the combined action of multiple driving factors under the three dimensions of habitat environment, degree of urbanization, and anthropogenic interference. Most of the interactions between any two factors showed non-linear or bifactorial enhancement effects. Furthermore, the one-factor explanatory power of urbanization and anthropogenic interference factors on bird diversity was significantly higher than that of the habitat environment factor.(3) Population heat distribution (PD), distance to the center of Shanghai (DC), and nighttime lighting index(NTL) were the main drivers of spatially stratified heterogeneity in bird diversity and the key indicators of urban–rural gradient changes. The interaction between PD and DC had the strongest explanatory power for the spatial differentiation of bird diversity.

Cypress: an R/Bioconductor package for cell-type-specific differential expression analysis power assessment.

Recent methodology advances in computational signal deconvolution have enabled bulk transcriptome data analysis at a finer cell-type level. Through deconvolution, identifying cell-type-specific differentially expressed (csDE) genes is drawing increasing attention in clinical applications. However, researchers still face a number of difficulties in adopting csDE genes detection methods in practice, especially in their experimental design. Here we present cypress, the first experimental design and statistical power analysis tool in csDE genes identification. This tool can reliably model purified cell-type-specific (CTS) profiles, cell-type compositions, biological and technical variations, offering a high-fidelity simulator for bulk RNA-seq convolution and deconvolution. cypress conducts simulation and evaluates the impact of multiple influencing factors, by various statistical metrics, to help researchers optimize experimental design and conduct power analysis. cypress is an open-source R/Bioconductor package at https://bioconductor.org/packages/cypress/.

Evaluating the Effectiveness of Arabic Language Summative Tests in Senior High Schools: A Comprehensive Analysis

The aims of this study is to describe the validity, reliability, difficulty level, differentiation power and effectiveness of the Examination of Arabic language Sumative Test Items for Class X Students of Al-Mumtaz IT Senior High School. This research uses a quantitative approach. The data obtained were analyzed using IBM SPSS statistics 23. The subjects of this study were class X students totaling 29 students. The results of the analysis of 30 multiple choice questions showed that from the validity aspect it was found that 67% were valid and 33% were invalid. From the reliability aspect, it was found that the reliability level of the items was high, namely the r coefficient of 0.864. From the aspect of difficulty level, it was found that about 63% of the items were easy, about 37% of the items were moderate. From the aspect of distinguishing power, it was found that about 60% of the items were good, about 27% of the items were not good, about 13% of the items were quite good. And from the aspect of eliminators it was found that about 56% were accepted, about 26% were rejected and about 17% were revised.

Liquid Binary and Ternary Electrolytes Mixtures for Low-Temperature Sulfurized Carbon Batteries

Active sulfurized carbon (SC) has been proposed as promising alternative to enable sulfur as the next generation cathode material due its ability to confine sulfur and suppresses polysulfide shuttling. Pragmatic cell performance of SC electrodes needs to extend over a wide range of temperatures from -20 °C to 60 °C. Low-temperature performance of SC cells is mainly limited by electrolyte wettability, ionic mobility between the electrodes, and the nature of the formed solid electrolyte interphase. In this work we have utilized electrolyte binary and ternary mixtures based on carbonates, ethers, and fluorinated solvents to enhance the SC cell discharge performance up to -20 °C. To understand the effects of electrolyte mixtures in the cell performance we have utilized electrochemical impedance spectroscopy (EIS) as a function of temperature and voltage. The lower cell resistance translates into a higher rate capability, cyclability, and low-temperature performance. Based on the EIS response and its spectra deconvolution we proposed an apparent electrical equivalent circuit that permits the elucidation of resistance elements and their magnitude such as the ohmic, electron charge transfer, surface film, and mass transport resistance to provide a phenomenological understanding on how the mixtures can enhance the electrochemical performance. Furthermore, differential capacity analysis and Hybrid Pulse Power Characterization (HPPC), are utilized to support the characterization. Finally, best performance electrolyte mixtures were utilized to build >0.5 Ah pouch cells for testing at low temperatures, discharge rates, and pressure conditions.

Spatiotemporal Variation Characteristics and Driving Factors of Vegetation NPP in the Ulansuhai Nur Basin from 2001 to 2020

Vegetation net primary productivity （NPP） represents the ability of plants to fix ecosystem carbon, which is a key indicator to determine the health status and sustainable development of ecosystems. Its spatial and temporal changes and driving factors play an important role in revealing the status of vegetation restoration and guiding ecological restoration. Based on MODIS17A3 NPP data, land use, and meteorological data from 2001 to 2020, the temporal and spatial variation characteristics and driving factors of vegetation NPP in the Ulansuhai Nur Basin of Inner Mongolia were explored by using the methods of coefficient of variation, Theil-Sen Median trend analysis, Mann-Kendall significance test, Hurst index, and Geodetector. The results showed that： ① From 2001 to 2020, the vegetation NPP in the Ulansuhai Nur Basin showed a fluctuating upward trend, with an average value （in terms of C） of 141.03 g·（m2·a）-1 and an average increase rate of 2.33 g·（m2·a）-1. The vegetation NPP had obvious spatial differentiation, which was characterized by high in the southwest and low in the northeast and high in Hetao Plain and low in sandy land and mountainous areas. ② NPP mainly showed an increasing trend, and the area proportions of increasing, decreasing, and unchanged areas were approximately 80%, 3%, and 17%, respectively. The average coefficient of variation of vegetation NPP was 0.149, which mainly showed low fluctuation change, and the area accounted for approximately 51%. The future change trend of NPP was mainly characterized by anti-persistence, with an area ratio of approximately 75%. ③ Land use, altitude, maximum temperature, and slope were the dominant driving factors of variation NPP change in the Ulansuhai Nur Basin, and the q values were all above 0.200. The interaction between altitude and relative humidity had the greatest explanatory power for the spatial differentiation of vegetation NPP in the Ulansuhai Nur Basin. There were significant differences in the explanatory power of land use and all factors except nighttime light to the spatial differentiation of vegetation NPP in the Ulansuhai Nur Basin. According to the research results, in the future, we should strengthen the ecosystem management of the Ulansuhai Nur Basin； continue to implement strict ecological protection and restoration policies； and comprehensively consider factors such as climate, topography, and human activities to carry out comprehensive ecological management according to local conditions to improve the quality of ecosystem services.