Balancing Strategy Research Articles

Nutrient transport from the Ganga–Brahmaputra–Meghna River system to the Bay of Bengal: past and future trends

Abstract The Ganga–Brahmaputra–Meghna (GBM) river basin is a lifeline for the livelihoods and well-being of millions of inhabitants. It has been experiencing increasing nutrient emissions from anthropogenic activities since the 1970s. This paper describes total nitrogen (TN) and total phosphorus (TP) sources and transport in the GBM basin at a 0.5-degree resolution for the past (1970–2019) and future (2020–2050) according to Shared Socioeconomic Pathways scenarios. Our results indicate a three-fold increase in the delivery and export of TN and a two-fold increase of TP in the GBM basin between 1970 and 2019. Elevated nutrient levels are driven by agriculture mainly, with sewage discharge important particularly in the large number of densely populated urban areas. Continuing current nutrient management practices in a business as usual scenario will increase the risk of eutrophication in the GBM basin and the Bay of Bengal. Implementing nutrient reduction strategies in a sustainable scenario will reduce TN and TP loads and concentrations, but nutrient imbalances remain strong with continued risk of harmful algal blooms. These findings call for integrating nutrient stoichiometry with balanced nutrient reduction strategies to mitigate nutrient pollution in the GBM River basin.

Advances in the Pathogenesis, Diagnosis, Treatment, and Prognosis of Marginal Zone Lymphoma.

The management of marginal zone lymphoma (MZL), an indolent B-cell non-Hodgkin lymphoma, requires a personalized and adaptive approach due to its clinical and prognostic heterogeneity. We believe treatment should emphasize a balanced strategy considering the subtype, disease burden, symptoms, and actionable genetic or environmental factors, such as infections or autoimmune diseases. For asymptomatic patients with low tumor burden or disseminated disease, a watch-and-wait approach remains appropriate, given MZL's indolent nature and the risks of overtreatment. Conversely, for symptomatic or high-burden cases, early intervention with chemoimmunotherapy is recommended for effective disease control. Surgery remains essential for both diagnosis and the treatment of localized disease. Incorporating molecular profiling and prognostic models, such as MZL-IPI and POD24, is crucial for decision-making and risk stratification. Testing for infectious agents like Helicobacter pylori or Hepatitis C virus should be standard practice, as eradication therapy offers a targeted, less toxic, and effective option in select patients. With ongoing advancements in understanding dysregulated signaling pathways and the tumor microenvironment, we anticipate novel targeted therapies and combination regimens will further improve outcomes. We advocate for molecular testing at diagnosis to identify actionable biomarkers, particularly for patients with refractory or relapsed disease. Finally, MZL management requires vigilant follow-up with adjustments based on evolving disease features. Treatment decisions should integrate patient preferences, clinical context, and the latest evidence to maximize survival while preserving quality of life.

It’s Scary to Use It, It’s Scary to Refuse It: The Psychological Dimensions of AI Adoption—Anxiety, Motives, and Dependency

The current study examines the psychological factors shaping AI adoption, focusing on anxiety, motivation, and dependency. It identifies two dimensions of AI anxiety: anticipatory anxiety, driven by fears of future disruptions, and annihilation anxiety, reflecting existential concerns about human identity and autonomy. We demonstrate a U-shaped relationship between AI anxiety and usage, where moderate engagement reduces anxiety, and high or low levels increase it. Perceived utility, interest, and attainment significantly correlate with AI engagement, while frequent AI usage is linked to high dependency but not to anxiety. These findings highlight the dual role of psychological factors in hindering and alleviating AI usage. This study enriches the understanding of emotional and motivational drivers in AI adoption and highlights the importance of balanced implementation strategies to foster sustainable and effective AI integration while mitigating the risks of over-reliance.

Owners’ perceptions of dog treat management in Western Romania

IntroductionWithin the broader-than-ever palette of pet foods, dog treats are an assortment sustained by powerful marketing tools and compelling advertising. The wide range and availability of these products often pair with the fondness of owners for their companions, leading to overfeeding them with rewards.MethodsThis study explored owner treat provision behaviors among 890 voluntarily participating dog owners in Western Romania through an online survey conducted between June and November 2023.ResultsThe majority of respondents were women (72%) and younger adults aged 18–24 (39%). Emotional attachment was the primary motivation for providing treats (52%), followed by perceived health benefits (35%) and training purposes (25%). However, 84% of respondents did not account for the caloric value of treats in their dogs' daily diet, and only 16% adjusted their dogs' main meals to compensate for treat provision. Preferences leaned toward treats with dental benefits (58%) and biscuits (52%). Many owners reported offering treats multiple times daily, highlighting the role of treats in owner-dog bonding. Chi-square tests of independence, with Bonferroni-adjusted post-hoc pairwise comparisons, revealed significant associations between treat provision frequency, owner demographics, and dog characteristics. Younger owners (18–24 years) were significantly more likely to provide treats at higher frequencies, with 31.8% giving treats 'multiple times daily' compared to 7.1% of older owners (>55 years) (p<0.002). Similarly, single owners provided treats more frequently, with 31.9% giving treats 'once daily' and 42.1% 'multiple times daily', compared to 7.1% and 22.4%, respectively, among owners in committed relationships (p<0.005). Owners who provided treats less frequently, 'seldom' (80.7%) or 'a few times a week' (87.8%), were more likely to have dogs with an ideal weight, while higher treat frequencies – 'once daily' (40.0%) or 'multiple times daily' (52.7%), were significantly associated with overweight or obese dogs (p<0.003).DiscussionThese findings underscore the importance of educating dog owners on aligning treat provision with caloric requirements and promoting responsible feeding practices. Veterinarians play a critical role in guiding owners toward balanced feeding strategies that incorporate treats into comprehensive dietary plans. Addressing treat provision behaviors is essential to mitigating health risks, improving canine nutrition, and promoting overall well-being.

Dynamic Robot Routing and Destination Assignment Policies for Robotic Sorting Systems

Robotic sorting systems (RSSs) use mobile robots to sort items by destination. An RSS pairs high accuracy and flexible capacity sorting with the advantages of a flexible layout. This is why several express parcel and e-commerce retail companies, who face heavy demand fluctuations, have implemented these systems. To cope with fluctuating demand, temporal robot congestion, and high sorting speed requirements, workload balancing strategies such as dynamic robot routing and destination reassignment may be of benefit. We investigate the effect of a dynamic robot routing policy using a Markov decision process (MDP) model and dynamic destination assignment using a mixed integer programming (MIP) model. To obtain the MDP model parameters, we first model the system as a semiopen queuing network (SOQN) that accounts for robot movement dynamics and network congestion. Then, we construct the MIP model to find a destination reassignment scheme that minimizes the workload imbalance. With inputs from the SOQN and MIP models, the Markov decision process minimizes parcel waiting and postponement costs and helps to find a good heuristic robot routing policy to reduce congestion. We show that the heuristic dynamic routing policy is near optimal in small-scale systems and outperforms benchmark policies in large-scale realistic scenarios. Dynamic destination reassignment also has positive effects on the throughput capacity in highly loaded systems. Together, in our case company, they improve the throughput capacity by 35%. Simultaneously, the effect of dynamic routing exceeds that of dynamic destination reassignment, suggesting that managers should focus more on dynamic robot routing than dynamic destination reassignment to mitigate temporal congestion. Funding: This work was supported by The Fundamental Research Funds for the Central Universities [Grant WK2040000094] and the National Natural Science Foundation of China [Grants 71921001 and 72091215/72091210]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2023.0458 .

Analisis Kebijakan Dalam Penanganan Dampak Serangan Orangutan (Pongo pygmaeus) Terhadap Tanaman Acacia sp. pada Hutan Tanaman Industri di PT. ‘XX’ Kalimantan Timur

Acacia sp. is widely cultivated in Indonesia's Industrial Plantation Forests (HTI), but orangutan attacks pose a significant threat to its sustainability. If not addressed, these disturbances can lead to substantial losses in Acacia cultivation, reducing the supply of industrial raw materials and hindering economic opportunities for local communities reliant on HTI development. This research aims to identify effective policy scenarios to mitigate the impact of orangutan attacks while ensuring the protection of these legally safeguarded primates. Utilizing the Analytic Hierarchy Process (AHP), insights were gathered from five experts through questionnaires and interviews, with data analyzed using Expert Choice 11 software. The research focused on PT. 'XX" Pengadan Village, Karangan District, East Kutai Regency, East Kalimantan. Based on this research, it was found that a stakeholder commitment approach is vital for managing orangutan interactions. Prioritizing the provision, management, and enrichment of conservation areas can help minimize attacks and support both orangutan conservation and the sustainability of Acacia sp. plantations. This balanced strategy aims to secure habitats for orangutans while safeguarding local livelihoods and promoting sustainable HTI practices.

The design of retroviral vectors used in the CAR-T products, risk management, and future perspective.

Chimeric antigen receptor T-cell (CAR-T) therapy is a revolutionary approach in cancer treatment. More than 10 CAR-T products have already approved on market worldly wide, and they use either gamma retroviral vectors or lentiviral vectors to deliver the CAR gene. Both vectors have the ability to effectively and persistently integrate the CAR gene into T cells. Despite the advancements in CAR-T therapy, the potential risks associated with the vectors, particularly the risks of the secondary malignancies, still remain as a concern. This article compares the characteristics of gamma retroviral and lentiviral vectors, discusses the development of vector packaging systems, and examines the design of self-inactivating (SIN) vectors. It also addresses the risks of secondary malignancies that might possibly be associated with the retroviral vectors, and the strategies to decrease the risks and increase the safer clinical use of the vectors. This article also discusses the current regulatory landscape and management approaches aiming to mitigate these risks through stringent safety measures and ongoing monitoring. Future perspectives focus on improving the safety profiles of the vectors and broadening their scope of use. The article provides a thorough overview of the most recent research discoveries and regulatory updates in the field of CAR-T therapy, highlighting the significance of a balanced strategy that strikes a balance between innovation and patient safety in the development and implementation of CAR-T therapy.

Dual balanced readout for scattered light noise mitigation in Michelson interferometers

Ground-based gravitational wave detectors use laser interferometry to detect the minuscule distance change between test masses caused by gravitational waves. Stray light that scatters back into the interferometer causes transient signals that can cover the same frequency range as a potential gravitational wave signal. This scattered light noise is a potentially limiting factor in current and future detectors thus making it relevant to find new ways to mitigate it. Here, we demonstrate experimentally a technique for the subtraction of scattered light noise from the displacement readout of a Michelson interferometer. It is based on using a balanced homodyne detector at both the symmetric and the antisymmetric port. While we have been able to demonstrate a noise reduction of 13.2 dB, the readout scheme seems to be only limited by the associated noise couplings, i.e., shot noise and the coupling of laser noise. We also discuss challenges for using the dual balanced homodyne detection scheme in more complex interferometer topologies, which could lead to improvements in scattered light noise mitigation of gravitational wave detectors. Published by the American Physical Society 2025

Using Virtual Reality to Enhance Learning Performance and Address Educational Resource Disparities in Architectural History Courses

Field surveys are an important component of architectural history courses, but they are challenging for students with limited resources or geographical constraints. This paper aims to explore the potential of virtual reality (VR) technology as a solution to this problem by testing its impact on student learning performance in an architectural history course. Dule Temple, a heritage building, is used as a case study to construct a VR environment with options for ground-based or free movement modes. A total of 102 third-year architecture students participated in the study, experiencing the VR environment and completing a survey. From the results, the VR scene’s level of detail achieved high levels of satisfaction. For learning performance, the results present the remarkable interestingness and effectiveness of VR in architectural history education. VR provides a comprehensive learning experience, enhancing the understanding of historical context, architectural styles, and spatial relationships. These findings show VR’s transformative potential as an educational medium, complementing and, in some respects, surpassing traditional approaches such as field surveys, 2D materials, and physical scale models. However, the study emphasizes that VR should not entirely replace traditional teaching methods. Instead, combining the strengths of VR and conventional techniques offers a balanced and effective strategy for architectural education. VR offers a transformative approach to address the imbalance of educational resources and realize sustainable education.

Control Strategy for Asymmetric Faults on the Low-Frequency Side of a Sparse Modular Multilevel Converter

Sparse modular multilevel converters (SMMCs) are a new type of lightweight high-voltage large-power AC/AC converter that significantly reduces the number of components compared to modular multilevel matrix converters (M3Cs). This study proposes a fault ride through a control strategy for SMMC to address the issues of arm energy imbalances and valve-side overvoltage, which occur during asymmetric faults on the low-frequency side. First, we establish models of the energy deviation of the arms under asymmetric short-circuit faults on the low-frequency side of SMMC. We also study the influence mechanism of the control strategies on the arm energy imbalance during faults. On this basis, an arm energy balancing strategy based on zero-sequence voltage injections combined with AC voltage control is proposed; this can achieve arm energy balance and suppress the negative sequence current and overvoltage of the SMMC. Finally, we construct a simulation model of an offshore wind power low-frequency transmission system based on the SMMC. The simulation results show that the proposed energy balance strategy can realize the stable operation of the low-frequency transmission system (LFTS) under asymmetric faults on the low-frequency side, that the maximum capacitor voltage deviation during the fault does not exceed 10% and that capacitor voltage returns to normal 0.25 s after the fault occurs.

State Compensation Model in Adaptive Event-Triggered Predictive Control: A Novel Approach to Mitigating Moving Bottlenecks

Moving bottlenecks, characterized by their high frequency and unpredictability, pose significant challenges to timely response and management, often resulting in road congestion and increased risk of traffic accidents. To address these issues, this paper proposes an adaptive event-triggered variable speed limit (AET-VSL) method based on a state compensation model, which emphasizes the concept of symmetry in the optimization of multi-segment speed limits. This symmetry approach facilitates a balanced and efficient control strategy that adjusts speed limits in a way that harmonizes traffic flow across multiple road segments, reducing congestion and improving overall traffic stability. The state compensation model builds on the classical METANET traffic flow model, incorporating coordination between road segments to reduce congestion while minimizing disruptions to traffic flow stability. By dynamically adjusting speed limits using real-time traffic data, the AET-VSL method addresses fluctuations in traffic conditions and ensures adaptive control to manage bottlenecks efficiently. A simulation framework was employed to evaluate the proposed strategy across varying traffic scenarios. Results demonstrate that AET-VSL outperforms traditional methods, providing consistent improvements in traffic performance. For instance, under low-traffic-flow conditions, AET-VSL reduced waiting time (WT) by 41.36%, potential collisions (PCs) by 51.92%, and fuel consumptionfuel consumption (FC) by 34.07%. This study highlights the novelty and effectiveness of AET-VSL, offering a scalable and reliable solution for dynamic traffic management and showcasing its potential to enhance traffic safety and efficiency.

Nurses' Perceptions of Patients With Co-Occurring Psychiatric and Substance Use Disorders in Psychiatric Settings: A Grounded Theory Study.

To explore psychiatric and mental health nurses' perceptions of patients with co-occurring psychiatric and substance use disorders in psychiatric settings. An exploratory qualitative study design based on grounded theory, employing Straussian analytic procedures. Semi-structured interviews were conducted with 11 psychiatric and mental health nurses. Participants were recruited at a public psychiatric hospital located in the Paris metropolitan area of France. Face-to-face interviews took place between February 2024 and May 2024. Field notes and interview data were continuously analysed during open, axial and selective coding phases. The core category identified was 'waiting for a patient's will to change to emerge' when caring for patients with co-occurring substance use disorders. This active waiting period involved a balancing strategy between two discrete care objectives: stabilising the patient's clinical status and keeping the nurse-patient relationship intact. Identifying a patient's will to change provided an opportunity to reconcile these two aspects of psychiatric nursing through the addition of a collaborative component to the relationship. The substantive theory generated by our findings contributes to understanding the interactional and relational processes that occur between nurses and patients presenting with co-occurring substance use disorders in the context of psychiatric care. Implications of our study include the need for further emphasis on collaborative approaches that can be applied even in early or pre-contemplative stages of recovery. Organisational policies should systematically include training in the field of addiction care, given the high prevalence of co-occurring substance use disorders in psychiatric settings. Our findings can assist nurses in critically examining the challenges they experience when engaging with patients with co-occurring substance use disorders. This research adheres to the COREQ (COnsolidated criteria for REporting Qualitative research) Checklist. No patient or public contribution.

Statistical analysis of work-life balance and job satisfaction: an empirical study of female employees in the cigarette industry

The concept of work-life balance has become increasingly popular in recent years. The demands of dedicating oneself to work, managing household responsibilities, and fulfilling non-work obligations have led many modern workers to adopt work-life balance strategies to harmonize their professional and personal lives. This study aims to analyze the effect of work-life balance on job satisfaction among female employees at Pitoe Cigarette Factory, Trenggalek. The research employed a simple linear regression analysis method, using data collected from questionnaires completed by 95 female employees as samples. The results of the simple linear regression test indicated a positive relationship between work-life balance and job satisfaction, with a p-value of 0.000, which is less than the significance threshold of 0.05. This finding demonstrates that improved work-life balance can contribute to increased job satisfaction among female employees. The coefficient of determination (R²) was found to be 0.413, indicating that 41.3% of the variation in job satisfaction is explained by work-life balance. Furthermore, the study revealed that both work-life balance and job satisfaction levels were categorized as moderate, suggesting the need for greater attention to managing the balance between work and personal life. These findings are expected to provide insights for Pitoe Cigarette Factory management and other companies in designing policies that support work-life balance, ultimately enhancing job satisfaction and productivity among female employees.

Work-Life Balance Strategies and their Influence on Employee Productivity

The aim of this study is to explore the impact of work-life balance strategies on employee productivity and organizational well-being at Sekolah Luar Biasa Erha Pabelan. As work environments become increasingly flexible with the rise of remote and hybrid work models, it is essential to understand how these strategies influence both individual and organizational outcomes. This research adopts a qualitative approach, utilizing semi-structured interviews and focus group discussions with the principal, teachers and educational staff at Sekolah Luar Biasa Erha Pabelan. The data collected were analyzed through thematic analysis, identifying key themes related to flexible working arrangements, managerial support, wellness programs, and barriers to effective implementation. The findings reveal that flexible working hours and remote work options significantly enhance employee productivity and satisfaction, while supportive workplace culture and wellness programs further contribute to well-being and organizational engagement. However, challenges such as limited awareness of policies, resistance from middle management, and resource constraints hinder the full potential of these initiatives. The study concludes that organizations must proactively address these barriers and continuously adapt their strategies to foster a sustainable work-life balance. Future research should investigate the effectiveness of personalized work-life balance solutions, the role of technology in managing boundaries, and cross-cultural differences in the implementation of these strategies.

Speech Emotion Recognition Model Based on Joint Modeling of Discrete and Dimensional Emotion Representation

This paper introduces a novel joint model architecture for Speech Emotion Recognition (SER) that integrates both discrete and dimensional emotional representations, allowing for the simultaneous training of classification and regression tasks to improve the comprehensiveness and interpretability of emotion recognition. By employing a joint loss function that combines categorical and regression losses, the model ensures balanced optimization across tasks, with experiments exploring various weighting schemes using a tunable parameter to adjust task importance. Two adaptive weight balancing schemes, Dynamic Weighting and Joint Weighting, further enhance performance by dynamically adjusting task weights based on optimization progress and ensuring balanced emotion representation during backpropagation. The architecture employs parallel feature extraction through independent encoders, designed to capture unique features from multiple modalities, including Mel-frequency Cepstral Coefficients (MFCC), Short-term Features (STF), Mel-spectrograms, and raw audio signals. Additionally, pre-trained models such as Wav2Vec 2.0 and HuBERT are integrated to leverage their robust latent features. The inclusion of self-attention and co-attention mechanisms allows the model to capture relationships between input modalities and interdependencies among features, further improving its interpretability and integration capabilities. Experiments conducted on the IEMOCAP dataset using a leave-one-subject-out approach demonstrate the model’s effectiveness, with results showing a 1–2% accuracy improvement over classification-only models. The optimal configuration, incorporating the joint architecture, dynamic weighting, and parallel processing of multimodal features, achieves a weighted accuracy of 72.66%, an unweighted accuracy of 73.22%, and a mean Concordance Correlation Coefficient (CCC) of 0.3717. These results validate the effectiveness of the proposed joint model architecture and adaptive balancing weight schemes in improving SER performance.

Bicycle-inspired simple balance control method for quadruped robots in high-speed running.

This paper explores the applicability of bicycle-inspired balance control in a quadruped robot model. Bicycles maintain stability and change direction by intuitively steering the handle, which induces yaw motion in the body frame and generates an inertial effect to support balance. Inspired by this balancing strategy, we implemented a similar mechanism in a quadruped robot model, introducing a yaw trunk joint analogous to a bicycle's steering handle. Simulation results demonstrate that the proposed model achieves stable high-speed locomotion with robustness against external disturbances and maneuverability that allows directional changes with only slight speed reduction. These findings suggest that utilizing centrifugal force plays a critical role in agile locomotion, aligning with the movement strategies of cursorial animals. This study underscores the potential of bicycle balance control as an effective and straightforward control approach for enhancing the agility and stability of quadruped robots as well as potentially offering insights into animal motor control mechanisms for agile locomotion.

Soft balancing in the regions: causes, characteristics and consequences

Abstract US decline and retrenchment is increasing the importance of regional dynamics across the international system. Over the past decade, International Relations scholars have described and conceptualized this development variously as ‘de-centred globalism’, a ‘multi-order world’, a ‘multiplex world’ or a multicultural ‘no one's world’, but the links between the regional and global levels and the roles and functions of regional institutions in power politics continue to be poorly understood. This special section uses the analytical lens of soft balancing—that is, attempts at restraining a threatening power through diplomatic and institutional delegitimation—to explore these links. Soft balancing has been used extensively to understand developments at the great power level, but its focus on diplomatic and institutional strategies holds considerable potential for explaining how rising powers, middle powers and smaller states seek to navigate the emerging international order. Contributors to the section discuss developments in the Indo-Pacific, central Asia, Europe and BRICS to answer questions such as: what are the characteristics of soft balancing in the regions? How do regional actors apply different soft balancing strategies? When and under what conditions will soft balancing strategies be effective? What is their impact on regional and global orders? This introduction offers an overview of soft balancing in theory and practice and their relevance to the world's regions.

Economic Balancing and China–United States Financial Ties

This paper develops the concept of economic balancing, a strategy whereby a state leverages economic policies to surpass a peer competitor. I argue that economic balancing is more likely to occur when a state identifies the economic power of a peer competitor as both an economic and military threat. Identifying a dual threat allows policymakers to link economic development and international security. This linkage, in turn, allows policymakers to build coalitions across bureaucracies, coordinate policy interventions, and obtain autonomy from competing domestic interests. Under these conditions, states can carry out the policy and institutional changes in the domestic economy necessary to pursue an economic balancing strategy. I demonstrate the argument’s plausibility with in-depth case studies of foreign direct management by China and the United States.

On Classical Inference of a Flexible Semi‐Parametric Class of Distributions Under a Joint Balanced Progressive Censoring Scheme

On Classical Inference of a Flexible Semi‐Parametric Class of Distributions Under a Joint Balanced Progressive Censoring Scheme

Energy Efficient and Balanced Task Assignment Strategy for Multi-AAV Patrol Inspection System in Mobile Edge Computing Network

Energy Efficient and Balanced Task Assignment Strategy for Multi-AAV Patrol Inspection System in Mobile Edge Computing Network