Yuan Ze University

• Self-powered TEG-TEC system enables simultaneous cooling and energy harvesting. • The Taguchi method is used to optimize four key design parameters efficiently. • Achieved maximum heat dissipation of 53.91 W, far surpassing standalone TEG. • COP increased dramatically, reaching up to 50.38 in the optimal configuration. • Predictions without the Thomson effect overestimate performance by 45%. Efficient thermal management is essential for the performance and reliability of compact energy and electronic systems. This study proposes a self-powered thermoelectric generation-cooling (TEG-TEC) system that integrates a thermoelectric generator (TEG) with a thermoelectric cooler (TEC) to enhance heat dissipation using only available waste heat. The TEG converts part of the temperature difference into electrical power that directly drives the TEC, eliminating the need for external electricity. A Taguchi-based three-dimensional numerical model is employed to optimize four design factors: TEC thermoelectric couples, heat-transfer surface area, element length, and convection coefficient, each at four levels. An L16 orthogonal array requires only 16 simulations to explore the design space. Under the prescribed thermal boundary conditions, the optimized configuration achieves a maximum cooling capacity of 53.91 W, whereas a standalone TEG module delivers only 0.99 W. The internal power-amplification coefficient of performance, defined as COP P = Q C , T E G / P TEG , reaches 50.38 for the best self-powered loop. In addition, the maximum thermal stress in the TEG module is reduced from 957.46 MPa in the standalone case to 936.69 MPa with the coupled TEG-TEC configuration, improving mechanical reliability. The Thomson effect reduces cooling performance by approximately 45%, underscoring the importance of incorporating Thomson heating into accurate TEG-TEC modeling. The proposed TEG-TEC configuration thus provides a compact, energy-efficient solution for low-load, space-constrained cooling while conceptually bridging waste-heat-driven power generation and active thermoelectric cooling.

Study DesignUmbrella systematic review.ObjectiveTo qualitatively synthesise systematic reviews evaluating the prevalence, correlates, and outcomes of mental illnesses in individuals with traumatic spinal cord injury (tSCI).MethodsSystematic reviews reporting on depression, anxiety, post-traumatic stress disorder (PTSD), substance use disorders (SUD), cognitive impairment, and related psychological outcomes in tSCI populations were identified and synthesized as per PRISMA guidelines. Data on prevalence, risk factors, assessment tools, and interventions were extracted. Methodological quality was appraised using AMSTAR 2, and primary study overlap was assessed.ResultsTwenty systematic reviews published between 2005 and 2025 were included. Depression was the most frequently studied condition (n = 16), followed by anxiety (n = 10), PTSD (n = 6), and SUD (n = 4), with several reviews addressing multiple conditions. Primary study sample sizes ranged from 3152 to over 50000 participants, with wide variation in injury characteristics, study design, and outcome measures. Pooled prevalence estimates indicated a substantial burden: depression affected up to 43% of community-dwelling individuals, anxiety symptoms around 27%, PTSD up to 62%, and hazardous alcohol use ≥50% in some cohorts. Common risk factors included pain, injury severity, incomplete injury, low social support, maladaptive coping, and co-occurring psychological symptoms. Evidence for effective interventions was limited, and few studies used standardised, validated tools across settings.ConclusionsMental health conditions are highly prevalent in the tSCI population, yet intervention research remains limited. Standardised assessment, longitudinal designs, and targeted, evidence-based interventions are urgently needed to address this critical but under-recognised aspect of tSCI care.

Abstract Erasures are the primary type of errors in physical systems dominated by leakage errors. While quantum error correction (QEC) using stabilizer codes can combat erasure errors, it remains unknown which constructions achieve capacity performance. If such codes exist, decoders with linear runtime in the code length are also desired. In this paper, we present erasure capacity-achieving quantum codes under maximum-likelihood decoding (MLD), though MLD requires cubic runtime in the code length. For QEC, using an accurate decoder with the shortest possible runtime will minimize the degradation of quantum information while awaiting the decoder’s decision. To address this, we propose belief propagation (BP) decoders that run in linear time and exploit error degeneracy in stabilizer codes, achieving capacity or near-capacity performance for a broad class of codes, including bicycle codes, product codes, and topological codes. We furthermore explore the potential of our BP decoders to handle mixed erasure and depolarizing errors, and also local deletion errors via concatenation with permutation invariant codes.