Evaluation of the CRISPR/Cas9 system as genome editing platform for the Mucopolysaccharidosis IV A using a strategy for induction of higher homologous recombination frequency by Diego Alejandro Suarez, Andrés Felipe Leal, Carlos Javier Alméciga Díaz

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Upper-Limb Robotic Rehabilitation: Online Sliding Mode Controller Gain Tuning Using Particle Swarm Optimization by Deira Sosa Méndez, David Bedolla-Martínez, Maarouf Saad, Yassine Kali, Cecilia E. García Cena, Ángel L. Álvarez

“…The proposed method was validated through experimental tests conducted on two healthy subjects, and the outcomes indicated a reduction of over 20% in tracking errors compared to heuristically tuned gains. …”
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Forecasting Forex EUR/USD Closing Prices Using a Dual-Input Deep Learning Model with Technical and Fundamental Indicators by Abolfazl Saghafi, Maryam Bagherian, Farhad Shokoohi

“…The model outperforms the second-best model, achieving a 29% reduction in mean absolute error (MAE) and root mean squared error (RMSE) in the training set and reductions of 24% and 23% in MAE and RMSE, respectively, in the test set. …”
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An Oracle Normalized Least Mean Square (NLMS) Algorithm and a Simple Bayesian Detection NLMS Algorithm Robust to Impulse Noise by Hadi Zayyani, Yaser Attar

“…Initially, to have a fast algorithm, an optimization problem is introduced and then an oracle NLMS algorithm is devised. It has the largest reduction in misalignment error at each iteration with respect to the previous iteration. …”
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Low Power OFDM Receiver Exploiting Data Sparseness and DFT Symmetry by Nikos Petrellis

“…Simulations were performed for two Quadrature Amplitude Modulation orders (16-QAM and 32-QAM), two options for the FFT size (1024 and 4096), two alternative input symbol structures for the inverse FFT (IFFT), and several sparseness levels and samples substitution options. The Symbol Error Rate (SER) and image reconstruction examples are used to show that a full reconstruction or a very low error can be achieved. …”
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Reduced-Order Models and Conditional Expectation: Analysing Parametric Low-Order Approximations by Hermann G. Matthies

“…Similarly, in the field of machine learning, a function mapping the parameter set to the image space of the machine learning model is learned from a training set of samples, typically minimising the mean square error. This set may be seen as a sample from some probability distribution, and thus the training is an approximate computation of the expectation, giving an approximation of the conditional expectation—a special case of Bayesian updating, where the Bayesian loss function is the mean square error. …”
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A Hybrid Smoothed Finite Element Method for Predicting the Sound Field in the Enclosure with High Wave Numbers by Haitao Wang, Xiangyang Zeng, Ye Lei

“…This method employs the smoothing technique to realize the reduction of the numerical dispersion. By constructing a type of mixed smoothing domain, the traditional node-based and face-based smoothing techniques are mixed in the hybrid SFEM to give a more accurate stiffness matrix, which is widely believed to be the ultimate cause for the numerical dispersion error. …”
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Low Overhead Qutrit Magic State Distillation by Shiroman Prakash, Tanay Saha

“…We construct a family of $[[9m-k, k, 2]]_3$ triorthogonal qutrit error-correcting codes for any positive integers $m$ and $k$ with $k \leq 3m-2$ that are suitable for magic state distillation. …”
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Improving the criteria of electricity consumptionforecasting in petrochemical industrial units based ondeep learning by Ehsan Tavakoli Garmaserh, Mehran Emadi

“…Experimental evaluations using benchmark datasets demonstrate significant improvements, achieving a Root Mean Square Error (RMSE) of 0.0693 and a Mean Absolute Percentage Error (MAPE) reduction of over 15% compared to state-of-the-art methods. …”
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Cost-effectiveness of financial incentives to improve glycemic control in adults with diabetes: A pilot randomized controlled trial. by Leonard E Egede, Rebekah J Walker, Clara E Dismuke-Greer, Sarah Pyzyk, Aprill Z Dawson, Joni S Williams, Jennifer A Campbell

“…Group 1 (low frequency) received a single incentive for absolute HbA1c reduction, Group 2 (moderate frequency) received a two-part incentive for home testing of glucose and absolute HbA1c reduction and Group 3 (high frequency) received a multiple component incentive for home testing, attendance of weekly telephone education classes and absolute HbA1c reduction. …”
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Nonvariational ADAPT algorithm for quantum simulations by Ho Lun Tang, Yanzhu Chen, Prakriti Biswas, Alicia B. Magann, Christian Arenz, Sophia E. Economou

“…Since it does not rely on a classical optimization subroutine, it may provide robustness against circuit parameter errors due to imperfect control or gate synthesis.…”
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A hybrid CNN-BILSTM deep learning framework for signal detection of a massive MIMONOMA system by Mohamed A. Abdelhamed, Mennatalla Samy, Bassem E. Elnaghi, Ahmed Magdy

“…Simulation results demonstrate that the CNN-BiLSTM model achieves a 60 % reduction in bit error rate (BER) for the far user (FU) and 55 % for the near user (NU) when high-priority (HP) bits are transmitted. …”
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A Robust Tool for 3D Rail Mapping Using UAV Data Photogrammetry, AI and CV: qAicedrone-Rail by Innes Barbero-García, Diego Guerrero-Sevilla, David Sánchez-Jiménez, David Hernández-López

“…The detection performance and metric results show a significant reduction in errors and increased precision compared to intermediate YOLO-based outputs. …”
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Deep Circuit Compression for Quantum Dynamics via Tensor Networks by Joe Gibbs, Lukasz Cincio

“…For all circuit depths and widths tested, we produce circuits with smaller errors than all equivalent depth Trotter unitaries, corresponding to reductions in error by up to 4 orders of magnitude and circuit depth compressions with a factor of over 6.…”
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Dynamic calibration of low-cost PM2.5 sensors using trust-based consensus mechanisms by Sachit Mahajan, Dirk Helbing

“…Results show mean absolute error (MAE) reductions of up to 68% for poorly performing sensors and 35–38% for reliable ones, outperforming conventional calibration methods. …”
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Novel sliding mode control of the manipulator based on a nonlinear disturbance observer by Keyou Guo, Haoze Zhang, Caili Wei, Haibing Jiang, Jiangnan Wang

“…Through simulation and comparative experiments conducted using MATLAB/Simulink, the controller model exhibited a 16.4% average reduction in the mean square value of tracking errors compared to existing control strategies, with improvements observed in various performance indicators. …”
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Research on the prediction algorithm of tread wear for locomotive wheels based on GA-ridge regression analysis by FANG Xin, LIU Tong, CHENG Yaping, SUN Yuduo, WANG Feier

“…The results indicate relatively lower prediction errors and standard deviations of errors when using the GA-ridge regression prediction algorithm. …”
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Unambiguous Multipath Mitigation Technique for BOC(n,n) and MBOC-Modulated GNSS Signals by Khaled Rouabah, Mustapha Flissi, Salim Attia, Djamel Chikouche

“…The computer simulation results show that the proposed scheme has superior performances in the reduction of the errors produced in the process of the delay estimation of line of sight (LOS) and caused by MP propagation. …”
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Research on Current Compensation Method for Wavelength Jumping in MG-Y Laser by WANG Di, ZHUANG Wei, ZHANG Xu, WANG Le, LIU Wanquan

“…Further experimental validation showed that by compensating for the three-channel currents at the channel switching point, wavelength errors were reduced to within 1 pm, indicating a significant improvement in performance.…”
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A model for developing a surgical and anaesthesia safety checklist in reducing surgical morbidity and mortality: A literature review by Handayani Rahmaya Nova, AryadiA M., Suandika Made, Yudha Magenda Bisma, Surtiningsih

“…Complications that often occur include patient/procedure/surgery site errors, anaesthesia equipment problems, lack of availability of necessary equipment, unexpected blood loss, unsterile equipment, and surgical objects left inside the patient. …”
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