Plasma Amino Acids May Improve Prediction Accuracy of Cerebral Vasospasm after Aneurysmal Subarachnoid Haemorrhage

Aneurysmal subarachnoid haemorrhages (aSAH) account for 5% of strokes and continues to place a great burden on patients and their families. Cerebral vasospasm (CVS) is one of the main causes of death after aSAH, and is usually diagnosed between day 3 and 14 after bleeding. Its pathogenesis remains poorly understood. To verify whether plasma concentration of amino acids have prognostic value in predicting CVS, we analysed data from 35 patients after aSAH (median age 55 years, IQR 39–62; 20 females, 57.1%), and 37 healthy volunteers (median age 50 years, IQR 38–56; 19 females, 51.4%). Fasting peripheral blood samples were collected on postoperative day one and seven. High performance liquid chromatography-mass spectrometry (HPLC-MS) analysis was performed. The results showed that plasma from patients after aSAH featured a distinctive amino acids concentration which was presented in both principal component analysis and direct comparison. No significant differences were noted between postoperative day one and seven. A total of 18 patients from the study group (51.4%) developed CVS. Hydroxyproline (AUC = 0.7042, 95%CI 0.5259–0.8826, p = 0.0248) and phenylalanine (AUC = 0.6944, 95%CI 0.5119–0.877, p = 0.0368) presented significant CVS prediction potential. Combining the Hunt-Hess Scale and plasma levels of hydroxyproline and phenylalanine provided the model with the best predictive performance and the lowest leave-one-out cross-validation of performance error. Our results suggest that plasma amino acids may improve sensitivity and specificity of Hunt-Hess scale in predicting CVS.

Вариационный подход к определению динамической прочности материала

The problem of the determination of material strength properties through the Kolsky experimental technique is considered. Small size specimens of M1 copper alloy are tested on a split Hopkinson pressure bars equipment. The experimental data of tensile tests observed under both dynamic and quasi-static conditions are analysed within the framework of the incubation time criterion and the Sign-Perturbed Sums method. It is shown that the influence of a test performance error is considered in the data treatment procedure based on the developed method.

Songbird subthalamic neurons project to dopaminergic midbrain and exhibit singing-related activity

Skill learning requires motor output to be evaluated against internal performance benchmarks. In songbirds, ventral tegmental area (VTA) dopamine neurons (DA) signal performance errors important for learning, but it remains unclear which brain regions project to VTA and how these inputs may contribute to DA error signaling. Here we find that the songbird subthalamic nucleus (STN) projects to VTA and that STN micro-stimulation can excite VTA neurons. We also discover that STN receives inputs from motor cortical, auditory cortical and ventral pallidal brain regions previously implicated in song evaluation. In the first neural recordings from songbird STN, we discover that the activity of most STN neurons is associated with body movements and not singing, but a small fraction of neurons exhibits precise song timing and performance error signals. Our results place the STN in a pathway important for song learning, but not song production, and expand the territories of songbird brain potentially associated with song learning.

Smart Inventory System untuk Distribusi Vaksin dengan Metode Economic Order Quantity

Sistem inventory adalah serangkaian aktivitas dalam melakukan proses pengelolaan data barang yang terdapat pada penyimpanan yang memiliki peran dan fungsi krusial untuk menyelesaikan permasalahan dalam mengelola, mengontrol, dan memudahkan pelaporan data barang. Sistem inventory diperlukan salah satunya untuk memanajemen persediaan stok vaksin. Saat ini manajemen persediaan vaksin pada dinas kesehatan hingga ke level puskesmas masih ditemukan permasalahan, seperti belum adanya standar perhitungan kuantitas pengadaan dan safety stock yang optimal sehingga persediaan menjadi tidak merata di beberapa wilayah yang menyebabkan terjadinya kelebihan dan kekosongan stok. Hal ini membuat pengelolaan biaya persediaan vaksin tidak efisien. Oleh karenanya, diperlukan sistem inventory yang mampu meningkatkan efisiensi pengelolaan stok vaksin yang optimal dengan meminimumkan biaya. Penelitian yang dilakukan, yaitu membangun smart inventory system menerapkan metode economic order quantity untuk mengoptimalkan persediaan dan mengimplementasikan teknologi RFID (Radio Frequency Identification) berbasis Internet of Things (IoT) untuk mengefisiensi pencatatan pergerakan stok secara otomatis. Sistem dianalisis dan dirancang menggunakan metode SDLC (System Development Life Cycle) sehingga spesifikasi kebutuhan diidentifikasi secara jelas agar dapat memecah permasalahan. Model yang digunakan adalah waterfall methodology. Selanjutnya dilakukan pengujian terhadap smart inventory system. Berdasarkan pengujian yang dilakukan menunjukkan smart inventory system memenuhi kebutuhan dalam pengelolaan stok vaksin secara efektif dan efisien dengan performance error yang terjadi hanya sebesar 1,98%.

Reduction of linear dynamic systems using generalized approach of pole clustering method

A new model order abatement method based on the clustering of poles and zeros of a large-scale continuous time system is proposed. The clustering of poles and zeros are used for finding the cluster centres. The abated model is identified from the cluster centres, which reflect the effectiveness of the dominant poles of the clusters. The cluster centre is determined by taking [Formula: see text] root of the sum of the inverse of [Formula: see text] power of poles (zeros) in a particular cluster. It is famous that the magnitude of the pole cluster centre plays an important role in the clustering technique for the simplification of large-scale systems. The magnitude of the cluster centres computed by the modified pole clustering method or some other methods based on the pole clustering techniques is large as compared to the proposed technique. The less magnitude of pole cluster centre reflects the better approximations and proper matching of the abated model with the original system. Therefore, the proposed method offers better approximations matching between actual and abated systems during the transient period compared to some other clustering methods, which supports the replacement of large-scale systems by proposed abated systems. The proposed technique is a generalized version of the standard pole clustering technique. The proposed method guarantees the retention of dominant poles, stability and other fundamental control properties of the actual plant in the abated model. The proposed algorithm is illustrated by the five standard systems taken from the literature. The accuracy and effectiveness of the proposed method are verified by comparing the time responses and various performance error indices.

3D Sight Distance Calculation and Estimation of its Effect on Road Accidents in GIS Environment

Nowadays, one of the main causes of human death is driving accidents. Across the world 1.2 million people die and several million people get injured annually as a result of road accidents. One of the main solutions that is important in resolving the problem of accidents is identifying the factors and their role and impact and the contribution of each in the accident. The stopping sight distance in the route is one of the initial factors in the driver’s performance error as well as the occurrence of an accident, financial losses, and deaths. The geometric design of roads is generally designed according to two-dimensional rules and regulations. Hence, today, given the remarkable advances in computer science and programming, there are many possibilities for 3D modeling of the route. Therefore, the calculation of the stopping sight distance should be based on existing facts and new scientific achievements. On the contrary, the stopping sight distance is one of the factors affecting driving crashes; therefore, this paper tries to investigate the accident occurrence probability in other spots of the existing route by calculating 3D stopping sight distance and using drivers’ free flow speed, as well as using the GIS software. In this way, the results of this study can pave the way for improving the geometric design of existing roads as well as prioritizing the correction of the accidental points of existing routes.

Design and in Silico Evaluation of a Closed-Loop Hemorrhage Resuscitation Algorithm with Blood Pressure as Controlled Variable

This paper concerns the design and rigorous in silico evaluation of a closed-loop hemorrhage resuscitation algorithm with blood pressure (BP) as controlled variable. A lumped-parameter control design model relating volume resuscitation input to blood volume (BV) and BP responses was developed and experimentally validated. Then, three alternative adaptive control algorithms were developed using the control design model: (i) model reference adaptive control with BP feedback, (ii) composite adaptive control with BP feedback, and (iii) composite adaptive control with BV and BP feedback. To the best of our knowledge, this is the first work to demonstrate model-based control design for hemorrhage resuscitation with readily available BP as feedback. The efficacy of these closed-loop control algorithms was comparatively evaluated as well as compared with an empiric expert knowledge-based algorithm based on 100 realistic virtual patients created using a well-established physiological model of cardiovascular hemodynamics. The in silico evaluation results suggested that the adaptive control algorithms outperformed the knowledge-based algorithm in terms of both accuracy and robustness in BP set point tracking: the average median performance error and median absolute performance error were significantly smaller by >99% and >91%, and as well, their inter-individual variability was significantly smaller by >88% and >94%. Pending in vivo evaluation, model-based control design may advance the medical autonomy in closed-loop hemorrhage resuscitation.

Songbird subthalamic neurons signal song timing and error and project to dopaminergic midbrain

Skill learning requires motor output to be evaluated against internal performance benchmarks. In songbirds, ventral tegmental area (VTA) dopamine neurons (DA) signal performance errors important for learning, but it remains unclear which brain regions project VTA and how these inputs may implement the sensorimotor comparisons necessary for error computation. Here we find that the songbird subthalamic nucleus (STN) projects to VTA and that STN microstimulation can excite VTA neurons. We also discover that STN receives inputs from auditory cortical and ventral pallidal brain regions previously implicated in song evaluation. In the first neural recordings from songbird STN, we discover that the activity of most STN neurons is associated with body movements and not singing, but a small fraction of neurons exhibits precise song timing and performance error signals consistent with performance evaluation. Together our results implicate the STN-VTA projection as an evolutionarily conserved pathway important for motor learning and expand the territories of songbird brain associated with song learning.New & NoteworthySongbird subthalamic (STN) neurons exhibit song-timing and performance error signals and are interconnected with auditory pallium, ventral pallidum and ventral tegmental area, three areas important for song learning.

High-Performance and Energy-Efficient Fault Tolerance FPGA-to-FPGA Communication

These days, due to the increasing demand for high speed and parallel computation, several real world applications and systems include multiple FPGAs in them. Due to this, FPGAs often need to communicate among them. So, communication between the FPGAs is one of the key factors that determines the accuracy, performance and correctness of the entire multiple FPGAs systems or applications. This paper presents the design of an efficient multi-bit fault tolerant communication system for FPGA-to-FPGA communication. The proposed design is synthesized and also simulated through Vivado design suit 2018.3 and was communicated with two Kintex-7 FPGA boards. When compared with the existing FPGA-to-FPGA communication and inter FPGA communication designs, the proposed design have higher performance, error detection and correction capability.