Random Number Sequence Research Articles

Modified FOLFOX6 with Cetuximab versus with Radiotherapy in Neoadjuvant Treatment of Locally Advanced Rectal Cancer: A Single-Center, Prospective, Randomized Controlled Trial.

In this trial, the feasibility and efficacy of neoadjuvant chemotherapy with targeted agents in the treatment of patients with locally advanced rectal cancer were evaluated. In this single-center, prospective, randomized controlled trial, we randomly assigned (1 : 1) patients with locally advanced rectal cancer with wild-type RAS/BRAF gene to two groups: 5 cycles of modified leucovorin calcium (folinic acid), fluorouracil, and oxaliplatin combination regimen (modified FOLFOX6, mFOLFOX6) concurrent with 25 times radiotherapy or 5 cycles of mFOLFOX6 plus cetuximab, all with subsequent total mesorectal excision (TME) resection and adjuvant chemotherapy. We performed a random assignment by a computer-generated random number sequence. The primary end point was the R0 resection rate. The secondary end points were rates of pathologic complete response, downstaging, adverse events, postoperative complications, preventive enterostomy and low anterior resection syndrome. From January 6, 2020 to October 28, 2022, 80 patients were assigned and evaluated. In the mFOLFOX6-RT and mFOLFOX6-Cet groups, the rate of R0 resection was 96.7 and 96.9% (p = 1.000); the rate of pathological complete response (pCR) was 23.3 and 21.9% (p = 0.891); and the rate of downstaging (ypStage 0 to 1) was 53.3 and 53.1% (p = 1.000), respectively. No statistical differences between the two groups were observed in the incidence of adverse events and postoperative complications. Additionally, lower rates of preventive enterostomy and low anterior resection syndrome were shown in the mFOLFOX6-Cet group compared to the mFOLFOX6-RT group. The neoadjuvant treatment strategy of mFOLFOX6 with cetuximab is feasible and promising for patients with locally advanced rectal cancer, even superior to mFOLFOX6 with radiotherapy.

True random number generation based on temporal fluctuations of abalone shell coherent random lasers.

The output modes of random lasers exhibit randomness, making them a potential high-quality physical entropy source for generating random numbers. In this paper, we controlled a low-cost and easily fabricated abalone shell random laser, generating forward and backward coherent random lasers simultaneously in a single channel, resulting in highly diverse mode variations. After post-processing steps such as third-order difference calculations and exclusive-or (XOR) logic operations, we generated a random number sequence for the first time, to the best of our knowledge, based on the temporal fluctuations of biomimetic random laser coherent modes. The instantaneous generation rate reached a preliminary 40 Gbps. Moreover, the random bits satisfy requirements such as random distribution, independence, and absence of bias, successfully passing the NIST SP800-22 standard test, confirming the high quality of the random number sequence.

Reducing Noise and Impact of High-Frequency Torque Ripple Caused by Injection Voltages by Using Self-Regulating Random Model Algorithm for SynRMs Sensorless Speed Control

For the sensorless control in a low-speed range of synchronous reluctance motors (SynRMs), injecting random high-frequency (HF) square-wave-type voltages has become a widely used and technologically mature method. It can solve the noise problem of traditional injection signal methods. However, all injection signal methods will cause problems such as torque ripple, which causes speed fluctuations. This article proposes a self-regulating random model algorithm for the random injection signal method, which includes a quantity adaptive module for adding additional random processes, an evaluation module for evaluating torque deviation degree, and an updated model module that is used to receive signals from the other two modules and complete model changes and output random model elements. The main function of this algorithm is to create a model that updates to suppress the evaluation value deviation based on the evaluation situation and outputs an optimal sequence of random numbers, thereby limiting speed bias always in a small range; this can reduce unnecessary changes in the output value of the speed regulator. The feasibility and effectiveness of the proposed algorithm and control method have been demonstrated in experiments based on a 5-kW synchronous reluctance motor.

Effect of telerehabilitation-based core-stability exercise on pain-related disability, pain self-efficacy, and psychological factors in individuals with non-specific chronic low back pain: a randomized controlled study

BackgroundCore-stability exercise is an exercise modality used in the management of patients with low back pain (LBP). Telerehabilitation is a new treatment approach that is gaining traction as an alternative rehabilitation approach. This study determined the effect of telerehabilitation-based core stability exercise (TCSE) and clinical-based core stability exercise (CCSE) on pain-related disability, pain self-efficacy, and psychological factors in patients with non-specific chronic low back pain (CLBP).Materials and methodsFifty participants (24 males and 26 females) with a mean age of 40.28 years participated in this randomized controlled study and were recruited from the out-patients physiotherapy clinic of 2 tertiary hospitals in Lagos State and were allocated into two groups (telerehabilitation-based core stability exercise group and clinical-based core stability exercise group which serves as the control) using computer-generated random number sequence. Pain-related disability, pain self-efficacy, and psychological status were assessed at baseline, and at the completion of the 4th and 8th week. Patients received supervised intervention protocols twice weekly for 8 consecutive weeks. Independent t-test, Mann–Whitney U test, and Friedman test were used in analyzing the data at an alpha level of 5%.ResultsThere was a statistically significant difference (P = 0.0001) noted within each group (telerehabilitation-based core stability exercise group and clinical-based core stability exercise group) in all the outcome measures assessed (Pain Disability Index, Pain Self-efficacy Questionnaire and Depression-Anxiety-Stress scale) but no group was superior to one another when compared.ConclusionTelerehabilitation-based core stability exercise was as efficacious as clinical-based core stability exercise in decreasing pain-related disability, improving pain self-efficacy and psychological factors, and should be incorporated as part of the treatment program in musculoskeletal rehabilitation for individuals with non-specific CLBP.Trial registrationPACTR202208607830603, 16th August 2022—retrospectively registered, https://pactr.samrc.ac.za/

Time sequence variation of incoherent and coherent random laser based on positive replica of abalone shell

Besides the scattering structures, the energy transfer (ET) process in the gain medium plays a significant role in the competition between coherent (comprising strongly coherent components) and incoherent (consisting of weakly coherent or “hidden” coherent components) modes of random lasers. In this study, bichromatic emission random lasers were successfully created using polydimethylsiloxane (PDMS) replicas with grooved structures that imitate the inner surface of abalone shells as scattering substrates. The influence mechanism of the ET process from the monomer to dimer in the Rhodamine 640 dye on the competition of random laser modes was thoroughly investigated from both spectral and temporal dimensions. It was confirmed that the ET process can reduce the gain of monomers while amplifying the gain of dimers. By considering the dominant high-efficiency ET processes, an energy transfer factor associated with the pump energy density was determined. Notably, for the first time, it was validated that the statistical distribution characteristics of the time sequence variations in the coherent random laser generated by dimers closely resemble a normal distribution. This finding demonstrates the feasibility of producing high-quality random number sequences.

Two-way ranging with carrier frequency and phase offset compensation based on software defined radio

In the context of Two-Way Ranging (TWR)measurements, distinct transmitter and receiver devices lead to discrepancies in clock timing, resulting in a Carrier Frequency Offset (CFO) and Carrier Phase Offset (CPO) that diminish the accuracy of distance measurements. Furthermore, moving objects also exacerbate these issues, increasing measurement errors. The effect of the CFO leads to variations and bit value inversion in the code in one frame when measuring two-way ranging distances with N random number sequence. In order to resolve this issue, the Fast Fourier Transform (FFT) is used in this work to determine the CFO and peak cross-correlation for the searching CPO. In outdoor experiments using Software Defined Radio (SDR) conducted over a maximum distance of 80 m, it was found that the precision of measurements was accurate within 1.25 m, and the overall accuracy was within 0.82 m when the Signal-to-Noise Ratio (SNR) was greater than 5 dB.

Blood-inspired random bit generation using microfluidics system

The development of random number generators (RNGs) using speckle patterns is pivotal for secure encryption key generation, drawing from the recent statistical properties identified in speckle-based imaging. Speckle-based RNG systems generate a sequence of random numbers through the unpredictable and reproducible nature of speckle patterns, ensuring a source of randomness that is independent of algorithms. However, to guarantee their effectiveness and reliability, these systems demand a meticulous and rigorous approach. In this study, we present a blood-inspired RNG system with a microfluidics device, designed to generate random numbers at a rate of 5.5 MHz and a high-speed of 1250 fps. This process is achieved by directing a laser beam through a volumetric scattering medium to procure speckle patterns. Additionally, designed microfluidic device requires only a minimal blood sample of 5 µl to capture these speckle patterns effectively. After implementing the two-pass tuple-output von Neumann debiasing algorithm to counteract statistical biases, we utilized the randomness statistical test suite from the National Institute of Standards and Technology for validation. The generated numbers successfully passed these tests, ensuring their randomness and unpredictability. Our blood-inspired RNG, utilizing whole blood, offers a pathway for affordable, high-output applications in fields like encryption, computer security, and data protection.

A general-purpose code for correlated sampling using batch statistics with MCNP6 for fixed-source problems

Background Correlated sampling can be applied with batch statistics using MCNP6’s tally fluctuation chart (TFC) to reduce the uncertainty of a difference of tallies between a base case and a perturbed case without modifying the source code. The cases are correlated if they are run with the same random number sequence. Equations implemented Equations used to apply correlated sampling to the difference of two tallies are summarized from previous work. Equations used to apply correlated sampling to a ratio of two tallies, to the difference of two tallies divided by a third tally, and to other combinations of ratios are presented. New computer code A general-purpose, command-line-driven computer program, COSUBS (Correlated Sampling Using Batch Statistics), is presented that reads MCNP6 TFCs from output files and applies these equations. The user specifies the input relative perturbation, if desired, and any normalization tally, if desired. Example problems show how to run COSUBS and interpret the output.

Validation of real-time fMRI neurofeedback procedure for cognitive training using counterbalanced active-sham study design

Investigation of neural mechanisms of real-time functional MRI neurofeedback (rtfMRI-nf) training requires an efficient study control approach. A common rtfMRI-nf study design involves an experimental group, receiving active rtfMRI-nf, and a control group, provided with sham rtfMRI-nf. We report the first study in which rtfMRI-nf procedure is controlled through counterbalancing training runs with active and sham rtfMRI-nf for each participant. Healthy volunteers (n = 18) used rtfMRI-nf to upregulate fMRI activity of an individually defined target region in the left dorsolateral prefrontal cortex (DLPFC) while performing tasks that involved mental generation of a random numerical sequence and serial summation of numbers in the sequence. Sham rtfMRI-nf was provided based on fMRI activity of a different brain region, not involved in these tasks. The experimental procedure included two training runs with the active rtfMRI-nf and two runs with the sham rtfMRI-nf, in a randomized order. The participants achieved significantly higher fMRI activation of the left DLPFC target region during the active rtfMRI-nf conditions compared to the sham rtfMRI-nf conditions. fMRI functional connectivity of the left DLPFC target region with the nodes of the central executive network was significantly enhanced during the active rtfMRI-nf conditions relative to the sham conditions. fMRI connectivity of the target region with the nodes of the default mode network was similarly enhanced. fMRI connectivity changes between the active and sham conditions exhibited meaningful associations with individual performance measures on the Working Memory Multimodal Attention Task, the Approach-Avoidance Task, and the Trail Making Test. Our results demonstrate that the counterbalanced active-sham study design can be efficiently used to investigate mechanisms of active rtfMRI-nf in direct comparison to those of sham rtfMRI-nf. Further studies with larger group sizes are needed to confirm the reported findings and evaluate clinical utility of this study control approach.

LS-14 test suite for long sequences

Random number sequences are used in many branches of science. Because of many techni- cal reasons and their practicality, pseudo random sequences are usually employed in place of true number sequences. Whether a sequence generated through a deterministic process is a pseudo random, in other words, random-looking sequence or it contains certain pat- terns, can be determined with the help of statistics and mathematics. Although, in the literature there are many statistical randomness tests for this purpose, there is no much work on test suites specialized for long sequences, that is sequences of length 1,000,000 bits or more. Most of the randomness tests for long sequences use some mathematical approximations to compute expected values of the random variables and hence their results contain some errors. Another approach to evaluate randomness criteria of long sequences is to partition the long sequence into a collection short sequences and evaluate the collection for the ran- domness using statistical goodness of fit tests. The main advantage of this approach is, as the individual sequences are short, there is no need to use mathematical approximations. On the other hand when the second approach is preferred, partition the long sequence into a collection of fixed length subsequences and this approach causes a loss of information in some cases. Hence the idea of dynamic partition should be included to perform a more reliable test suite. In this paper, we propose three new tests, namely the entire R2 run, dynamic saturation point, and dynamic run tests. Moreover, we introduce a new test suite, called LS-14, consisting of 14 tests to evaluate randomness of long sequences. As LS-14 employs all three approaches: testing the entire long sequence, testing the collection of fixed length partitions of it, and finally, testing the collection obtained by the dynamic partitions of it, the proposed LS-14 test suit differs from all existing suites. Mutual comparisons of all 14 tests in the LS-14 suite, with each other are computed. Moreover, results obtained from the proposed test suite and NIST SP800-22 suite are compared. Examples of sequences with certain patterns which are not observed by NIST SP800-22 suite but detected by the proposed test suite are given.

Erratum: Kolmogorov complexity of sequences of random numbers generated in Bell's experiments [Phys. Rev. A 98 , 042131 (2018)

Erratum: Kolmogorov complexity of sequences of random numbers generated in Bell's experiments [Phys. Rev. A <b>98</b> , 042131 (2018)

High-quality random bit generation based on a cascade-coupled nano-laser system

In this paper, a novel method is proposed to generate high-quality chaotic signals using three cascade-coupled nano-lasers (NLs), and generate high-speed, high-quality random number sequences. The master NL (MNL) is subjected to optical feedback, and its output is injected into the intermediate NL (INL), which is further injected into the slave NL (SNL). In the simulation, we first adjust proper parameters so that the SNL generates a chaotic signal with a large bandwidth and time-delay signature concealment. After performing self-delayed differential processing on the chaotic signal, and utilizing an 8-bit analog-to-digital converter for sampling and quantization, followed by extraction of the m-bits least significant bit, the final random bit sequence is obtained. Finally, we use NIST SP 800-22 to test the generated random numbers. The results demonstrate that the obtained random number sequence successfully passed all tests specified by NIST SP 800-22.

Modified Social Group Optimization to Solve the Problem of Economic Emission Dispatch with the Incorporation of Wind Power

Economic dispatch, emission dispatch, or their combination (EcD, EmD, EED) are essential issues in power systems optimization that focus on optimizing the efficient and sustainable use of energy resources to meet power demand. A new algorithm is proposed in this article to solve the dispatch problems with/without considering wind units. It is based on the Social Group Optimization (SGO) algorithm, but some features related to the selection and update of heuristics used to generate new solutions are changed. By applying the highly disruptive polynomial operator (HDP) and by generating sequences of random and chaotic numbers, the perturbation of the vectors composing the heuristics is achieved in our Modified Social Group Optimization (MSGO). Its effectiveness was investigated in 10-unit and 40-unit power systems, considering valve-point effects, transmission line losses, and inclusion of wind-based sources, implemented in four case studies. The results obtained for the 10-unit system indicate a very good MSGO performance, in terms of cost and emissions. The average cost reduction of MSGO compared to SGO is 368.1 $/h, 416.7 $/h, and 525.0 $/h for the 40-unit systems. The inclusion of wind units leads to 10% reduction in cost and 45% in emissions. Our modifications to MSGO lead to better convergence and higher-quality solutions than SGO or other competing algorithms.

EVALUATING A TRANSITIONAL CARE PROGRAM FOR OLDER ADULTS WITH FRAILTY BETWEEN HOSPITAL AND HOME

Abstract Older adults with frailty experience numerous health problems even after hospital discharge, highlighting the necessity of continued intervention until their recovery and return to daily routines. This mixed methods research (i.e., quantitative and qualitative studies) aimed to evaluate the effectiveness of a transitional care program developed for older adults with frailty during the transition from hospital to home and how it was helpful. From June to December 2021, 32 older adults with frailty were enrolled in a randomized controlled trial at a university-affiliated hospital in Korea. They were allocated to either an intervention group (n=16) or a control group (n=16) according to a random number sequence. The intervention group received a 12-week transitional care program that included inpatient care, structured discharge, and follow-up interventions (e.g., home visits and phone follow-ups); the control group received usual care only. At 12 weeks, program participants (eight frail older adults and eight family caregivers) had interviews for the qualitative research. The results showed that the intervention group had a higher score in knowledge readiness (p=.046) at discharge, empowerment (p=.032), and connectedness at four weeks (p=.037); community resource utilization (p &amp;lt;.001) and emergency room visit rate (p=.049) at 12 weeks; and improvement in depression (p &amp;lt;.001), family interaction (p=.045), and subjective health status (p=.002) over time. Participants described the program as a supportive, connected, timely, and personalized intervention. Overall, the study demonstrated that the transitional care program effectively improved the health outcomes of older adults with frailty and facilitated a safe transition between hospital and home.

Chaos-based Image Encryption in Embedded Systems using Lorenz-Rossler System

Digital data is increasing rapidly in the world day by day. Information security is important during data exchange over the Internet. The way to securely transmit images over the network is through the image encryption technique. In the proposed cryptography system, the hybridization of Lorenz-Rossler chaotic systems is used, and a random number sequence is generated. The security analyses such as histogram, correlation, differential attack, information entropy, and duration analysis of the study are performed. It is seen that the proposed system performs well, especially in terms of correlation. Additionally, the performance of the developed embedded system platforms is compared after testing on Nvidia Jetson Nano and Xilinx PYNQ Z1 boards. The Nvidia Jetson Nano board is more performant than the Xilinx PYNQ Z1 board. The safety and feasibility of the proposed system have been demonstrated.

A novel pseudo-random number generator based on multivariable optimization for image-cryptographic applications

Pseudo-random number generators (PRNGs) play an important role to ensure the security and confidentiality of image cryptographic algorithms. Their primary function is to generate a sequence of numbers that possesses unpredictability and randomness, which is crucial for the algorithms to work effectively and provide the desired level of security. However, traditional PRNGs frequently encounter limitations like insufficient randomness, predictability, and vulnerability to cryptanalysis attacks. To overcome these limitations, we propose a novel method namely an elliptic curve genetic algorithm (ECGA) for the construction of an image-dependent pseudo-random number generator (IDPRNG) that merges elliptic curves (ECs) and a genetic algorithm (GA). The ECGA consists of two primary stages. First, we generate an EC-based initial sequence of random numbers using pixels of a plain-image and parameters of an EC that depart from traditional methods of population initialization. In our proposed approach, the image itself serves as the seed for the initial population in the genetic algorithm optimization, taking into account the image-dependent nature of cryptographic applications. This allows the PRNG to adapt its behavior to the unique characteristics of the input image, leading to enhanced security and improved resistance against differential attacks. Furthermore, the use of a good initial population reduces the number of generations required by a genetic algorithm which results in decreased computational cost. In the second stage, we use well-known operations of a genetic algorithm to optimize the generated sequence by maximizing a multi-variable fitness function that is based on both the information entropy and the period of the PRNG. By combining elliptic curves and genetic algorithms, we enhance the randomness and security of the ECGA. To evaluate the effectiveness and security of our generator, we conducted comprehensive experiments using various benchmark images and applied several standard tests, including the National Institute of Standards and Technology (NIST) test suite. We then compared the results with the state-of-the-art PRNGs. The experimental results demonstrate that the ECGA outperforms the state-of-the-art PRNGs in terms of uniformity, randomness, and cryptographic strength.

A Randomized Controlled Trial to Evaluate the Impact of an Exercise Therapy Program Based on Sports in People with Acquired Brain Injury: Discover Study Protocol.

Acquired brain injury (ABI) constitutes a significant and growing global public health concern. People with ABI often face a range of physical and psychosocial challenges that span the domains of "body structure and function", "activity", and "participation", as defined by the International Classification of Functioning, Disability, and Health. Multidisciplinary approaches based on exercise therapy with social leisure activities are essential to improve physical recovery and health-related quality of life after injury. Adults with ABI, aged > 18 years, in the subacute or chronic stage (within more than one month after the injury) will be recruited through a rehabilitation center. Adults will be randomized to receive either a racket sports-based exercise therapy program combined with usual care (sET) or usual care alone (UC) using a random number sequence with a 1:1 allocation ratio. sET intervention consists of an 8-week exercise therapy program focusing on different racket sports skills, 1 h in duration, 2 days/week. It will be delivered by a physiotherapist in tailored, face-to-face, group-based sessions. Primary outcomes will be the health-related quality of life (SF-36) and upper extremity motor function (Fugl-Meyer Assessment-Upper Extremity Scale). The study proposes an intervention that combines sports-based exercise therapy with usual care. It aims to determine whether this intervention improves the health-related quality of life and upper limb motor function in adults with ABI compared with usual care alone. The results of this study may have clinical implications for the rehabilitation of this population.

KAOTİK YILAN OPTİMİZE EDİCİ

Metaheuristic algorithms provide approximate or optimal solutions for optimization problems in a &#x0D; reasonable time. With this feature, metaheuristic algorithms have become an impressive research area &#x0D; for solving difficult optimization problems. Snake Optimizer is a population-based metaheuristic &#x0D; algorithm inspired by the mating behavior of snakes. In this study, different chaotic maps were &#x0D; integrated into the parameters of the algorithm instead of random number sequences to improve the &#x0D; performance of Snake Optimizer, and Snake Optimizer variants using four different chaotic mappings &#x0D; were proposed. The performances of these proposed variants for eight different chaotic maps were &#x0D; examined on classical and CEC2019 test functions. The results revealed that the proposed algorithms &#x0D; contribute to the improvement of Snake Optimizer performance. In the comparison with the literature, &#x0D; the proposed Chaotic Snake Optimizer algorithm found the best mean values in many functions and &#x0D; took second place among the algorithms. As a result of the tests, Chaotic Snake Optimizer has been &#x0D; shown to be a promising, successful, and preferable algorithm.

МЕТОДИКА КРИТЕРІЇВ СУМ У ЗАДАЧАХ ТЕСТУВАННЯ НЕЗАЛЕЖНОСТІ ПОСЛІДОВНОСТЕЙ ВИПАДКОВИХ ЧИСЕЛ

Random and pseudo-random number generators (RNGs) were initially used to solve numerical integration problems (the Monte Carlo method). Currently, the RNGs are used in cryptography and simulation modeling. The latter one typically uses RNGs based on computer algorithms and programs. This article presents a method aimed at testing the independence of random numbers sequences (RNSs). The method is based on the sums properties of independent random variables. Algorithms based on this method operate fast. Here not only the instant statistics including correlation coefficients are analyzed, but also the properties of empirical functions of RNSs distributed sums. In this article, the analysis is limited only to the case of uniformly distributed RNSs. The calculations performed prove the high selective efficiency of the proposed criteria, which allows to reliably distinguish between dependent and independent RNSs. Due to the high operation speed, the proposed algorithms and criteria can be used for testing very long RNSs (especially in Big Data tasks).

Further analysis of the statistical independence of the NIST SP 800-22 randomness tests

In multiple applications, from Statistics to Particle Physics and notably in Cryptography and Computer Security, it is necessary to obtain long sequences of random numbers. In order to verify the properties of these sequences, different statistical tests are commonly applied, which are usually included in the so-called test batteries or test suites. The batteries need to be both effective and efficient. Their effectiveness relates to how well they can spot non-randomness behaviour, the efficiency is related to the computational time they require. It is therefore essential for tests included in batteries to measure their independence features: Test independence is important for good effectiveness, as high correlations between tests could lead to a decreased efficiency (testing for the same features multiple times) and effectiveness (missing an opportunity to test for an orthogonal randomness property when we essentially measure the same twice). Moreover, the related study of test coverage is often based on the assumption that tests are independent. This paper describes a series of experiments aimed at scrutinizing dependencies among the statistical tests in the NIST SP 800-22 suite. In order to do so, sequences of varying lengths from sources of varying entropy have been generated and tested. Afterwards, an inferential study was carried out to find whether significant correlations exist and to present our findings in a statistically sound way.