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With the popularization of Internet of Things applications, trillions of new devices with different application requirements, such as smart wearables and smart home appliances, will be connected to the network. Hence, it is crucial to ensure the data transmission security of these low-power and multifunctional sensor nodes. In this paper, a novel lightweight block cipher, GFSPX, is proposed for resource-constrained microdevices. The proposed algorithm combines a generalized Feistel structure with the substitution permutation networks structure to design the round function, which effectively addresses the inherent problem of slow diffusion in the traditional Feistel structure. Furthermore, the introduction of Addition or AND, Rotation, XOR operations in the round function to process part of the plaintext reduces the demand for hardware resource of the algorithm. The avalanche test results indicate that the GFSPX algorithm has strong diffusion and can satisfy the avalanche effect in just six rounds. The security analysis results verify the security of the GFSPX algorithm against differential and linear cryptanalysis attacks, algebraic attacks, structural attacks and key scheduling attacks. Finally, the performance analysis results indicate that the hardware implementation cost of GFSPX algorithm is relatively low, requiring only 1715 GE based on 0.13 micron logic process. In addition, the software implementation of this algorithm works well at an encryption rate of 12.31 Mb/s. [ABSTRACT FROM AUTHOR]

The ARX mutations encompass a nearly continuous spectrum of neurodevelopmental disorders (NDDs), ranging from lissencephaly to Proud syndrome, as well as infantile spasms without brain malformations, and including both syndromic and non-syndromic intellectual disabilities (IDs). We describe worsening neuropsychiatric symptoms in the offspring of a Korean family with ID/developmental delay (DD) caused by a novel ARX p.Lys385Ter variant. Sequential genetic testing was performed to investigate the ID, DD, agenesis of the corpus callosum (ACC), and developmental epileptic encephalopathy (DEE) observed in the proband. A comprehensive trio clinical exome sequencing approach using a Celemics G-Mendeliome Clinical Exome Sequencing Panel was employed. Given the clinical manifestations observed in the proband, gene panel sequencing identified a heterozygous ARX variant, c.1153A>T/p.Lys385Ter (Reference transcript ID: NM_139058.3), as the most likely cause of ID, DD, ACC, and DEE in the proband. Sanger sequencing confirmed the segregation of the ARX variant, c.1153A>T/p.Lys385Ter, with the phenotype and established the maternally inherited dominant status of the heterozygous variant in the patient, as well as in her grandmother, mother, and aunt. Our case report adds to the understanding of the female phenotype in ARX-related disorders caused by loss-of-function variants in the ARX gene. Genetic counseling for ARX families should proceed with caution, as female carriers can exhibit a wide range of phenotypes, from normal cognitive development to ID/DD, ACC, and DEE. [ABSTRACT FROM AUTHOR]

Differential-linear cryptanalysis is an efficient cryptanalysis method to attack ARX ciphers, which have been used to present the best attacks on many ARX primitives such as Chaskey and Chacha. In this paper, we present the differential-linear cryptanalysis of another ARX-based block cipher SPARX-64/128. We first construct multiple 6-round differential-linear distinguishers based on the structure of SPARX-64/128, and then extend them into 14-round differential-linear distinguishers by adding a 7-round differential characteristic before and a one-round linear approximation after the distinguishers. Then we introduce a new linear approximation of modular addition, and use it to extend one more round after the 14-round differential-linear distinguishers. With the 15-round differential-linear distinguishers, we present a differential-linear attack on 18-round SPARX-64/128. [ABSTRACT FROM AUTHOR]

The impossible differential (ID) attack is one of the most important cryptanalytic techniques for block ciphers. There are two phases to finding an ID attack: searching for the distinguisher and building a key recovery upon it. Previous works only focused on automated distinguisher discovery, leaving key recovery as a manual post-processing task, which may lead to a suboptimal final complexity. At EUROCRYPT 2023, Hadipour et al. introduced a unified constraint programming (CP) approach based on satisfiability for finding optimal complete ID attacks in strongly aligned ciphers. While this approach was extended to weakly-aligned designs like PRESENT at ToSC 2024, its application to ARX and AndRX ciphers remained as future work. Moreover, this method only exploited ID distinguishers with direct contradictions at the junction of two deterministic transitions. In contrast, some ID distinguishers, particularly for ARX and AndRX designs, may not be detectable by checking only the existence of direct contradictions. This paper fills these gaps by extending Hadipour et al.’s method to handle indirect contradictions and adapting it for ARX and AndRX designs. We also present a similar method for identifying zero-correlation (ZC) distinguishers. Moreover, we extend our new model for finding ID distinguishers to a unified optimization problem that includes both the distinguisher and the key recovery for AndRX designs. Our method improves ID attacks and introduces new distinguishers for several ciphers, such as SIMON, SPECK, Simeck, ChaCha, Chaskey, LEA, and SipHash. For example, we achieve a one-round improvement in ID attacks against SIMON-64-96, SIMON-64-128, SIMON-128-128, SIMON-128-256 and a two-round improvement against SIMON-128- 192. These results significantly contribute to our understanding of the effectiveness of automated tools in the cryptanalysis of different design paradigms.

The ARX mutations encompass a nearly continuous spectrum of neurodevelopmental disorders (NDDs), ranging from lissencephaly to Proud syndrome, as well as infantile spasms without brain malformations, and including both syndromic and non-syndromic intellectual disabilities (IDs). We describe worsening neuropsychiatric symptoms in the offspring of a Korean family with ID/developmental delay (DD) caused by a novel ARX p.Lys385Ter variant. Sequential genetic testing was performed to investigate the ID, DD, agenesis of the corpus callosum (ACC), and developmental epileptic encephalopathy (DEE) observed in the proband. A comprehensive trio clinical exome sequencing approach using a Celemics G-Mendeliome Clinical Exome Sequencing Panel was employed. Given the clinical manifestations observed in the proband, gene panel sequencing identified a heterozygous ARX variant, c.1153A>T/p.Lys385Ter (Reference transcript ID: NM_139058.3), as the most likely cause of ID, DD, ACC, and DEE in the proband. Sanger sequencing confirmed the segregation of the ARX variant, c.1153A>T/p.Lys385Ter, with the phenotype and established the maternally inherited dominant status of the heterozygous variant in the patient, as well as in her grandmother, mother, and aunt. Our case report adds to the understanding of the female phenotype in ARX-related disorders caused by loss-of-function variants in the ARX gene. Genetic counseling for ARX families should proceed with caution, as female carriers can exhibit a wide range of phenotypes, from normal cognitive development to ID/DD, ACC, and DEE.

Background: Variants in the Aristaless‐related homeobox (ARX) gene lead to a variety of phenotypes, with intellectual disability being a steady feature. Other features can include severe epilepsy, spasticity, movement disorders, hydranencephaly, and ambiguous genitalia in males. X‐linked Ohtahara syndrome or Type 1 early infantile epileptic encephalopathy (EIEE1) is a severe early‐onset epileptic encephalopathy with arrested psychomotor development caused by hemizygous mutations in the ARX gene, which encodes a transcription factor in fundamental brain developmental processes. Methods: We presented a case report of a 2‐year‐old boy who exhibited symptoms such as microcephaly, seizures, and severe multifocal epileptic abnormalities, and genetic techniques such as autozygosity mapping, Sanger sequencing, and whole‐exome sequencing. Results: We confirmed that the patient had the NM_139058.3:c.84C>A; p.(Cys28Ter) mutation in the ARX gene. Conclusion: The patient with EIEE1 had physical symptoms and hypsarrhythmia on electroencephalogram. Genetic testing identified a causative mutation in the ARX gene, emphasizing the role of genetic testing in EIEE diagnosis. [ABSTRACT FROM AUTHOR]

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In this paper, we propose an efficient method for handling large datasets in linear parameter-varying (LPV) model identification. The method is based on least-squares support vector machine (LS-SVM) identification in the primal space. To make the identification computationally feasible, even for very large datasets, we propose estimating a finite-dimensional feature map. To achieve this, we propose a two-step method to reduce the computational effort. First, we define the training set as a fixed-size subsample of the entire dataset, considering collision entropy for subset selection. The second step involves approximating the feature map through the eigenvalue decomposition of the kernel matrices. This paper considers both autoregressive with exogenous input (ARX) and state-space (SS) model forms. By comparing the problem formulation in the primal and dual spaces in terms of accuracy and computational complexity, the main advantage of the proposed technique is the reduction in space and time complexity during the training stage, making it preferable for handling very large datasets. To validate our proposed primal approach, we apply it to estimate LPV models using provided inputs, outputs, and scheduling signals for two nonlinear benchmarks: the parallel Wiener-Hammerstein system and the Silverbox system. The performances of our proposed approach are compared with the dual LS-SVM approach and the kernel principal component regression. [ABSTRACT FROM AUTHOR]

The cnidarian model organism Hydra has long been studied for its remarkable ability to regenerate its head, which is controlled by a head organizer located near the hypostome. The canonical Wnt pathway plays a central role in head organizer function during regeneration and during bud formation, which is the asexual mode of reproduction in Hydra. However, it is unclear how shared the developmental programs of head organizer genesis are in budding and regeneration. Time-series analysis of gene expression changes during head regeneration and budding revealed a set of 298 differentially expressed genes during the 48-h head regeneration and 72-h budding time courses. In order to understand the regulatory elements controlling Hydra head regeneration, we first identified 27,137 open-chromatin elements that are open in one or more sections of the organism body or regenerating tissue. We used histone modification ChIP-seq to identify 9,998 candidate proximal promoter and 3,018 candidate enhancer-like regions respectively. We show that a subset of these regulatory elements is dynamically remodeled during head regeneration and identify a set of transcription factor motifs that are enriched in the enhancer regions activated during head regeneration. Our results show that Hydra displays complex gene regulatory structures of developmentally dynamic enhancers, which suggests that the evolution of complex developmental enhancers predates the split of cnidarians and bilaterians.

Abstract Background Variants in the Aristaless‐related homeobox (ARX) gene lead to a variety of phenotypes, with intellectual disability being a steady feature. Other features can include severe epilepsy, spasticity, movement disorders, hydranencephaly, and ambiguous genitalia in males. X‐linked Ohtahara syndrome or Type 1 early infantile epileptic encephalopathy (EIEE1) is a severe early‐onset epileptic encephalopathy with arrested psychomotor development caused by hemizygous mutations in the ARX gene, which encodes a transcription factor in fundamental brain developmental processes. Methods We presented a case report of a 2‐year‐old boy who exhibited symptoms such as microcephaly, seizures, and severe multifocal epileptic abnormalities, and genetic techniques such as autozygosity mapping, Sanger sequencing, and whole‐exome sequencing. Results We confirmed that the patient had the NM_139058.3:c.84C>A; p.(Cys28Ter) mutation in the ARX gene. Conclusion The patient with EIEE1 had physical symptoms and hypsarrhythmia on electroencephalogram. Genetic testing identified a causative mutation in the ARX gene, emphasizing the role of genetic testing in EIEE diagnosis.

The district heating system (DHS) consumes a lot of energy in winter, and its control accuracy needs to be improved urgently. To apply advanced process control (APC) in DHS, the thermal dynamic model of the existing buildings is essential. This paper uses the subspace method which is a data-driven approach for modelling the thermal dynamics of the building. The model's performance is analyzed using the collected data, and the differences compared to the classical methods are also analyzed. The method reduces the RMSE by about 20% compared with the ARX model for the same complexity. Subsequently, the analysis of the training residuals indicates that the estimate of periodic intra-building disturbance can be obtained by minimizing the training residuals. By introducing the estimated disturbance function, the RMSE on the test set is further reduced by 26%. At the end of the article, a simple parameter extrapolation experiment is conducted, and the result shows that the parameters can be extrapolated to other buildings without large errors. [ABSTRACT FROM AUTHOR]

Background: While many pancreatic neuroendocrine tumours (PanNET) show indolent behaviour, predicting the biological behaviour of small nonfunctional PanNETs remains a challenge. Nonfunctional PanNETs with an epigenome and transcriptome that resemble islet alpha cells (ARX‐positive) are more aggressive than neoplasms that resemble islet beta cells (PDX1‐positive). In this study, we explore the ability of immunohistochemistry for ARX and PDX1 and telomere‐specific fluorescence in situ hybridisation (FISH) for alternative lengthening of telomeres (ALT) to predict recurrence. Methods: Two hundred fifty‐six patients with PanNETs were identified, and immunohistochemistry for ARX and PDX1 was performed. Positive staining was defined as strong nuclear staining in >5% of tumour cells. FISH for ALT was performed in a subset of cases. Results: ARX reactivity correlated with worse disease‐free survival (DFS) (P = 0.011), while there was no correlation between PDX1 reactivity and DFS (P = 0.52). ALT‐positive tumours (n = 63, 31.8%) showed a significantly lower DFS (P < 0.0001) than ALT‐negative tumours (n = 135, 68.2%). ARX reactivity correlated with ALT positivity (P < 0.0001). Among nonfunctional tumours, recurrence was noted in 18.5% (30/162) of ARX‐positive tumours and 7.5% (5/67) of ARX‐negative tumours. Among WHO grade 1 and 2 PanNETs with ≤2 cm tumour size, 14% (6/43) of ARX‐positive tumours recurred compared to 0 of 33 ARX‐negative tumours and 33.3% (3/9) ALT‐positive tumours showed recurrence versus 4.4% (2/45) ALT‐negative tumours. Conclusion: Immunohistochemistry for ARX and ALT FISH status may aid in distinguishing biologically indolent cases from aggressive small low‐grade PanNETs, and help to identify patients who may preferentially benefit from surgical intervention. [ABSTRACT FROM AUTHOR]

'Rotation and shift' based diffusion functions are used in modern ciphers especially in ARX (Addition, Rotation, and XOR) based designs. They are preferred over other alternatives as they are efficient and lightweight. Usually, such diffusion functions map an n-bit block to another n-bit block. One of the requirements for an n-bit to n-bit diffusion function is that, it should be invertible. In this paper, we present mathematical models for different classes of 'rotation and shift' based diffusion functions and explore their invertibility. We derive sufficient conditions under which diffusion functions of these classes are invertible. [ABSTRACT FROM AUTHOR]

The advancement Internet of things has led to an increasing exchange of information. Privacy and security has become a major concern. In this emerging ubiquitous computing world, Lightweight cryptographic algorithms are tailor made to secure the information in low resource devices for the Internet of Things (IoT) applications. In this paper an area efficient, high performance lightweight cipher, MBRISI cipher is proposed. The cipher is a combination of BRIGHT family of ciphers comprises of Addition-Modulo, Rotation and EX-OR (ARX) operations and the modification of SIMON cipher and also a novel lightweight key generation algorithm is used. The proposed cipher is better than the state of art existing lightweight ciphers and can be extended to support different block sizes and key sizes for the low resource environments like the IoT. The proposed MBRISI cipher encrypts a 32-bit plaintext employing a 64-bit key is implemented and then analyzed. The cipher is implemented in MATLAB tool (for software implementation) and is analyzed for correlation coefficient, entropy and histogram, avalanche criterion and Key-sensitivity. The Verilog code is written and simulated using Xilinx-Vivado tool and synthesized using FPGA's Artix-7 and Basys-3. [ABSTRACT FROM AUTHOR]

4H leukodystrophy is a rare genetic disorder classically characterized by hypomyelination, hypodontia and hypogonadotropic hypogonadism. With the discovery that 4H is caused by mutations that affect RNA polymerase III, mainly involved in the transcription of small non-coding RNAs, patients with atypical presentations with mainly a neuronal phenotype were also identified. Pathomechanisms of 4H brain abnormalities are still unknown and research is hampered by a lack of preclinical models. We aimed to identify cells and pathways that are affected by 4H mutations using induced pluripotent stem cell models. RNA sequencing analysis on induced pluripotent stem cell-derived cerebellar cells revealed several differentially expressed genes between 4H patients and control samples, including reduced ARX expression. As ARX is involved in early brain and interneuron development, we studied and confirmed interneuron changes in primary tissue of 4H patients. Subsequently, we studied interneuron changes in more depth and analysed induced pluripotent stem cell-derived cortical neuron cultures for changes in neuronal morphology, synaptic balance, network activity and myelination. We showed a decreased percentage of GABAergic synapses in 4H, which correlated to increased neuronal network activity. Treatment of cultures with GABA antagonists led to a significant increase in neuronal network activity in control cells but not in 4H cells, also pointing to lack of inhibitory activity in 4H. Myelination and oligodendrocyte maturation in cultures with 4H neurons was normal, and treatment with sonic hedgehog agonist SAG did not improve 4H related neuronal phenotypes. Quantitative PCR analysis revealed increased expression of parvalbumin interneuron marker ERBB4 , suggesting that the development rather than generation of interneurons may be affected in 4H. Together, these results indicate that interneurons are involved, possibly parvalbumin interneurons, in disease mechanisms of 4H leukodystrophy. [ABSTRACT FROM AUTHOR]

In this paper, we present 4 major contributions to ARX ciphers and in particular, to the Salsa/ChaCha family of stream ciphers: We propose an improved differential-linear distinguisher against ChaCha. To do so, we propose a new way to approach the derivation of linear approximations by viewing the algorithm in terms of simpler subrounds. Using this idea, we show that it is possible to derive almost all linear approximations from previous works from just 3 simple rules. Furthermore, we show that with one extra rule, it is possible to improve the linear approximations proposed by Coutinho and Souza at Eurocrypt 2021 (Coutinho and Neto, in: Canteaut, Standaert (eds) Advances in cryptology—EUROCRYPT 2021—40th annual international conference on the theory and applications of cryptographic techniques, Zagreb, Croatia, October 17–21, 2021, proceedings, Part I. Lecture notes in computer science, vol 12696, Springer, 2021). We propose a technique called Bidirectional Linear Expansions (BLE) to improve attacks against Salsa. While previous works only considered linear expansions moving forward into the rounds, BLE explores the expansion of a single bit in both forward and backward directions. Applying BLE, we propose the first differential-linear distinguishers reaching 7 and 8 rounds of Salsa and we improve Probabilistic Neutral Bit (PNB) key-recovery attacks against 8 rounds of Salsa. At Eurocrypt 2022 (Dey et al in Revamped differential-linear cryptanalysis on reduced round chacha, Springer, 2022), Dey et al. proposed a technique to combine two input–output positions in a PNB attack. In this paper, we generalize this technique for an arbitrary number of input–output positions. Combining this approach with BLE, we are able to improve key recovery attacks against 7 rounds of Salsa. Using all the knowledge acquired studying the cryptanalysis of these ciphers, we propose some modifications in order to provide better diffusion per round and higher resistance to cryptanalysis, leading to a new stream cipher named Forró. We show that Forró has higher security margin; this allows us to reduce the total number of rounds while maintaining the security level, thus creating a faster cipher in many platforms, especially in constrained devices. Finally, we developed CryptDances, a new tool for the cryptanalysis of Salsa, ChaCha, and Forró designed to be used in high performance environments with several GPUs. With CryptDances it is possible to compute differential correlations, to derive new linear approximations for ChaCha automatically, to automate the computation of the complexity of PNB attacks, among other features. We make CryptDances available for the community at . [ABSTRACT FROM AUTHOR]

In this article, a chaotic computing paradigm is investigated for the parameter estimation of the autoregressive exogenous (ARX) model by exploiting the optimization knacks of an improved chaotic grey wolf optimizer (ICGWO). The identification problem is formulated by defining a mean square error-based fitness function between true and estimated responses of the ARX system. The decision parameters of the ARX model are calculated by ICGWO for various populations, generations, and noise levels. The comparative performance analyses with standard counterparts indicate the worth of the ICGWO for ARX model identification, while the statistical analyses endorse the efficacy of the proposed chaotic scheme in terms of accuracy, robustness, and reliability. [ABSTRACT FROM AUTHOR]

The wind turbine (WT) dynamics are affected by wind variations and system parameter changes as well. To deal with the pitch control problem a Self-Tuning Controller (STC) with Proportional-Derivative (PD) structure has been proposed for the benchmark model (BM). This BM also models some sensors, actuators and system faults. The STC design herein is pivoted on a second-order auto-regressive exogenous (ARX) model. At first, three identification methods for the ARX model are presented: Recursive Least Square method (RLS), RLS with exponential forgetting (RLS-EF) and RLS with adaptive directional forgetting (RLS-ADF). In comparison, the performance of RLS-ADF is better than the rest two. The STC PD controller supersedes contemporary adaptive control approaches to fix up the generated power to its rating for above-rated wind. Secondly, on analysis, the proposed STC PD controller is fault-tolerant for nine types of faults. In the third stage, in extensive Monte Carlo Simulation (MCS), the sensitivity test to system parameter variation is carried out including the sensor faults. The result in the presence of a fault, as well as parameter variation, shows minimal deviation from normal conditions indicating the suitability of the STC PD controller to keep the system intact except in case of multiple faults. [ABSTRACT FROM AUTHOR]

Insulinomas are rare functional pancreatic neuroendocrine tumors. While most insulinomas are indolent and cured after surgery, 10--15% of cases show aggressive or malignant tumor behavior and metastasize locally or to distant organs. Patients with metastatic insulinoma survive significantly shorter. Recognizing aggressive insulinomas can help to predict prognosis, guide therapy and determine follow-up intensity after surgery. This review offers a summary of the literature on the significant clinical, pathological, genetic and epigenetic differences between indolent and aggressive insulinomas. Aggressive insulinomas are characterized by rapid onset of symptoms, larger size, expression of ARX and alpha-1-antitrypsin and decreased or absent immunohistochemical expression of insulin, PDX1 and GLP-1R. Moreover, aggressive insulinomas often harbor ATRX or DAXX mutations, the alternative lengthening of telomeres phenotype and chromosomal instability. Tumor grade and MEN1 and YY1 mutations are less useful for predicting behavior. Aggressive insulinomas have similarities to normal alpha-cells and non-functional pancreatic neuroendocrine tumors, while indolent insulinomas remain closely related to normal beta-cells. In conclusion, indolent and aggressive insulinoma are different entities, and distinguishing these will have future clinical value in determining prognosis and treatment. [ABSTRACT FROM AUTHOR]

The System identification (SI) black box method is used in this study to obtain the mathematical model of a fiber braided bending actuator (FBBA) using MATLAB Simulink. Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. In the system, PRBS generators are used to generate an input signal for the electro-pneumatic valve. The auto-regressive with exogenous input (ARX) model is chosen. As the controller for the FBBA position system, PID with the Genetic Algorithm (GA) tuning method and auto-tuned tuning method is proposed. The reference angle, simulation, and actual test are compared. The mathematical model gained from the SI method is verified through the simulation and test result of the position control. It was found that the model obtained through SI able represent the actual plant. [ABSTRACT FROM AUTHOR]

Abstract Rotational‐XOR (RX) cryptanalysis is a cryptanalytic method aimed at finding distinguishable statistical properties in Addition‐Rotation‐XOR‐C ciphers, that is, ciphers that can be described only by using modular addition, cyclic rotation, XOR and the injection of constants. In this study, we extend RX‐cryptanalysis to AND‐RX ciphers, a similar design paradigm where the modular addition is replaced by vectorial bitwise AND; such ciphers include the block cipher families Simon and Simeck. We analyse the propagation of RX‐differences through AND‐RX rounds and develop a closed form formula for their expected probability. Inspired by the MILP verification model proposed by Sadeghi et al., we develop a SAT/SMT model for searching compatible RX‐characteristics in Simon‐like ciphers, that is, that there is at least one right pair of messages/keys to satisfy the RK‐characteristics. To the best of our knowledge, this is the first model that takes the RX‐difference transitions and value transitions simultaneously into account in Simon‐like ciphers. Meanwhile, we investigate how the choice of the round constants affects the resistance of Simon‐like ciphers against RX‐cryptanalysis. Finally, we show how to use an RX‐distinguisher for a key recovery attack. Evaluating our model we find compatible RX‐characteristics of up to 20, 27 and 34 rounds with respective probabilities of 2−26, 2−44 and 2−56 for versions of Simeck with block sizes of 32, 48 and 64 bits, respectively, for large classes of weak keys in the related‐key model. In most cases, these are the longest published distinguishers for the respective variants of Simeck. In the case of Simon, we present compatible RX‐characteristics for round‐reduced versions of all 10 instances. We observe that for equal block and key sizes, the RX‐distinguishers cover fewer rounds in Simon than in Simeck. Concluding the paper, we present a key recovery attack on Simeck 64 reduced to 28 rounds using a 23‐round RX‐characteristic.

In Addition-Rotation-Xor (ARX) ciphers, the large domain size obstructs the application of the boomerang connectivity table. In this paper, we explore the problem of computing this table for a modular addition and the automatic search of boomerang characteristics for ARX ciphers. We provide dynamic programming algorithms to efficiently compute this table and its variants. These algorithms are the most efficient up to now. For the boomerang connectivity table, the execution time is 42(n − 1) simple operations while the previous algorithm costs 82(n − 1) simple operations, which generates a smaller model in the searching phase. After rewriting these algorithms with boolean expressions, we construct the corresponding Boolean Satisfiability Problem models. Two automatic search frameworks are also proposed based on these models. This is the first time bringing the SAT-aided automatic search techniques into finding boomerang attacks on ARX ciphers. Finally, under these frameworks, we find out the first verifiable 10-round boomerang trail for SPECK32/64 with probability 2−29.15 and a 12-round trail for SPECK48/72 with probability 2−44.15. These are the best distinguishers for them so far. We also perceive that the previous boomerang attacks on LEA are constructed with an incorrect computation of the boomerang connection probability. The result is then fixed by our frameworks.

In this paper we present several analyses on ChaCha, a software stream cipher. First, we consider a divide-and-conquer approach on the secret key bits by partitioning them. The partitions are based on multiple input-output differentials to obtain a significantly improved attack on 6-round ChaCha256 with a complexity of 299.48. It is 240 times faster than the currently best known attack. This is the first time an attack on a round reduced ChaCha with a complexity smaller than 2k/2, where the secret key is of k bits, has been successful. Further, all the attack complexities related to ChaCha are theoretically estimated in general and there are several questions in this regard as pointed out by Dey, Garai, Sarkar and Sharma in Eurocrypt 2022. In this regard, we propose a toy version of ChaCha, with a 32-bit secret key, on which the attacks can be implemented completely to verify whether the theoretical estimates are justified. This idea is implemented for our proposed attack on 6 rounds. Finally, we show that it is possible to estimate the success probabilities of these kinds of PNB-based differential attacks more accurately. Our methodology explains how different cryptanalytic results can be evaluated with better accuracy rather than claiming that the success probability is significantly better than 50%.

Mendel's law of segregation states that the two alleles at a diploid locus should be transmitted equally to the progeny. A genetic segregation distortion, also referred to as transmission ratio distortion (TRD), is a statistically significant deviation from this rule. TRD has been observed in several mammal species and may be due to different biological mechanisms occurring at diverse time points ranging from gamete formation to lethality at post-natal stages. In this review, we describe examples of TRD and their possible mechanisms in mammals based on current knowledge. We first focus on the differences between TRD in male and female gametogenesis in the house mouse, in which some of the most well studied TRD systems have been characterized. We then describe known TRD in other mammals, with a special focus on the farmed species and in the peculiar common shrew species. Finally, we discuss TRD in human diseases. Thus far, to our knowledge, this is the first time that such description is proposed. This review will help better comprehend the processes involved in TRD. A better understanding of these molecular mechanisms will imply a better comprehension of their impact on fertility and on genome evolution. In turn, this should allow for better genetic counseling and lead to better care for human families. [ABSTRACT FROM AUTHOR]

The study of lightweight block ciphers has been a "hot topic". As one of the main structures of block ciphers, the Feistel structure has attracted much attention. However, the traditional Feistel structure cipher changes only half of the plaintext in an iterative round, resulting in slow diffusion. Therefore, more encryption rounds are required to ensure security. To address this issue, a new algorithm, GFRX, is proposed, which combines a generalized Feistel structure and ARX (Addition or AND, Rotation, XOR). The GFRX algorithm uses an ARX structure with different non-linear components to deal with all the branches of a generalized Feistel structure so that it can achieve a better diffusion effect in fewer rounds. The results of a security analysis of the GFRX algorithm show that the effective differential attacks do not exceed 19 rounds and that the effective linear attacks do not exceed 13 rounds. Therefore, the GFRX algorithm has an adequate security level for differential and linear analysis. Avalanche test results obtained for the GFRX algorithm show that the GFRX algorithm has strong diffusion and only takes six rounds to meet the avalanche effect. In addition, the GFRX algorithm can achieve different serialization levels depending on different hardware resource requirements and can achieve full serialization, which ensures operational flexibility in resource-constrained environments. [ABSTRACT FROM AUTHOR]

The differential-linear attack, combining the power of the two most effective techniques for symmetric-key cryptanalysis, was proposed by Langford and Hellman at CRYPTO 1994. From the exact formula for evaluating the bias of a differential-linear distinguisher (JoC 2017), to the differential-linear connectivity table technique for dealing with the dependencies in the switch between the differential and linear parts (EUROCRYPT 2019), and to the improvements in the context of cryptanalysis of ARX primitives (CRYPTO 2020, EUROCRYPT 2021), we have seen significant development of the differential-linear attack during the last four years. In this work, we further extend this framework by replacing the differential part of the attack by rotational-XOR differentials. Along the way, we establish the theoretical link between the rotational-XOR differential and linear approximations and derive the closed formula for the bias of rotational differential-linear distinguishers, completely generalizing the results on ordinary differential-linear distinguishers due to Blondeau, Leander, and Nyberg (JoC 2017) to the case of rotational differential-linear cryptanalysis. We then revisit the rotational cryptanalysis from the perspective of differential-linear cryptanalysis and generalize Morawiecki et al.’s technique for analyzing Keccak, which leads to a practical method for estimating the bias of a (rotational) differential-linear distinguisher in the special case where the output linear mask is a unit vector. Finally, we apply the rotational differential-linear technique to the cryptographic permutations involved in FRIET, Xoodoo, Alzette, and SipHash. This gives significant improvements over existing cryptanalytic results, or offers explanations for previous experimental distinguishers without a theoretical foundation. To confirm the validity of our analysis, all distinguishers with practical complexities are verified experimentally. Moreover, we discuss the possibility of applying the rotational differential-linear technique to S-box-based designs or keyed primitives, and propose some open problems for future research. [ABSTRACT FROM AUTHOR]

As the most critical equipment in the pre-calcination process of dry cement production, the temperature of the precalciner is an essential factor affecting the quality of cement. However, the cement calcination system is time-delayed, nonlinear, and multi-disturbance, which makes it difficult to predict and control the precalciner temperature. In this study, a deep learning-based Hammerstein model is proposed, and a model predictive control system is built to predict and control the precalciner temperature. In the prediction model, the CNN-GRU network architecture is used to extract the operating states of the precalciner, and an attention mechanism is employed to find and emphasize the important historical information in the extracted states. Then, an ARX model is built to predict the temperature of the precalciner using the extracted operating state information. The complex nonlinear model solution in the control system is formed into a linear control problem and an inverse solution problem. The generalized predictive control (GPC) is used for linear control, and the improved sparrow search algorithm (ISSA) is used for the problem of an inverse solution. Tested with data from a cement plant in Hebei, China, the prediction accuracy of the model proposed in this paper is 99%, and the established control algorithm has less overshoot compared to PID and better stability in anti-disturbance tests. It is demonstrated that the prediction model developed in this study has better accuracy and the control strategy based on this model has good robustness. [ABSTRACT FROM AUTHOR]

Rotational-XOR cryptanalysis is a very recent technique for ARX ciphers. In this paper, the probability propagation formula of RX-cryptanalysis in modular addition is extended, and the calculation of RX-difference probability for any rotation parameter (⁠|$0

Pada penelitian ini dilakukan pengendalian kecepatan motor DC menggunakan Proportional Integral Derivative Model Reference Adaptive Control (PID MRAC). Pemodelan sistem motor DC sudah banyak diberikan pada penelitian sebelumnya dengan melakukan penurunan terhadap torsi dan tegangan motor. Pada penelitian ini dilakukan pengambilan data motor DC untuk mendapatkan nilai input dan output sehingga didapatkan model matematika sistem dengan menggunakan metode Autoregressive with External Input (ARX). Model matematika yang didapatkan berupa model diskrit yang selanjutnya dibuat menjadi bentuk kontinu. Model matematika tersebut akan diberikan kendali PID MRAC untuk memperbaiki sinyal error antara input dan output. Sinyal input pada kendali PID merupakan kesalahan antara input dan output sistem yang akan dibandingkan dengan output yang telah ditala dengan menggunakan parameter adaptive. Terdapat dua macam parameter adaptive untuk kesalahan positif dan negativ. Sinyal keluaran dari parameter adaptif akan memaksa keluaran sistem untuk mengikuti model referensi yang diberikan. Dari hasil percobaan yang dilakukan, menunjukkan bahwa keluaran sistem dapat mengikuti model referensi yang diberikan dengan Mean Sequare Error (MSE) sebesar 0.005 dan memiliki ketahanan yang baik dengan nilai GM adalah ~ dan PM adalah positif yang dilihat dari diagram Bode.

We have compared the thermodynamics of substrate and redox partner binding of P450cam to its close homologue, CYP101D1, using isothermal titration calorimetry (ITC). CYP101D1 binds camphor about 10-fold more weakly than P450cam which is consistent with the inability of camphor to cause a complete low- to high-spin shift in CYP101D1. Even so molecular dynamics simulations show that camphor is very stable in the CYP101D1 active site similar to P450cam. ITC data on the binding of the CYP101D1 ferredoxin redox partner (abbreviated Arx) shows that the substrate-bound closed state of CYP101D1 binds Arx more tightly than the substrate-free open form. This is just the opposite to P450cam where Pdx (ferredoxin redox partner of P450cam) favors binding to the P450cam open state. In addition, CYP101D1-Arx binding has a large negative ΔS while the P450cam-Pdx has a much smaller ΔS indicating that interactions at the docking interface are different. The most obvious difference is that PDXD38 which forms an important ion pair with P450camR112 at the center of the interface is ArxL39 in Arx. This suggests that Arx may adopt a different orientation than Pdx in order to optimize nonpolar interactions with ArxL39.

Non-coding "ultraconserved" regions containing hundreds of consecutive bases of perfect sequence conservation across mammalian genomes can function as distant-acting enhancers. However, initial deletion studies in mice revealed that loss of such extraordinarily constrained sequences had no immediate impact on viability. Here, we show that ultraconserved enhancers are required for normal development. Focusing on some of the longest ultraconserved sites genome wide, located near the essential neuronal transcription factor Arx, we used genome editing to create an expanded series of knockout mice lacking individual or combinations of ultraconserved enhancers. Mice with single or pairwise deletions of ultraconserved enhancers were viable and fertile but in nearly all cases showed neurological or growth abnormalities, including substantial alterations of neuron populations and structural brain defects. Our results demonstrate the functional importance of ultraconserved enhancers and indicate that remarkably strong sequence conservation likely results from fitness deficits that appear subtle in a laboratory setting.

(1) Background: Since the current crises that has inevitably impacted the financial market, market prediction has become more crucial than ever. The question of how risk managers can more accurately predict the evolution of their portfolio, while taking into consideration systemic risks brought on by a systemic crisis, is raised by the low rate of success of portfolio risk-management models. Sentiment analysis on natural language sentences can increase the accuracy of market prediction because financial markets are influenced by investor sentiments. Many investors also base their decisions on information taken from newspapers or on their instincts. (2) Methods: In this paper, we aim to highlight how sentiment analysis can improve the accuracy of regression models when predicting the evolution of the opening prices of some selected stocks. We aim to accomplish this by comparing the results and accuracy of two cases of market prediction using regression models with and without market news sentiment analysis. (3) Results: It is shown that the nonlinear autoregression model improves its goodness of fit when sentiment analysis is used as an exogenous factor. Furthermore, the results show that the polynomial autoregressions fit better than the linear ones. (4) Conclusions: Using the sentiment score for market modelling, significant improvements in the performance of linear autoregressions are showcased. [ABSTRACT FROM AUTHOR]

Nature-inspired metaheuristic algorithms have gained great attention over the last decade due to their potential for finding optimal solutions to different optimization problems. In this study, a metaheuristic based on the dwarf mongoose optimization algorithm (DMOA) is presented for the parameter estimation of an autoregressive exogenous (ARX) model. In the DMOA, the set of candidate solutions were stochastically created and improved using only one tuning parameter. The performance of the DMOA for ARX identification was deeply investigated in terms of its convergence speed, estimation accuracy, robustness and reliability. Furthermore, comparative analyses with other recent state-of-the-art metaheuristics based on Aquila Optimizer, the Sine Cosine Algorithm, the Arithmetic Optimization Algorithm and the Reptile Search algorithm—using a nonparametric Kruskal–Wallis test—endorsed the consistent, accurate performance of the proposed metaheuristic for ARX identification. [ABSTRACT FROM AUTHOR]

We present several improvements to the framework of differential-linear attacks with a special focus on ARX ciphers. As a demonstration of their impact, we apply them to Chaskey and ChaCha and we are able to significantly improve upon the best attacks published so far. [ABSTRACT FROM AUTHOR]