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Background: Deep brain stimulation (DBS) targeting the globus pallidus internus (GPi) and subthalamic nucleus (STN) is employed for the treatment of dystonia. Pallidal low-frequency oscillations have been proposed as a pathophysiological marker for dystonia. However, the role of subthalamic oscillations and STN-GPi coupling in relation to dystonia remains unclear. Objective: We aimed to explore oscillatory activities within the STN-GPi circuit and their correlation with the severity of dystonia and efficacy achieved by DBS treatment. Methods: Local field potentials were recorded simultaneously from the STN and GPi from 13 dystonia patients. Spectral power analysis was conducted for selected frequency bands from both nuclei, while power correlation and the weighted phase lag index were used to evaluate power and phase couplings between these two nuclei, respectively. These features were incorporated into generalized linear models to assess their associations with dystonia severity and DBS efficacy. Results: The results revealed that pallidal theta power, subthalamic beta power and subthalamic-pallidal theta phase coupling and beta power coupling all correlated with clinical severity. The model incorporating all selected features predicts empirical clinical scores and DBS-induced improvements, whereas the model relying solely on pallidal theta power failed to demonstrate significant correlations. Conclusions: Beyond pallidal theta power, subthalamic beta power, STN-GPi couplings in theta and beta bands, play a crucial role in understanding the pathophysiological mechanism of dystonia and developing optimal strategies for DBS.

Abstract Background Deep brain stimulation (DBS) is a promising therapy for refractory Gilles de la Tourette syndrome (GTS). However, its long-term efficacy, safety, and recommended surgical age remain controversial, requiring evidence to compare different age categories. Methods This retrospective cohort study recruited 102 GTS patients who underwent DBS between October 2006 and April 2022 at two national centers. Patients were divided into two age categories: children (aged 0.05), and the children group received significantly higher improvement in GTS-QOL scores than adults (55.9% vs. 47.9%, p = 0.049). Conclusions DBS showed acceptable long-term efficacy and safety for both children and adults with GTS. Surgeries performed for patients younger than 18 years seemed to show acceptable long-term efficacy and safety and were not associated with increased risks of loss of benefit compared to patients older than 18 at the time of surgery. However, surgeries for children should also be performed cautiously to ensure their refractoriness and safety.

Abstract Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson’s disease, Essential Tremor, Dystonia, Essential Tremor, Huntington’s disease, and Tourette’s syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder – BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.

Abstract Subthalamic nucleus deep brain stimulation (STN-DBS) has the potential to delay Parkinson’s disease (PD) progression. Whether oxidative stress participates in the neuroprotective effects of DBS and related signaling pathways remains unknown. To address this, we applied STN-DBS to mice and monkey models of PD and collected brain tissue to evaluate mitophagy, oxidative stress, and related pathway. To confirm findings in animal experiments, a cohort of PD patients was recruited and oxidative stress was evaluated in cerebrospinal fluid. When PD mice received STN stimulation, the mTOR pathway was suppressed, accompanied by elevated LC3 II expression, increased mitophagosomes, and a decrease in p62 expression. The increase in mitophagy and balance of mitochondrial fission/fusion dynamics in the substantia nigra caused a marked enhancement of the antioxidant enzymes superoxide dismutase and glutathione levels. Subsequently, fewer mitochondrial apoptogenic factors were released to the cytoplasm, which resulted in a suppression of caspase activation and reservation of dopaminergic neurons. While interfaced with an mTOR activator, oxidative stress was no longer regulated by STN-DBS, with no neuroprotective effect. Similar results to those found in the rodent experiments were obtained in monkeys treated with chronic STN stimulation. Moreover, antioxidant enzymes in PD patients were increased after the operation, however, there was no relation between changes in antioxidant enzymes and motor impairment. Collectively, our study found that STN-DBS was able to increase mitophagy via an mTOR-dependent pathway, and oxidative stress was suppressed due to removal of damaged mitochondria, which was attributed to the dopaminergic neuroprotection of STN-DBS in PD.

In bronchial ultrasound elastography, accurately segmenting mediastinal lymph nodes is of great significance for diagnosing whether lung cancer has metastasized. However, due to the ill-defined margin of ultrasound images and the complexity of lymph node structure, accurate segmentation of fine contours is still challenging. Therefore, we propose a dual-stream feature-fusion attention U-Net (DFA-UNet). Firstly, a dual-stream encoder (DSE) is designed by combining ConvNext with a lightweight vision transformer (ViT) to extract the local information and global information of images; Secondly, we propose a hybrid attention module (HAM) at the bottleneck, which incorporates spatial and channel attention to optimize the features transmission process by optimizing high-dimensional features at the bottom of the network. Finally, the feature-enhanced residual decoder (FRD) is developed to improve the fusion of features obtained from the encoder and decoder, ensuring a more comprehensive integration. Extensive experiments on the ultrasound elasticity image dataset show the superiority of our DFA-UNet over 9 state-of-the-art image segmentation models. Additionally, visual analysis, ablation studies, and generalization assessments highlight the significant enhancement effects of DFA-UNet. Comprehensive experiments confirm the excellent segmentation effectiveness of the DFA-UNet combined attention mechanism for ultrasound images, underscoring its important significance for future research on medical images.

In this paper, we present two constructions of quantum locally testable codes (QLTC) with constant soundness. In the first approach, we introduce an operation called check product, and show how this operation gives rise to QLTCs of constant soundness, constant rate, and distance scaling with locality. In the second approach, we consider hypergraph product of a quantum code and a classical repetition code, and observe a special case in which the soundness of component codes is preserved. This insight leads us to construct QLTCs of constant soundness, scalable rate and distance, and constant average locality. Our work marks a step towards constructing QLTCs of high soundness and distance, which would give a different construction to the No Low-Energy Trivial States (NLTS) theorem.

Subsystem quantum error-correcting codes typically involve measuring a sequence of noncommuting parity check operators. They can sometimes exhibit greater fault tolerance than conventional subspace codes, which use commuting checks. However, unlike subspace codes, it is unclear if subsystem codes—in particular their advantages—can be understood in terms of ground-state properties of a physical Hamiltonian. In this paper, we address this question for the three-dimensional subsystem toric code (3D STC), as recently constructed by Kubica and Vasmer [Nat. Commun. 13, 6272 (2022)2041-172310.1038/s41467-022-33923-4], which exhibits single-shot error correction. Motivated by a conjectured relation between single-shot properties and thermal stability, we study the zero- and finite-temperature phases of an associated noncommuting Hamiltonian. By mapping the Hamiltonian model to a pair of 3D Z_{2} gauge theories coupled by a kinetic constraint, we find various phases at zero temperature, all separated by first-order transitions: There are 3D toric code-like phases with deconfined point-like excitations in the bulk, and there are phases with a confined bulk supporting a 2D toric code on the surface when appropriate boundary conditions are chosen. The latter is similar to the surface topological order present in 3D STC. However, the similarities between the single-shot correction in 3D STC and the confined phases are only partial: they share the same sets of degrees of freedom, but they are governed by different dynamical rules. Instead, we argue that the process of single-shot error correction can more suitably be associated with a path (rather than a point) in the zero-temperature phase diagram, a perspective, which inspires alternative measurement sequences enabling single-shot error correction. Moreover, since none of the above-mentioned phases survives at nonzero temperature, the single-shot error-correction property of the code does not imply thermal stability of the associated Hamiltonian phase.

Temporal interference (TI) stimulation, a novel non-invasive stimulation strategy, has recently been shown to modulate neural activity in deep brain regions of living mice. Yet, it is uncertain if this method is applicable to larger brains and whether the electric field produced under traditional safety currents can penetrate deep regions as observed in mice. Despite recent model-based simulation studies offering positive evidence at both macro- and micro-scale levels, the absence of electrophysiological data from actual brains hinders comprehensive understanding and potential application of TI. This study aims to directly measure the spatiotemporal properties of the interfered electric field in the rhesus monkey brain and to validate the effects of TI on the human brain. Two monkeys were involved in the measurement, with implantation of several stereo-electroencephalography (SEEG) depth electrodes. TI stimulation was applied to anesthetized monkeys using two pairs of surface electrodes at differing stimulation parameters. Model-based simulations were also conducted and subsequently compared with actual recordings. Additionally, TI stimulation was administered to patients with motor disorders to validate its effects on motor symptoms.Through the integration of computational electric field simulation with empirical measurements, it was determined that the temporally interfering electric fields in the deep central regions are capable of attaining a magnitude sufficient to induce a subthreshold modulation effect on neural signals. Additionally, an improvement in movement disorders was observed as a result of TI stimulation. This study is the first to systematically measure the TI electric field in living non-human primates, offering empirical evidence that TI holds promise as a more focal and precise method for modulating neural activities in deep regions of a large brain. This advancement paves the way for future applications of TI in treating neuropsychiatric disorders.

Abstract Parkinson’s disease (PD) is associated with excessive beta activity in the basal ganglia. Brain sensing implants aim to leverage this biomarker for demand-dependent adaptive stimulation. Sleep disturbance is among the most common non-motor symptoms in PD, but its relationship with beta activity is unknown. To investigate the clinical potential of beta activity as a biomarker for sleep quality in PD, we recorded pallidal local field potentials during polysomnography in PD patients off dopaminergic medication and compared the results to dystonia patients. PD patients exhibited sustained and elevated beta activity across wakefulness, rapid eye movement (REM), and non-REM sleep, which was correlated with sleep disturbance. Simulation of adaptive stimulation revealed that sleep-related beta activity changes remain unaccounted for by current algorithms, with potential negative outcomes in sleep quality and overall quality of life for patients.

The present study aimed to explore whether water flow velocity could affect the swimming ability and overall energy metabolism of wild Amur grayling (Thymallus grubii). Swimming performance was assessed by measuring critical swimming speed (Ucrit), burst speed (Uburst), and oxygen consumption rate (MO2) based on the stepped velocity test method. Our results showed that the absolute values of Ucrit and Uburst tended to increase with body length. In contrast, the relative values of Ucrit and Uburst tended to decrease and increase, respectively. MO2 in Amur grayling was elevated with increasing velocity, suggesting relatively high swimming efficiency. We also measured the biochemical indices related to energy metabolism. Lactate dehydrogenase, hexokinase, and pyruvate kinase activities significantly increased (p < 0.05). Hepatic glycogen, glucose, and muscle glycogen contents decreased with the increasing trend of velocity (p < 0.05), the lactic acid contents of the blood and muscles increased significantly with the increase in velocities (p < 0.05), and changes in creatine phosphate content showed no significant difference (p > 0.05). The results not only denote the relationship between body size and swimming speed but also show the effects of water flow velocity on energy metabolism in Amur grayling. The results provide basic data for the construction of fish passage.

Background & Aims: OATP1B3/SLCO1B3 is a human liver-specific transporter for the clearance of endogenous compounds (eg, bile acid [BA]) and xenobiotics. The functional role of OATP1B3 in humans has not been characterized, as SLCO1B3 is poorly conserved among species without mouse orthologs. Methods: Slc10a1-knockout (Slc10a1-/-), Slc10a1hSLCO1B3 (endogenous mouse Slc10a1 promoter-driven human-SLCO1B3 expression in Slc10a1-/- mice), and human SLCO1B3 liver-specific transgenic (hSLCO1B3-LTG) mice were generated and challenged with 0.1% ursodeoxycholic-acid (UDCA), 1% cholic-acid (CA) diet, or bile duct ligation (BDL) for functional studies. Primary hepatocytes and hepatoma-PLC/RPF/5 cells were used for mechanistic studies. Results: Serum BA levels in Slc10a1-/- mice were substantially increased with or without 0.1% UDCA feeding compared with wild-type (WT) mice. This increase was attenuated in Slc10a1hSLCO1B3-mice, indicating that OATP1B3 functions as a significant hepatic BA uptake transporter. In vitro assay using primary hepatocytes from WT, Slc10a1-/-, and Slc10a1hSLCO1B3-mice indicated that OATP1B3 has a similar capacity in taking up taurocholate/TCA as Ntcp. Furthermore, TCA-induced bile flow was significantly impaired in Slc10a1-/- mice but partially recovered in Slc10a1hSLC01B3-mice, indicating that OATP1B3 can partially compensate the NTCP function in vivo. Liver-specific overexpression of OATP1B3 markedly increased the level of hepatic conjugated BA and cholestatic liver injury in 1% CA-fed and BDL mice. Mechanistic studies revealed that conjugated BAs stimulated Ccl2 and Cxcl2 in hepatocytes to increase hepatic neutrophil infiltration and proinflammatory cytokine production (eg, IL-6), which activated STAT3 to repress OATP1B3 expression by binding to its promoter. Conclusions: Human OATP1B3 is a significant BA uptake transporter and can partially compensate Ntcp for conjugated BA uptake in mice. Its downregulation in cholestasis is an adaptive protective response.

Background: Sleep disturbances are highly prevalent in movement disorders, potentially due to the malfunctioning of basal ganglia structures. Pallidal deep brain stimulation (DBS) has been widely used for multiple movement disorders and been reported to improve sleep. We aimed to investigate the oscillatory pattern of pallidum during sleep and explore whether pallidal activities can be utilized to differentiate sleep stages, which could pave the way for sleep-aware adaptive DBS. Methods: We directly recorded over 500 h of pallidal local field potentials during sleep from 39 subjects with movement disorders (20 dystonia, 8 Huntington's disease, and 11 Parkinson's disease). Pallidal spectrum and cortical-pallidal coherence were computed and compared across sleep stages. Machine learning approaches were utilized to build sleep decoders for different diseases to classify sleep stages through pallidal oscillatory features. Decoding accuracy was further associated with the spatial localization of the pallidum. Results: Pallidal power spectra and cortical-pallidal coherence were significantly modulated by sleep-stage transitions in three movement disorders. Differences in sleep-related activities between diseases were identified in non-rapid eye movement (NREM) and REM sleep. Machine learning models using pallidal oscillatory features can decode sleep-wake states with over 90% accuracy. Decoding accuracies were higher in recording sites within the internus-pallidum than the external-pallidum, and can be precited using structural (P

In this paper, we use an evolutionary game theory approach to build a relationship model of students and clubs for the purpose of improving student enthusiasm for participating in club activities. First, the process of the model building is introduced, which mainly includes the basic assumptions and the equilibrium point stability analysis. Based on this analysis, we find that the motivation adjustment of students and clubs is a dynamic process and that unilateral efforts alone cannot achieve an ideal result. Then, we use real data from Yanshan University to evaluate the model, the results of which indicate that the model can analyze the relationship between students and clubs effectively. Finally, we provide relevant suggestions based on the model established in this study, whereby we contribute a theoretical basis and practical guidance for how students can actively participate in clubs, as well as how clubs can better develop themselves.

Whether or not the Kronecker coefficients of the symmetric group count some set of combinatorial objects is a longstanding open question. In this work we show that a given Kronecker coefficient is proportional to the rank of a projector that can be measured efficiently using a quantum computer. In other words a Kronecker coefficient counts the dimension of the vector space spanned by the accepting witnesses of a QMA verifier, where QMA is the quantum analogue of NP. This implies that approximating the Kronecker coefficients to within a given relative error is not harder than a certain natural class of quantum approximate counting problems that captures the complexity of estimating thermal properties of quantum many-body systems. A second consequence is that deciding positivity of Kronecker coefficients is contained in QMA, complementing a recent NP-hardness result of Ikenmeyer, Mulmuley, and Walter. We obtain similar results for the related problem of approximating row sums of the character table of the symmetric group. Finally, we discuss an efficient quantum algorithm that approximates normalized Kronecker coefficients to inverse-polynomial additive error.

This study is focused on examining the feasibility of applying laser hardening to a commercial metallic bike rim, employing a CW IR fibre laser. The research comprises two main phases. The first phase involves an assessment of the impact of laser parameters on the metallic microstructure, while the second phase involves the actual laser hardening of the bike rim. A comprehensive evaluation encompassing hardness measurements, optical microscopy, and scanning electron microscopy was conducted on the samples. The microstructure type can be manipulated by skilfully adjusting the laser parameters, allowing for the creation of various microstructure variants within the laser-hardened zone for specific laser conditions. In this regard, multiple microstructure types were observed. The hardness of the laser-processed zones exhibited variations corresponding to the specific microstructure. Notably, the molten zone (MZ) and the second heat-affected zone (HAZ II) exhibited the highest levels of hardness. Furthermore, it was observed that a scan overlap of ≥ 75% led to an augmentation in hardness. This study sheds light on the intricate interplay between laser parameters, microstructure, and resultant hardness in the context of laser hardening of metallic materials.

Background: Subthalamic nucleus deep brain stimulation (STN-DBS) improves sleep qualities in Parkinson’s disease (PD) patients; however, it remains elusive whether STN-DBS improves sleep by directly influencing the sleep circuit or alleviates other cardinal symptoms such as motor functions, other confounding factors including stimulation intensity may also involve. Studying the effect of microlesion effect (MLE) on sleep after STN-DBS electrode implantation may address this issue. Objective: To examine the influence of MLE on sleep quality and related factors in PD, as well as the effects of regional and lateral specific correlations with sleep outcomes after STN-DBS electrode implantation. Study Design: Case–control study; Level of evidence, 3. Data Sources and Methods: In 78 PD patients who underwent bilateral STN-DBS surgery in our center, we compared the sleep qualities, motor performances, anti-Parkinsonian drug dosage, and emotional conditions at preoperative baseline and postoperative 1-month follow-up. We determined the related factors of sleep outcomes and visualized the electrodes position, simulated the MLE-engendered volume of tissue lesioned (VTL), and investigated sleep-related sweet/sour spots and laterality in STN. Results: MLE improves sleep quality with Pittsburgh Sleep Quality Index (PSQI) by 13.36% and Parkinson’s Disease Sleep Scale-2 (PDSS-2) by 17.95%. Motor ( P = 0.014) and emotional ( P = 0.001) improvements were both positively correlated with sleep improvements. However, MLE in STN associative subregions, as an independent factor, may cause sleep deterioration ( r = 0.348, P = 0.002), and only the left STN showed significance ( r = 0.327, P = 0.004). Sweet spot analysis also indicated part of the left STN associative subregion is the sour spot indicative of sleep deterioration. Conclusion: The MLE of STN-DBS can overall improve sleep quality in PD patients, with a positive correlation between motor and emotional improvements. However, independent of all other factors, the MLE in the STN associative subregion, particularly the left side, may cause sleep deterioration.

Recently, a class of fractal surface codes (FSCs), has been constructed on fractal lattices with Hausdorff dimension $2+\epsilon$, which admits a fault-tolerant non-Clifford CCZ gate \cite{zhu2021topological}. We investigate the performance of such FSCs as fault-tolerant quantum memories. We prove that there exist decoding strategies with non-zero thresholds for bit-flip and phase-flip errors in the FSCs with Hausdorff dimension $2+\epsilon$. For the bit-flip errors, we adapt the sweep decoder, developed for string-like syndromes in the regular 3D surface code, to the FSCs by designing suitable modifications on the boundaries of the holes in the fractal lattice. Our adaptation of the sweep decoder for the FSCs maintains its self-correcting and single-shot nature. For the phase-flip errors, we employ the minimum-weight-perfect-matching (MWPM) decoder for the point-like syndromes. We report a sustainable fault-tolerant threshold ($\sim 1.7\%$) under phenomenological noise for the sweep decoder and the code capacity threshold (lower bounded by $2.95\%$) for the MWPM decoder for a particular FSC with Hausdorff dimension $D_H\approx2.966$. The latter can be mapped to a lower bound of the critical point of a confinement-Higgs transition on the fractal lattice, which is tunable via the Hausdorff dimension.

Abstract Neuroscientific studies on the function of the basal ganglia often examine the behavioral performance of patients with movement disorders, such as Parkinson’s disease (PD) and dystonia (DT), while simultaneously examining the underlying electrophysiological activity during deep brain stimulation surgery. Nevertheless, to date, there have been no studies comparing the cognitive performance of PD and DT patients during surgery. In this study, we assessed the memory function of PD and DT patients with the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE). We also tested their cognitive performance during the surgery using a continuous recognition memory test. The results of the MoCA and MMSE failed to reveal significant differences between the PD and DT patients. Additionally, no significant difference was detected by the intraoperative memory test between the PD and DT patients. The intraoperative memory test scores were highly correlated with the MMSE scores and MoCA scores. Our data suggest that DT patients perform similarly to PD patients in cognitive tests during surgery, and intraoperative memory tests can be used as a quick memory assessment tool during surgery.

Low-frequency oscillations (LFOs, 28 Hz) in the subthalamic nucleus(STN) are known to reflect cognitive conflict. However, it is unclear if LFOs mediate communication and functional interactions among regions implicated in conflict processing, such as the motor cortex (M1), premotor cortex (PMC), and superior parietal lobule (SPL). To investigate the potential contribution of LFOs to cognitive conflict mediation, we recorded M1, PMC, and SPL activities by right subdural electrocorticography (ECoG) simultaneously with bilateral STN local field potentials (LFPs) by deep brain stimulation electrodes in 13 patients with Parkinson's disease who performed the arrow version of the Eriksen flanker task. Elevated cue-related LFO activity was observed across patients during task trials, with the earliest onset in PMC and SPL. At cue onset, LFO power exhibited a significantly greater increase or a trend of a greater increase in the PMC, M1, and STN, and less increase in the SPL during high-conflict (incongruent) trials than in low-conflict (congruent) trials. The local LFO power increases in PMC, SPL, and right STN were correlated with response time, supporting the notion that these structures are critical hubs for cognitive conflict processing. This power increase was accompanied by increased functional connectivity between the PMC and right STN, which was correlated with response time across subjects. Finally, ipsilateral PMC-STN Granger causality was enhanced during high-conflict trials, with direction from STN to PMC. Our study indicates that LFOs link the frontal and parietal cortex with STN during conflicts, and the ipsilateral PMC-STN connection is specifically involved in this cognitive conflict processing.

Abstract Background Digestive tract reconstruction in totally laparoscopic total gastrectomy can be divided into two types: instrument anastomosis and hand-sewn anastomosis. This study explored the feasibility and safety of hand-sewn sutures in esophagojejunostomy of totally laparoscopic total gastrectomy, compared with instrument anastomosis using an overlap linear cutter. Methods This retrospective cohort study was conducted from January 2017 to January 2020 at one institution. The clinical data of 50 patients who underwent totally laparoscopic total gastrectomy, with an average follow-up time of 12 months, were collected. The clinicopathologic data, short-term survival prognosis, and results of patients in the hand-sewn anastomosis (n=20) and the overlap anastomosis (n=30) groups were analyzed. Results There were no significant differences between the groups in sex, age, body mass index, American Society of Anesthesiologists score, tumor location, preoperative complications, abdominal operation history, tumor size, pTNM stage, blood loss, first postoperative liquid diet, exhaust time, or postoperative length of hospital stay. The hand-sewn anastomosis group had a significantly prolonged operation time (204±26.72min versus 190±20.90min, p=0.04) and anastomosis time (58±22.0min versus 46±15.97min, p=0.029), and a decreased operation cost (CNY 77,100±1700 versus CNY 71,900±1300, p

Online microwave drying process monitoring has been challenging due to the incompatibility of metal components with microwaves. This paper developed a microwave drying system based on online machine vision, which realized real-time extraction and measurement of images, weight, and temperature. An image-processing algorithm was developed to capture material shrinkage characteristics in real time. Constant-temperature microwave drying experiments were conducted, and the artificial neural network (ANN) and extreme learning machine (ELM) were utilized to model and predict the moisture content of materials during the drying process based on the degree of material shrinkage. The results demonstrated that the system and algorithm operated effectively, and ELM provided superior predictive performance and learning efficiency compared to ANN.

A real-time aroma monitoring system to control a microwave combined with hot air drying (MHAD) process of carrot was designed. The samples were first dried at four fixed temperature gradients of 2°C/mm, 4°C/mm, 6°C/mm and 8°C/mm to investigate the effect of temperature gradient on the aroma diffusion. Carrot samples could be dried in a shorter time from 140 min to 100 min from low-temperature gradients 2°C/mm to high-temperature gradient 8°C/mm. Main volatiles lost more and charring volatiles was induced at highest temperature gradients 8°C/mm. A fuzzy logic controller was then designed and employed to control the drying process. Based on the temperature curve achieved under fuzzy logic control, a simple linear control method was developed where e-nose online assistance could be omitted. Color, vitamin C, rehydration ratio and sensory evaluation were performed after rehydration. With the new control strategies, carrot color and overall appearance were intact and less time and energy were consumed.

As an agricultural plant, the cantaloupe contains rich nutrition and high moisture content. In this paper, the estimation problem of the moisture ratio model during a cantaloupe microwave drying process was considered. First of all, an image processing-based cantaloupe drying system was designed and the expression of the moisture ratio with regard to the shrinkage was built. Secondly, a maximum likelihood principle-based iterative evolution (MLP-IE) algorithm was put forward to estimate the moisture ratio model. After that, aiming at enhancing the model fitting ability of the MLP-IE algorithm, a maximum likelihood principle-based improved iterative evolution (MLP-I-IE) algorithm was proposed by designing the improved mutation strategy, the improved scaling factor, and the improved crossover rate. Finally, the MLP-IE algorithm and MLP-I-IE algorithm were applied for estimating the moisture ratio model of cantaloupe slices. The results showed that both the MLP-IE algorithm and MLP-I-IE algorithm were effective and that the MLP-I-IE algorithm performed better than the MLP-IE algorithm in model estimation and validation.

For food drying, moisture content and shrinkage are vital in the drying process. This paper is concerned with the moisture ratio modeling and prediction issues of the Hami melon drying process. First, an experimental system was developed; it included an adjustable-power microwave drying unit and an image-processing unit. The moisture contents and the areas of Hami melon slices at different times were sampled in real time. Then, the expression of the moisture ratio with regard to shrinkage was derived by using the Weierstrass approximation theorem. A maximum likelihood fitness function-based population evolution (MLFF-PE) algorithm was then put forward to fit the moisture ratio model and predict the moisture ratio. The results showed that the proposed MLFF-PE algorithm was effective at fitting and predicting the moisture ratio model of the drying process of Hami melon slices.

Background: The successful application of subthalamic nucleus (STN) deep brain stimulation (DBS) surgery relies mostly on optimal lead placement, whereas the major challenge is how to precisely localize STN. Microstimulation, which can induce differentiating inhibitory responses between STN and substantia nigra pars reticulata (SNr) near the ventral border of STN, has indicated a great potential of breaking through this barrier.Objective: This study aims to investigate the feasibility of localizing the boundary between STN and SNr (SSB) using microstimulation and promote better lead placement.Methods: We recorded neurophysiological data from 41 patients undergoing STN-DBS surgery with microstimulation in our hospital. Trajectories with typical STN signal were included. Microstimulation was applied near the bottom of STN to determine SSB, which was validated by the imaging reconstruction of DBS leads.Results: In most trajectories with microstimulation (84.4%), neuronal firing in STN could not be inhibited by microstimulation, whereas in SNr long inhibition was observed following microstimulation. The success rate of localizing SSB was significantly higher in trajectories with microstimulation than those without. Moreover, results from imaging reconstruction and intraoperative neurological assessments demonstrated better lead location and higher therapeutic effectiveness in trajectories with microstimulation and accurately identified SSB.Conclusion: Microstimulation on microelectrode recording is an effective approach to localize the SSB. Our data provide clinical evidence that microstimulation can be routinely employed to achieve better lead placement.

We investigate topological order on fractal geometries embedded in n dimensions. We consider the n-dimensional lattice with holes at all length scales the corresponding fractal (Hausdorff) dimension of which is D_{H}=n−δ. In particular, we diagnose the existence of the topological order through the lens of quantum information and geometry, i.e., via its equivalence to a quantum error-correcting code with a macroscopic code distance or the presence of macroscopic systoles in systolic geometry. We first prove a no-go theorem that Z_{N} topological order cannot survive on any fractal embedded in two spatial dimensions and with D_{H}=2−δ. For fractal-lattice models embedded in three dimensions (3D) or higher spatial dimensions, Z_{N} topological order survives if the boundaries on the holes condense only loop or, more generally, k-dimensional membrane excitations (k≥2), thus predicting the existence of fractal topological quantum memories (at zero temperature) or topological codes that are embeddable in 3D. Moreover, for a class of models that contain only loop or membrane excitations and are hence self-correcting on an n-dimensional manifold, we prove that Z_{N} topological order survives on a large class of fractal geometries independent of the type of hole boundary and is hence extremely robust. We further construct fault-tolerant logical gates in the Z_{2} version of these fractal models, which we term fractal surface codes, using their connection to global and higher-form topological symmetries equivalent to sweeping the corresponding gapped domain walls. In particular, we discover a logical controlled-controlled-Z (ccz) gate corresponding to a global symmetry in a class of fractal codes embedded in 3D with Hausdorff dimension asymptotically approaching D_{H}=2+ϵ for arbitrarily small ϵ, which hence only requires a space overhead Ω(d^{2+ϵ}), where d is the code distance. This in turn leads to the surprising discovery of certain exotic gapped boundaries that only condense the combination of loop excitations and certain gapped domain walls. We further obtain logical C^{p}Z gates with p≤n−1 on fractal codes embedded in n dimensions. In particular, for the logical C^{n−1}Z in the nth level of the Clifford hierarchy, we can reduce the space overhead to Ω(d^{n−1+ϵ}). On the mathematical side, our findings in this paper also lead to the discovery of macroscopic relative systoles in a class of fractal geometries.

Deep brain stimulation (DBS) surgery offers a unique opportunity to record local field potentials (LFPs), the electrophysiological population activity of neurons surrounding the depth electrode in the target area. With direct access to the subcortical activity, LFP research has provided valuable insight into disease mechanisms and cognitive processes and inspired the advent of adaptive DBS for Parkinson's disease (PD). A frequency-based framework is usually employed to interpret the implications of LFP signatures in LFP studies on PD. This approach standardizes the methodology, simplifies the interpretation of LFP patterns, and makes the results comparable across studies. Importantly, previous works have found that activity patterns do not represent disease-specific activity but rather symptom-specific or task-specific neuronal signatures that relate to the current motor, cognitive or emotional state of the patient and the underlying disease. In the present review, we aim to highlight distinguishing features of frequency-specific activities, mainly within the motor domain, recorded from DBS electrodes in patients with PD. Associations of the commonly reported frequency bands (delta, theta, alpha, beta, gamma, and high-frequency oscillations) to motor signs are discussed with respect to band-related phenomena such as individual tremor and high/low beta frequency activity, as well as dynamic transients of beta bursts. We provide an overview on how electrophysiology research in DBS patients has revealed and will continuously reveal new information about pathophysiology, symptoms, and behavior, e.g., when combining deep LFP and surface electrocorticography recordings.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the presence of α-synuclein (α-Syn)-rich Lewy bodies (LBs) and the preferential loss of dopaminergic (DA) neurons in the substantia nigra (SN) pars compacta (SNpc). However, the widespread involvement of other central nervous systems (CNS) structures and peripheral tissues is now widely documented. The onset of the molecular and cellular neuropathology of PD likely occurs decades before the onset of the motor symptoms characteristic of PD, so early diagnosis of PD and adequate tracking of disease progression could significantly improve outcomes for patients. Because the clinical diagnosis of PD is challenging, misdiagnosis is common, which highlights the need for disease-specific and early-stage biomarkers. This review article aims to summarize useful biomarkers for the diagnosis of PD, as well as the biomarkers used to monitor disease progression. This review article describes the role of α-Syn in PD and how it could potentially be used as a biomarker for PD. Also, preclinical and clinical investigations encompassing genetics, immunology, fluid and tissue, imaging, as well as neurophysiology biomarkers are discussed. Knowledge of the novel biomarkers for preclinical detection and clinical evaluation will contribute to a deeper understanding of the disease mechanism, which should more effectively guide clinical applications.

Background Mitochondria are unique organelles that are found in most eukaryotic cells. The main role of the mitochondria is to produce ATP. The nuclear genome encoded proteins Cbs1 and Cbs2 are located at the mitochondrial inner membrane and are reported to be essential for the translation of mitochondrial cytochrome b mRNA. Genetic studies show that Cbs2 protein recognizes the 5′ untranslated leader sequence of mitochondrial cytochrome b mRNA. However, due to a lack of biochemical and structural information, this biological process remains unclear. To investigate the structural characteristics of how Saccharomyces cerevisiae (S. cerevisiae) Cbs2 tethers cytochrome b mRNA to the mitochondrial inner membrane, a preliminary X-ray crystallographic study was carried out and is reported here. Methods The target gene from S. cerevisiae was amplified by polymerase chain reaction. The PCR fragment was digested by the NdeI and XhoI restriction endonucleases and then inserted into expression vector p28. After sequencing, the plasmid was transformed into Escherichia coli C43 competent cells. The selenomethionine derivative Cbs2 protein was overexpressed using M9 medium based on a methionine-biosynthesis inhibition method. The protein was first purified to Ni2+-nitrilotriacetate affinity chromatography and then further purified by Ion exchange chromatography and Gel-filtration chromatography. The purified Se-Cbs2 protein was concentrated to 10 mg/mL. The crystallization trials were performed using the sitting-drop vapor diffusion method at 16 °C. The complete diffraction data was processed and scaled with the HKL2000 package and programs in the CCP4 package, respectively. Results Cbs2 from S. cerevisiae was cloned, prokaryotic expressed and purified. The analysis of the size exclusion chromatography showed that the Cbs2 protein peaked at a molecular weight of approximately 90 KDa. The crystal belonged to the space group C2, with unit-cell parameters of a = 255.11, b = 58.10, c = 76.37, and β = 95.35°. X-ray diffraction data was collected at a resolution of 2.7 Å. The Matthews coefficient and the solvent content were estimated to be 3.22 Å 3 Da-1 and 61.82%, respectively. Conclusions In the present study Cbs2 from S. cerevisiae was cloned, expressed, purified, and crystallized for structural studies. The molecular weight determination results indicated that the biological assembly of Cbs2 may be a dimer.The preliminary X-ray crystallographic studies indicated the presence of two Cbs2 molecules in the asymmetric unit. This study will provide an experimental basis for exploring how Cbs2 protein mediates cytochrome b synthesis.

We consider a two-dimensional quantum memory of qubits on a torus which encode the extended Fibonacci string-net code and devise strategies for error correction when those qubits are subjected to depolarizing noise. Building on the concept of tube algebras, we construct a set of measurements and of quantum gates which map arbitrary qubit errors to the string-net subspace and allow for the characterization of the resulting error syndrome in terms of doubled Fibonacci anyons. Tensor network techniques then allow us to quantitatively study the action of Pauli noise on the string-net subspace. We perform Monte Carlo simulations of error correction in this Fibonacci code and compare the performance of several decoders. For the case of a fixed-rate sampling depolarizing noise model, we find an error correction threshold of 4.7% using a clustering decoder.

We study quasi-exact quantum error-correcting codes and quantum computation with them. A quasi-exact code is an approximate code such that it contains a finite number of scaling parameters, the tuning of which can flow it to corresponding exact codes, serving as its fixed points. The computation with a quasi-exact code cannot realize any logical gate to arbitrary accuracy. To overcome this, the notion of quasi-exact universality is proposed, which makes quasi-exact quantum computation a feasible model especially for executing moderate-size algorithms. We find that the incompatibility between universality and transversality of the set of logical gates does not persist in the quasi-exact scenario. A class of covariant quasi-exact codes is defined which proves to support a transversal and quasi-exact universal set of logical gates for SU(d). This work opens the possibility of quantum computation with quasi-exact universality, transversality, and fault tolerance.

In topology, a torus remains invariant under certain nontrivial transformations known as modular transformations. In the context of topologically ordered quantum states of matter supported on a torus geometry in real space, these transformations encode the braiding statistics and fusion rules of emergent anyonic excitations and thus serve as a diagnostic of topological order. Moreover, modular transformations of higher genus surfaces, e.g., a torus with multiple handles, can enhance the computational power of a topological state, in many cases providing a universal fault-tolerant set of gates for quantum computation. However, due to the intrusive nature of modular transformations, which abstractly involve global operations, physical implementations of them in local systems have remained elusive. Here, we show that by engineering an effectively folded manifold corresponding to a multilayer topological system, modular transformations can be applied in a single shot by independent local unitaries, providing a novel class of transversal logical gates for fault-tolerant quantum computation. Specifically, we demonstrate that multilayer topological states with appropriate boundary conditions and twist defects allow modular transformations to be effectively implemented by a finite sequence of local SWAP gates between the layers. We further provide methods to directly measure the modular matrices, and thus the fractional statistics of anyonic excitations, providing a novel way to directly measure topological order. A more general theory of transversal gates and the deep connection to anyon symmetry transformation and symmetry-enriched topological orders are also discussed.

The color code is a topological quantum error-correcting code supporting a variety of valuable fault-tolerant logical gates. Its two-dimensional version, the triangular color code, may soon be realized with currently available superconducting hardware despite constrained qubit connectivity. To guide this experimental effort, we study the storage threshold of the triangular color code against circuit-level depolarizing noise. First, we adapt the Restriction Decoder to the setting of the triangular color code and to phenomenological noise. Then, we propose a fault-tolerant implementation of the stabilizer measurement circuits, which incorporates flag qubits. We show how information from flag qubits can be used in an efficient and scalable way with the Restriction Decoder to maintain the effective distance of the code. We numerically estimate the threshold of the triangular color code to be 0.2%, which is competitive with the thresholds of other topological quantum codes. We also prove that 1-flag stabilizer measurement circuits are sufficient to preserve the full code distance, which may be used to find simpler syndrome extraction circuits of the color code.

In this work we introduce two code families, which we call the heavy-hexagon code and the heavy-square code. Both code families are implemented by assigning physical data and ancilla qubits to both vertices and edges of low-degree graphs. Such a layout is particularly suitable for superconducting qubit architectures to minimize frequency collisions and cross talk. In some cases, frequency collisions can be reduced by several orders of magnitude. The heavy-hexagon code is a hybrid surface and Bacon-Shor code mapped onto a (heavy-) hexagonal lattice, whereas the heavy-square code is the surface code mapped onto a (heavy-) square lattice. In both cases, the lattice includes all the ancilla qubits required for fault-tolerant error correction. Naively, the limited qubit connectivity might be thought to limit the error-correcting capability of the code to less than its full distance. Therefore, essential to our construction is the use of flag qubits. We modify minimum-weight perfect-matching decoding to efficiently and scalably incorporate information from measurements of the flag qubits and correct up to the full code distance while respecting the limited connectivity. Simulations show that high threshold values for both codes can be obtained using our decoding protocol. Further, our decoding scheme can be adapted to other topological code families.

Background: Dystonia and Huntington's disease (HD) are both hyperkinetic movement disorders but exhibit distinct clinical characteristics. Aberrant output from the globus pallidus internus (GPi) is involved in the pathophysiology of both HD and dystonia, and deep brain stimulation (DBS) of the GPi shows good clinical efficacy in both disorders. The electrode externalized period provides an opportunity to record local field potentials (LFPs) from the GPi to examine if activity patterns differ between hyperkinetic disorders and are associated with specific clinical characteristics.Methods: LFPs were recorded from 7 chorea-dominant HD and nine cervical dystonia patients. Differences in oscillatory activities were compared by power spectrum and Lempel-Ziv complexity (LZC). The discrepancy band power ratio was used to control for the influence of absolute power differences between groups. We further identified discrepant frequency bands and frequency band ratios for each subject and examined the correlations with clinical scores.Results: Dystonia patients exhibited greater low frequency power (6–14 Hz) while HD patients demonstrated greater high-beta and low-gamma power (26–43 Hz) (p < 0.0298, corrected). United Huntington Disease Rating Scale chorea sub-score was positively correlated with 26–43 Hz frequency band power and negatively correlated with the 6–14 Hz/26–43 Hz band power ratio.Conclusion: Dystonia and HD are characterized by distinct oscillatory activity patterns, which may relate to distinct clinical characteristics. Specifically, chorea may be related to elevated high-beta and low-gamma band power, while dystonia may be related to elevated low frequency band power. These LFPs may be useful biomarkers for adaptive DBS to treat hyperkinetic diseases.

A basic question in the theory of fault-tolerant quantum computation is to understand the fundamental resource costs for performing a universal logical set of gates on encoded qubits to arbitrary accuracy. Here we consider qubits encoded with constant space overhead (i.e. finite encoding rate) in the limit of arbitrarily large code distance $d$ through the use of topological codes associated to triangulations of hyperbolic surfaces. We introduce explicit protocols to demonstrate how Dehn twists of the hyperbolic surface can be implemented on the code through constant depth unitary circuits, without increasing the space overhead. The circuit for a given Dehn twist consists of a permutation of physical qubits, followed by a constant depth local unitary circuit, where locality here is defined with respect to a hyperbolic metric that defines the code. Applying our results to the hyperbolic Fibonacci Turaev-Viro code implies the possibility of applying universal logical gate sets on encoded qubits through constant depth unitary circuits and with constant space overhead. Our circuits are inherently protected from errors as they map local operators to local operators while changing the size of their support by at most a constant factor; in the presence of noisy syndrome measurements, our results suggest the possibility of universal fault tolerant quantum computation with constant space overhead and time overhead of $\mathcal{O}(d/\log d)$. For quantum circuits that allow parallel gate operations, this yields the optimal scaling of space-time overhead known to date.

Qubits strongly coupled to a photonic crystal give rise to qubit-photon dressed bound states. These bound states, comprising the qubits and spatially localized photonic modes induced around the qubits, are the basis for many exotic physical scenarios. The localization of these states changes with qubit detuning from the photonic crystal band edge, offering an avenue of in situ control of bound-state interaction. Here, we present experimental results from a device with two transmon qubits coupled to a superconducting microwave photonic crystal and realize tunable on-site and interbound state interactions. We observe a fourth-order two-photon virtual process between bound states indicating strong coupling between the photonic crystal and transmon qubits. Because of their localization-dependent interaction, these states offer the ability to realize one-dimensional chains of bound states with tunable and potentially long-range interactions that preserve the qubits’ spatial organization. The widely tunable, strong, and robust interactions demonstrated with this system are promising benchmarks towards realizing larger, more complex systems that use bound states to build and study quantum spin models.

Entanglement, and, in particular, the entanglement spectrum, plays a major role in characterizing many-body quantum systems. While there has been a surge of theoretical works on the subject, no experimental measurement has been performed to date because of the lack of an implementable measurement scheme. Here, we propose a measurement protocol to access the entanglement spectrum of many-body states in experiments with cold atoms in optical lattices. Our scheme effectively performs a Ramsey spectroscopy of the entanglement Hamiltonian and is based on the ability to produce several copies of the state under investigation, together with the possibility to perform a global swap gate between two copies conditioned on the state of an auxiliary qubit. We show how the required conditional swap gate can be implemented with cold atoms, either by using Rydberg interactions or coupling the atoms to a cavity mode. We illustrate these ideas on a simple (extended) Bose-Hubbard model where such a measurement protocol reveals topological features of the Haldane phase.

Photon-based strongly correlated lattice models like the Jaynes–Cummings and Rabi lattices differ from their more conventional relatives like the Bose–Hubbard model by the presence of an additional tunable parameter: the frequency detuning between the pseudo-spin degree of freedom and the harmonic mode frequency on each site. Whenever this detuning is large compared to relevant coupling strengths, the system is said to be in the dispersive regime. The physics of this regime is well-understood at the level of a single Jaynes–Cummings or Rabi site. Here, we extend the theoretical description of the dispersive regime to lattices with many sites, for both strong and ultra-strong coupling. We discuss the nature and spatial range of the resulting qubit–qubit and photon–photon coupling, demonstrate the emergence of photon-pairing and squeezing and illustrate our results by exact diagonalization of the Rabi dimer.