Critical Current Distribution in Spin Transfer Switched Magnetic Tunnel Junctions

The spin transfer switching current distribution within a cell was studied in magnetic tunnel junction based structures having alumina barriers with resistance-area product (RA) of 10 to 30 Ohm-um2 and tunneling magneto-resistance (TMR) of ~20%. These were patterned into current perpendicular to plane configured nano-pillars having elliptical cross-sections of area ~0.02 um2. The width of the critical current distribution (sigma/average of distribution), measured using 30 ms current pulse width, was found to be 7.5% and 3.5% for cells with thermal factor (KuV/kBT) of 40 and 65 respectively. The distribution width did not change significantly for pulse widths between 1 s and 4 ms. An analytical expression for probability density function, p(I/Ico) was derived considering the thermally activated spin transfer model, which supports the experimental observation that the thermal factor is the most significant parameter in determining the within cell critical current distribution width.Comment: 12 pages, 4 figure

Spin-Polarized Current Induced Torque in Magnetic Tunnel Junctions

We present tight-binding calculations of the spin torque in non-collinear magnetic tunnel junctions based on the non-equilibrium Green functions approach. We have calculated the spin torque via the effective local magnetic moment approach and the divergence of the spin current. We show that both methods are equivalent, i.e. the absorption of the spin current at the interface is equivalent to the exchange interaction between the electron spins and the local magnetization. The transverse components of the spin torque parallel and perpendicular to the interface oscillate with different phase and decay in the ferromagnetic layer (FM) as a function of the distance from the interface. The period of oscillations is inversely proportional to the difference between the Fermi-momentum of the majority and minority electrons. The phase difference between the two transverse components of the spin torque is due to the precession of the electron spins around the exchange field in the FM layer. In absence of applied bias and for a relatively thin barrier the perpendicular component of the spin torque to the interface is non-zero due to the exchange coupling between the FM layers across the barrier.Comment: 6 pages, 3 figure

Spin Transfer Switching and Spin Polarization in Magnetic Tunnel Junctions with Mgo and Alox Barriers

We present spin transfer switching results for MgO based magnetic tunneling junctions (MTJs)with large tunneling magnetoresistance (TMR) ratio of up to 150% and low intrinsic switching current density of 2-3 x 10 MA/cm2. The switching data are compared to those obtained on similar MTJ nanostructures with AlOx barrier. It is observed that the switching current density for MgO based MTJs is 3-4 times smaller than that for AlOx based MTJs, and that can be attributed to higher tunneling spin polarization (TSP) in MgO based MTJs. In addition, we report a qualitative study of TSP for a set of samples, ranging from 0.22 for AlOx to 0.46 for MgO based MTJs, and that shows the TSP (at finite bias) responsible for the current-driven magnetization switching is suppressed as compared to zero-bias tunneling spin polarization determined from TMR.Comment: To appear in Appl. Phys. Lett. soo

Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment

We introduce a novel task within the field of 3D dance generation, termed dance accompaniment, which necessitates the generation of responsive movements from a dance partner, the "follower", synchronized with the lead dancer's movements and the underlying musical rhythm. Unlike existing solo or group dance generation tasks, a duet dance scenario entails a heightened degree of interaction between the two participants, requiring delicate coordination in both pose and position. To support this task, we first build a large-scale and diverse duet interactive dance dataset, DD100, by recording about 117 minutes of professional dancers' performances. To address the challenges inherent in this task, we propose a GPT-based model, Duolando, which autoregressively predicts the subsequent tokenized motion conditioned on the coordinated information of the music, the leader's and the follower's movements. To further enhance the GPT's capabilities of generating stable results on unseen conditions (music and leader motions), we devise an off-policy reinforcement learning strategy that allows the model to explore viable trajectories from out-of-distribution samplings, guided by human-defined rewards. Based on the collected dataset and proposed method, we establish a benchmark with several carefully designed metrics.Comment: ICLR 202

Lanthanum halide nanoparticle scintillators for nuclear radiation detection

Nanoparticles with sizesscintillators, in order to determine the viability of using scintillators employing nanostructured lanthanum trifluoride. Preliminary results of this investigation are consistent with the idea that these materials have an intrinsic response to nuclear radiation that may be correlated to the energy of the incident radiation

Burden of carbon monoxide poisoning in China, 1990–2019: A systematic analysis of data from the global burden of disease study 2019

BackgroundCarbon monoxide (CO) poisoning is one of the most common toxic occupational diseases, but related data in China are scarce. A better understanding of the burden of CO poisoning is essential for improving its management.MethodsA systematic analysis of data from the Global Burden of Disease (GBD) Study 2019 was conducted. Following the general analytical strategy used in the GBD Study 2019, the sex- and age-specific incidence and mortality rates of CO poisoning and disability-adjusted life years (DALYs) due to CO poisoning in China were analyzed. Estimated average annual percentage changes (AAPCs) in age-standardized rates were calculated by joinpoint regression analysis. The effects of age, period and cohort on the incidence of CO poisoning and DALYs due to CO poisoning were estimated by an age-period-cohort model.ResultsThe age-standardized incidence and mortality rates as well as DALYs of CO poisoning per 100,000 population were estimated to be 21.82 [95% uncertainty interval (UI): 15.05–29.98], 0.93 (95% UI: 0.63–1.11), and 40.92 (95% UI: 28.43–47.85), respectively, in 2019. From 1990 to 2019, the AAPCs in the age-standardized incidence significantly increased in both males and females, while the age-standardized mortality rates and DALYs significantly decreased in both males and females. The incidence of CO poisoning peaked in individuals aged 15–19 years. Males had a higher burden of CO poisoning than females. The age effect showed that the relative risks (RRs) of incident CO poisoning decreased with age among males and females and that individuals aged 15–24 years had the highest RRs. The RRs of incident CO poisoning increased with time. The cohort effect showed that the incidence increased in successive birth cohorts.ConclusionsThe incidence of CO poisoning in China increased from 1990 to 2019. More attention should be given to improving the burden of CO poisoning in Chinese adolescents. The results of this study can be used by health authorities to inform preventative measures to reduce the burden of CO poisoning

Association between gut microbiota and hepatocellular carcinoma from 2011 to 2022: Bibliometric analysis and global trends

BackgroundHepatocellular carcinoma (HCC) is a primary malignant tumor responsible for approximately 90% of all liver cancers in humans, making it one of the leading public health problems worldwide. The gut microbiota is a complex microbial ecosystem that can influence tumor formation, metastasis, and resistance to treatment. Therefore, understanding the potential mechanisms of gut microbiota pathogenesis is critical for the prevention and treatment of HCC.Materials and methodsA search was conducted in the Web of Science Core Collection (WoSCC) database for English literature studies on the relationship between gut microbiota and HCC from 2011 to 2022. Bibliometric analysis tools such as VOSviewer, CiteSpace, and R Studio were used to analyze global trends and research hotspots in this field.ResultsA total of 739 eligible publications, comprising of 383 articles and 356 reviews, were analyzed. Over the past 11 years, there has been a rapid increase in the annual number of publications and average citation levels, especially in the last five years. The majority of published articles on this topic originated from China (n=257, 34.78%), followed by the United States of America (n=203, 27.47%), and Italy (n=85, 11.50%). American scholars demonstrated high productivity, prominence, and academic environment influence in the research of this subject. Furthermore, the University of California, San Diego published the most papers (n=24) and had the highest average citation value (value=152.17) in the study of the relationship between gut microbiota and HCC. Schnabl B from the USA and Ohtani N from Japan were the authors with the highest number of publications and average citation value, respectively.ConclusionIn recent years, research on the gut microbiota’s role in HCC has made rapid progress. Through a review of published literature, it has been found that the gut microbiota is crucial in the pathogenesis of HCC and in oncotherapy

Fracture Failure Mechanisms of Long Single PA6 Fibers

The present study investigates the failure mechanisms of industrial fiber materials, using a custom designed fiber cutting performance test bench. The fracture morphologies of single PA6 fibers are examined by scanning electron microscopy. The analysis reveals that fiber cutting can be distinguished according to four distinct stages of fiber failure represented by shearing, cutting, brittle fracture, and tensile failure, which are the result of different mechanisms active during the processes of crack initiation, extension, and fracture. The results of fractographic analysis are further verified by an analysis of the blade assembly speed with respect to time over the entire fracture failure process based on high-speed camera data. The results of fractographic analysis and blade assembly speed are fully consistent

On matrix completion-based channel estimators for massive MIMO systems

Large-scale symmetric arrays such as uniform linear arrays (ULA) have been widely used in wireless communications for improving spectrum efficiency and reliability. Channel state information (CSI) is critical for optimizing massive multiple-input multiple-output(MIMO)-based wireless communication systems. The acquisition of CSI for massive MIMO faces challenges such as training shortage and high computational complexity. For millimeter wave MIMO systems, the low-rankness of the channel can be utilized to address the challenge of training shortage. In this paper, we compared several channel estimation schemes based on matrix completion (MC) for symmetrical arrays. Performance and computational complexity are discussed and compared. By comparing the performance in different scenarios, we concluded that the generalized conditional gradient with alternating minimization (GCG-Alt) estimator provided a low-cost, robust solution, while the alternating direction method of multipliers (ADMM)-based hybrid methods achieved the best performance when the array response was perfectly known