Professionalisation of Student Affairs Educators in China: History, challenges, and solutions

Student affairs administration in Chinese universities is characterised by a dual-layer system of governance, with student affairs practitioners, i.e. advisors to students, being supervised by either central university administration or by affiliated colleges. In the last decade, government-oriented developments have achieved great success in China. This paper introduces the background and major strategies adopted by the Chinese government in professionalising university advisors. Major challenges are analysed, and solutions to address these challenges are proposed

Transformer-QEC: Quantum Error Correction Code Decoding with Transferable Transformers

Quantum computing has the potential to solve problems that are intractable for classical systems, yet the high error rates in contemporary quantum devices often exceed tolerable limits for useful algorithm execution. Quantum Error Correction (QEC) mitigates this by employing redundancy, distributing quantum information across multiple data qubits and utilizing syndrome qubits to monitor their states for errors. The syndromes are subsequently interpreted by a decoding algorithm to identify and correct errors in the data qubits. This task is complex due to the multiplicity of error sources affecting both data and syndrome qubits as well as syndrome extraction operations. Additionally, identical syndromes can emanate from different error sources, necessitating a decoding algorithm that evaluates syndromes collectively. Although machine learning (ML) decoders such as multi-layer perceptrons (MLPs) and convolutional neural networks (CNNs) have been proposed, they often focus on local syndrome regions and require retraining when adjusting for different code distances. We introduce a transformer-based QEC decoder which employs self-attention to achieve a global receptive field across all input syndromes. It incorporates a mixed loss training approach, combining both local physical error and global parity label losses. Moreover, the transformer architecture's inherent adaptability to variable-length inputs allows for efficient transfer learning, enabling the decoder to adapt to varying code distances without retraining. Evaluation on six code distances and ten different error configurations demonstrates that our model consistently outperforms non-ML decoders, such as Union Find (UF) and Minimum Weight Perfect Matching (MWPM), and other ML decoders, thereby achieving best logical error rates. Moreover, the transfer learning can save over 10x of training cost.Comment: Accepted to ICCAD 2023, FAST ML for Science Workshop; 7 pages, 8 figure

DNA barcoding of Antarctic marine zooplankton for species identification and recognition

Polar zooplankton are particularly sensitive to climate change, and have been used as rapid-responders to indicate climate-induced changes in the fragile Antarctic ecosystem. DNA barcoding provides an alternative approach for rapid zooplankton species identification. Ninety-four specimens belonging to 32 Antarctic zooplankton species were barcoded to construct a comprehensive reference library. An 830 to 1 050 base-pair region of the mitochondrial cytochrome c oxidase subunit I (mtCOI) gene was obtained as DNA barcodes. The intraspecific variation of the gene ranged from 0 to 2.6% (p-distance), with an average of 0.67% (SD=0.67%). The distance between species within the same genera ranged from 0.1% (Calanus) to 29.3%, with an average of 15.3% (SD=8.4%). The morphological and genetic similarities between Calanus propinquus and C. simillimus raise new questions about the taxonomic status of C. simillimus. With the exception of the two Calanus species, the intraspecific genetic divergence was much smaller than the interspecific divergence among congeneric species, confirming the existence of a barcode gap for Antarctic zooplankton. In addition, species other than Calanus sp. formed a monophyletic group. Therefore, we have confirmed DNA barcoding as an accurate and efficient approach for zooplankton identification in the Antarctic area (except for Hydromedusa, Tunicata, and other gelatinous zooplankton). Indicator vector analysis further confirmed this conclusion. The new primer sets issued here may facilitate the study of Antarctic marine zooplankton species composition by environmental metagenetic analysis

Miniscalpel-Needle Treatment Is Effective for Work-Related Neck and Shoulder Musculoskeletal Disorders

Background. Work-related musculoskeletal disorders (MSDs) are a group of painful disorders of muscles, tendons, and nerves, such as neck and shoulder MSD. This study was designed to use miniscalpel-needle (MSN) technique as an intervention for work-related MSDs. Methods. Thirty-one patients with work-related MSDs and 28 healthy subjects were enrolled as controls in this study. The MSD symptoms of each patient were assessed by visual analog scale (VAS) and neck disability index (NDI). Blood samples were collected from control subjects and MSD patients before and after treatment. Serum levels of C-reactive protein (CRP) and tumor necrosis factor (TNF) were measured using ELISA. Results. Prior to MSN treatment, serum levels of CRP and TNF were significantly higher in the MSD patients than the healthy controls. Serum CRP levels correlated with VAS and NDI scores, and serum TNF levels correlated with NDI scores. Compared to pretreatment, VAS and NDI scores were significantly lower in MSD patients after MSN treatment, while serum CRP and TNF levels were significantly lower compared with the healthy control levels. Conclusions. Our results indicate that MSN may be an effective intervention for work-related MSDs and be associated with lower serum levels of inflammatory biomarkers

Transplantation of Human Undifferentiated Embryonic Stem Cells into A Myocardial Infarction Rat Model

Human embryonic stem (hES) cells hold great therapeutic potential for cell transplantation. To date, it remains uncertain whether undifferentiated hES cells can differentiate into cardiac lineage in vivo during myocardial infarction. Here we provide the first report that undifferentiated hES cells can survive in rat hearts during myocardial infarction without the formation of teratoma using undifferentiated green fluorescent protein (GFP)-transgenic hES cells. Using a laser-capture microscope to dissect the GFP-positive cell area from the hES-injected hearts, we documented the expression of human cardiac-specific genes, including GATA-4, Nkx-2.5, and cardiac troponin I. Taken together, our results demonstrate that undifferentiated hES cells can be driven to the cardiac lineage under the local injured environment in the heart, which may provide a potential method for regenerating de novo myocardium to treat myocardial infarction.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63274/1/scd.2006.110206.pd

Towards Advantages of Parameterized Quantum Pulses

The advantages of quantum pulses over quantum gates have attracted increasing attention from researchers. Quantum pulses offer benefits such as flexibility, high fidelity, scalability, and real-time tuning. However, while there are established workflows and processes to evaluate the performance of quantum gates, there has been limited research on profiling parameterized pulses and providing guidance for pulse circuit design. To address this gap, our study proposes a set of design spaces for parameterized pulses, evaluating these pulses based on metrics such as expressivity, entanglement capability, and effective parameter dimension. Using these design spaces, we demonstrate the advantages of parameterized pulses over gate circuits in the aspect of duration and performance at the same time thus enabling high-performance quantum computing. Our proposed design space for parameterized pulse circuits has shown promising results in quantum chemistry benchmarks.Comment: 11 Figures, 4 Table

RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training

Quantum state preparation, a crucial subroutine in quantum computing, involves generating a target quantum state from initialized qubits. Arbitrary state preparation algorithms can be broadly categorized into arithmetic decomposition (AD) and variational quantum state preparation (VQSP). AD employs a predefined procedure to decompose the target state into a series of gates, whereas VQSP iteratively tunes ansatz parameters to approximate target state. VQSP is particularly apt for Noisy-Intermediate Scale Quantum (NISQ) machines due to its shorter circuits. However, achieving noise-robust parameter optimization still remains challenging. We present RobustState, a novel VQSP training methodology that combines high robustness with high training efficiency. The core idea involves utilizing measurement outcomes from real machines to perform back-propagation through classical simulators, thus incorporating real quantum noise into gradient calculations. RobustState serves as a versatile, plug-and-play technique applicable for training parameters from scratch or fine-tuning existing parameters to enhance fidelity on target machines. It is adaptable to various ansatzes at both gate and pulse levels and can even benefit other variational algorithms, such as variational unitary synthesis. Comprehensive evaluation of RobustState on state preparation tasks for 4 distinct quantum algorithms using 10 real quantum machines demonstrates a coherent error reduction of up to 7.1 $\times$ and state fidelity improvement of up to 96\% and 81\% for 4-Q and 5-Q states, respectively. On average, RobustState improves fidelity by 50\% and 72\% for 4-Q and 5-Q states compared to baseline approaches.Comment: Accepted to FASTML @ ICCAD 2023. 14 pages, 20 figure

Biocompatible Single-Crystal Selenium Nanobelt Based Nanodevice as a Temperature-Tunable Photosensor

Selenium materials are widely used in photoelectrical devices, owing to their unique semiconductive properties. Single-crystal selenium nanobelts with large specific surface area, fine photoconductivity, and biocompatibility provide potential applications in biomedical nanodevices, such as implantable artificial retina and rapid photon detector/stimulator for optogenetics. Here, we present a selenium nanobelt based nanodevice, which is fabricated with single Se nanobelt. This device shows a rapid photo response, different sensitivities to visible light of variable wave length, and temperature-tunable property. The biocompatibility of the Se nanobelts was proved by MTT test using two cell lines. Our investigation introduced a photosensor that will be important for multiple potential applications in human visual system, photocells in energy or MEMS, and temperature-tunable photoelectrical device for optogenetics research

The Effect of Treadmill Training Pre-Exercise on Glutamate Receptor Expression in Rats after Cerebral Ischemia

Physical exercise has been demonstrated to be neuroprotective in both clinical and laboratory settings. However, the exact mechanism underlying this effect is unclear. Our study aimed to investigate whether pre-ischemic treadmill training could serve as a form of ischemic preconditioning in a rat model undergoing middle cerebral artery occlusion (MCAO). Thirty-six rats were divided into three groups: a sham control group, a non-exercise with operation group and an exercise with operation group. After treadmill training, ischemia was induced by occluding the MCA for 2 h, followed by reperfusion. Half of the rats in each group were sacrificed for mRNA detection of mGluR5 and NR2B 80 min after occlusion. The remaining animals were evaluated for neurological deficits by behavioral scoring and then decapitated to assess the infarct volume. The mRNA expression of mGluR5 and NR2B was detected by real-time PCR. The results suggest that pre-ischemic treadmill training may induce brain ischemic tolerance by reducing the mRNA levels of mGluR5 and NR2B, and thus, the results indicate that physical exercise might be an effective method to establish ischemic preconditioning