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1. DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation

Author

Wu, Xueqing, Zheng, Rui, Sha, Jingzhen, Wu, Te-Lin, Zhou, Hanyu, Tang, Mohan, Chang, Kai-Wei, Peng, Nanyun, and Huang, Haoran

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Data analysis is a crucial analytical process to generate in-depth studies and conclusive insights to comprehensively answer a given user query for tabular data. In this work, we aim to propose new resources and benchmarks to inspire future research on this crucial yet challenging and under-explored task. However, collecting data analysis annotations curated by experts can be prohibitively expensive. We propose to automatically generate high-quality answer annotations leveraging the code-generation capabilities of LLMs with a multi-turn prompting technique. We construct the DACO dataset, containing (1) 440 databases (of tabular data) collected from real-world scenarios, (2) ~2k query-answer pairs that can serve as weak supervision for model training, and (3) a concentrated but high-quality test set with human refined annotations that serves as our main evaluation benchmark. We train a 6B supervised fine-tuning (SFT) model on DACO dataset, and find that the SFT model learns reasonable data analysis capabilities. To further align the models with human preference, we use reinforcement learning to encourage generating analysis perceived by human as helpful, and design a set of dense rewards to propagate the sparse human preference reward to intermediate code generation steps. Our DACO-RL algorithm is evaluated by human annotators to produce more helpful answers than SFT model in 57.72% cases, validating the effectiveness of our proposed algorithm. Data and code are released at https://github.com/shirley-wu/daco, Comment: NeurIPS 2024 Dataset and Benchmark Track

Published
2024

4. Improving Generalization of Alignment with Human Preferences through Group Invariant Learning

Author

Zheng, Rui, Shen, Wei, Hua, Yuan, Lai, Wenbin, Dou, Shihan, Zhou, Yuhao, Xi, Zhiheng, Wang, Xiao, Huang, Haoran, Gui, Tao, Zhang, Qi, and Huang, Xuanjing

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

The success of AI assistants based on language models (LLMs) hinges crucially on Reinforcement Learning from Human Feedback (RLHF), which enables the generation of responses more aligned with human preferences. As universal AI assistants, there's a growing expectation for them to perform consistently across various domains. However, previous work shows that Reinforcement Learning (RL) often exploits shortcuts to attain high rewards and overlooks challenging samples. This focus on quick reward gains undermines both the stability in training and the model's ability to generalize to new, unseen data. In this work, we propose a novel approach that can learn a consistent policy via RL across various data groups or domains. Given the challenges associated with acquiring group annotations, our method automatically classifies data into different groups, deliberately maximizing performance variance. Then, we optimize the policy to perform well on challenging groups. Lastly, leveraging the established groups, our approach adaptively adjusts the exploration space, allocating more learning capacity to more challenging data and preventing the model from over-optimizing on simpler data. Experimental results indicate that our approach significantly enhances training stability and model generalization.

Published
2023

5. Secrets of RLHF in Large Language Models Part I: PPO

Author

Zheng, Rui, Dou, Shihan, Gao, Songyang, Hua, Yuan, Shen, Wei, Wang, Binghai, Liu, Yan, Jin, Senjie, Liu, Qin, Zhou, Yuhao, Xiong, Limao, Chen, Lu, Xi, Zhiheng, Xu, Nuo, Lai, Wenbin, Zhu, Minghao, Chang, Cheng, Yin, Zhangyue, Weng, Rongxiang, Cheng, Wensen, Huang, Haoran, Sun, Tianxiang, Yan, Hang, Gui, Tao, Zhang, Qi, Qiu, Xipeng, and Huang, Xuanjing

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Large language models (LLMs) have formulated a blueprint for the advancement of artificial general intelligence. Its primary objective is to function as a human-centric (helpful, honest, and harmless) assistant. Alignment with humans assumes paramount significance, and reinforcement learning with human feedback (RLHF) emerges as the pivotal technological paradigm underpinning this pursuit. Current technical routes usually include \textbf{reward models} to measure human preferences, \textbf{Proximal Policy Optimization} (PPO) to optimize policy model outputs, and \textbf{process supervision} to improve step-by-step reasoning capabilities. However, due to the challenges of reward design, environment interaction, and agent training, coupled with huge trial and error cost of large language models, there is a significant barrier for AI researchers to motivate the development of technical alignment and safe landing of LLMs. The stable training of RLHF has still been a puzzle. In the first report, we dissect the framework of RLHF, re-evaluate the inner workings of PPO, and explore how the parts comprising PPO algorithms impact policy agent training. We identify policy constraints being the key factor for the effective implementation of the PPO algorithm. Therefore, we explore the PPO-max, an advanced version of PPO algorithm, to efficiently improve the training stability of the policy model. Based on our main results, we perform a comprehensive analysis of RLHF abilities compared with SFT models and ChatGPT. The absence of open-source implementations has posed significant challenges to the investigation of LLMs alignment. Therefore, we are eager to release technical reports, reward models and PPO codes, aiming to make modest contributions to the advancement of LLMs.

Published
2023

6. Current Situation, Problems, and Countermeasures of Modern Marine Ranch Construction in Zhuhai City

Author

WENG Zheng, WU Qitao, FANG Kai, HUANG Haoran, CHEN Cheng, and LIANG Cuiping

Subjects
modern marine ranching, sustainable development, zhuhai city, Oceanography, GC1-1581
Abstract

Modern marine ranching, as an ecosystem and sustainable development model that combines environmental protection, resource conservation, and sustainable fisheries output, has broad development prospects and important strategic significance. Zhuhai City has abundant marine resources, and the construction of modern marine ranching has unique advantages. This paper analyzes the current development status of modern marine ranching construction in Zhuhai City, explores existing problems, and proposes countermeasures and suggestions for the construction of modern marine ranching in Zhuhai City, including aquaculture processing, seedling cultivation, fishery port economic zone construction, industrial integration, seafood branding, fishery equipment and smart fisheries, financial insurance and policy guarantees, talent introduction and cultivation, and recreational fisheries, providing reference opinions for the high-quality development of modern marine ranching in Zhuhai City.

Published
2024

7. Calibration Set Optimization by Dragonfly Algorithm for Near-Infrared Modeling of Wheat Flour Protein Content

Author

HU Yunchao, LIU Zhijian, WANG Ying, HUANG Haoran, WANG Honghong, WU Cai’e, XIONG Zhixin

Subjects
dragonfly algorithm, near-infrared spectroscopy, optimization of calibration set, protein content of wheat flour, Food processing and manufacture, TP368-456
Abstract

In order to optimize the calibration set for near-infrared modeling of the protein content in wheat flour, the binary dragonfly algorithm (BDA) was used to select representative samples from the primary calibration set divided by the traditional Kennard/Stone (K/S) method. Based on the representative samples, a partial least square regression (PLSR) model for estimating the protein content in wheat flour was established, and the prediction set was employed to evaluate the stability and prediction performance of the model. The results indicated that an optimal calibration set with 30 samples was selected finally by BDA, and the proposed model exhibited a coefficient of determination of prediction (Rp2) of 0.956 4 and a root mean square errors of prediction (RMSEP) of 0.278 1, which increased by 1.87% and decreased by 15.57% compared with those (0.938 8 and 0.329 4) from K/S partition of 100 primary calibration sets, respectively. The average number of calibration sets selected from 10 BDA experiments was 30.2, and the protein content of wheat flour was predicted better by the 10 models developed than that obtained based on the primary calibration set. Therefore, BDA can select a small number of representative calibration set samples based on which a PLSR model with good robustness and high prediction accuracy for the protein content of wheat flour can be established. The proposed method can provide an efficient tool for calibration set selection in near-infrared spectroscopic analysis of the quality of wheat flour.

Published
2024
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10. Two-Level Supervised Contrastive Learning for Response Selection in Multi-Turn Dialogue

Author

Zhang, Wentao, Xu, Shuang, and Huang, Haoran

Subjects
Computer Science - Computation and Language
Abstract

Selecting an appropriate response from many candidates given the utterances in a multi-turn dialogue is the key problem for a retrieval-based dialogue system. Existing work formalizes the task as matching between the utterances and a candidate and uses the cross-entropy loss in learning of the model. This paper applies contrastive learning to the problem by using the supervised contrastive loss. In this way, the learned representations of positive examples and representations of negative examples can be more distantly separated in the embedding space, and the performance of matching can be enhanced. We further develop a new method for supervised contrastive learning, referred to as two-level supervised contrastive learning, and employ the method in response selection in multi-turn dialogue. Our method exploits two techniques: sentence token shuffling (STS) and sentence re-ordering (SR) for supervised contrastive learning. Experimental results on three benchmark datasets demonstrate that the proposed method significantly outperforms the contrastive learning baseline and the state-of-the-art methods for the task.

Published
2022

13. Discovery of Novel Activators of Large-Conductance Calcium-Activated Potassium Channels for the Treatment of Cerebellar Ataxia

Author

Srinivasan, Sharan R, Huang, Haoran, Chang, Wei-Chih, Nasburg, Joshua A, Nguyen, Hai M, Strassmaier, Tim, Wulff, Heike, and Shakkottai, Vikram G

Subjects
Medical Physiology, Biomedical and Clinical Sciences, Brain Disorders, Neurodegenerative, Orphan Drug, Rare Diseases, Neurosciences, 5.1 Pharmaceuticals, 1.1 Normal biological development and functioning, Neurological, Animals, Ataxia, Calcium, Cerebellar Ataxia, Large-Conductance Calcium-Activated Potassium Channels, Mice, Potassium, Potassium Channels, Calcium-Activated, Spinocerebellar Ataxias, Biochemistry and Cell Biology, Pharmacology and Pharmaceutical Sciences, Pharmacology & Pharmacy, Biochemistry and cell biology, Pharmacology and pharmaceutical sciences
Abstract

Impaired cerebellar Purkinje neuron firing resulting from reduced expression of large-conductance calcium-activated potassium (BK) channels is a consistent feature in models of inherited neurodegenerative spinocerebellar ataxia (SCA). Restoring BK channel expression improves motor function and delays cerebellar degeneration, indicating that BK channels are an attractive therapeutic target. Current BK channel activators lack specificity and potency and are therefore poor templates for future drug development. We implemented an automated patch clamp platform for high-throughput drug discovery of BK channel activators using the Nanion SyncroPatch 384PE system. We screened over 15,000 compounds for their ability to increase BK channel current amplitude under conditions of lower intracellular calcium that is present in disease. We identified several novel BK channel activators that were then retested on the SyncroPatch 384PE to generate concentration-response curves (CRCs). Compounds with favorable CRCs were subsequently tested for their ability to improve irregular cerebellar Purkinje neuron spiking, characteristic of BK channel dysfunction in SCA1 mice. We identified a novel BK channel activator, 4-chloro-N-(5-chloro-2-cyanophenyl)-3-(trifluoromethyl)benzene-1-sulfonamide (herein renamed BK-20), that exhibited a more potent half-maximal activation of BK current (pAC50 = 4.64) than NS-1619 (pAC50 = 3.7) at a free internal calcium concentration of 270 nM in a heterologous expression system and improved spiking regularity in SCA1 Purkinje neurons. BK-20 had no activity on small-conductance calcium-activated potassium (SK)1-3 channels but interestingly was a potent blocker of the T-type calcium channel, Cav3.1 (IC50 = 1.05 μM). Our work describes both a novel compound for further drug development in disorders with irregular Purkinje spiking and a unique platform for drug discovery in degenerative ataxias. SIGNIFICANCE STATEMENT: Motor impairment associated with altered Purkinje cell spiking due to dysregulation of large-conductance calcium-activated potassium (BK) channel expression and function is a shared feature of disease in many degenerative ataxias. BK channel activators represent an outstanding therapeutic agent for ataxia. We have developed a high-throughput platform to screen for BK channel activators and identified a novel compound that can serve as a template for future drug development for the treatment of these disabling disorders.

Published
2022

15. Spelling Error Correction with Soft-Masked BERT

Author

Zhang, Shaohua, Huang, Haoran, Liu, Jicong, and Li, Hang

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Spelling error correction is an important yet challenging task because a satisfactory solution of it essentially needs human-level language understanding ability. Without loss of generality we consider Chinese spelling error correction (CSC) in this paper. A state-of-the-art method for the task selects a character from a list of candidates for correction (including non-correction) at each position of the sentence on the basis of BERT, the language representation model. The accuracy of the method can be sub-optimal, however, because BERT does not have sufficient capability to detect whether there is an error at each position, apparently due to the way of pre-training it using mask language modeling. In this work, we propose a novel neural architecture to address the aforementioned issue, which consists of a network for error detection and a network for error correction based on BERT, with the former being connected to the latter with what we call soft-masking technique. Our method of using `Soft-Masked BERT' is general, and it may be employed in other language detection-correction problems. Experimental results on two datasets demonstrate that the performance of our proposed method is significantly better than the baselines including the one solely based on BERT., Comment: To be published at ACL 2020

Published
2020

25. Energy-Efficiency-Oriented Spatial Configuration of VRV Outdoor Units in an Equipment Layer Under Background Wind Conditions.

Author

Liu, Lin, Huang, Haoran, and Tian, Xiaoyu

Subjects
WIND speed, ATMOSPHERIC temperature, TEMPERATURE distribution, INLETS, COOLING
Abstract

This study provides a spatial configuration method to improve the cooling efficiency of multiple VRV outdoor units placed on equipment layers with high floors. Relevant factors include wind parameters, the placement of multiple outdoor units, and louver. A total of 96 cases were designed. CFD simulations were used to obtain the inlet air temperature distributions of multiple outdoor units and then calculate their cooling efficiency. The results found that these factors have effects on the average cooling efficiency of outdoor units in a single row to a certain extent. The influencing degrees of these factors, from large to small, were the louver angle, wind parameters, and the placement of multiple outdoor units. When the cooling efficiency of outdoor units was maximum and the louver angle was 15°, the louvers could be oriented perpendicular to the dominant wind direction (90°) when wind speed was ≥6 m/s, and the unit spacing was 600 mm. Based on this, when the number of outdoor units was expanded in the limited space, staggered arrangements with different directions of heat exchange surfaces were a recommended optimization layout. This study provides technical support for improving the working efficiency of VRV outdoor units in an equipment layer. [ABSTRACT FROM AUTHOR]

Published
2024
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26. BWSAR: A Single-Drone Search-and-Rescue Methodology Leveraging 5G-NR Beam Sweeping Technologies for Victim Localization.

Author

He, Ming, Du, Keliang, Huang, Haoran, Song, Qi, and Liu, Xinyu

Subjects
OPTIMIZATION algorithms, TRAJECTORY optimization, NATURAL disasters, 5G networks, SYNCHRONIZATION
Abstract

Drones integrated with 5G New Radio (NR) base stations have emerged as a promising solution for efficient victim search and localization in emergency zones where cellular networks are disrupted by natural disasters. Traditional approaches relying solely on uplink Sounding Reference Signal (SRS) for localization face limitations due to User Equipment (UE) power constraints. To overcome this, our paper introduces BWSAR, a novel three-stage Search-and-Rescue (SAR) methodology leveraging 5G-NR beam sweeping technologies. BWSAR utilizes downlink Synchronization Signal Block (SSB) for coarse-grained direction estimation, guiding the drone towards potential victim locations. Subsequently, finer-grained beam sweeping with Positioning Reference Signal (PRS) is employed within the identified direction, enabling precise three-dimensional UE coordinate estimation. Furthermore, we propose a trajectory optimization algorithm to expedite the drone's navigation to emergency areas. Simulation results underscore BWSAR's efficacy in reducing positioning errors and completing SAR missions swiftly, within minutes. [ABSTRACT FROM AUTHOR]

Published
2024
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27. MTSS1/Src family kinase dysregulation underlies multiple inherited ataxias

Author

Brown, Alexander S, Meera, Pratap, Altindag, Banu, Chopra, Ravi, Perkins, Emma M, Paul, Sharan, Scoles, Daniel R, Tarapore, Eric, Magri, Jessica, Huang, Haoran, Jackson, Mandy, Shakkottai, Vikram G, Otis, Thomas S, Pulst, Stefan M, Atwood, Scott X, and Oro, Anthony E

Subjects
Neurosciences, Rare Diseases, Brain Disorders, Genetics, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, Neurological, Animals, Ataxia, Disease Models, Animal, Humans, Mice, Mice, Inbred C57BL, Microfilament Proteins, Neoplasm Proteins, Proteins, Purkinje Cells, Spinocerebellar Ataxias, Spinocerebellar Degenerations, src-Family Kinases, neurodegeneration, Src kinase, BAR domain proteins, spinocerebellar ataxia, actin cytoskeleton
Abstract

The genetically heterogeneous spinocerebellar ataxias (SCAs) are caused by Purkinje neuron dysfunction and degeneration, but their underlying pathological mechanisms remain elusive. The Src family of nonreceptor tyrosine kinases (SFK) are essential for nervous system homeostasis and are increasingly implicated in degenerative disease. Here we reveal that the SFK suppressor Missing-in-metastasis (MTSS1) is an ataxia locus that links multiple SCAs. MTSS1 loss results in increased SFK activity, reduced Purkinje neuron arborization, and low basal firing rates, followed by cell death. Surprisingly, mouse models for SCA1, SCA2, and SCA5 show elevated SFK activity, with SCA1 and SCA2 displaying dramatically reduced MTSS1 protein levels through reduced gene expression and protein translation, respectively. Treatment of each SCA model with a clinically approved Src inhibitor corrects Purkinje neuron basal firing and delays ataxia progression in MTSS1 mutants. Our results identify a common SCA therapeutic target and demonstrate a key role for MTSS1/SFK in Purkinje neuron survival and ataxia progression.

Published
2018

30. Query Answering with Inconsistent Existential Rules under Stable Model Semantics

Author

Wan, Hai, Zhang, Heng, Xiao, Peng, Huang, Haoran, and Zhang, Yan

Subjects
Computer Science - Artificial Intelligence
Abstract

Traditional inconsistency-tolerent query answering in ontology-based data access relies on selecting maximal components of an ABox/database which are consistent with the ontology. However, some rules in ontologies might be unreliable if they are extracted from ontology learning or written by unskillful knowledge engineers. In this paper we present a framework of handling inconsistent existential rules under stable model semantics, which is defined by a notion called rule repairs to select maximal components of the existential rules. Surprisingly, for R-acyclic existential rules with R-stratified or guarded existential rules with stratified negations, both the data complexity and combined complexity of query answering under the rule {repair semantics} remain the same as that under the conventional query answering semantics. This leads us to propose several approaches to handle the rule {repair semantics} by calling answer set programming solvers. An experimental evaluation shows that these approaches have good scalability of query answering under rule repairs on realistic cases., Comment: Accepted by AAAI 2016

Published
2016

31. In‐Doped ZnO Electron Transport Layer for High‐Efficiency Ultrathin Flexible Organic Solar Cells.

Author

Liu, Xiujun, Ji, Yitong, Xia, Zezhou, Zhang, Dongyang, Cheng, Yingying, Liu, Xiangda, Ren, Xiaojie, Liu, Xiaotong, Huang, Haoran, Zhu, Yanqing, Yang, Xueyuan, Liao, Xiaobin, Ren, Long, Tan, Wenliang, Jiang, Zhi, Lu, Jianfeng, McNeill, Christopher, and Huang, Wenchao

Subjects
SOLAR cells, ELECTRON mobility, ELECTRON transport, ZINC oxide, HIGH temperatures
Abstract

Sol–gel processed zinc oxide (ZnO) is one of the most widely used electron transport layers (ETLs) in inverted organic solar cells (OSCs). The high annealing temperature (≈200 °C) required for sintering to ensure a high electron mobility however results in severe damage to flexible substrates. Thus, flexible organic solar cells based on sol–gel processed ZnO exhibit significantly lower efficiency than rigid devices. In this paper, an indium‐doping approach is developed to improve the optoelectronic properties of ZnO layers and reduce the required annealing temperature. Inverted OSCs based on In‐doped ZnO (IZO) exhibit a higher efficiency than those based on ZnO for a range of different active layer systems. For the PM6:L8‐BO system, the efficiency increases from 17.0% for the pristine ZnO‐based device to 17.8% for the IZO‐based device. The IZO‐based device with an active layer of PM6:L8‐BO:BTP‐eC9 exhibits an even higher efficiency of up to 18.1%. In addition, a 1.2‐micrometer‐thick inverted ultrathin flexible organic solar cell is fabricated based on the IZO ETL that achieves an efficiency of 17.0% with a power‐per‐weight ratio of 40.4 W g−1, which is one of the highest efficiency for ultrathin (less than 10 micrometers) flexible organic solar cells. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Coexistence of superconductivity and ferromagnetism in Sr0.5Ce0.5FBiS2

Author

Li, Lin, Li, Yuke, Jin, Yuefeng, Huang, Haoran, Chen, Bin, Xu, Xiaofeng, Dai, Jianhui, Zhang, Li, Yang, Xiaojun, Zhai, Huifei, Cao, Guanghan, and Xu, Zhuan

Subjects
Condensed Matter - Superconductivity
Abstract

Through the combination of X-ray diffraction, electrical transport, magnetic susceptibility, and the heat capacity measurements, we studied the effect of Ce doping in the newly discovered SrFBiS${2}$ system. It is found that Sr${0.5}$Ce${0.5}$FBiS${2}$ undergoes a second-order transition below $7.5 K, followed by a superconducting transition with the critical temperature Tc=2.8 K. Our transport, specific heat and DC-magnetization results suggest the presence of bulk ferromagneticcorrelation of Ce ion below 7.5 K that coexist with superconductivity when the temperature is further lowered below 2.8 K., Comment: 6 pages, 5 figures

Published
2014
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36. Multi-Global Navigation Satellite System (GNSS) real-time tropospheric delay retrieval based on state-space representation (SSR) products from different analysis centers.

Author

Yao, Wanqiang, Huang, Haoran, Ma, Xiongwei, Zhang, Qi, Yao, Yibin, Lin, Xiaohu, Zhao, Qingzhi, and Huang, Yunzheng

Subjects
*GLOBAL Positioning System, *BEIDOU satellite navigation system, *WEATHER & climate change, *STANDARD deviations, *ARTIFICIAL satellites in navigation
Abstract

The troposphere plays an important role in a range of weather and various climate changes. With the development of the Global Navigation Satellite System (GNSS), the zenith tropospheric delay (ZTD) retrieval using GNSS technology has become a popular method. Research on ZTD accuracies of state-space representation (SSR) corrections from different analysis centers derived from real-time precise point positioning (RT-PPP) is important for Earth observation correction, meteorological disaster forecasting, and warning with the increasing abundance of state-space representation (SSR) products obtained by the International GNSS Service (IGS) analysis center. Therefore, accuracies and availability of real-time orbits and clock errors obtained by the Chinese Academy of Sciences (CAS), GMV Aerospace and Defense (GMV), Centre National d'Etudes Spatiales (CNE), and Wuhan University (WHU) are evaluated, and the RT positioning performance and ZTD accuracies are analyzed for Global Positioning System (GPS), Galileo (GAL), and BeiDou Navigation Satellite System-3 (BDS3) satellites. The results indicate that CAS has the higher satellite availability, providing SSR corrections for 82 GPS, Galileo, and BDS3 satellites. The accuracies of GPS, Galileo, and BDS3 orbits are best at WHU, CAS, and WHU with values of 5.57, 5.91, and 11.77 cm , respectively; the standard deviations (SDs) of clock error are all better than 0.22, 0.19, and 0.55 ns , and the root mean square errors (RMSEs) are better than 0.54, 0.32, and 1.46 ns. CAS has the best signal-in-space ranging errors (SISREs) followed by WHU, while CNE and GMV are worse. In the RT-PPP test, convergence times for CAS and WHU are 14.9 and 14.4 min , respectively, with 3D positioning accuracy for both of around 3.3 cm , which is better than for CNE and GMV. Among them, WHU SSR has the higher accuracy of RT-PPP-derived ZTD, with an RMSE of 6.06 mm and desirable availability with a completeness rate of 89 %. [ABSTRACT FROM AUTHOR]

Published
2024
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38. Effect of neoadjuvant endocrine therapy on the acoustic environment in tissue of prostate cancer: a study of histopathological characteristics

Author

Zou, Longquan, primary, Chen, Wei, additional, Fu, Guangqing, additional, Han, Dengjun, additional, Zeng, Xiang, additional, Zhang, Cai, additional, Gong, Xiaobo, additional, Liu, Hong, additional, Liu, Jianhui, additional, Wang, Zhibiao, additional, Liang, Yong, additional, and Huang, Haoran, additional

Published
2023
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47. Impact of Various Dopants on Thermoelectric Transport Properties of Polycrystalline GeSb2Te4.

Author

Jiang, Yihan, Pan, Zhenyu, Huang, Haoran, Wan, Shun, Chen, Heyang, Zhao, Kunpeng, Wei, Tian‐Ran, and Shi, Xun

Subjects
THERMOELECTRIC materials, ELECTRIC conductivity, PHASE change materials, SEEBECK coefficient, CARRIER density, CHALCOGENS
Abstract

GeSb2Te4 (GST124), one of the well‐known phase‐change materials for nonvolatile memory and rewritable optical storage, has been recently found to be promising thermoelectric materials with low lattice thermal conductivity and high electrical conductivity. However, its thermoelectric performance is greatly restricted by the excessively high hole concentration. Herein, the impact of a series of group IIIA (Al, Ga, In) and group VIA (S, Se) dopants on the electrical transport properties of polycrystalline GST124 has been studied. It is found that element sulfur (S) has the best doping efficiency because the GeS bonds are very strong and ionic that are beneficial for suppressing Ge vacancies to reduce the carrier concentration. Meanwhile, element indium (In) also shows decent doping efficiency because its ionic radius is close to the Ge ion and the InTe bonds have moderate bonding strength. Moreover, In doping introduces a resonant level in the valence band, leading to enhanced Seebeck coefficient and power factor. A high figure of merit (zT)of 0.73 at 700 K and an average zT of 0.48 over 300–750 K are obtained in Ge0.92In0.08Sb2Te4, which are 26% and 66% higher than pristine GST124. This study will advance the understanding and development of high‐performance GeSbTe‐based thermoelectric materials. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Clinical efficacy and safety of ultrasound-guided high-intensity focused ultrasound for breast fibroadenoma: a systematic review and meta-analysis.

Author

Wu, Xiuying, Yue, Xuewen, Liu, Hong, Huang, Haoran, Yao, Dan, Guo, Yujun, Chen, Wenzhi, and Zhang, Cai

Subjects
HIGH-intensity focused ultrasound, VISUAL analog scale, BREAST ultrasound, ECCHYMOSIS, ULTRASONIC imaging
Abstract

Objective: The purpose of this systematic review and meta-analysis was to assess the clinical efficacy and safety of ultrasound (US)-guided high intensity focused ultrasound (HIFU) in the treatment of breast fibroadenoma in different studies. Methods: Studies evaluating the efficacy and safety of US-guided HIFU in the treatment of histologically-proven FA with follow-up outcomes of more than 3 months were searched through MEDLINE/PubMed databases. Volume reduction rate (VRR) and side effects were extracted and compared for further analysis. Results: Of 29 identified articles, 10 studies involving 385 women and more than 545 FAs met the inclusion criteria. The mean VRR at 6 months and 12 months after HIFU was 52.00% and 72.00%. In terms of intraoperative safety, nine studies reported mild to moderate pain, with an average visual analogue scale (VAS) score ranging from 1.60 to 7.10. The most common postoperative side effect associated with HIFU was subcutaneous ecchymosis and less frequent were pain, erythema, and skin pigmentation, most of which disappeared within weeks. No serious side effects were observed. Conclusion: S-guided HIFU is an effective and safe noninvasive treatment for breast FA that does not cause serious side effects. Further studies are needed to explore crucial influencing factors of VRR. [ABSTRACT FROM AUTHOR]

Published
2024
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