Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy and safety of cycloserine-containing regimens in the treatment of multidrug-resistant tuberculosis: a nationwide retrospective cohort study in China

Background Our aim was to assess whether the use of cycloserine (CS) would bring additional benefit for multidrug-resistant tuberculosis (MDR-TB) patients, and to estimate the incidence and associated risk factors of adverse drug reactions (ADRs) from CS. Patients and methods In this study, we retrospectively reviewed the clinical outcomes and ADRs of MDR-TB patients treated with CS containing regimens between January 2012 and June 2015 in China. Results A total of 623 MDR-TB cases enrolled in this study received regimens containing CS. Of these cases, in 411 of the patients 374 (66.0%) were “cured” and 37 (5.9%) “complete treatment” by the end of the study. The elderly, patients with prolonged previous exposure to and history of anti-TB drugs, and pre-existing co-morbidity were more likely to be associated with adverse outcomes of MDR-TB patients (P<0.05). Hyperuricemia (22.8%, 142/623) was the most frequently observed ADR among these cases, while the most noted ADRs associated with the administration of CS was psychiatric symptoms, accounting for 4.3% (27/623) of study population. Nineteen (70.4%) out of 27 cases with psychiatric symptoms occurred before the 6-month timepoint, and were notably, the highest proportion of serious adverse, 29.6% (8/27) of which were noted after discontinuation of CS. Conclusion Our study demonstrates that a CS-containing regimen achieved a highly successful outcome in the treatment of MDR-TB and promising tolerance in Chinese population. The potential emergence of serious psychiatric symptoms highlights that patients need to be closely monitored for these conditions during treatment that includes CS.
Reports of Satellite Tracking Green Sea Turtles in China

Since the Huidong Gangkou Sea Turtle Reserve was established in 1985,it has been recorded more than 1280 female green sea turtles Chelonia mydas have nested on the Sea Turtle Bay,and already released nearly 60 000 juvenile sea turtles to this day.The tests of satellite tracking sea turtles had been carried out from 2001 in China Mainland,and after that,more than 20 sea turtles' migratory routes were tracked.In 2010,three adult female green sea turtles were tracked by using U.S.satellite signal transmitters and working with the French ARGOS CLS satellite system.Our results reveal that two turtles named "Xisha" and "Nansha",which were tracked for 26 days respectively,both disappeared in the waters near the city of Haikou;From the Hailing island of Yangjiang city,"Dongsha" migrated southeast to the Philippines,then along the Philippines west coast to the south,finally,it sticked around in the west waters of the Palawan Island.It was tracked for a total of 111 days.This study suggests that the Gangkou sea turtles had different migratory routes,and they present a preference for shallow coastal migration,we suggest that our government take effective measures to protect sea turtles.
LongT5-Mulla: LongT5 With Multi-Level Local Attention for a Longer Sequence

Efficient Transformer models typically employ local and global attention methods, or utilize hierarchical or recurrent architectures, to process long text inputs in natural language processing tasks. However, these models face challenges in terms of sacrificing either efficiency, accuracy, or compatibility to develop their application in longer sequences. To maintain both the accuracy of global attention and the efficiency of local attention, while keeping a good compatibility to be easily applied to an existing pre-trained model, in this paper, we propose multi-level local attention (Mulla attention), which is a hierarchical local attention that acts on both the input sequence and multiple pooling sequences of different granularity simultaneously, thus performing long-range modeling while maintaining linear or log-linear complexity. We apply Mulla attention to LongT5 and implement our LongT5-Mulla sequence-to-sequence model, without introducing new parameters except for positional embeddings. Experiments show that our model can surpass all baseline models, including two original variants of LongT5, in the 8~16k-input long text summarization task on the Multi-News, arXiv and WCEP-10 datasets, with improvements of at least +0.22, +0.01, +0.52 percentage points (pp) averaged Rouge scores respectively, while at the meantime being able to effectively process longer sequences that have 16~48k tokens with at least 52.6% lower memory consumption than LongT5-tglobal, and +0.56~1.62 pp averaged Rouge scores higher than LongT5-local. These results demonstrate that our proposed LongT5-Mulla model can effectively process long sequences and extend the maximum input length for long text tasks from 16k to 48k while maintaining accuracy and efficiency.
Alleged Malpractice in Orthopedic Surgery in The Netherlands: Lessons Learned from Medical Disciplinary Jurisprudence

Background: Orthopedic surgery is a specialty at risk for medical malpractice claims. We aimed to assess the frequency of alleged malpractice cases related to orthopedic surgery in the Netherlands from the last 15 years. Methods: We systematically searched the database of the Dutch Medical Disciplinary Court for verdicts related to orthopedic surgery between January 2009 and July 2023 and extracted case data and data on allegations and outcomes. Results: We identified 158 verdicts (mean of 10.5 per year), of which 151 (96%) were filed against specialists and 7 (4%) against residents. Cases were most frequently classified as incorrect treatment/diagnosis (n = 107, 67.7%). Cases were related to the subspecialties of knee (n = 34, 21.5%), hip (n = 31, 19.6%), ankle (n = 25, 15.8%), spine (n = 22, 13.9%), and shoulder (n = 19, 12.0%). A total of 32 cases (20.3%) were judged as partially founded and 9 (6%) as founded. The Dutch Medical Disciplinary Court imposed 28 warnings, 10 reprimands, and 3 temporary suspensions. A total of 68 appeals were submitted, of which 95% were rejected for filing patients. In three instances, unfounded verdicts were changed to two warnings and a reprimand. In four appeals by an orthopedic surgeon, a warning and reprimand were dismissed, and two reprimands were changed to warnings. Conclusions: The amount of malpractice cases against orthopedic surgeons in the Netherlands is relatively low. The cases in our study may improve our understanding of allegations against physicians and improve the quality of patient care.
The rise of responsible metrics as a professional reform movement: A collective action frames account

Abstract Recent years have seen a rise in awareness around “responsible metrics” and calls for research assessment reforms internationally. Yet within the field of quantitative science studies and in research policy contexts, concerns about the limitations of evaluative bibliometrics are almost as old as the tools themselves. Given that many of the concerns articulated in recent reform movements go back decades, why has momentum for change grown only in the past 10 years? In this paper, we draw on analytical insights from the sociology of social movements on collective action frames to chart the emergence, development, and expansion of “responsible metrics” as a professional reform movement. Through reviewing important texts that have shaped reform efforts, we argue that hitherto, three framings have underpinned the responsible metrics reform agenda: the metrics skepticism framing, the professional-expert framing, and the reflexivity framing. We suggest that although these three framings have coexisted within the responsible metrics movement to date, cohabitation between these framings may not last indefinitely, especially as the responsible metrics movement extends into wider research assessment reform movements.
Effects of land uses on carbon emissions and their spatial-temporal patterns in Hunan Province

Changes in land use are the main cause of carbon emission increases.According to the relevant statistical data,we measured and analyzed the effects of land uses on carbon emissions and their spatial-temporal patterns in Hunan province.The results showed that the net carbon emission had an increasing trend with the average speed of 478.15×104 t · a-1 from 2003 to 2009.The carbon intensity had a declining trend.A reversed "U" shape curve between carbon intensity and per capita GDP was found.The knee point of reversed "U" shape curve was associated with per capital GDP of 9.7 to 10 thousand yuan.The construction land and cultivated land were the main carbon sources.The carbon emission by construction land had been increasing by 483.19×104 t · a-1,contributing to over 84% of the net carbon emission.The forest land was the main carbon sink and its absorption was 769.97×104 t · a-1 averagely.There were obvious differences in net carbon emission in 2009,with a gradually reducing trend from east to west and from north to south.Loudi,Yueyang,Xiangtan and Chenzhou were the type of HE-LE(High emission-Low efficiency) while Yongzhou,Huaihua,Jishou and Zhangjiajie were LE-HE(Low emission-High efficiency). Shaoyang,Changsha,Changde,Zhuzhou,Hengyang and Yiyang were the type of ME-ME(Middle emission-Middle efficiency).
Measuring how the knowledge space shapes the technological progress of European regions

This work aims to investigate the features of the regional knowledge space that are more likely to be conducive to technological progress (TP), either in terms of dimension and relevance. We acknowledge the importance of knowledge assets for new knowledge production and we identify more or less path dependent processes that allow a region to be more competitive in terms of innovation potential. In particular, adopting an evolutionary view of regional development, we consider a regional knowledge space as composed of a knowledge base (KB) and a selection environment (SE), which differently affect the technological progress of the region. Empirical evidence come from a quantitative analysis of 269 European regions, whose data are included in the RegPat database. Results show that the variety of KB impacts positively on the technological progress at large. The variety of SE impacts positively only on the technological progress in terms of relevance, while the size of the SE impacts positively only on the quantitative side of the technological progress. Unrelated variety of KB and SE affects technological progress more widely than their correspondent related variety indicators.
Dynamic Memory-Based Curiosity: A Bootstrap Approach for Exploration in Reinforcement Learning

The sparsity of extrinsic rewards presents a significant challenge for deep reinforcement learning (DRL). As an alternative, researchers have focused on intrinsic rewards to improve exploration efficiency. One of the most representative approaches is utilizing curiosity. However, the challenge of designing effective intrinsic rewards remains, as artificial curiosity differs significantly from human curiosity. In this article, we introduce a novel curiosity approach for DRL, named DyMeCu, which stands for Dynamic Memory-based Curiosity. Inspired by human curiosity and information theory, DyMeCu constructs a dynamic memory using the online learner following the bootstrap paradigm. Additionally, we design a two-learner architecture inspired by ensemble techniques to access curiosity better. The information gap between the two learners serves as the intrinsic reward for agents, and the state information is consistently consolidated into the dynamic memory. Compared with previous curiosity methods, DyMeCu can better mimic human curiosity by using a dynamic memory that can be dynamically grown based on a bootstrap paradigm with two learners. Large-scale empirical experiments on multiple benchmarks, including DeepMind Control Suite and Atari Suite, demonstrate that DyMeCu outperforms competitive curiosity-based methods with or without extrinsic rewards. In the Atari Suite, DyMeCu achieves a mean human-normalized score of 5.076 on a subset of 26 Atari games, achieving a 77.4% relative improvement over the best other baselines. In the DeepMind Control Suite, DyMeCu presents new state-of-the-art results across 11 tasks of all 12 when compared to curiosity-based methods and other pre-training strategies.
Robot motion visual measurement based on RANSAC and weighted constraints method

Precision of the coordinate transformation model parameters is crucial for the accuracy of the vision-based robot spatial motion measurement method. In this work, an optimization algorithm integrating RANSAC and iterative weighted singular value decomposition (IR-SVD) is proposed for improving the coordinate transformation model solution precision, aiming at enhancing the spatial motion measurement accuracy of the binocular vision system. Considering noises existing in reference transformation point pairs, the RANSAC algorithm is introduced to filter the raw measurement point pairs and extract inliers, thereby eliminating potential gross errors and realizing the cluster of advantageous points. An enhanced SVD method based on iterative weighted constraints is proposed to substitute traditional SVD. After calculating the coordinate transformation model parameters, the measurement errors of inliers are solved synchronously, and the weights are reallocated in light of the measurement errors value, subsequently recalculating the coordinate transformation model parameters repeatedly until the errors converge. The validation experiments are conducted on the self-built three-degree-of-freedom rectangular coordinate robot platform. The experimental results of discrete point-to-point motion and continuous trajectory motion measurement show that the proposed method can improve the coordinate transformation model parameters solution accuracy effectively, comparing with the traditional SVD method. Comparative experiment with existing commonly used coordinate transformation methods including Quaternion and iterative closest point indicates that the proposed method exhibits the best applicability and minimal errors in robot motion visual measurement. Both accuracy of the coordinate transformation model solution and the visual system’s motion measurement are enhanced with this newly-proposed, optimized method.
Turbulence mitigation methods for sea scenarios

Visual and infrared imagery is degraded by turbulence caused by atmospheric conditions. Because the degradation gets worse for longer distances, turbulence especially hampers long range observation. At sea this turbulence affects classification and identification of ships and other objects. State of the art software based processing algorithms assuming a static background assumption will fail in such conditions because of the non-static sea background. Therefore, we propose an adapted processing chain aiming to provide optimal turbulence correction for ships seen in the camera view. First we propose to use standard object detection and tracking methods for an indication of the location of the ship. Subsequently, image registration is performed within the ship’s region of interest, covering only the ship of interest. After this region of interest registration, standard turbulence mitigation software can be applied to the region of interest. For ships with other movement than translation only we propose a two-step motion estimation using local optical flow. In this paper we show results of this processing chain for sea scenarios using our TNO turbulence mitigation method. Ship data is processed using the algorithm proposed above and the results are analyzed by both human observation and by image analysis. The improvement of the imagery is qualitatively shown by examining details which cannot be seen without processing and can be seen with processing. Quantitatively, the improvement is related to the energy per spatial frequency in the original and processed images and the signal to noise improvement. This provides a model for the improvement of the results, and is related to the improvement of the classification and identification range. The results show that with this novel approach the classification and identification range of ships is improved.
Usefulness of self-selected scenarios for simple triage and rapid treatment method using virtual reality.

BACKGROUND Repeated triage training is necessary to maintain and improve the accuracy of simple triage and rapid treatment (START), a popular triage method. Virtual reality (VR) may be more effective than conventional training methods. This study aimed to verify the educational usefulness of START using VR originally developed for students. METHODS A VR was initially developed with a function that allowed students to select the triage procedure and its evaluation. Triage was performed using a simple modified START method, and eight scenarios were developed. The participants included 70 paramedic students classified into VR and live lecture groups. They took a 20-question written test that evaluated their academic ability before the course. After the course, a practical test and a 20-question written test were conducted. The total score of the practical test was 43 points. Triage procedure (1 point), observation and evaluation (1-5 points), and triage categories (1 point) were evaluated in this test. RESULTS The VR and live lecture groups consisted of 33 and 29 participants, respectively. No significant differences were observed pre- and post-test. In the practical test, the median (interquartile range) score was 29 (26-32) and 25 (23-29) for the VR and live lecture groups, respectively, with the VR group scoring significantly higher (P=0.03). CONCLUSION Our results confirmed the educational usefulness of selective VR for active learning of START. Therefore, VR combined with live lectures and simulations would be an optimal educational technique.
THE INFLUENCE OF INULIN AND PSYLLIUM ADDITION TO ICE-CREAM AND ITS EFFECTS ON THE SENSORIAL PROPERTIES

The objective of this research was to investigate the effect of substituting fructose by different levels of inulin (3 and 6%) and the addition of psyllium fibers (3 and 6%) on the quality attributes of lingonberry ice cream. Five formulations comprised of the control sample using fructose and the other four samples applying inulin and psyllium fibers, respectively, were examined to determine: pH, total acidity, sugar content, viscosity, water activity, color analysis, and sensory properties in order to find their optimum ratios. A positive linear correlation between psyllium fibers addition and apparent viscosity of the lingonberry ice cream was observed. Supplementation of inulin fibers revealed that lingonberry ice cream with 3 % inulin had the most appealing sensory characteristics. The results suggest that the addition of inulin and psyllium fibers as fiber-enriching agents can be used in the ice cream industry in order to fortify the diet.
Dynamic Pass-through Effect of Global Oil Price on China's Gasoline and Diesel Market: Empirical Analysis Based on the Structural Vector Autoregressive Models

: The paper attempts to assess the dynamic effect of global oil price shocks on China gasoline and diesel markets. Using responses of these two markets to international oil price fluctuations, we establish structural vector autoregressive (SVAR) models respectively, estimating the impulse response functions (IRF) and variance decomposition results. Base on monthly data on global oil prices, Chinese gasoline and diesel prices, consumption and production from January 2014 to March 2022, we found that: ( ⅰ ) Both two markets responded relatively fast to global oil price shocks, peaking statistically within two to three months, with the gasoline market being more sensitive to oil price fluctuations. ( ⅱ ) The impact of oil price fluctuations on the markets can last for two to three years, and the impact on the gasoline market last significantly longer than that on the diesel market while the pass-through effect of international oil prices on China’s diesel market is stronger, reflected in the variance decomposition results. The above results show that diesel market is more able to withstand the impact of oil price fluctuations than the gasoline market, and it is also more stable from the previous period. Based on the existing policy and market environment, we believe that this situation will not change in the short term.
Effect of intercropping on potato bacterial wilt disease and tuber yield in Kenya

Potato (Solanum tuberosum L.) is a major tuber crop in Kenya, whose productivity is heavily impaired by bacterial wilt disease, caused by Ralstonia solanacearum (Smith). Existing management strategies have not been effective, owing to the diversity and robustness of the pathogen and variation in the host range. The objective of this study was to evaluate the effectiveness of intercropping on the incidence of bacterial wilt and yield of potato in Kenya. A field experiment was conducted in four potato-growing counties, namely; Nyandarua, Nakuru, Bomet and Bungoma in Kenya. Treatments included intercroping with spring onion (Allium fistulosum L.); garden pea (Pisum sativum L.); and cabbage (Brassica oleracea var. capitata L.). Treatments also included a pure stand of potato as the control. Generally, intercropping had a significant suppressive effect (P<0.05) on the incidence and severity of bacterial wilt disease. Intercropping potato with spring onion, in particular, had the highest disease suppressive effect, followed by intercropping potato with cabbage; and lastly by potato with garden pea. Accordingly, potato-onion intercrop recorded the highest potato tuber yield (12.9 t ha-1), while the potato pure stand recorded the lowest tuber yield (7.9 t ha-1). Bacterial wilt disease incidence positively correlated with disease severity (r = 0.931; P<0.05). In contrast, the disease incidence and severity negatively correlated with tuber yield. In terms of Land Equivalent Ratio (LER), the highest value (1.64) was with potato-onion intercrop; and the lowest (1.35) with the potato-garden pea intercrop.
Drivers of uncertainty in simulated ocean circulation and heat uptake

The impact of uncertainties in air‐sea fluxes and ocean model parameters on the ocean circulation and ocean heat uptake (OHU) is assessed in a novel modeling framework. We use an ocean‐only model forced with the simulated sea surface fields of the CMIP5 climate models. The simulations are performed using control and 1% CO2 warming scenarios. The ocean‐only ensemble adequately reproduces the mean Atlantic Meridional Overturning Circulation (AMOC) and the zonally integrated OHU. The ensemble spread in AMOC strength, its weakening, and Atlantic OHU due to different air‐sea fluxes is twice as large as the uncertainty range related to vertical and mesocale eddy diffusivities. The sensitivity of OHU to uncertainties in air‐sea fluxes and model parameters differs vastly across basins, with the Southern Ocean exhibiting strong sensitivity to air‐sea fluxes and model parameters. This study clearly demonstrates that model biases in air‐sea fluxes are one of the key sources of uncertainty in climate simulations.