Miracle-dz/UniFAR-FTUs huggingface dataset:
Downstaging Therapies for Unresectable Hepatocellular Carcinoma Prior to Hepatic Resection: A Systematic Review and Meta-Analysis

Introduction Hepatocellular carcinoma (HCC) is a high-grade malignant disease with unfavorable prognosis, and although surgical therapy is necessary, not all patients with HCC are suitable candidates for surgery. Downstaging as preoperative therapeutic strategy, which can convert unresectable HCC into resectable HCC, intends to increase the resection rate and improve prognosis. Methods We searched multiple databases updated to December 30, 2020, for studies on transcatheter arterial chemoembolization (TACE), Yttrium 90 microsphere selective internal radiation (SIR)/transcatheter radioembolization (TARE), hepatic arterial infusion (HAI), and systemic treatment as downstaging treatment before resection for patients with unresectable HCC. Results A total of 20 comparative and non-comparative studies were finally included in the meta-analysis. The pooled downstaging rate of hepatic resection (HR) was 14% [95% confidence interval (CI) 0.10–0.17] with significant heterogeneity (I 2 = 94.51%). The chemotherapy, combination, and non-cirrhosis groups exhibit higher rates of downstaging, but these differences were not significant. For comparative studies, the overall survival (OS) rates of resection after downstaging were far better than those inpatients who received locoregional therapy (LRT) or systemic treatment alone at 1 year (RR 1.87, 95% CI 1.48–2.38), 3 years (RR 5.56, 95% CI 2.55–12.10), and 5 years (RR 5.47, 95% CI 2.22–13.49). In addition, the pooled disease-free survival (DFS) rates in patients undergoing HR after successful downstaging were 78% (95% CI 0.62–0.93) at 1 year, 47% (95% CI 0.25–0.68) at 3 years, and 46% (95% CI 0.32–0.59) at 5 years. The pooled OS rates were 88% (95% CI 0.82–0.95) at 1 year, 64% (95% CI 0.59–0.69) at 3 years, and 42% (95% CI 0.29–0.54) at 5 years. Conclusions Downstaging may serve as a screening tool to identify patients who might benefit from surgery. Resection after successful downstaging can improve prognosis.
Is There Limited Utility for Lifestyle Recommendations for Diabetes Prevention Among Overweight or Obese Depressed Patients?

Background: Lifestyle interventions like diet and exercise are commonly recommended for diabetes prevention, but it is unclear if depression modifies the likelihood of adherence. We evaluated the relationship between high depressive symptomatology and adherence to lifestyle interventions among patients with pre-diabetes. Methods: We conducted an analysis of the nationally representative National Health and Nutrition Examination Survey (NHANES) 2017–2018. Adults, aged ≥18 years old who were overweight or obese (BMI ≥25) and had diagnosed or undiagnosed pre-diabetes (HbA1c 5.7–6.4) were included. Depressive symptomatology was classified by the Patient Health Questionniare-9 (PHQ-9). We used self-reported adherence to physician suggested lifestyle changes of diet and exercise. Results: In this nationally representative survey of overweight or obese adults with pre-diabetes, 14.8% also have high depressive symptomatology. In unadjusted analyses, an interaction was observed with high depressive symptomatology acting as an effect modifier for adherence to exercise oriented interventions among patients with diagnosed pre-diabetes (p = 0.027). In logistic regressions, adjusting for age, sex, race, outpatient medical care in the past 12 months, and obesity, among patients with diagnosed pre-diabetes, depressed patients were less likely to attempt to exercise more (OR = 0.31; 95% CI: 0.10, 0.94) and no association between high depressive symptomatology and attempting to lose weight was observed (OR = 0.45; 95% CI: 0.14, 1.42). Conclusions: The findings of this nationally representative study of US adults, high depressive symptomatology decreases the likelihood of adherence to exercise based lifestyle recommendations among patients with diagnosed pre-diabetes.
The Effects of Continuous vs. Intermittent Prism Adaptation Protocols for Treating Visuospatial Neglect: A Randomized Controlled Trial

Visuospatial neglect may interfere with activities of daily living (ADL). Prism adaptation (PA) is one treatment option and may involve two components: recalibration (more strategic) and realignment (more implicit). We examined whether recalibration or realignment is the driving force in neglect rehabilitation using PA. In a randomized controlled trial with two recruitment series and a cross-over design, 24 neglect patients were allocated to a continuous (PA-c) or intermittent (PA-i) PA procedure. During the PA-c condition, goggles were worn without doffing. In the PA-i condition, patients donned goggles twice (first series of patients) or three times (second series) during training to induce more recalibrations. Primary outcome parameters were performance (omissions) on the Apples Cancellation Test and ADL scores. To assess the efficacy of the PA treatment, we compared effect sizes of the current study with those from three groups from previous studies at the same rehabilitation unit: (1) a passive treatment with a similar intensity, (2) a placebo treatment with a similar intensity, and (3) a PA treatment with fewer therapy sessions. Treatment conditions did not significantly predict scores on primary and most secondary outcome parameters. However, the spontaneous ipsilesional body orientation improved only in patients receiving the PA-i condition and this improvement also appeared in patients showing a strong after-effect (irrespective of condition). Effect sizes for the Apples Cancellation Test and the Functional Independence Measure were larger for both PA treatment protocols than the historical control groups. We conclude that more recalibrations during an intermittent PA treatment may have a beneficial effect on spontaneous body orientation but not on other aspects of neglect or on ADL performance. Clinical Trial Registration: German Clinical Trials Register, identifier: DRKS00018813, DRKS00021539.
The Sharp Rise in the Use of Low- and No-Calorie Sweeteners in Non-Alcoholic Beverages in Slovenia: An Update Based on 2020 Data

Reducing added sugars in non-alcoholic beverages is an important public health goal, which can result in increased use of low- and no-calorie sweeteners (LNCS). The aim of this study was to investigate recent changes in the use of LNCS in non-alcoholic beverages in the Slovenian food supply. The national branded foods dataset was updated with beverages available in 2020, and compared with previous datasets. The data were extracted from food labels. In 2020, N = 1,650 unique beverages were found in shops from five different retailers, covering the majority of the national market. The use of LNCS increased from 13.2% in 2017 and 15.5% in 2019 to 20.2% in 2020, with a major growth in soft drinks (16.8, 19.6, and 26.7%, respectively). We observed a significant growth of beverages containing both LNCS and added sugar. Results were also consistent with sales data, which showed that increased offer of beverages with LNCS also resulted in similarly increased sales of such beverages. The average energy and total sugar content in non-alcoholic beverages decreased, which reflects both the higher percentage of beverages with LNCS, and also the reduction of the sugar content in beverages with only added sugar. Analyses of product-specific reformulation practices highlighted reduced sugar content in 16.8% of products, and in 3.6% with the use of LNCS. The most commonly used LNCS are acesulfame K, sucralose, and aspartame. Typically, combinations are used, however steviol glycosides, sucralose and saccharin are also used alone, in most cases combined with added sugar. The results indicated rapid changes in the use of LNCS in non-alcoholic beverages in the Slovenian food supply, making further monitoring of this area highly relevant.
Artificial Intelligence in Functional Food Ingredient Discovery and Characterisation: A Focus on Bioactive Plant and Food Peptides

Scientific research consistently demonstrates that diseases may be delayed, treated, or even prevented and, thereby, health may be maintained with health-promoting functional food ingredients (FFIs). Consumers are increasingly demanding sound information about food, nutrition, nutrients, and their associated health benefits. Consequently, a nutrition industry is being formed around natural foods and FFIs, the economic growth of which is increasingly driven by consumer decisions. Information technology, in particular artificial intelligence (AI), is primed to vastly expand the pool of characterised and annotated FFIs available to consumers, by systematically discovering and characterising natural, efficacious, and safe bioactive ingredients (bioactives) that address specific health needs. However, FFI-producing companies are lagging in adopting AI technology for their ingredient development pipelines for several reasons, resulting in a lack of efficient means for large-scale and high-throughput molecular and functional ingredient characterisation. The arrival of the AI-led technological revolution allows for the comprehensive characterisation and understanding of the universe of FFI molecules, enabling the mining of the food and natural product space in an unprecedented manner. In turn, this expansion of bioactives dramatically increases the repertoire of FFIs available to the consumer, ultimately resulting in bioactives being specifically developed to target unmet health needs.
Research on the Influence of Emotional Intelligence and Emotional Labor on the Service Recovery Effect of Online Travel Agency

At present, online travel agency (OTA) service failure events emerge continually, which makes the OTA service operation mode face new challenges. This study uses the situational experiment method to explore the effects of OTA employees’ emotional intelligence and emotional labor (surface behavior and deep behavior) on the effect of service recovery. The results show that the emotional intelligence of OTA employees has a positive impact on the surface behavior and deep behavior; the emotional intelligence and deep behavior of employees have a significant positive impact on service recovery satisfaction, but the positive impact of employees’ surface behavior on service recovery satisfaction is not statistically significant; finally, service recovery satisfaction has a positive impact on customer loyalty. This study helps to better explain the mechanism of OTA service recovery effect and provides a theoretical reference for improving the service recovery effect of OTA.
REALIZATION OF THE SPECTRAL RESPONSIVITY SCALE IN KRISS

Korea Research Institute of Standards and Science (KRISS) realizes the spectral responsivity scale using a laser-based absolute cryogenic radiometer (ACR) as the primary standard. The ACR calibrates Si trap detectors, which serve as the working standards disseminating the scale through direct comparison. Outside the calibrated wavelength range of the trap detectors, a pyroelectric detector is used as the transfer standard. We present the recently renovated apparatus setup for establishing and maintaining the spectral responsivity scale in KRISS, as well as the measured characteristics of the new working standards.
An “Uncharacterized” Australian Virus Is the Earliest Known Example of Ross River Virus with Changes in the nsP3 Protein Associated with the Explosive Outbreak of Ross River Virus Infection in the Pacific Region from 1979 to 1980

Ross River virus recovered from a South Australian patient during an outbreak of epidemic polyarthritis in 1971 is the earliest known genome sequence with the duplicated 12-amino-acid motif in the nsP3 protein that was found in strains responsible for the outbreak of epidemic polyarthritis in the Pacific region in 1979 to 1980. ABSTRACT Ross River virus recovered from a South Australian patient during an outbreak of epidemic polyarthritis in 1971 is the earliest known genome sequence with the duplicated 12-amino-acid motif in the nsP3 protein that was found in strains responsible for the outbreak of epidemic polyarthritis in the Pacific region from 1979 to 1980.
ST-CCN-PM2.5: fine-grained PM2.5 concentration prediction via spatial-temporal causal convolution network

PM2.5 concentration is an important evaluation index of urban air quality. Improving the prediction and early warning ability of PM2.5 concentration is of great significance for guiding residents' real-time protection and efficient control of air pollution. A large number of studies have shown that the temporal and spatial correlation between PM2.5 concentration of surrounding stations and target stations directly affects the prediction accuracy of the model. There is still a lack on how to select strongly correlated and representative temporal and spatial information, and the selection methods are somewhat subjective. In this paper, air pollutants and meteorological factors are taken as the influencing factors, and a PM2.5 prediction model (ST-CCN-PM2.5) based on causal convolution network is proposed to improve the performance of PM2.5 concentration prediction at a fine-grained spatial-temporal scale. We use spatial attention mechanism to fuse spatial correlation information, and optimize threshold parameters. Based on time attention mechanism, the sliding window size is adjusted to dilate the time-series input. Finally, the hourly records of air pollutants and meteorological factors monitored by 95 monitoring stations in Haikou city are employed, and the performance is compared with baseline. Compared with AR and ARMA models, the MSE values decrease by 38.9% and 40.9%, and R2 values increase by 2.3% and 2.6%, respectively. Compared with GRU, SVR, LSTM and ANN models, the MSE value of ST-CCN-PM2.5 decreases by 44.8%, 45.4%, 46.5% and 49.0%, respectively, and its R2 value increases by 3.6%. The final results show that the prediction performance of ST-CCN-PM2.5 model is significantly improved compared with the baseline, which proves that the model has stronger reflection ability and prediction generalization ability for dynamic nonlinear system, and proves the potential of the model in the prediction of fine particle PM2.5 concentration.
Evolutionary Operation: A Statistical Method for Process Improvement

This book is about the philosophy and practice of Evolutionary Operation (called EVOP for short), a simple but powerful statistical tool with wide application in industry. Experience has long shown that statistical methods, sometimes quite sophisticated in character, can be of great value in improving the efficiency of laboratory and pilot-plant investigations made by specially trained chemists and engineers. What originally motivated the introduction of EVOP, however, was the idea that the widespread and daily use of simple statistical design and analysis during routine production by process operatives themselves could reap enormous additional rewards.
Integrated NDE and FEM characterization of composite rotors

A structural assessment by integrating finite-element methods (FEM) and a nondestructive evaluation (NDE) of two flywheel rotor assemblies is presented. Composite rotor A is pancake like with a solid hub design, and composite rotor B is cylindrical with a hollow hub design. Detailed analyses under combined centrifugal and interference-fit loading are performed. Two- and three-dimensional stress analyses and two-dimensional fracture mechanics analyses are conducted. A comparison of the structural analysis results obtained with those extracted via NDE findings is reported. Contact effects due to press-fit conditions are evaluated. Stress results generated from the finite-element analyses were corroborated with the analytical solution. Cracks due to rotational loading up to 48 000 rpm for rotor A and 34 000 rpm for rotor B were successfully imaged with NDE and predicted with FEM and fracture mechanics analyses. A procedure that extends current structural analysis to a life prediction tool is also defined.
A 50 kV solid state multipulse kicker modulator

Performance requirements, design concepts, and test results for a prototype multipulse kicker modulator based on solid-state switches and a voltage-adding transformer topology are described. Tape-wound cores are stacked to form the transformer primary windings and a cylindrical pipe that passes through the circular inner diameters of the cores serves as the secondary winding of the step-up transformer. Boards containing MOSFET switches, trigger circuitry, and energy-storage capacitors plug into the core housings. A 50 kV prototype modulator that meets most of the facility requirements has been designed, fabricated, and tested at LLNL. More recent work has been concerned with designing and testing cores and boards with the full volt-second capability needed for 24-pulse operation. Results of the 50 kV prototype tests, preliminary tests of the full-volt-second cores and boards, and future development needs are described.
Energy storage capacitors: aging, and diagnostic approaches for life validation

Over the last decade, significant increases in capacitor reliability have been achieved through a combination of advanced manufacturing techniques, new materials, and diagnostic methodologies to provide requisite life-cycle reliability for high energy pulse applications. Recent innovations in analysis of aging, including dimensional analysis, are introduced for predicting component performance and fault tolerance. In addition, voltage scaling issues that may drive bank fault-tolerance performance are described.
Effects of On-Street Bicycle Facility Configuration on Bicyclist and Motorist Behavior

Growing awareness of environmental and public health problems associated with motorized transportation has led to a recent effort to promote nonmotorized modes of travel. Previous studies have shown that facility design plays a large role in encouraging bicycling. With the aim of defining the roadway configurations that lead to safe motorist and bicyclist behavior, this research examines the impact of design elements, including the type and width of the bicycle facility, the presence of adjacent motor vehicle traffic, parking turnover rate, land use, and the type of motorist-bicyclist interaction. Observational studies conducted at 48 sites in three large Texas cities characterize bicyclist and motorist behavior through lateral position measurements and instances of motorist encroachment on an adjacent lane. These observations were used to build two multivariate regression models and allowed for direct site-to-site comparisons. Notable results include the observation that bicycle lanes create a safer and more predictable riding environment relative to wide outside lanes, and that the provision of a buffer between parked cars and bicycle lanes is the only reliable method for ensuring that bicyclists do not put themselves at risk of being hit by opening car doors.
Evaluation of methods for estimating coalescence times using ancestral recombination graphs

The ancestral recombination graph (ARG) is a structure that describes the joint genealogies of sampled DNA sequences along the genome. Recent computational methods have made impressive progress towards scalably estimating whole-genome genealogies. In addition to inferring the ARG, some of these methods can also provide ARGs sampled from a defined posterior distribution. Obtaining good samples of ARGs is crucial for quantifying statistical uncertainty and for estimating population genetic parameters such as effective population size, mutation rate, and allele age. Here, we use standard neutral coalescent simulations to benchmark the estimates of pairwise coalescence times from three popular ARG inference programs: ARGweaver, Relate, and tsinfer+tsdate. We compare 1) the true coalescence times to the inferred times at each locus; 2) the distribution of coalescence times across all loci to the expected exponential distribution; 3) whether the sampled coalescence times have the properties expected of a valid posterior distribution. We find that inferred coalescence times at each locus are most accurate in ARGweaver, and often more accurate in Relate than in tsinfer+tsdate. However, all three methods tend to overestimate small coalescence times and underestimate large ones. Lastly, the posterior distribution of ARGweaver is closer to the expected posterior distribution than Relate’s, but this higher accuracy comes at a substantial trade-off in scalability. The best choice of method will depend on the number and length of input sequences and on the goal of downstream analyses, and we provide guidelines for the best practices.
Pseudomonas Synergizes with Fluconazole against Candida during Treatment of Polymicrobial Infection

Polymicrobial infections are challenging to treat because we don’t fully understand how pathogens interact during infection and how these interactions affect drug efficacy. Candida albicans and Pseudomonas aeruginosa are opportunistic pathogens that can be found in similar sites of infection such as in burn wounds and most importantly in the lungs of CF and mechanically ventilated patients. C. albicans is particularly difficult to treat because of the paucity of antifungal agents, some of which lack fungicidal activity. In this study, we investigated the efficacy of anti-fungal treatment during C. albicans-P. aeruginosa coculture in vitro and co-infection in the mucosal zebrafish infection model analogous to the lung. ABSTRACT Polymicrobial infections are challenging to treat because we don’t fully understand how pathogens interact during infection and how these interactions affect drug efficacy. Candida albicans and Pseudomonas aeruginosa are opportunistic pathogens that can be found in similar sites of infection such as in burn wounds and most importantly in the lungs of CF and mechanically ventilated patients. C. albicans is particularly difficult to treat because of the paucity of antifungal agents, some of which lack fungicidal activity. In this study, we investigated the efficacy of anti-fungal treatment during C. albicans-P. aeruginosa coculture in vitro and co-infection in the mucosal zebrafish infection model analogous to the lung. We find that P. aeruginosa enhances the activity of fluconazole (FLC), an anti-fungal drug that is fungistatic in vitro, to promote both clearance of C. albicans during co-infection in vivo and fungal killing in vitro. This synergy between FLC treatment and bacterial antagonism is partly due to iron piracy, as it is reduced upon iron supplementation and knockout of bacterial siderophores. Our work demonstrates that FLC has enhanced activity in clinically relevant contexts and highlights the need to understand antimicrobial effectiveness in the complex environment of the host with its associated microbial communities.
ICT adoption and diffusion in the construction industry of a developing economy: The case of the sultanate of Oman

The government of the Sultanate of Oman has launched a long-term development strategy, the ‘Oman Vision 2020’ plan, which focuses on Information and Communications Technology (ICT) and the fundamental establishment of a knowledge economy. However, the Omani construction sector, in particular, is lagging behind this vision. There are a number of limitations and barriers to the effective development of the industry, and a considerable gap exists between the modus operandi of the construction sectors in developed economies and that in Oman. This study aims to develop an in-depth and evidenced understanding of the structure, current practices, limitations and barriers, as well as specific characteristics of construction in Oman. The results reveal a number of socio-cultural and regulatory barriers reflected in a lack of (i) ICT strategic thinking in the surveyed organizations hindered by short-term cost and profit concerns and (ii) awareness, training and education programmes.