Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiac Function After Cardiotoxic Treatments for Childhood Cancer—Left Ventricular Longitudinal Strain in Screening

Background: The majority of childhood cancer survivors (CCSs) have been exposed to cardiotoxic treatments and often present with modifiable cardiovascular risk factors. Our aim was to evaluate the value of left ventricular (LV) longitudinal strain for increasing the sensitivity of cardiac dysfunction detection among CCSs. Methods: We combined two national cohorts: neuroblastoma and other childhood cancer survivors treated with anthracyclines. The final data consisted of 90 long-term CCSs exposed to anthracyclines and/or high-dose chemotherapy with autologous stem cell rescue and followed up for > 5 years and their controls (n = 86). LV longitudinal strain was assessed with speckle tracking (Qlab) and LV ejection fraction (EF) by three-dimensional echocardiography (3DE). Results: Of the CCSs, 11% (10/90) had abnormal LV longitudinal strain (i.e., < -17.5%); of those, 70% (7/10) had normal 3DE LV EF. Multivariable linear model analysis demonstrated that follow-up time (p = 0.027), sex (p = 0.020), and BMI (p = 0.002) were significantly associated with LV longitudinal strain. Conversely, cardiac risk group, hypertension, age, cumulative anthracycline dose or exposure to chest radiation were not. Conclusion: LV longitudinal strain is a more sensitive method than LV EF for the detection of cardiac dysfunction among CCSs. Therefore, LV longitudinal strain should be added to the screening panel, especially for those with modifiable cardiovascular risk factors.
GAS6/Axl Signaling Modulates Blood-Brain Barrier Function Following Intravenous Thrombolysis in Acute Ischemic Stroke

Background and Purpose Recent studies have shown that several proteins, including Axl, are related to hemorrhagic transformation (HT) following intravenous thrombolysis by affecting blood-brain barrier (BBB) function. However, the effects of these proteins on BBB function have been studied primarily in animal models. In this study, we aimed to identify serum protein markers that predict HT following intravenous thrombolysis in patients with acute ischemic stroke (AIS) and verify whether these serum proteins regulate BBB function and HT in animal stroke models. Methods First, 118 AIS patients were enrolled in this study, including 52 HT patients and 66 non-HT patients. In Step 1, baseline serum levels of Axl, angiopoietin-like 4, C-reactive protein, ferritin, hypoxia-inducible factor-1 alpha, HTRA2, Lipocalin2, matrix metallopeptidase 9, platelet-derived growth factor-BB, and tumor necrosis factor alpha were measured using a quantitative cytokine chip. Next, sequence mutations and variations in genes encoding the differentially expressed proteins identified in Step 1 and subsequent function-related proteins were detected. Finally, we verified whether manipulation of differentially expressed proteins affected BBB function and HT in a hyperglycemia-induced rat stroke model. Results Serum Axl levels were significantly lower in the HT group than in the non-HT group; none of the other protein markers differed significantly between the two groups. Genetic testing revealed that sequence variations of GAS6 (the gene encoding the Axl ligand)-derived long non-coding RNA, GAS6-AS1, were significantly correlated with an increased risk of HT after intravenous thrombolysis. In animal studies, administration of recombinant GAS6 significantly reduced brain infarction and neurological deficits and attenuated BBB disruption and HT. Conclusions Lower serum Axl levels, which may result from sequence variations in GAS6-AS1, are correlated with an increased risk of HT after intravenous thrombolysis in stroke patients. Activation of the Axl signaling pathway by the GAS6 protein may serve as a therapeutic strategy to reduce HT in AIS patients.
Effects of Thelytokous Parthenogenesis-Inducing Wolbachia on the Fitness of Trichogramma dendrolimi Matsumura (Hymenoptera: Trichogrammatidae) in Superparasitised and Single-Parasitised Hosts

Thelytokous Wolbachia-infected Trichogramma species have long been considered as biological control agents against lepidopteran pests in agriculture and forestry. Wolbachia has been suggested to increase the probability of the superparasitism of Trichogramma, but the fate of infected offspring in the superparasitised host is still unknown. The present study aimed to evaluate the fitness of thelytokous Wolbachia-infected (TDW) and bisexual Wolbachia-free (TD) Trichogramma dendrolimi Matsumura (Hymenoptera: Trichogrammatidae) lines in superparasitised or single-parasitised hosts. The results showed that irrespective of whether Trichogramma wasps were developed from superparasitised or single-parasitised hosts, the TDW line was characterized by reduced fitness, including lower fecundity, shorter longevity, and smaller body size of F1 offspring, and lower emergence rate of F2 offspring than the TD line. This was not true for the survival rate and developmental time of F1 offspring. Additionally, the fitness parameters of T. dendrolimi that developed from superparasitised hosts were lower compared with that of T. dendrolimi that developed from single-parasitised hosts. Interestingly, Wolbachia-infected females had higher dispersal capacity than bisexual females when they developed from superparasitised hosts. The results indicated that Wolbachia negatively affects fitness of T. dendrolimi, but enhance dispersal capacity of T. dendrolimi females in superparasitism condition. Further studies need to be carried out to select the best line that will allow Wolbachia and their host Trichogramma to be better adapted to one another.
Basic Psychological Needs in the Work Context: A Systematic Literature Review of Diary Studies

According to the self-determination theory, individuals' basic psychological needs for autonomy, competence, and relatedness should be satisfied for optimal psychological growth. The satisfaction of these needs seems to vary due to changes in a person's social context, and the outcomes of the satisfaction of these needs also vary along with the needs. Despite several studies investigating daily and weekly variations in need satisfaction and its correlates, no systematic investigation exists. This study aimed to conduct a narrative synthesis of existing quantitative diary studies of basic psychological needs in the work context. We specifically aimed to evaluate if psychological need satisfaction varies daily and weekly and judge whether they vary more daily or weekly. Additionally, we also aimed to review the literature regarding the relations between daily or weekly variations in need satisfaction and its assumed antecedents and outcomes. We included peer-reviewed articles in English that measured work-related basic psychological needs using a quantitative diary study design. Database searching (Web of Science, ScienceDirect, EBSCOhost, and Scopus) led to the extraction of 2 251 records by February 2020. Duplicates were removed, the remaining records were screened (n = 820), and 30 articles were assessed using eligibility criteria. Two authors individually conducted the screening and eligibility processes to manage selection bias. In total, 21 articles were included in the final review. The review indicated that basic psychological need satisfaction showed considerable within-person variation and was more dynamic daily (compared to weekly). Job demands, job resources, organisational resources, and individual characteristics appeared to associate with these variations. The organisational context seemed to matter the most for need satisfaction. Variations in need satisfaction were also related to employee well-being, performance, and motivation. Despite the small number of published studies (particularly for weekly studies), our results indicate that researchers should pay attention to within-person variations in need satisfaction. Measuring daily need satisfaction could be prioritised. Different antecedents and outcomes seem to be associated with different needs. Thus, when needs are viewed as distinct constructs instead of unidimensional ones, one can derive greater insights. The study is funded by the National Research Foundation.
S0960258521000052jra 169..177

The wheat industry rejects grain with unacceptably high α-amylase enzyme levels due to the risk of poor endproduct quality. There are two main causes of elevated grain α-amylase: (1) preharvest sprouting in response to rain before harvest and (2) late maturity α-amylase (LMA) induction in response to a cool temperature shock during late grain development. LMA induction was detected in a panel of 24 Northwestern US spring wheat lines. Thus, this problem previously described in Australian and U.K. varieties also exists in U.S. varieties. Because LMA induction results were highly variable using published methods, a characterization of LMA-inducing conditions was conducted in an LMA-susceptible soft white spring wheat line, WA8124. Problems with elevated α-amylase in untreated controls were reduced by raising the temperature, 25°C day/18°C night versus 20°C day/10°C night. LMA induction was not improved by colder temperatures (15°C day/4°C night) versus moderately cold temperatures (18°C day/7.5°C night or 10°C day/10°C night). While previous studies observed LMA induction by heat stress, it failed to induce LMA in WA8124. Thus, not all LMA-susceptible cultivars respond to heat. The timing of LMA susceptibility varied between two cultivars and within a single cultivar grown at slightly different temperatures. Thus, variability in LMA induction likely results from variability in the timing of the grain developmental stage during which cold shock induces LMA. Thus, it was concluded that the visual inspection of grain is needed to correctly identify LMA-sensitive spikes at the soft dough stage of grain development (Zadok’s stage 85).
Multiparametric Platform for Profiling Lipid Trafficking in Human Leukocytes: Application for Hypercholesterolemia

Systematic insight into cellular dysfunctions can improve understanding of disease etiology, risk assessment and patient stratification. We present a multiparametric high-content imaging platform enabling quantification of low-density lipoprotein (LDL) uptake and lipid storage in cytoplasmic droplets of primary leukocyte subpopulations. We validated this platform with samples from 65 individuals with variable blood LDL-cholesterol (LDL-c) levels, including familial hypercholesterolemia (FH) and non-FH subjects. We integrated lipid storage data into a novel readout, lipid mobilization, measuring the efficiency with which cells deplete lipid reservoirs. Lipid mobilization correlated positively with LDL uptake and negatively with hypercholesterolemia and age, improving differentiation of individuals with normal and elevated LDL-c. Moreover, combination of cell-based readouts with a polygenic risk score for LDL-c explained hypercholesterolemia better than the genetic risk score alone. This platform provides functional insights into cellular lipid trafficking from a few ml’s of blood and is applicable to dissect metabolic disorders, such as hypercholesterolemia.We have limited information on how cellular lipid uptake and processing differ between individuals and influence the development of metabolic diseases, such as hypercholesterolemia. Available assays are labor intensive, require skilled personnel and are difficult to scale to higher throughput, making it challenging to obtain systematic functional cell-based data from individuals. To overcome this problem, we established a scalable automated analysis pipeline enabling reliable quantification of multiple cellular readouts, including lipid uptake, storage and mobilization, from different white blood cell populations. This approach provides new personalized insights into the cellular basis of hypercholesterolemia and obesity.
Seasonality in fuel consumption: a case study of a gas station

Oil and its derivatives are very important goods in the world, not only because of their huge use but also because the consequences of that use. The literature has plenty of works with economic analysis of the use of oil. Having available a huge amount of data, we propose an innovative approach: based on daily information of sales in a gas station since 2001 to 2018, we make a seasonality analysis of those sales. In separate analysis, using information of the both existing shifts, of the week day and of the month, we conclude that seasonality in sales is significant. This is an important information for firm managers, which could use this information to better define their strategies.
The effects of Chinese herbal medicine on the pregnancy outcomes of infertile women with polycystic ovary syndrome undergoing in vitro fertilization-embryo transfer: a systematic review and meta-analysis

Background: At present, Chinese herbal medicine (CHM) has already been widely used as an important adjuvant treatment for polycystic ovary syndrome (PCOS) patients undergoing in vitro fertilizationembryo transfer (IVF-ET). This systematic review and meta-analysis were designed to evaluate the effects of CHM on the pregnancy outcomes of infertile women with PCOS undergoing IVF-ET. Methods: We searched seven electronic databases systematically for published articles to January 2021. All randomized controlled trials (RCTs) comparing CHM with blank or placebo for infertile PCOS patients undergoing IVF-ET were included. The measures of treatment effect were the pooled odds ratios (OR) of the clinical pregnancy rate, the abortion rate and the ovarian hyperstimulation syndrome (OHSS) incidence. Results: This meta-analysis included 10 studies involving 663 patients comparing CHM with blank or placebo for infertile PCOS patients undergoing IVF-ET. The pooled data showed that CHM could improve the clinical pregnancy rate (OR = 2.41, 95% CI: 1.73–3.35, p < 0.01) and reduce the OHSS incidence (OR = 0.31, 95% CI: 0.18–0.55, p < 0.01) of infertile PCOS patients with IVF-ET treatment. No significant difference in the abortion rate was found between the CHM and control groups (OR = 0.64, 95% CI: 0.23–1.81, p = 0.40). Discussion: CHM can be used as an auxiliary treatment for infertile PCOS patients undergoing IVF-ET.
Automated vision based defect detection using gray level co-occurrence matrix for beverage manufacturing industry

Defect inspection emerged as an important role for product quality monitoring process since it is a requirement of International Organization for Standardization (ISO) 9001. The used of manual inspection is impractical because of time consuming, human error, tiredness, repetitive and low productivity. Small and medium enterprises (SMEs) are industries that having problems in maintaining the quality of their products due to small capital provided. Therefore, automatic inspection is a promising approach to maintain product quality as well as to resolve the existing problems related to delay outputs and cost burden. This article presents a computerized analysis to detect color concentration defects that occur in beverage production based on texture information provided by gray level co-occurrence matrix (GLCM). Based on the texture information, GLCM cross-section is computed to extract the parameters for features of color concentration. The distance value between two colors is then computed using co-occurrence histogram. The defect results either pass or reject is determined using Euclidean distance and rule-based classification. The experimental results show 100% accuracy which makes the proposed technique can implimented for beverage manufacturing inspection process.
CONSEQUENCES OF THE HIGH ABUNDANCE OF BOMBUS TERRESTRIS ON THE POLLINATION OF VICIA FABA

One of the main visitors to Fabia bean crops (Vicia faba) in South America is the invasive bumblebee species Bombus terrestris. This is particularly true in Chile, where B. terrestris was first introduced in 1997 and is now common over much of the country. In this study, we evaluated the activity of the principal pollinators of V. faba over two cropping seasons by assessing their visitation rates while distinguishing between legitimate visits, likely to lead to pollination, and nectar robbery. We then determined the net contribution of insect visitation on pod and seed set. We recorded seven species of floral visitors. Most visits (legitimate visits and robbery) were from the honeybee (Apis mellifera), with B. terrestris being the next most common visitor. In the case of B. terrestris, 87.19% of visits were nectar robbery. On average, the same flower perforation was visited 23 times by B. terrestris during the flower's lifespan. In general, the frequency of legitimate visits varied with pollinator identity and year. For B. terrestris, each flower received an average of 0.95 legitimate visits during its entire lifespan. The time spent by B. terrestris visiting flowers for both nectar robbery or pollen collection decreased after the first day of flowering suggesting resource depletion. The number of pods, total seed number, and seed weight were lower where self rather than open pollination. This suggests that open pollination increased reproductive success. We conclude that B. terrestris was likely to contribute relatively little to pollination while at the same time depleting floral resources throughout the flowers’ lifespan. Bombus terrestris is likely to make V. faba flowers less attractive to other more effective pollinators. As a result, this may potentially drive interspecific competition for pollen and nectar within the crop. Keywords—Apis mellifera, Bombus dahlbomii, Bombus ruderatus, Bombus terrestris, Cadeguala, nectar robbery
Modelling of faults in LoopStructural 1.0

Abstract. Without properly accounting for both fault kinematics and observations of a faulted surface, it is challenging to create 3D geological models of faulted geological units. Geometries where multiple faults interact, where the faulted surface geometry significantly deviate from a flat plane and where the geological interfaces are poorly characterised by sparse datasets are particular challenges. There are two existing approaches for incorporating faults into geological surface modelling. One approach incorporates the fault displacement into the surface description but does not incorporate fault kinematics and in most cases will produce geologically unexpected results such as shrinking intrusions, fold hinges without offset and layer thickness growth in flat oblique faults. The second approach builds a continuous surface without faulting and then applies a kinematic fault operator to the continuous surface to create the displacement. Both approaches have their strengths; however, neither approach can capture the interaction of faults within complicated fault networks, e.g. fault duplexes, flower structures and listric faults because they either (1) impose an incorrect (not defined by data) fault slip direction or (2) require an over-sampled dataset that describes the faulted surface location. In this study, we integrate the fault kinematics into the implicit surface, by using the fault kinematics to restore observations, and the model domain prior to interpolating the faulted surface. This new approach can build models that are consistent with observations of the faulted surface and fault kinematics. Integrating fault kinematics directly into the implicit surface description allows for complexly faulted stratigraphy and fault–fault interactions to be modelled. Our approach shows significant improvement in capturing faulted surface geometries, especially where the intersection angle between the faulted surface and the fault surface varies (e.g. intrusions, fold series) and when modelling interacting faults (fault duplex).
Distinguish the Textures of Grasped Objects by Robotic Hand Using Artificial Neural-Network

 Feature vector was acquired from force and actuator sensors in time series response.  Arduino microcontroller and the Matlab program are integrated to acquire sensor data.  Neural-Network used as an intelligent classifier to distinguish the object softness. The object identification properties with tactile sensing are valuable in interaction with the environment for both humans and robots, and it is the core of sensing used for exploration and determining properties of objects that are inaccessible from visual perception. Object identification often involves with rigid mechanical grippers, tactile information and intelligent algorithms. This paper proposes a methodology for feature extraction techniques and discriminates objects for different softness using adaptive robotic grippers, which are equipped with force and angle sensors in each four fingers of an underactuated robot hand. Arduino microcontroller and the Matlab program are integrated to acquire sensor data and to control the gripping action. The neuralnetwork method used as an intelligent classifier to distinguish between different object softness by using feature vector acquired from the force sensor measurements and actuator positions in time series response during the grasping process using only a single closure grasping. The proposed method efficiency was validated using experimental paradigms that involving three sets of model objects and everyday life objects with various shapes, stiffness, and sizes. A R T I C L E I N F O Handling editor: Muhsin J. Jweeg
Ensemble prediction of protein secondary structure through feature-based accuracy estimation

Protein secondary structure prediction is a fundamental task in computational biology, basic to many bioinformatics workflows, with a diverse collection of tools currently available. An approach from machine learning with the potential to capitalize on such a collection is ensemble prediction , which runs multiple predictors and combines their predictions into a single one, output by the ensemble. We conduct a thorough study of eight different approaches to ensemble secondary structure prediction, several of which are novel, and show we can indeed obtain an ensemble method that significantly exceeds the accuracy of individual state-of-the-art tools. The best approaches build on a recent technique known as feature-based accuracy estimation , which estimates the unknown true accuracy of a prediction, here using features of both the prediction output and information internal to the prediction method. In particular, a hybrid approach to ensemble prediction that leverages accuracy estimation is now the most accurate method currently available: on average over standard CASP and PDB benchmarks, it exceeds the state-of-the-art Q 3 accuracy for 3-state prediction by nearly 4%, and exceeds the state-of-the-art Q 8 accuracy for 8-state prediction by more than 8%. An implementation of our hybrid approach to ensemble protein secondary structure prediction in a new tool we call Ssylla , together with accuracy estimators for the best prediction methods in widespread use, is available at http://ssylla.cs. arizona.edu .