Miracle-dz/UniFAR-FTUs huggingface dataset:
Biochemical characteristics of Trichoderma atroviride associated with conidium fitness for biological control

ABSTRACT Effects of abiotic factors during production (temperature, nutrients, water activity, pH) on conidium fitness (quantity and quality) of Trichoderma atroviride LU132 (a key biocontrol agent) were studied. Conidia from the culturing regimes which resulted in greatest and least bioactivity against Rhizoctonia solani in dual culture assays were selected to assess effects of storage conditions on conidial fitness over time. Further studies assessed interaction effects of temperatures (20°C or 30°C) and sugars (dextrose or sucrose) on conidium germination and bioactivity as fresh conidia, or after 6 months of storage. Biochemical analyses of sugars and fatty acids were carried out to determine relationships between quality variations and cellular characteristics for conidia produced in different culturing conditions. Low trehalose content in conidia (e.g. at 20°C) was associated with the least conidium fitness, although high trehalose content did not necessarily support conidium fitness. High proportions of total fatty acids in conidia were mostly associated with the least conidium fitness. When Trichoderma was grown at high carbon to nitrogen ratio (e.g. at C:N 160:1), the total conidium fatty acids content increased. This study also indicated that the monosaccharide dextrose is metabolically optimal for T. atroviride LU132 at 20°C while the disaccharide sucrose is optimal at 30°C. These studies indicate that physical growth conditions and nutritional requirements attribute in conidium fitness of T. atroviride LU132, and provide important knowledge supporting optimum production of biocontrol agents based on T. atroviride, and possibly other similar biocontrol agents.
Life Cycle Assessment of Natural Fiber-Based Insulator Corrugated Paper Box to Identify Eco-Design Strategies

 Abstract. This study explored the potential use of natural fibers as alternative insulate lining in a corrugated paper box for fresh asparagus transportation packaging. Life Cycle Assessment (LCA) was used to evaluate the potential environmental impacts of a natural fiber-based insulation prototype that could help identify the eco-design strategies. The environmental performances of the prototype were evaluated and compared with a corrugated paper box, with forced air cooling before shipment, and a corrugated paper box lined with polyethylene foam and filled with dry ice. The system boundary was the whole life cycle of products. The functional unit on which the comparison was defined as a corrugated paper box (1,100 cm×1,100 cm×1,000 cm) with a load of 300 kg of fresh asparagus for the transportation to a specific oversea destination by air fleet. Data collection was from primary data (i.e. natural fiber-based insulator production) and the background data were sourced from the national life cycle inventory databases (i.e. electricity, water, polyethylene foam), supplemented by international databases (i.e. chemical production, transportation) and literature review (i.e. corrugated paper box production). The LCA results indicated that, for the natural fiber-based insulation production, the highest impact on global warming was associated with the use of electricity by the fiber-drying oven; moreover, the use of sodium hydroxide, for the fiber extraction, caused a significant impact on eco-toxicity. The strategies for eco-design to improve the environmental performances of the natural-fiber insulation could be achieved by avoiding the chemical-extraction process and increasing the energy efficiency of the fiber-drying process. The alternative application of mechanically-steam explosion of natural fibers, instead of the chemical extraction method, could potentially reduce the environmental impact on freshwater eutrophication 83%, human toxicity 74% and terrestrial eco-toxicity 76%. By using a drying technique with higher energy efficiency, it could potentially reduce the use of electricity by approximately 50%. The environmental impacts could potentially be reduced on climate change 29%, terrestrial acidification 25% and freshwater eco-toxicity 15%, respectively.
Plasma and Cerebrospinal Fluid Beta-Endorphin Levels Show a Strong Association in Children with Cerebral Malaria

Background: Beta (β)-endorphins are endogenous neuropeptides found in the plasma and cerebrospinal fluid (CSF) of humans but there have been reports of the relationship between the plasma and CSF β-endorphin levels in different clinical conditions. However, the relationship between β-endorphin levels in the plasma and CSF of children with cerebral malaria (CM) has not been reported. Aim: To determine the relationship between β-endorphin levels in the CSF and plasma of children with CM. Settings and Design: This cross-sectional study involved 40 children, aged between 6 months and 14 years, admitted with a diagnosis of CM at the Obafemi Awolowo University Teaching Hospitals Complex (OAUTHC), Ile-Ife, Nigeria. Materials and Methods: One milliliter (mL) of venous blood and 1mL of CSF obtained from each subject at admission were used to determine the β-endorphin levels using enzyme-linked immunosorbent assay (ELISA) method. Statistical Analysis: Bivariate linear regression was used to determine the association between plasma and CSF β-endorphin levels using the correlation coefficient (r), coefficient of determination (R2), and P values. Results: The plasma β-endorphin levels significantly positively correlated with CSF β-endorphin (r = 0.568, P = 0.001) such that for every unit rise in plasma β-endorphin, CSF β-endorphin rose by 0.252 pmol/L (confidence interval: 0.132–0.371 pmol/L). Conclusion: The finding of positive correlation between plasma and CSF β-endorphin levels in this study suggests a possible direct link between plasma and CSF in CM, probably from the disruption of the blood–brain barrier that has been reported in CM.
Search for supersymmetry in events with at least one soft lepton, low jet multiplicity, and missing transverse momentum in proton-proton collisions at s=13 TeV

A search for supersymmetry with a compressed mass spectrum using events with a high-momentum jet attributed to initial state radiation, high missing transverse momentum, and a low-momentum lepton is presented. In particular, scenarios of top squark pair production are investigated, where the mass difference to the lightest supersymmetric particle (LSP) is smaller than the mass of the W boson. The search is performed in a sample of proton-proton collisions recorded with the CMS detector at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 35.9 fb−1. The results are consistent with the expectation from standard model processes and limits are set on the production cross section in the plane of the top squark vs. LSP masses. The signal models used for the interpretation of the results assume either four-body decays of the top squark, t̃→ b f f ′LSP, or decays via an intermediate chargino, t̃→ bχ̃ 1 → b f f ′LSP. Assuming a 100% branching ratio of the corresponding decay, top squark masses below 500 (540) GeV for four-body (chargino-mediated) decay are excluded at 95% confidence level for a mass difference to the LSP of about 30 GeV. These limits are currently the most stringent in the single lepton final state and are similar to those of analyses targeting other final states in this region of supersymmetry parameter space with 2016 data.
U2Fusion: A Unified Unsupervised Image Fusion Network

This study proposes a novel unified and unsupervised end-to-end image fusion network, termed as U2Fusion, which is capable of solving different fusion problems, including multi-modal, multi-exposure, and multi-focus cases. Using feature extraction and information measurement, U2Fusion automatically estimates the importance of corresponding source images and comes up with adaptive information preservation degrees. Hence, different fusion tasks are unified in the same framework. Based on the adaptive degrees, a network is trained to preserve the adaptive similarity between the fusion result and source images. Therefore, the stumbling blocks in applying deep learning for image fusion, e.g., the requirement of ground-truth and specifically designed metrics, are greatly mitigated. By avoiding the loss of previous fusion capabilities when training a single model for different tasks sequentially, we obtain a unified model that is applicable to multiple fusion tasks. Moreover, a new aligned infrared and visible image dataset, RoadScene (available at https://github.com/hanna-xu/RoadScene), is released to provide a new option for benchmark evaluation. Qualitative and quantitative experimental results on three typical image fusion tasks validate the effectiveness and universality of U2Fusion. Our code is publicly available at https://github.com/hanna-xu/U2Fusion.
Solar cell efficiency enhancement using a hemisphere texture containing metal nanostructures

One major problem of the conventional solar cells is low conversion efficiency. In this work, we have proposed a new design including hemisphere texturing on top and metallic plasmonic nanostructure under the silicon layer to enhance the optical absorption inside the photosensitive layer. The finite-difference time-domain (FDTD) method has been used to investigate the interaction of light with the proposed structure. The simulation results demonstrated that the designed structure gives rise to 40% light absorption enhancement and 27% solar cell efficiency enhancement compared to a simple cell structure. The hemisphere texturing acts as a light concentrator and results in local electric field enhancement inside the silicon layer, and metallic nanostructure excites the plasmons. By combining the advantages of these two designs, the short circuit of the proposed structure showed more than 65% enhancement compared to the conventional structure.
Robust Feature Engineering for Parkinson Disease Diagnosis: New Machine Learning Techniques (Preprint)

BACKGROUND Parkinson disease (PD) is a common neurodegenerative disorder that affects between 7 and 10 million people worldwide. No objective test for PD currently exists, and studies suggest misdiagnosis rates of up to 34%. Machine learning (ML) presents an opportunity to improve diagnosis; however, the size and nature of data sets make it difficult to generalize the performance of ML models to real-world applications. OBJECTIVE This study aims to consolidate prior work and introduce new techniques in feature engineering and ML for diagnosis based on vowel phonation. Additional features and ML techniques were introduced, showing major performance improvements on the large mPower vocal phonation data set. METHODS We used 1600 randomly selected /aa/ phonation samples from the entire data set to derive rules for filtering out faulty samples from the data set. The application of these rules, along with a joint age-gender balancing filter, results in a data set of 511 PD patients and 511 controls. We calculated features on a 1.5-second window of audio, beginning at the 1-second mark, for a support vector machine. This was evaluated with 10-fold cross-validation (CV), with stratification for balancing the number of patients and controls for each CV fold. RESULTS We showed that the features used in prior literature do not perform well when extrapolated to the much larger mPower data set. Owing to the natural variation in speech, the separation of patients and controls is not as simple as previously believed. We presented significant performance improvements using additional novel features (with 88.6% certainty, derived from a Bayesian correlated t test) in separating patients and controls, with accuracy exceeding 58%. CONCLUSIONS The results are promising, showing the potential for ML in detecting symptoms imperceptible to a neurologist.
The Area under the Curve (AUC) of Oral Glucose Tolerance Test (OGTT) Could Be a Measure Method of Hyperglycemia in All Pregnant Women

Objective: We adopted the area under the curve (AUC) of oral glucose tolerance test (OGTT) as a measure method of the severity of maternal hyperglycemia and investigated its relationship with adverse perinatal outcomes among women with and without gestational diabetes mellitus (GDM). Research design and methods: This is a retrospective cohort study. Our study group collected the medical records of 15,296 women who received perinatal care in 15 hospitals in Beijing and who delivered from July 1, 2013, to December 31, 2013. And several original articles on this cohort have been published. In this study, we analyze the relationship between AUC and adverse perinatal outcomes, so that in multiple pregnant cases, patients with pre-pregnancy diabetes, hypertension, and abnormal kidney function and those who did not receive a 75-g OGTT were excluded. A Chi-squared test and logistic regression analysis were used to determine the associations. Results: In total, 13,561 women were included. As the AUC of OGTT increased, the prevalence of macrosomia (odds ratio [OR] 1.059, 95% confidence interval [95% CI] 1.029 - 1.090, p < 0.001) and hypertensive diseases (OR 1.106, 95% CI 1.064 - 1.149, p < 0.001) also increased. For patients with same levels of AUC values, no significant differences in the risk of macrosomia, preterm birth and neonatal complications were observed between the GDM and non-GDM groups. Women with an AUC higher than 14.20 (mmol * h/L) had a higher risk of adverse outcomes regardless of the presence of GDM. Conclusions: The AUC could be a measure method of the severity of maternal hyperglycemia, and women with a high AUC should undergo aggressive management to avoid adverse outcomes regardless of the presence of GDM.
RoHS substances in mixed plastics from Waste Electrical and Electronic Equipment

With the contribution of the LIFE financial instrument of the European Community. We are grateful to the WEEE Forum and the European Community for having supported this project. A special thank goes to all those members of the WEEE Forum who provided laboratory samples. Finally, we would like to express our gratitude to the Swiss WEEE system operators SENS and SWICO, who initiated this project by supporting an extended literature review.
Relative toxicity of selected insecticides against adult whiteflyBemisia tabaci (Hemiptera: Aleyrodidae) transmitting Mesta yellow vein mosaic virus

Whitefly (Bemisia tabaci) is an important pest of more than 600 host plant species and vector of various plant begomovirus. Bioassay of five insecticides namely, imidacloprid 200 SL (Confidor), flonicamid 50 WG, (Ulala), spiromesifen 240 SC, (Oberon) diafenthiouron 500 SC (Pegasus) and dimetheoate 30 EC (Tafgor) were tested against adult whitefly of kenaf crop. These insecticides gave adult whitefly mortality in ranged of 30 to 88, 22 to 60, 25 to 65, 28 to 75 and 20 to 50 per cent respectively under controlled laboratory conditions after 24 hours treatments. Among the insecticides studied, imidacloprid was found most toxic (LC50-6.6 ppm) to adult whiteflies followed by diafenthiouron (LC50-22.59 ppm). Similarly, the insecticides flonicamid (LC50-24.85 ppm) and spiromesifen (LC50- 28.37 ppm) possess toxic against whitefly but dimetheoate (LC50-7100 ppm) was found least toxic. On the basis of LC50 values, imidacloprid was found most toxic to adult whiteflies followed by diafenthiouron and emerged as best insecticides for managing the whiteflies.
Whose Truth is the "Ground Truth"? College Admissions Essays and Bias in Word Vector Evaluation Methods

Word vectors are widely used as input features in natural language processing (NLP) tasks. Researchers have found that word vectors often encode the biases of society, and steps have been taken towards debiasing the vectors themselves. However, little has been said about the fairness of the methods used to evaluate the quality of vectors. Analogical and word similarity tasks are commonplace, but both rely on purportedly ground truth statements about the semantic relationships between words (e.g. “man is to woman as king is to queen”). These analogies look reasonable when only taking into account the literal meanings of words, but two issues arise: (1) people don’t always use words in a literal sense, and (2) the same word may be used diﬀerently by different groups of people. In this paper, we split a dataset of over 800,000 college admissions essays into quartiles based on reported household income (RHI) and train sets of word vectors on each quartile. We then test these sets of vectors on common intrinsic evaluation tasks. We ﬁnd that vectors trained on the essays of higher income students encode more of each task’s target semantic relationships than vectors trained on the essays of lower income students. These results hold even when controlling for word frequency. We conclude that the tasks themselves are biased towards the writing of higher income students, and we challenge the notion that there exist ground truth semantic relationships that word vectors must encode in order to be useful.
Finite Element Analysis of Composite Hat-Stiffened Panels Subjected to Edge Compression Load

This paper deals with optimizing smeared extensional stiffness ratio of stiffeners to that of skin of laminated composite hat-stiffened panel with the variation of pitch length stiffeners, depth of stiffeners and panel orthotropy ratio for three different plie configurations to maximize buckling capacity of the panel. Critical buckling load and global buckling mode shape of the laminated composite hat-stiffened panel are studied for the design of lightweight structures. Parametric studies of hat-stiffened panel under in-plane compressive load are presented with simply supported boundary conditions. Models are analyzed by applying Finite Element method using ABAQUS. A database is provided based on smeared stiffness approach for two different hatstiffened (600-hat-stiffened and 750-hat-stiffened) panels with variation of pitch length stiffeners, depth of stiffeners, panel orthotropy ratio and smeared extensional stiffness ratio of stiffeners to that of skin with three different plie configurations. On the basis of the study, optimum smeared extensional stiffness ratio is increased with increasing of orthotropy ratio for all similar skin, but it is also increased with decreasing extensional stiffness ratio to maximize buckling capacity of hat-stiffened panel and general guidelines are developed for the design of better hat-stiffened panel.
THE BURDEN OF CO-OCCUPANCY: INTRASPECIFIC RESOURCE COMPETITION AND SPACING PATTERNS IN AMERICAN MINK, MUSTELA VISON

Abstract Live-trapping and radiotracking of American mink (Mustela vison) on 24 km of the River Thames, United Kingdom, revealed range sizes (male: 6.8 km, female: 2.7 km), numbers of other mink found in the range of each male (0.98 males, 1.95 females) and each female (1.18 males, 0.32 females), and range overlaps between dyads of males (88.2%), a male and a female (male: 32.6%, female: 69.1%), and females (66.3%). We used these data to estimate the potential energetic burden of conspecifics on each other. As a monthly average, cohabiting males and other females take an estimated 30% and 9%, respectively, of the total energy consumption by mink within the range of each female. Similarly, cohabiting males and females consume an estimated 21% and 40%, respectively, of the energy in each male's range. Intraspecific resource depression may force both sexes, especially males, to maintain larger ranges. We suggest that, in the case of American mink, intraspecific prey-resource competition affects the range sizes of both sexes.
UPDATED FATIGUE TEST METHODS FOR STRUCTURAL FOAMS AND SANDWICH BEAMS

Foam-cored sandwich yacht hulls are subjected to high core shear stresses during slamming events. As slamming is repetitive by nature, failures observed on boats may be due to fatigue. This study aims to investigate possible improvements to fatigue testing of both foam core materials and sandwich specimens. In general test set-up induces differences between the ways a material behaves in a test coupon and in a real application. One such difference is “edge effect”, as the material behaviour can change close to a free edge. For example, the micro-structure may have been affected by the specimen machining, which may influence failure initiation. This is exacerbated if the test set-up induces stress concentrations close to the edge. Another difference is that in a standard core shear fatigue testing by 4 point bending, the stress field is spatially static, when in a slamming event the stress field is spatially variable. Does the material react differently to a static and moving stress field? This study aims to develop a core shear test method replicating a moving stress field, free of edge effect. This paper presents the finding of the initial steps of this study: The edge effect has been investigated using modified loading fixture. The moving stress field has been investigated with a modified 4point bending test using asynchronous loading. The differences in test results between the modified test methods and the relevant standard test methods indicate that both aspects affect measured fatigue life. 1 Design Engineer, Gurit (Asia Pacific), Auckland, New Zealand 2 Associate Professor, Laboratoire GeM, Université de Nantes 3 Master’s student, Laboratoire GeM, Université de Nantes 4 Professor, Laboratoire GeM, Université de Nantes 5 Professor, Laboratoire GeM, Université de Nantes
Exploiting Resource Contention in Highly Mobile Environments and Its Application to Vehicular Ad-Hoc Networks

As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. However, mobile environments also need to consider handover issues. Furthermore, in a highly mobile environment, traditional reactive approaches to handover are inadequate and thus proactive techniques have been investigated. Recent research in proactive handover techniques defined two key parameters: Time Before Handover (TBH) and Network Dwell Time (NDT) for a mobile node in any given networking topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is possible to express contention for resources in terms of No Contention, Partial Contention, and Full Contention. This proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This paper therefore presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments.
Do Tax Law Changes Influence Ex-Dividend Stock Price Behavior? Evidence from 1926 to 2005

"We test the Elton and Gruber model of ex-dividend stock pricing over a period spanning all US tax law changes since 1926. Our results indicate that price drop ratios (ΔP/D) and ex-day returns are related to dividend and capital gains tax rates in the theorized manner. Consistent with tax clienteles, we also find that ex-day price movements of higher dividend yield stocks are driven more by corporate tax rates, while lower yield stocks are more influenced by personal rates. Finally, we demonstrate that the positive relationship between ΔP/D and the dividend yield becomes stronger as the tax differential | t d - t cg | widens. " Copyright (c) 2010 Financial Management Association International.