Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of high temperature during pre- and post-anthesis stages of floral development on fruit-set and pollen germination in peanut

Peanut ( Arachis hypogaea L.) crops are often exposed to day temperatures > 35°C for short periods during flowering, resulting in lower yields. Research was conducted to study and quantify the effects of short episodes (1-6 d) of high temperatures during the pre- and post-anthesis stages of floral development on fruit-set, pollen viability, germination and tube growth. Plants of peanut cv. ICGV-86015 were grown in controlled environments at 28/22°C (day/night). High daytime air temperature treatments ranging from 28 (control) to 48°C were imposed at different times between 6 d before anthesis (DBA) and 6 d after anthesis (DAA) for 1, 3 or 6 d. Floral buds or flowers were tagged at different stages to determine fruit-set. Exposure to bud (tissue) temperature ≥ 39°C for 1 d significantly reduced fruit-set compared to the control at 28°C, and the magnitude of the reduction varied with stage of floral development. Floral buds were most sensitive to high temperature at 4 DBA and at anthesis, coinciding with micro-sporogenesis and pollination or fertilisation, respectively. The critical bud temperature at these stages was 33°C, above which fruit-set was reduced by 6% °C -1 . Lower fruit-set due to high temperatures at pre-anthesis and anthesis stages were due to pollen sterility and retarded pollen tube growth, respectively.
Marketing Universals: Consumers’ Use of Brand Name, Price, Physical Appearance, and Retailer Reputation as Signals of Product Quality

Marketing universals are defined as consumer behaviors within a segment and toward a particular product category that are invariant across cultures. Using several definitions of culture and three different criteria for universality, the authors evaluate whether the use of brand, price, retailer reputation, and physical product appearance as signals of quality are marketing universals for consumer electronics products. Using a sample representing 38 nationalities, they find that there are few differences in the use of quality signals across cultures for a high priority segment of consumers. They draw conclusions for the adaptation versus standardization debate and argue that certain behaviors are likely to be universal, whereas others are not. Understanding such differences is essential to designing international marketing strategies.
Effects of Anaerobic Preculture on Aerobic Stress Responses of Campylobacter jejuni

Survival responses to aerobic stress in the Campylobacterjejuni are highly influenced by preculturing conditions in either microaerobic or anaerobic environments before the stress is induced. In anaerobically precultured cells, culturability was maintained longer than that in microaerobically precultured cells under aerobic conditions, without significant concomitant damage to cellular components by aerobic stress, although the culturability finally fell below the level of detection. These results suggest a possibility that the survival of C. jejuni in natural aerobic environments is highly influenced by the environmental conditions, such as varied oxygen partial pressure, where the bacterium has resided.
Exploring visual dysphemisms in pieces of news related to immigrant minors in a Spanish newspaper

This article describes the main visual characteristics used in different multimodal pieces of news related to immigrant minors in the newspaper El País, which is one of the most important newspapers in Spain. The corpus of examples consists of all the pieces of news dealing with immigrant children published from 1 January 2011 to 31 December 2011. For the framework of analysis, the study draws on visual grammar and critical discourse analysis. The study reveals that immigrant minors are represented dysphemistically in the multimodal texts analysed so that the most pejorative side of their reality is portrayed. The author thus aims to provide a visual analysis of the way in which immigrant minors are represented visually in a serious Spanish newspaper. In doing so, she aims to show visual ways of manipulation and reinforcing of stereotypes related to immigrants, in general, and immigrant minors in particular.
Connecting perebor conjectures: search to decision reduction for formulas

A longstanding open question is whether there is an equivalence between the computational task of determining the minimum size of any circuit computing a given function and the task of producing a minimum-sized circuit for a given function. While it is widely conjectured that both tasks require "perebor," or brute-force search, researchers have not yet ruled out the possibility that the search problem requires exponential time but the decision problem has a linear time algorithm. In this paper, we make progress in connecting the search and decision complexity of minimizing formulas. Let MFSP denote the problem that takes as input the truth table of a Boolean function f and an integer size parameter s and decides whether there is a formula for f of size at most s. Let Search-MFSP denote the corresponding search problem where one has to output some optimal formula for computing f. Our main result is that given an oracle to MFSP, one can solve Search-MFSP in time polynomial in the length N of the truth table of f and the number t of "near-optimal" formulas for f, in particular O(N6t2)-time. While the quantity t is not well understood, we use this result (and some extensions) to prove that given an oracle to MFSP: • there is a deterministic [MATH HERE]-time oracle algorithm for solving Search-MFSP on all but a o(1)-fraction of instances, and • there is a randomized O(2.67N)-time oracle algorithm for solving Search-MFSP on all instances. Intriguingly, the main idea behind our algorithms is in some sense a "reverse application" of the gate elimination technique.
ActiveLink: Deep Active Learning for Link Prediction in Knowledge Graphs

Neural networks have recently been shown to be highly effective at predicting links for constructing knowledge graphs. Existing research has mainly focused on designing 1) deep neural network models that are expressive in capturing fine-grained semantics, e.g., NTN and ConvE, but that are however less scalable; or 2) shallow models that are scalable, e.g., TransE and DistMult, yet limited in capturing expressive semantic features. In this work, we demonstrate that we can get the best of both worlds while drastically reducing the amount of data needed to train a deep network by leveraging active learning. We present a novel deep active learning framework, ActiveLink, which can be applied to actively train any neural link predictor. Inspired by recent advances in Bayesian deep learning, ActiveLink takes a Bayesian view on neural link predictors, thereby enabling uncertainty sampling for deep active learning. ActiveLink extends uncertainty sampling by exploiting the underlying structure of the knowledge graph, i.e., links between entities, to improve sampling effectiveness. To accelerate model training, ActiveLink further adopts an incremental training method that allows deep neural networks to be incrementally trained while optimizing their generalizability at each iteration. Extensive validation on real-world datasets shows that ActiveLink is able to match state-of-the-art approaches while requiring only 20% of the original training data.
Antioxidant potential of various parts of Ferula assafoetida L.

Ferula assafoetida Linn, (Apiaceae) is used in herbal medicine globally for cure and prevention of many diseases. Current research has been carried out to investigate antioxidant potential of this plant. Results indicated that sufficient amount of total phenolic contents and total flavonoid contents are present in its leaves, flowers and seeds. Some top-benched bioassays like 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) free radical scavenging activity, hydroxyl radical scavenging activity, nitric oxide scavenging activity and superoxide radical scavenging activity confirmed the radical scavenging and antioxidant potential of this plant. Since F. assafoetida hold immense therapeutic potential besides food uses, its usage in dietary supplementation can be exploited largely as a functional food. Key words: Ferula assafoetida, total phenolic contents, antioxidant potential, Pakistan.
How Does Enforcement Deter Gray Market Incidence?

Gray market activity has become increasingly prevalent. The prevailing wisdom in marketing is to use more severe enforcement to deter gray marketing. However, the certainty and speed of enforcement may also have a bearing on the incidence of violations. This article examines whether and how enforcement deters gray marketing. The results from a field survey of manufacturers and an experimental design suggest that, by itself, enforcement severity has no impact. Deterrence results only when the multiple facets of enforcement are used in combination.
Perspective-2-Ellipsoid: Bridging the Gap Between Object Detections and 6-DoF Camera Pose

Recent years have seen the emergence of very effective ConvNet-based object detectors that have reconfigured the computer vision landscape. As a consequence, new approaches that propose object-based reasoning to solve traditional problems, such as camera pose estimation, have appeared. In particular, these methods have shown that modelling 3D objects by ellipsoids and 2D detections by ellipses offers a convenient manner to link 2D and 3D data. Following that promising direction, we propose here a novel object-based pose estimation algorithm that does not require any sensor but a RGB camera. Our method operates from at least two object detections, and is based on a new paradigm that enables to decrease the Degrees of Freedom (DoF) of the pose estimation problem from six to three, while two simplifying yet realistic assumptions reduce the remaining DoF to only one. Exhaustive search is performed over the unique unknown parameter to recover the full camera pose. Robust algorithms designed to deal with any number of objects as well as a refinement step are introduced. Effectiveness of the method has been assessed on the challenging T-LESS and Freiburg datasets.
A Hybrid Automatic Elasticity Solution for the IaaS Layer based on Dynamic Thresholds and Time Series

Currently, the most popular auto-elastic solutions at cloud computing providers are rule-based solutions with fixed thresholds. However, these solutions struggle with two main pain key points: reactive nature and hard configuration issues. In this paper, we propose a hybrid auto-scaling approach that overcomes the deficiencies of the solutions based on rules with fixed thresholds. The proposed auto-scaling consists is a hybrid approach, consisting of a set of self-adaptive predictions and reactive component-based dynamic thresholds.
Molecular mapping of quantitative trait loci (QTLs) determining resistance to Sugarcane mosaic virus in maize using simple sequence repeat (SSR) markers

Molecular marker technology was used to map quantitative trait loci (QTLs) associated with resistance to Sugarcane mosaic virus (SCMV). This disease is spread worldwide and can cause devastating yield losses in susceptible maize cultivars. The aim of this study was to estimate genetic determination of resistance to SCMV in a maize population consisting of 120 F3 lines from a cross between maize inbred lines TR56 (susceptible) and TR42 (resistant). This population was evaluated for SCMV resistance in replicated greenhouse trials under artificial inoculation. The method of composite interval mapping (CIM) was employed for QTL analysis. Two genes were mapped on chromosome 6 using simple sequence repeat (SSR) and bulked segregant analyses (BSA), and a gene on chromosome 3 was found to be not significant. The resistance gene Scm1a on chromosome 6 (bin 6.00/6.01) was flanked by microsatellite markers bnlg1043 and phi126 with genetic distances of 1.0 and 0.6 cM, respectively whereas the genetic distances between two flanking markers bnlg1371 and bnlg1600 and the resistance gene Scm1b were 1.0 and 1.1 cM, respectively. Other SSRs from chromosomes 1, 5 and 10 detected no QTL using single marker analysis.
The Design of Hand Gestures for Selecting Virtual Objects

ABSTRACT Providing input for the selection of objects in virtual, augmented, and mixed-mode reality can be done with hand-held controllers or hand gestures depending on the complexity and precision required. Free hand gestures have the advantages of eliminating the need for a controller, not needing to see the controls on the controller, and potentially being less fatiguing. However, the designs of hand gestures for object selection have not been thoroughly evaluated for usability and performance. Eighteen participants evaluated four different ray-casting hand gestures (index thrust, index click, palm thrust, and palm click) and three snapback thresholds while selecting 2D targets of different sizes. Dependent variables were mean time to select targets, number of selections not completed, number of incorrect targets selected, and subjective preference. The index thrust and index click gestures were preferred by subjects and had faster mean selection times and lower number of incorrect target selections. There were no significant differences between snapback thresholds on productivity, error, or preference. Overall, the index thrust and index click gestures were associated with greater user confidence, particularly with smaller targets.
Development of an Unmanned Dry Ice Decontamination System for Ultra-High Voltage Environments

To solve the problems of difficulty cleaning for “blind spots” in power equipment operation and maintenance inspections, the dry ice decontamination UAV system is designed. The proposed system is divided into the hardware and software parts. The system hardware is designed in three main parts, which are the remote control system for the ground station platform, the adaptive system for the UAV-mounted platform, and the decontamination control system. The system software mainly consists of four main parts: The first is dry ice crusher control thread, and the second is solenoid valve opening and closing thread. The third part is vibration motor running down thread, and the fourth is thread running with the rudder. After that, the accuracy and practicality of the UAS to achieve live dry ice decontamination of UHV insulators was verified through several tests, which illustrated the feasibility of live dry ice decontamination by UAV operation.
Impact of Users’ Socio-Cultural and Religious Orientation on Government Resource Planning (GRP) Systems Usage in Saudi Arabia

This study investigates the impact of users’ socio-cultural orientation and religious values on government resource planning systems in the Kingdom of Saudi Arabia. Although many studies have been conducted on the adoption of technology in developed nations, only a few analyses have focused on the Middle Eastern region. This research fills that gap. The study developed an integrated conceptual research model based on existing technology acceptance theories, namely theory of reasoned action, technology acceptance model, unified theory of acceptance and use of technology and Hofstede’s cultural dimensions theory. An online survey questionnaire was sent to 1677 employees at the Ministry of Foreign Affairs in Saudi Arabia and a total of 377 completed questionnaires were received of which 340 were considered usable, making a response rate of 22.48%. Data was analyzed using multivariate statistical analysis. The analysis finds there is a relationship between the socio-cultural and religious constructs with reference to attitude about using government resource planning systems. Results reveal that 55% of the variance (R2 = 0.557) of employees’ attitude to the GRP application can be explained by the effect of socio-cultural and religious variables. Findings show that cultural values (t (340) = 3.862, p< 0.000), social network (t (340) = 4.095, p< 0.000), peers’ influence (t (340) = 4.515, p< 0.000) and religious values (t (340) = 5.062, p< 0.000) are significant predictors of GRP acceptance. Furthermore, the analysis shows demographic factors moderate between the determinants and users’ perceptions. These findings have important implications for the acceptance and implementation of GRP systems in Saudi Arabia.
Prediction of Cardiovascular Complications in Diabetes from Pharmacy Administrative Claims

Diabetes is a chronic disease characterised by high blood glucose levels, resulting in reduced life expectancy and requiring lifelong treatment. Because of their frequent necessity to seek healthcare services, diabetic patients generate huge volumes of administrative claims, detailing their healthcare encounters and prescription history. In the Veneto region (NE Italy), as in the rest of the country, these data are collected systematically and cover all eligible beneficiaries (~5 million in Veneto). Since cardiovascular complications are the main drivers of excess mortality in diabetes, forecasting their onset is desirable for patients’ care and policymaking. Hence, in the present work, we investigate the possibility of predicting 3-year cardiovascular outcomes following a 1-year baseline period of pharmacy data collection. We implement an approach based on recurrent neural networks that combines the chronologically-ordered sequence of prescriptions filled by a diabetic patient and basic biographical information (age, gender, estimated diabetes duration) to determine whether he or she will experience a 4P-MACE (4-point major adverse cardiovascular event; defined as death, myocardial infarction, stroke, or heart failure) endpoint. We develop our model with the data of 97,466 known diabetic patients identified using a validated claims-based algorithm. Independent performance tests on 4,873 subjects yield an area under the receiver-operating characteristic curve of 0.791 and a concordance index of 0.765 for the 4P-MACE primary outcome. We find death to be the easiest 4P-MACE component to predict (AUROC = 0.846), followed by heart failure (0.796), stroke (0.714), and, finally, myocardial infarction (0.708). Secondary, stratified experiments highlight independence of performance from gender, age, and number of prescriptions filled in a year with respect to the primary outcome. To the best of our knowledge, this is the first large-scale prediction model of cardiovascular complications in medication-treated diabetes solely based on sequences of filled prescriptions collected from administrative claims.
A Method for Improvement the Parameter Estimation of Non-linear Regression in Growth Model to Predict Project Cost at Completion

In this paper, we propose a comparison between existing parameter estimation methods of a nonlinear regression-based growth model to forecast project duration as well as its cost at completion. To analyze and perform some experiments, we used the Gompertz growth model and the dataset comes from a number of similar previous studies. Two other nonlinear models were also applied to compare the results with the Gompertz model in terms of fitness-function score. The performance of the proposed methods is also the key for further studies in fitting the S- curve and predicting the Estimate-to-Complete and the Estimate-at-Completion of certain projects.
Carbon­yl(8-hydroxy­quinolinato)[tris­(2,4-di-tert-butyl­phen­yl)phosphite]rhodium(I) acetone hemisolvate

Mol­ecules of the title compound, [Rh(C9H6NO){(C14H21O)3P}(CO)]·0.5(CH3)2CO, where (C9H6NO) = 8-hydroxy­quinolinato and {(C14H21O)3P} = tris­(2,4-di-tert-butyl­phen­yl)phosphite, pack in a tail-to-tail fashion with an inter­molecular quinoline ligand-to-ligand π-stacking distance of 3.312 (1) A. The effective cone angle (ΘE) for the phosphite ligand is 192°. The bidentate oxine ligand has a bite angle of 81.00 (8)° and the Rh—P bond length is 2.1819 (6) A.
Online Photometric Calibration of Optical Flow Visual-Inertial SLAM System

Recently, optical flow method is widely used in visual simultaneous localization and mapping (VSLAM). Based on the two assumptions of gray invariant hypothesis and spatial consistency in optical flow method, but the first assumption for auto-exposure videos cannot be established, because the camera will automatically adjust the exposure parameters to make the overall image brighter and darker. The variation of illumination can greatly affect the accuracy and robustness of VSLAM. To solve the light-sensitivity problem of visual-inertial SLAM (VI_SLAM) based on sparse optical flow method, a real-time photometric calibration algorithm was proposed. Adaptive compensation KLT is used to replace the traditional KLT optical flow tracking, and the response function of the camera, irradiance attenuation factor and exposure time are jointly optimized to correct the image brightness value, enhance the stability of front-end visual tracking, and improve the accuracy of sliding window optimization at the back-end. We tested the optimized system (VINS_photon) on large datasets and compared it with state-of-the-art SLAM. Experimental results show that the performance of VINS_photon has been evidently improved after the optimization of photometric parameters.
Buakea (Lepidoptera: Noctuidae), A New Genus of African Stem Borers: Morphological, Ecological and Molecular Data

A new genus of African stem borers of the subtribe Sesamiina (Lepidoptera: Noctuidae), Buakea gen. n. , is described as well as the three species it includes, two new, B. venusta sp. n. and B. kaeuae sp. n. , and a species that until now was placed in the genus Busseola Thurau, B. obliquifascia (Hampson) comb. n. The three species are monophagous on different graminaceous host plants, and the two sister species B. kaeaue and B. obliquifascia were collected in different ecological zones and altitudes, which suggests an ecological mode of speciation. Bayesian and maximum likelihood phylogenies inferred from two mitochondrial genes showed that the genus is monophyletic and does not share a recent common ancestor with the genus Busseola. However no strongly supported phylogenetic relationship could be established with the other six genera of the subtribe included in the analysis.
Study of Information Retrieval Method by Understanding User Situation from Computer Screen

Information workers involved in business operations such as data entry or help-desk support often have a hard time searching for information, especially when a situation is unfamiliar. In this paper, we propose a method that automatically retrieves text information shown on workers’ computer screens to analyze their situations and recommend helpful information to support their operations. We evaluated the effectiveness of our approach by using 96 situations (=computer screens) collected from help-desk tasks and 204 enterprise documents containing related business rules for those tasks. We evaluated the way of utilizing words in the situations to retrieve helpful information effectively. In our findings, necessary words to retrieve helpful information were not included in the words that appear frequently in the 96 situations but the words that only appear in certain situations. Moreover, when recommending a helpful page that contains fewer business rules, word selection becomes highly important. We also analyzed what kinds of situations and information quantity in documents changed the effectiveness of our approach.