Miracle-dz/UniFAR-FTUs huggingface dataset:
Abnormal Shapes Identification of Gedong Mango Using Dimensionless Shape Factors in Image Processing

In addition to size, export quality requirements for gedong mango among others are clean surface, free of damaged mechanically or biologically, free from pests and diseases, and normal fruit shape. The abnormal fruit shape in mangoes is known as sitting mango, which is not easy to roll over when pushed because the fruit surface is flat on certain sides. Several dimensionless shape factors can be used to identify the shape of an object through image processing. Some shape factors that are often used to identify shapes of object in image processing include roundness, roundness ratio, sphericity, axial ratio, inequality degree of projected area and spherical disproportion. This study aims to identify the shape of the fruit using several dimensionless shape factors and determine the shape factors that can be used to distinguish normal and abnormal fruit shapes for gedong mangoes. The results showed that abnormal and normal mango gedong fruit shapes could be distinguished by image processing using the roundness, sphericity, and spherical disproportion form factors in certain deviant shapes but not for all samples.
Research on user granularity-level personalized social text generation technology

With the introduction of large-scale pre-trained language models, breakthroughs have been made in text generation technology research. On this basis, in order to assist users to complete personalized creation, this paper proposes a user-level fine-grained control generation model. First, we design the Encoder-Decoder framework based on the GPT2 structure, and model and encode the user’s static personalized information on the Encoder side. Then add a bidirectional independent attention module to receive the personalized feature vector on the Decoder side. The attention module in the original GPT2 structure captures the dynamic personalized features in the user text, namely writing style, expression way, etc. Next, the scores of each attention module are weighted and fused to participate in the subsequent decoding to automatically generate social texts constrained by the user’s personalized feature attributes. However, the semantic sparsity of the user’s basic information will cause occasional conflicts between the generated text and some personalized features. Therefore, we use the Alignment module to perform the secondary enhancement and generation of consistent understanding between the output data of the Decoder and the user’s personalized features, and finally realize the personalized social text generation. Experiments show that compared with the GPT2 baseline model, the fluency of the model is improved by 0.3%-0.6%, and on the basis of no loss of language fluency, the social text generated by the model can have significant user personalization characteristics, among which personalization and consistency the two evaluation indicators of sexuality both increased significantly by 8.4% and 9%.
Process Mining for IS Project Success Factors Management: A proposal

Research on Success Factors (SF) of Information Systems (IS) projects carried out over the last decades has resulted in a vast literature. However, extant studies typically aim to identify and list generic SF for projects, denoting a static perspective, with few concerns of practical nature regarding their use as management tools to support decisions throughout the projects’ lifecycle. On the other hand, process mining has been used to discover, analyze, and improve project management processes. In this paper, we propose a new approach that involves relating the performance of those processes with SF in IS projects. By using process mining, the aim is to automatically extract and manage SF in projects, measure processes performance, and provide project managers with information on how SF correlate with performance. This will provide managers with enhanced information regarding status and improvement opportunities for current and future projects. The main purpose is to contribute to the project management theory and practice by providing a decision support system that can associate performance with IS projects’ SF automatically obtained from internal and external data sources.
Investigating the Influence of Task Complexity and Outcome Variety on User Performance in Crowdsourcing Projects

: Nowadays many companies leverage crowdsourcing to solve problems in order to reduce cost. The quality of the solution submitted by the participant is especially important for the company, so how to improve participation performance has become an essential research topic. From the perspective of task design, this paper proposes a theoretical model based on the job characteristics model to explore how task complexity and outcome variety affect participation performance through influencing self-efficacy and task meaningfulness. We will collect data through an online experiment to validate our proposed research model in the context of a crowdsourced translation task. Participation performance will be measured with subjective questionnaire and objective translation grades. Findings of this research will have theoretical implications and provide practical guidelines for crowdsourcing projects
Quantum Communication Networks and Trust Management: A Survey

This paper summarizes the state of art in quantum communication networks and trust management in recent years. As in the classical networks, trust management is the premise and foundation of quantum secure communication and cannot simply be attributed to security issues, therefore the basic and importance of trust management in quantum communication networks should be taken more seriously. Compared with other theories and techniques in quantum communication, the trust of quantum communication and trust management model in quantum communication network environment is still in its initial stage. In this paper, the core technologies of establishing secure and reliable quantum communication networks are categorized and summarized, and the trends of each direction in trust management of quantum communication network are discussed in depth.
Replicate altitudinal clines reveal that evolutionary flexibility underlies adaptation to drought stress in annual <i><fc>M</fc>imulus guttatus</i>

Examining how morphology, life history and physiology vary along environmental clines can reveal functional insight into adaptations to climate and thus inform predictions about evolutionary responses to global change. Widespread species occurring over latitudinal and altitudinal gradients in seasonal water availability are excellent systems for investigating multivariate adaptation to drought stress. Under common garden conditions, we characterized variation in 27 traits for 52 annual populations ofMimulus guttatus sampled from 10 altitudinal transects. We also assessed variation in the critical photoperiod for flowering and surveyed neutral genetic markers to control for demography when analyzing clinal patterns. Many drought escape (e.g. flowering time) and drought avoidance (e.g. specific leaf area, succulence) traits exhibited geographic or climatic clines, which often remained significant after accounting for population structure. Critical photoperiod and flowering time in glasshouse conditions followed distinct clinal patterns, indicating different aspects of seasonal phenology confer adaptation to unique agents of selection. Although escape and avoidance traits were negatively correlated range-wide, populations from sites with short growing seasons produced both early flowering and dehydration avoidance phenotypes. Our results highlight how abundant genetic variation in the component traits that build multivariate adaptations to drought stress provides flexibility for intraspecific adaptation to diverse climates.
Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography Supplementary : Atomistic simulations

In the main manuscript, we demonstrate that the machine learning (ML) approach can successfully identify short-range-ordering (SRO) in an Fe-Al alloy with nominal Al concentration around 18%at. Applying this methodology to APT tips annealed at 873 K and 523 K, we have searched for both D03 and B2 SRO clusters. Experimentally, there we find no evidence for D03 clustering beyond that expected to happen by random chance (i.e. “statistical clustering”) at either temperature. For B2 , although the absolute number of clusters is small, we do see experimental evidence for such SRO at the lower annealing temperature of 523 K. Can these observations be replicated using atomistic simulations? Since such simulations are much less expensive than physical experiments, if simulations are found to agree with experiment at the two available temperatures, this would give us confidence to scan the entire interpolating temperature regime much more densely to look for trends and regions of transition. In the event that simulations do not match experiment, are there still lessons to be learned about the underlying mechanisms that drive SRO in this system? This problem can be attacked directly using coupled Monte Carlo / Molecular Dynamics (MCMD) calculations which allow a system of comparable size to the experimental domain to equilibrate chemically. Such calculations allow all factors contributing to the classical free energy – potential energy, vibrational entropy, and configurational entropy – to be directly
Hybrid Solution of Stochastic Optimal Control Problems Using Gauss Pseudospectral Method and Generalized Polynomial Chaos Algorithms

Abstract : Two numerical methods, Gauss Pseudospectral Method and Generalized Polynomial Chaos Algorithm, were combined to form a hybrid algorithm for solving nonlinear optimal control and optimal path planning problems with uncertain parameters. The algorithm was applied to two concept demonstration problems: a nonlinear optimal control problem with multiplicative uncertain elements and a mission planning problem sponsored by USSTRATCOM. The mission planning scenario was constructed to find the path that minimizes the probability of being killed by lethal threats whose locations are uncertain to statistically quantify the effects those uncertainties have on the flight path solution, and to use the statistical properties to estimate the probability that the vehicle will be killed during mission execution. The results demonstrated that the method is able to effectively characterize how the optimal solution changes with uncertainty and that the results can be presented in a form that can be used by mission planners and aircrews to assess risks associated with a mission profile.
Maladaptive Laterality in Cortical Networks Related to Social Communication in Autism Spectrum Disorder

Neuroimaging studies of individuals with autism spectrum disorders (ASDs) consistently find an aberrant pattern of reduced laterality in brain networks that support functions related to social communication and language. However, it is unclear how the underlying functional organization of these brain networks is altered in ASD individuals. We tested four models of reduced laterality in a social communication network in 70 ASD individuals (14 females) and a control group of the same number of tightly matched typically developing (TD) individuals (19 females) using high-quality resting-state fMRI data and a method of measuring patterns of functional laterality across the brain. We found that a functionally defined social communication network exhibited the typical pattern of left laterality in both groups, whereas there was a significant increase in within- relative to across-hemisphere connectivity of homotopic regions in the right hemisphere in ASD individuals. Furthermore, greater within- relative to across-hemisphere connectivity in the left hemisphere was positively correlated with a measure of verbal ability in both groups, whereas greater within- relative to across-hemisphere connectivity in the right hemisphere in ASD, but not TD, individuals was negatively correlated with the same verbal measure. Crucially, these differences in patterns of laterality were not found in two other functional networks and were specifically correlated to a measure of verbal ability but not metrics of other core components of the ASD phenotype. These results suggest that previous reports of reduced laterality in social communication regions in ASD is because of the two hemispheres functioning more independently than seen in TD individuals, with the atypical right-hemisphere network component being maladaptive. SIGNIFICANCE STATEMENT A consistent neuroimaging finding in individuals with ASD is an aberrant pattern of reduced laterality of the brain networks that support functions related to social communication and language. We tested four models of reduced laterality in a social communication network in ASD individuals and a TD control group using high-quality resting-state fMRI data. Our results suggest that reduced laterality of social communication regions in ASD may be because of the two hemispheres functioning more independently than seen in TD individuals, with atypically greater within- than across-hemisphere connectivity in the right hemisphere being maladaptive.
Study of the effects of progesterone thepy on the oestrogen-inced senitivity of rat utes

in Krebs solution containing half the normal concentration of Ca++, equilibrated with 5% carbon dioxide in oxygen and maintained at 350 C. In vivo experiments were carried out on cockerels anaesthetized with halothane and decerebrated; after an interval of 60-90 min contractions of the oesophagus to stimulation of the vagus and descending oesophageal nerves were recorded by a balloon-tambour system (Hassan, 1967). In both in vitro and in vivo experiments the nerves were stimulated with square wave pulses (width 10 msec, frequency 20 c/s and intensity SV) the duration of stimulation being 5-15 sec applied every 2-15 min. Exposure of the isolated oesophagus to hyoscine (1-100 ,ug/ml.) for 30 min abolished the contraction produced by stimulation of either nerve if the duration of stimulation was less than 5 sec; however, prolonged stimulation produced a delayed contraction which was not antagonized by hyoscine (100 jig/ml.) although cocaine (50 jig/ml.) abolished it (Bartlet & Hassan, 1968b). The hyoscine-resistant contraction was abolished by cutting the nerves, but mepyramine, methysergide or bretylium had no effect on it. Physostigmiine (5 ,ug/ml.) did not have a significant effect on the hyoscine-resistant contraction and physostigmine (50 jig/ml.) antagonized it (P<0.05). In six experiments tubocurarine (50 jig/ml.) reduced the height of the hyoscine-resistant contraction by a mean (± S.E. of mean) of 21 % ( ± 8, P<0.05) and hexamethonium (100 ,ug/ml.) reduced it by a mean of 59% (+ 14, n=3, P<0.05). In previous experiments with pentobarbitone-anaesthetized chickens, the contraction of the oesophagus in vivo produced by stimulation of the vagus and descending oesophageal nerves was abolished by intravenous hyoscine (Hassan, 1967). Decerebrate preparations have now been used to find out whether the pentobarbitone had blocked a hyoscineresistant response of the oesophagus to nerve stimulation. Hyoscine (100 ,ug/kg intravenously) abolished the contractions of the oesophagus produced by prolonged stimulation of the vagus and descending oesophageal nerves. The in vivo experiments suggest that the vagus and descending oesophageal nerves are cholinergic, but the in vitro experiments suggest that these nerves release acetylcholine which acts on receptors inaccessible to hyoscine added to the organ bath.
Stratification and thermodynamics in mean-field dynamos

We extend previous investigations of axisymmetric, incompressible mean-field dynamos to the compressible case with strong stratification. We take thermodynamic effects into account using the anelastic approximation and show that the effects of stratification, compressibility and thermodynamics on the rotation law are small when we compare our results with those previously obtained for incompressible models. For solar values of the Taylor number cylindrical contours of the angular velocity typically occur - even for strong stratification. The stagnation line of the meridional circulation is close to the bottom of the convection zone
in Yeast Mitochondria

radioactive peak was most readily obtained when Nonidet (NP 40) or BRIJ 58 was used to disrupt the mitochondria after pulse-labelling, but similar ribosome-like particles were also obtained by use of sodium deoxycholate or Triton X-100. Mitochondria disrupted in very low Mg2+ concentrations showed radioactivity to about 50 S. The results are entirely consistent with the assumption that animal mitochondria contain mitoribosomes sedimenting at less than 80 S. Experiments in which radioactive mitoribosomes were mixed with unlabelled E. coli ribosomes and sedimented in a sucrose density gradient containing IOmM-Mg2+ showed that the two peaks (radioactivity and extinction) were close together whereas E. coli ribosomes were readily separable under these conditions from rat liver cytoribosomes and Krebs-cell cytoribosomes. These results reinforce the suggestion that in protein synthesis mitochondria resemble bacteria much more closely than they do the eukaryotic cytoplasmic ribosomes.
Host control of plasmid replication: Requirement for the or factor ay32 in transcription of mini-F replication initiator gene

Replication of F factor or mini-F plasmid is strongly inhibited in the rpoH (htpR) mutants of Escherichia coli deficient in the a factor (0.32) known to be required for heat shock gene expression. Transcription of the mini-F repE gene encoding a replication initiator protein (E protein) was examined by operon fusion and by direct determination of repE mRNA. The synthesis rate and the level of repE mRNA were found to increase transiently upon temperature upshift (30°C to 42°C) in wild-type cells but to decrease rapidly in the rpoH mutants. Thus o.32 appeared to be directly involved in transcription of repE whose product, E protein, in turn activates DNA replication from the mini-F ori2 region. This scheme of host-controlled plasmid replication is further supported by the analysis of transcription in vitro: RNA synthesis can be initiated from the repE promoter by a minor form of RNA polymerase containing or32 but not by the major polymerase containing the normal cr factor a70. The '32-mediated transcription from the repE promoter is strongly inhibited by the E protein. We conclude that transcription of the mini-F repE gene is mediated by the host transcription factor or32 and is negatively controlled by its own product. The
The ALPINE-ALMA [CII] survey

We present ALMA observations of a merging system atz ∼ 4.57, observed as a part of the ALMA Large Program to INvestigate [CII] at Early times (ALPINE) survey. Combining ALMA [CII]158 μm and far-infrared continuum data with multi-wavelength ancillary data, we find that the system is composed of two massive (M⋆ ≳ 1010 M⊙) star-forming galaxies experiencing a major merger (stellar mass ratiormass ≳ 0.9) at close spatial (∼13 kpc; projected) and velocity (Δv < 300 km s−1) separations, and two additional faint narrow [CII]-emitting satellites. The overall system belongs to a larger scale protocluster environment and is coincident to one of its overdensity peaks. Additionally, ALMA reveals the presence of [CII] emission arising from a circumgalactic gas structure, extending up to a diameter-scale of ∼30 kpc. Our morpho-spectral decomposition analysis shows that about 50% of the total flux resides between the individual galaxy components, in a metal-enriched gaseous envelope characterised by a disturbed morphology and complex kinematics. Similarly to observations of shock-excited [CII] emitted from tidal tails in local groups, our results can be interpreted as a possible signature of interstellar gas stripped by strong gravitational interactions, with a possible contribution from material ejected by galactic outflows and emission triggered by star formation in small faint satellites. Our findings suggest that mergers could be an efficient mechanism of gas mixing in the circumgalactic medium around high-zgalaxies, and thus play a key role in the galaxy baryon cycle at early epochs.
FGNET-RH: Fine-Grained Named Entity Typing via Refinement in Hyperbolic Space

Fine-Grained Named Entity Typing (FG-NET) aims at classifying the entity mentions into a wide range of entity types (usually hundreds) depending upon the context. While distant supervision is the most common way to acquire supervised training data, it brings in label noise, as it assigns type labels to the entity mentions irrespective of mentions’ context. In attempts to deal with the label noise, leading research on the FG-NET assumes that the fine-grained entity typing data possesses a euclidean nature, which restraints the ability of the existing models in combating the label noise. Given the fact that the fine-grained type hierarchy exhibits a hierarchical structure, it makes hyperbolic space a natural choice to model the FG-NET data. In this research, we propose FGNET-RH, a novel framework that benefits from the hyperbolic geometry in combination with the graph structures to perform entity typing in a performance-enhanced fashion. FGNET-RH initially uses LSTM networks to encode the mention in relation with its context, later it forms a graph to distill/refine the mention’s encodings in the hyperbolic space. Finally, the refined mention encoding is used for entity typing. Experimentation using different benchmark datasets shows that FGNET-RH improves the performance on FG-NET by up to 3.5% in terms of strict accuracy.
Top-k Consistency of Learning to Rank Methods

This paper is concerned with the consistency analysis on listwise ranking methods. Among various ranking methods, the listwise methods have competitive performances on benchmark datasets and are regarded as one of the state-of-the-art approaches. Most listwise ranking methods manage to optimize ranking on the whole list (permutation) of objects, however, in practical applications such as information retrieval, correct ranking at the top k positions is much more important. This paper aims to analyze whether existing listwise ranking methods are statistically consistent in the top-k setting. For this purpose, we define a top-k ranking framework, where the true loss (and thus the risks) are defined on the basis of topk subgroup of permutations. This framework can include the permutation-level ranking framework proposed in previous work as a special case. Based on the new framework, we derive sufficient conditions for a listwise ranking method to be consistent with the top-k true loss, and show an effective way of modifying the surrogate loss functions in existing methods to satisfy these conditions. Experimental results show that after the modification, the methods can work significantly better than their original versions, indicating the correctness of our theoretical analysis.
Quantum Speedup of Natural Gradient for Variational Bayes

Variational Bayes (VB) is a critical method in machine learning and statistics, underpinning the recent success of Bayesian deep learning. The natural gradient is an essential component of eﬃcient VB estimation, but it is prohibitively computationally expensive in high dimensions. We propose a computationally eﬃcient regression-based method for natural gradient estimation, with convergence guarantees under standard assumptions. The method enables the use of quantum matrix inversion to further speed up VB. We demonstrate that the problem setup fulﬁlls the conditions required for quantum matrix inversion to deliver computational eﬃciency. The method works with a broad range of statistical models and does not require special-purpose or simpliﬁed variational distributions.