Miracle-dz/UniFAR-FTUs huggingface dataset:
Convolutional Neural Networks for Image-Based Corn Kernel Detection and Counting

Precise in-season corn grain yield estimates enable farmers to make real-time accurate harvest and grain marketing decisions minimizing possible losses of profitability. A well developed corn ear can have up to 800 kernels, but manually counting the kernels on an ear of corn is labor-intensive, time consuming and prone to human error. From an algorithmic perspective, the detection of the kernels from a single corn ear image is challenging due to the large number of kernels at different angles and very small distance among the kernels. In this paper, we propose a kernel detection and counting method based on a sliding window approach. The proposed method detects and counts all corn kernels in a single corn ear image taken in uncontrolled lighting conditions. The sliding window approach uses a convolutional neural network (CNN) for kernel detection. Then, a non-maximum suppression (NMS) is applied to remove overlapping detections. Finally, windows that are classified as kernel are passed to another CNN regression model for finding the (x,y) coordinates of the center of kernel image patches. Our experiments indicate that the proposed method can successfully detect the corn kernels with a low detection error and is also able to detect kernels on a batch of corn ears positioned at different angles.
On Arrival Time Difference Between Lensed Gravitational Waves and Light

It is known that geometrical optics no longer applies to gravitational lensing if the wavelength of a propagating wave becomes comparable to or larger than the Schwarzschild radius of a lensing object. We investigate the propagation of gravitational waves in wave optics, particularly focusing on the difference between their arrival time and the arrival time of light. We argue that, contrary to the observation in the previous work, gravitational waves never arrive at an observer earlier than light when both gravitational waves and light are emitted from a same source simultaneously.
Robust quantum minimum finding with an application to hypothesis selection

We consider the problem of finding the minimum element in a list of length $N$ using a noisy comparator. The noise is modelled as follows: given two elements to compare, if the values of the elements differ by at least $\alpha$ by some metric defined on the elements, then the comparison will be made correctly; if the values of the elements are closer than $\alpha$, the outcome of the comparison is not subject to any guarantees. We demonstrate a quantum algorithm for noisy quantum minimum-finding that preserves the quadratic speedup of the noiseless case: our algorithm runs in time $\tilde O(\sqrt{N (1+\Delta)})$, where $\Delta$ is an upper-bound on the number of elements within the interval $\alpha$, and outputs a good approximation of the true minimum with high probability. Our noisy comparator model is motivated by the problem of hypothesis selection, where given a set of $N$ known candidate probability distributions and samples from an unknown target distribution, one seeks to output some candidate distribution $O(\varepsilon)$-close to the unknown target. Much work on the classical front has been devoted to speeding up the run time of classical hypothesis selection from $O(N^2)$ to $O(N)$, in part by using statistical primitives such as the Scheffe test. Assuming a quantum oracle generalization of the classical data access and applying our noisy quantum minimum-finding algorithm, we take this run time into the sublinear regime. The final expected run time is $\tilde O( \sqrt{N(1+\Delta)})$, with the same $O(\log N)$ sample complexity from the unknown distribution as the classical algorithm. We expect robust quantum minimum-finding to be a useful building block for algorithms in situations where the comparator (which may be another quantum or classical algorithm) is resolution-limited or subject to some uncertainty.
Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior

Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behavior as well as detecting and tracking them. This narrative review article is Part II of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychological models, from the perspective of an AV designer. This self-contained Part II covers the higher levels of this stack, consisting of models of pedestrian behavior, from prediction of individual pedestrians’ likely destinations and paths, to game-theoretic models of interactions between pedestrians and autonomous vehicles. This survey clearly shows that, although there are good models for optimal walking behavior, high-level psychological and social modelling of pedestrian behavior still remains an open research question that requires many conceptual issues to be clarified. Early work has been done on descriptive and qualitative models of behavior, but much work is still needed to translate them into quantitative algorithms for practical AV control.
Inclusive Cognitive Hierarchy

Abstract Cognitive hierarchy theory, a collection of structural models of non-equilibrium thinking, in which players’ best responses rely on heterogeneous beliefs on others’ strategies including naive behavior, proved powerful in explaining observations from a wide range of games. We propose an inclusive cognitive hierarchy model, in which players do not rule out the possibility of facing opponents at their own thinking level. Our theoretical results show that inclusiveness is crucial for asymptotic properties of deviations from equilibrium behavior in expansive games. We show that the limiting behaviors are categorized in three distinct types: naive, Savage rational with inconsistent beliefs, and sophisticated. We test the model in a laboratory experiment of collective decision-making. The data suggests that inclusiveness is indispensable with regard to explanatory power of the models of hierarchical thinking.
The effect of explicit correctivefeedback on phonological intelligibility

The effect of explicit instruction on pronunciation has been a scarcely studied area in the field of Second Language teaching. Thus, whether to correct errors or not to correct errors was strictly based on the intuitive notions of facilitators due to the lack of researchand guidance on error correction. During the 19 th century, L2 researchers began to study the impact of Corrective Feedback on pronunciation and discovered a discernible effect of explicit instruction on pronunciationon the basis of „Uptake‟ (Moley, 1994; Light& Spada, 1999; Kazuya, 2013& Baker, 2016). Uptake, as defined by Lyster &Ranta (1997), is „‟a student‟s utterance that immediately follows a teacher‟s feedback and that constitutes a reaction in some way to the teacher‟s intention to draw attention (.)”. However, whether immediate uptake is an indicator of acquisition has stirred doubts in the field of L2 research. This study is thereby conducted in view of bridging an existing research gap by examining the sustained effect of explicit instruction on improving phonological „‟Intelligibility‟‟. A sample of six students was polarized into two groups: the feedback group and the control group. The fivefold framework for teaching pronunciation communicatively proposed by Celce-Murcia, Brinton, & Goodwin (1996)was used to provide CF.Thefeedback group was exposed toexplicit feedback while they were engaging in ten predetermined tasks over a period of one week.The control group was deprived of output production and explicit feedback. Data gathered from the post and the delayed posttests were analyzed. The findings exhibit that phonological instruction has a positive effectoncontrolled speech, however, in order to internalize and produce the target from accurately at discourse level continuous practice followed by explicit feedback is recommended.
SUSTAINABILITY STRATEGIES FOR SMALL TEA ENTERPRISES IN KENYA

This study presents findings on factors that influence sustainability of small tea enterprises in Kenya. Specifically, the study sought to assess the influence of enterprise characteristics on sustainability of small tea enterprises, analyze the influence of the way of doing business on sustainability of the enterprises, explore the relationship between finance and sustainability, examine the relationship between resources and sustainability and analyzed how independent variables (enterprise characteristics, way of doing business, finance, resources, product and services) influence the dependent variable (sustainability) on small tea enterprises in Kenya. The population of the study is an estimated 420,000 small tea entrepreneurs who are members of Kenya Tea Development Agency spread in the seven tea-growing regions in Kenya. The study was a cross-sectional survey, and descriptive in design, carried out in the seven tea-growing regions. The study used a mixed method, which involved both qualitative and quantitative data analysis. Self-administered questionnaires were used for primary data collection while journals, books and the Internet were used for secondary data collection. Factor analysis was used to measure the variability among the variables. For test statistics, p-value less than 5% was considered significant. Cronbach’s analysis was used to test the equality of means of all independent variables. A regression model was also developed to establish the strength of the relationship between the dependent variable and independent variables. Presentation of information was done using mean scores and percentages and standard deviation. The findings indicated that four out of five hypotheses of the study were supported. These findings, it is hoped, will bridge the gaps in literature, identify and articulate alternative models for assessing sustainability of small tea enterprises for adoption, and will be used in the academia, agribusiness and by policy makers to improve the tea sector in Kenya.
IDENTIFICATION OF GIFTED AND TALENTED LEARNERS WITH HEARING IMPARMENT IN INCLUSIVE EDUCATION PROGRAMMES IN KENYA

International and national policy documents support the provision of education for gifted and talented learners with hearing impairment in inclusive education programmes. The study investigated the identification of gifted and talented learners with hearing impairment in inclusive education programmes in Kenya. Qualitative and quantitative research utilizing concurrent triangulation study design focused on respondents’’ experiences on identification process of gifted and talented learners with hearing impairment in inclusive education programmes in Kenya. Interview, questionnaires, focus group discussion and observation checklists were used to collect data from purposely selected respondents which included 1 Principal 28 teachers and 208 learners of a technical institution in Kenya, 1 National Council for Persons with Disabilities officer, 3Educational Assessment and Research Center officers and 2 Quality Assurance and Standards officers in Siaya County, Kenya. The major findings of the study were that learners with hearing impairment volunteered themselves or were identified by their peers as gifted and talented, others were identified by their teachers when they were exposed to variety of activities in and outside the classrooms and workshops. There was also disconnect between Special Needs Education Policy and practice, and between various stakeholders. The conclusion drawn was that Kenya used informal identification tools such as self, peer, parent/caregiver or teachers nomination. Standardized identification tools could not be used in Kenya to identify gifted and talented learners with hearing impairment in inclusive education programme because they were culturally biased, which is against the principle of the United Nations Conventions on the Rights of the Child that Kenya ratified and has entrenched in its laws and policies. There is need for Kenya Institute of Curriculum Development to develop a standardized identification tool for gifted and talented learners with hearing impairment. International Journal of Arts and Entrepreneurship. Vol. 7 Issue 2 (2018) http://www.ijsse. org ISSN 2307-6305 Page | 86
Relationship Between Factors and Effects on Grapevine Phenomenon among Staffs in Public Higher Education Institutions

An effective communication is required by an organization in order to avoid any ambiguity of information disseminated. Any understanding or interpretation of information in a communication phenomenon can cause grapevine. When grapevine is out of control in universities, the parties involved will always find a way to manage ethically to enhance professionalism and quality of work. In addition, it shows more barriers in communication among elites because of their status in practising autocratic leadership which makes the situation worse because the lower classes are not given a chance to speak. As such, administrative and support staffs in Public Higher Education Institutions (PHEI) have no exception to feel stress and depress caused by the problems and conflicts that arise. The purpose of this study is to examine the relationship between factors and effects on grapevine phenomenon among staffs in PHEI. The method of collecting primary data using questionnaires which were distributed to 346 respondents in this study was based on a quantitative method which was survey. Respondents were chosen through purposive sampling from five faculties of public universities in Malaysia. Based on the results, the major factor that affect spread of the grapevine among staffs is due to incomplete information from formal sources while the major effect affects staff relationship, strained which can cause negative effect like dispersion.
List of Abbreviations : 29 AN : Anorexia nervosa 30 BN : Bulimia nervosa

46 Objective: No study has assessed the association between dietary pattern and incidence of eating 47 disorders. This study aimed to assess the association between the adherence to the Mediterranean 48 dietary pattern (MDP) and the incident risk of anorexia (AN) and bulimia nervosa (BN). 49 Research Methods & Procedures: We conducted a prospective cohort study on 11800 women 50 from the SUN Project. Participants were classified as having incident AN or BN if they were free of 51 AN or BN at baseline and reported a physician-made diagnosis of AN or BN during follow-up. 52 Nutritional status, lifestyle and behavioural variables were investigated and used as covariates. A 53 validated 136-item food frequency questionnaire and the Trichopoulou score were used to assess 54 adherence to MDP. 55 Results: After a median follow-up of 9.4 years, 100 new cases of AN and BN were identified. The 56 multivariate HR (95%CI) of AN and BN for the 2 upper categories of adherence to the MDP were 57 0.39 (0.20-0.75) and 0.32 (0.14-0.70) (Ptrend=0.021). Inverse dose-response relationships were found 58 for the consumption of cereals and olive oil and marginally for the polyunsaturated fatty acids 59 intake. To address reverse causation, multivariable linear regressions were run by means of a cross60 sectional approach between the adherence to the MDP and the risk of AN and BN at baseline. No 61 difference in adherence was found between participants with and without eating disorders. 62 Conclusion: Our results suggest a potential inverse association between MDP and the risk of AN 63 and BN. Additional longitudinal studies and trials are needed. 64
Mask Encoding for Single Shot Instance Segmentation

To date, instance segmentation is dominated by two-stage methods, as pioneered by Mask R-CNN. In contrast, one-stage alternatives cannot compete with Mask R-CNN in mask AP, mainly due to the difficulty of compactly representing masks, making the design of one-stage methods very challenging. In this work, we propose a simple single-shot instance segmentation framework, termed mask encoding based instance segmentation (MEInst). Instead of predicting the two-dimensional mask directly, MEInst distills it into a compact and fixed-dimensional representation vector, which allows the instance segmentation task to be incorporated into one-stage bounding-box detectors and results in a simple yet efficient instance segmentation framework. The proposed one-stage MEInst achieves 36.4% in mask AP with single-model (ResNeXt-101-FPN backbone) and single-scale testing on the MS-COCO benchmark. We show that the much simpler and flexible one-stage instance segmentation method, can also achieve competitive performance. This framework can be easily adapted for other instance-level recognition tasks. Code is available at: git.io/AdelaiDet
Trapped Gravitational Waves in Jackiw–Teitelboim Gravity

We discuss the possibility that gravitational fluctuations (“gravitational-waves”) are trapped in space by gravitational interactions in two dimensional Jackiw–Teitelboim gravity. In the standard geon (gravitational electromagnetic entity) approach, the effective energy is entirely deposited in a thin layer, the active region, that achieves spatial self-confinement and raises doubts about the geon’s stability. In this paper we relinquish the “active region” approach and obtain self-confinement of “gravitational waves” that are trapped by the vacuum geometry and can be stable against the backreaction due to metric fluctuations.
Zero-Assignment Constraint for Graph Matching With Outliers

Graph matching (GM), as a longstanding problem in computer vision and pattern recognition, still suffers from numerous cluttered outliers in practical applications. To address this issue, we present the zero-assignment constraint (ZAC) for approaching the graph matching problem in the presence of outliers. The underlying idea is to suppress the matchings of outliers by assigning zero-valued vectors to the potential outliers in the obtained optimal correspondence matrix. We provide elaborate theoretical analysis to the problem, i.e., GM with ZAC, and figure out that the GM problem with and without outliers are intrinsically different, which enables us to put forward a sufficient condition to construct valid and reasonable objective function. Consequently, we design an efficient outlier-robust algorithm to significantly reduce the incorrect or redundant matchings caused by numerous outliers. Extensive experiments demonstrate that our method can achieve the state-of-the-art performance in terms of accuracy and efficiency, especially in the presence of numerous outliers.
Transformational versus servant leadership: their role on employee eudaimonic well-being

The increasing mental health crisis has seen organisations work to help promote and foster the mental well-being of their employees. Leadership is one of the most utilised tools in this pursuit. The current study aims to explore the role of transformational and servant leadership on employee eudaimonic well-being, a relatively unexplored element of mental health. In addition it aims to explore the link between leader eudaimonic well-being and employee eudaimonic well-being. An online self-report questionnaire was distributed to 266 employees within a scientific research organisation. The results revealed that both transformational and servant leadership were significantly positively associated with employee eudaimonic wellbeing. However, transformational and servant leadership were highly correlated, limiting the scope of the analysis and suggesting that transformational leadership is a stronger predictor of employee eudaimonic well-being. It was further found that leader eudaimonic well-being was not significantly associated with employee eudaimonic well-being. These results have both theoretical and practical implications for understanding the most effective way to promote employee well-being. Future research should aim to expand the current analyses to determine the potential influence of organisational contextual factors, as well as further analysing the underlying mechanisms linking transformational and servant leadership to employee eudaimonic well-being.
Mapping Emotions to Expressions

This review provides an overview of the research on nonverbal expressions of positive emotions, organised into emotion families, that is, clusters sharing common characteristics. Epistemological positive emotions (amusement, relief, awe, and interest) are found to have distinct, recognisable displays via vocal or facial cues, while the agency-approach positive emotions (elation and pride) appear to be associated with recognisable visual, but not auditory, cues. Evidence is less strong for the prosocial emotions (love, compassion, gratitude, and admiration) in any modality other than touch, and there is little support for distinct recognisable signals of the savouring positive emotions (contentment, sensory pleasure, and desire). In closing, some limitations of extant work are noted and some proposals for future research are outlined.
Exploring the Italian equine gene pool via high-throughput genotyping

Introduction: The Italian peninsula is in the center of the Mediterranean area, and historically it has been a hub for numerous human populations, cultures, and also animal species that enriched the hosted biodiversity. Horses are no exception to this phenomenon, with the peculiarity that the gene pool has been impacted by warfare and subsequent “colonization”. In this study, using a comprehensive dataset for almost the entire Italian equine population, in addition to the most influential cosmopolitan breeds, we describe the current status of the modern Italian gene pool. Materials and Methods: The Italian dataset comprised 1,308 individuals and 22 breeds genotyped at a 70 k density that was merged with publicly available data to facilitate comparison with the global equine diversity. After quality control and supervised subsampling to ensure consistency among breeds, the merged dataset with the global equine diversity contained data for 1,333 individuals from 54 populations. Multidimensional scaling, admixture, gene flow, and effective population size were analyzed. Results and Discussion: The results show that some of the native Italian breeds preserve distinct gene pools, potentially because of adaptation to the different geographical contexts of the peninsula. Nevertheless, the comparison with international breeds highlights the presence of strong gene flow from renowned breeds into several Italian breeds, probably due to historical introgression. Coldblood breeds with stronger genetic identity were indeed well differentiated from warmblood breeds, which are highly admixed. Other breeds showed further peculiarities due to their breeding history. Finally, we observed some breeds that exist more on cultural, traditional, and geographical point of view than due to actual genetic distinctiveness.