Miracle-dz/UniFAR-FTUs huggingface dataset:
A Preliminary Study on Germinated Oil Palm Seeds Quality Classiﬁcation with Convolutional Neural Networks

Malaysia and Indonesia produce 85% of palm oil in the world [8]. In Malaysia, the yearly requirement of oil palm planting materials is conservatively estimated to be 50 million [12]. To dispatch high quality seeds, traditional oil palm seed production is laborious and prone to human error. Recently, techniques that extract phenotypic traits of seeds from images automatically are gaining great interest in the seed industry as an alternative method for seed quality assessment [4], among which only a few are reported for germinated seeds [2, 10]. Whilst both detecting and classifying individual seeds are challenging, we focus on the latter in the present study by arranging and capturing germinated oil palm seed images such that the individual seeds can be easily detected. The conventional seed phenotyping platforms extract traits such as colour, morphological (e.g. area, perimeter, extend, and solidity), and textural (e.g. contrast, correlation, energy, and homogeneity) features from the segmented seed images for phenotypic analyses [1, 5]. Those traits are based on quantified manual criteria and are restrictive due to human bias. On the other hand, the use of state-of-the-art Convolutional Neural Networks (CNNs) has demonstrated superior performance over traditional methods in classifying Crambe seed quality based on X-ray images [3] and differentiating corn species [5]. The advantage of using CNNs is to let a model to learn the features that are discriminant for a classification task but with large amount of labelled data [13]. One of the main criterion for manual quality inspection of germinated oil palm seeds is to examine the sprouts, however, with no published quantified measures. It thus motivates us to explore the ways to combine non-quantified human domain knowledge with CNN to classify the quality of a germinated oil palm seed. Germinated Oil Palm Seed Dataset We collected three batches of germinated oil palm seeds, each consisting of 215, 90, and 120 images with 10-11 seeds per image. Both batch-1 and batch-3 were collected using a Sanoto MK40 Figure 1. Sample images of dataset batch-1 good (1st row), bad (2nd row), batch-2 (3rd row), and batch-3 (4th row). Red and green bounding boxes are annotations for good and bad seeds respectively. The images are manually cropped for tighter view.
A G RAPHICAL M ODEL P ERSPECTIVE ON F EDERATED L EARNING

Federated learning describes the distributed training of models across multiple clients while keeping the data private on-device. In this work, we formalize the server-orchestrated federated learning process as a hierarchical latent variable model where the server provides the parameters of a prior distribution over the client-specific model parameters. We then show that with simple Gaussian priors and a hard version of the well known Expectation-Maximization (EM) algorithm, learning in such a model corresponds to FedAvg, the most popular algorithm for this federated learning setting. This perspective on federated learning unifies several recent works in the field and opens up the possibility for extensions through different choices in the hierarchical model. Based on this view, we further propose a variant of the hierarchical model that employs prior distributions to promote sparsity. By using the hard-EM algorithm for learning, we obtain FedSparse, a procedure that can learn sparse neural networks in the federated learning setting. FedSparse reduces communication costs from client to server and vice-versa, as well as the computational costs for inference with the sparsified network – both of which are of great practical importance in federated learning.
WIKIBIAS: Detecting Multi-Span Subjective Biases in Language

Biases continue to be prevalent in modern text and media, especially subjective bias – a special type of bias that introduces improper atti-tudes or presents a statement with the presupposition of truth. To tackle the problem of detecting and further mitigating subjective bias, we introduce a manually annotated parallel corpus W IKI B IAS with more than 4,000 sentence pairs from Wikipedia edits. This corpus contains annotations towards both sentence-level bias types and token-level biased segments. We present systematic analyses of our dataset and results achieved by a set of state-of-the-art baselines in terms of three tasks: bias classiﬁcation, tagging biased segments, and neutralizing biased text. We ﬁnd that current models still struggle with detecting multi-span biases despite their reasonable performances, suggesting that our dataset can serve as a useful research benchmark. We also demonstrate that models trained on our dataset can generalize well to multiple domains such as news and political speeches. 1
Metabolism of pesticides by human Cytocrome P450 (CYPs)

As far the today's scenario, organophosphate pesticides (OPs) are widely used pesticides around the world. These are metabolized by cytochrome P450 enzymes by various reactions and pathways. Humans are inexorably exposed to pesticides in a variety of ways. Metabolism is one amongst factors that can affect the overall toxic profile of a pesticide. During metabolism, the pesticide is biotransformed by phase I cytochrome enzyme and then conjugated to more soluble and excretable by phase II. A metabolic enzyme plays a key role in converting the chemicals into inert derivatives which could be easily eliminated from the body. Chronic exposure to low levels of pesticide can cause mutations. As a susceptibility biomarker, the CYP genetic polymorphism can affect the activation and inactivation of pesticide metabolizing genes. In this research work, a metabolism and interactions of pesticides have been investigated by using cytochrome P450 (CYP) technique. Also, a Genotoxicological studies have been carried out in order to get an overall picture of genotoxic exposure. The overall analysis concluded that Genotyping of CYP polymorphisms provides important genetic information that plays role in modulating pesticide metabolism which helps to recognize the effects of pesticides on the human body. Index Terms Organophosphate pesticides, Pesticide metabolism, Cytochrome P450 enzymes, Gene polymorphism.
REIFICATION OF FARMER CONCEPTS IN NSSO SURVEY

This paper shows that auto-critical “review” of definitions by the National Sample Survey Office (NSSO), as revised by formal abstract changes in concepts, devoid of substance, may not be a driving force of practical change in the farmers’ condition or even their understanding. Review process of the NSSO lost sight of the ground reality of Indian agriculture even as NSSO unwittingly acknowledged in general terms “changed scenario of agriculture in the country”. Abstractly revised unrealistic concepts and definitions, have affected the efficacy of the findings of Situation Assessment Survey to truly “capture the condition of agricultural households”. Nevertheless “findings” of the NSSO have sustained so far as they negated formal “concepts” and their underlying criteria. Farmer and farmer-household appear hard pressed, to make conceptual “exit” and “move-out” from traditional farming. Findings of this paper show that subsistence-farming-based farmer-households negate the idea and concept, projected on them, to change into calculative-capitalist Agricultural Production Units (APUs). It turns out that dialectical conflict and tug of war exists between the family-food-security/consumption-centered “farmer-households” versus market-oriented economic-capitalist “APUs”. The contradiction is likely to continue until human essence of real farmer/farmer-household is restored in place of “reified farmer”. Index Terms – farmer, agricultural household, APU, Situation Assessment Survey, NSSO, reification, concept
Generating Connected Synthetic Electronic Health Records and Social Media Data for Modeling and Simulation

Researchers are using big data sets, specifically large sets of electronic health records (EHR) and social media data, for experiments, such as investigating the potential to understand the spread of diseases and a variety of other issues. Applications of advanced algorithms, machine learning, and artificial intelligence indicate a potential for rapidly advancing improvements in public health. For example, several reports indicate that social media data can be used to predict disease outbreak and spread (Brown, 2015). Since real-world EHR data has complicated security and privacy issues preventing it from being widely used by researchers, there is a real need to synthetically generate EHR data that is realistic and representative. Current EHR generators, such as Synthea  (Walonoski et al., 2017) only simulate and generate pure medical-related data. However, adding patients’ social media data with their simulated EHR data would make combined data more comprehensive and realistic for healthcare research. This paper presents a patients’ social media data generator that complements and extends an EHR data generator. By adding coherent social media data to EHR data, a variety of issues can be examined for emerging interests, such as where a contagious patient may have been and others with whom they may have been in contact. Social media data, specifically Twitter data, is generated with phrases indicating the onset of symptoms corresponding to the synthetically generated EHR reports of simulated patients. This enables creation of an open data set that is scalable up to a big-data size, and is not subject to the security, privacy concerns, and restrictions of real healthcare data sets. This capability is important to the modeling and simulation community, such as scientists and epidemiologists who are developing algorithms to analyze the spread of diseases. It enables testing a variety of analytics without revealing real-world private patient information.
Study of Assessment of the Severity of Anxiety, Depression, and Quality of Life in Caregivers of Patients with Cancer

With a population that is aging more and more the role of the caregiver is increasingly recognized as important from a functional and economic point of view. (2) Cancer patients and their caregivers wants to seek the information regarding illness of patient for better understanding or management of the cancer or to provide adequate care to the cancer patient. (3,4) Caregivers are expected to function, providing direct care, assistance in daily living activities, case management, emotional support, compainionship and medical supervision. (5)
Knowledge management: Barriers to capturing lessons learned from Australian construction contractors perspective

Purpose – A research study has been undertaken at the University of South Australia to introduce application of lessons learned process in construction contractors ' bidding process in the context of knowledge management. The study aims to identify barriers to effectively capture lessons learned in Australian construction industry and how knowledge management can benefit from lessons learned application. Design/methodology/approach – The research study has been undertaken through conducting a “methodological triangulation” and “interdisciplinary triangulation”. This involved an extensive literature review of knowledge management, organisation learning, lessons learned and associated processes and administration of a questionnaire to a sample of construction contractors operating in Australia to elicit opinions on the main barriers to capturing lessons learned, practices such as existence and retention of documentation procedures. A total of 81 useable responses were received from 450 organisations. Response data were subjected to descriptive and inferential statistics with correlation analysis to examine the strength of relationship among the barriers. Findings – The top-3 barriers to the effective capturing of lessons learned were “lack of employee time”, “lack of resources” and “lack of clear guidelines”, whereas, “lack of management support” was the least ranked barrier. The study established that despite the majority of the ACCs having formal procedures for recording the tenders submitted and their outcomes, only a minority actually retained the lessons learned documentation for each project. The larger contractors were found to be more aware of the importance of lessons learned documentation. A comparative analysis with previous studies also found a disparity in the ranking of the barriers. Research limitations/implications – The majority of the participants were small construction contractors in Australia. The reason is that the researchers were not aware of the contractors ' size prior to inviting them for participation in the research study. Second the findings may not generalize to other industries or to organisations operating in other countries. Originality/value – The findings of this survey help ACCs to understand the importance of lessons learned documentation as part of lessons learned implementation and identify the barriers to effectively document their lessons learned. The study provides insights on the barriers and proposes advocated solutions in form of drivers and enablers (critical success factors) of organisational learning capturing among the Australian construction contractors. By reviewing the current literature, “post-project reviews” and “lessons learned” as important elements of organisation learning knowledge transfer, are addressed. Finally, contribution of this study to knowledge and practice has been discussed in this paper.
J ul 2 01 2 Consistency of M estimates for separable nonlinear regression models

Consider a nonlinear regression model : yi = g (xi, θ) + ei, i = 1, . , n, where the xi are random predictors xi and θ is the unknown parameter vector ranging in a set Θ ⊂R. All known results on the consistency of the least squares estimator and in general of M estimators assume that either Θ is compact or g is bounded, which excludes frequently employed models such as the Michaelis-Menten, logistic growth and exponential decay models. In this article we deal with the so-called separable models, where p = p1 + p2, θ =(α, β) with α ∈A ⊂ R p1 , β ∈B ⊂ R2and g has the form g (x, θ) = βh (x, α) where h is a function with values in R2 . We prove the strong consistency of M estimators under very general assumptions, assuming that h is a bounded function of α, which includes the three models mentioned above.
Addressing Overchoice: Automatically Generating Meaningful Filters from Hotel Reviews

In this paper we present a hotel filter recommendation method designed to address the cognitive load users face in an overchoice scenario. As online products and services are continuously diversifying, user needs are also becoming increasingly sophisticated. However, with more items to choose from, grasping the entire choice set and differentiating among all matching options becomes increasingly difficult, leading to sub-optimal outcomes. Conventional hotel reservation platforms provide with a limited set of additional filters, but these can not accommodate all intricate user needs. Employing natural language processing and machine learning techniques, we provide a simple framework that identifies meaningful filters from customer reviews. We define criteria and scoring methods to acquire relevant and interesting filters that may help customers refine their needs or even identify hidden, previously unknown ones. Our simulated user experiments show that our proposal is capable of identifying intricate and useful filters, leading to increased customer satisfaction.
Synchronization Using Mobile Cloud Computing

: Now a day’s Mobile cloud storage are most popular to the storage and Exchange the Data . in the paper to identify, analyze and address the synchronization inefficiency problem of modern mobile cloud storage services. in the Existing Synchronization is fail to the available bandwidth. It generated the large amount of the data . it unwanted data are Synchronization to create traffic. We implement the Quick Synchronization of the data using three different technique use to improve the Synchronization efficiency to any other services and its improve the performance of the Synchronization time to the system. Data is generating day by day in cloud computing data is saved on cloud. So here we have to combine the mobile computing with cloud computing so that we can handle the mobile based application with cloud platform. So when we store our data on cloud. Here the existing commercial system fail to make full use of available bandwidth and generate a large amount of unnecessary traffic. It happens because of the inherent limitations of the sync protocol and the distributed architecture.
Imaging in hypertrophic cardiomyopathy. Expert consensus statement of the Polish Clinical Forum for Cardiovascular Imaging

Polskie Kliniczne Forum Obrazowania Serca i Naczyń: Edyta Płońska-Gościniak, Magdalena Kostkiewicz, Tomasz Miszalski-Jamka, Andrzej Szyszka, Piotr Lipiec, Andrzej Gackowski, Tomasz Kukulski, Mirosław Dziuk, Cezary Kępka, Mariusz Skowerski, Zbigniew Gąsior, Jerzy Walecki, Krystian Wita, Mirosław Kowalski, Janusz Kochanowski, Piotr Scisło, Mieczysław Pasowicz, Piotr Szymański, Katarzyna Mizia-Stec, Anna Klisiewicz, Piotr Hoffman, Piotr Podolec, Piotr Pruszczyk, Jarosław D. Kasprzak, Adam Torbicki
Molecular Characterization of Vibrio Harveyi and Vibrio alginolyticus with the Impact of Stressful Environment on Some Naturally Infected Marine Fish

Cultured seabass (Dicentrarchus labrax L.) and seabream (Sparus aurata L.) are marine species of high economic important especially in Mediterranean aquaculture. Among bacterial diseases of marine cultured and wild fish, vibriosis caused by Vibrio species is one of the most prevalent diseases. In the present work, we report the isolation and identification of the V. harveyi and V. alginolyticus, based on biochemical and molecular characterization, from cultured seabass and seabream native to private fish farms at Mathalath-El Diba region, Domitte City at Domitte Governorate, Egypt during summer season. The most prominent clinical signs of diseased fish were hemorrhagic ulceration on the dorsal musculature and caudal peduncle area as well as sever protrusion of the eye outside the orbital cavity. Histological examination of seabass revealed haemorrhage on the liver and nodular formation on different organs especially in kidney and liver. While, diseased seabream showed marbling appearance of gill with nodular formation and necrotic area distributed over the liver. Physico-chemical characteristics of water samples collected parallel to fish samples indicated that pH and organic matter of the water sample was within the permissible limits. However, the unionized ammonia, nitrate, and hydrogen sulphate concentrations were higher than the acceptable limits. Moreover, the heavy metals (copper, zinc, cadmium, lead, mercury, nickel, and iron) contained of water samples were higher than permissible limits. In regards to the haematological parameters associated with diseased and apparently healthy seabream and seabass. The total protein, albumin, and globulin were lower in diseased seabass and seabream than apparently healthy fish. Serum lysozyme and bactericidal activity was lower in the diseased fish than apparently healthy seabass and seabream. Levels of aspartate amino-transferase (S.AST) and alanine amino transferase (S.ALT) in plasma of diseased seabass and seabream were higher than apparent healthy seabass and seabream. Altogether, higher level of heavy metal concentrations in water samples than the permissible limits act as chemical stressors that help in increase the prevalence of V. harveyi and V. alginolyticus species in seabass and seabream.
The modes of existence of gameplay: an applied exercise with Cities: Skylines1

This text presents an application of the theories proposed by Bruno Latour in An inquiry into modes of existence as a key to understand gameplay, based on game situation from Cities: Skylines. The analysis is presented after a review of the theoretical framework and a brief presentation of the gameplay situation, highlighting the most prominent modes of existence in Cities: Skylines’ gameplay ([FIC], [TEC] e [HAB]) and their intersections ([FIC-TEC], [FIC-HAB] and [TEC-HAB]).
Punish and Perish: The Human Factor in Cybersecurity

According to many prominent experts, IT users are the “weakest link” in cyber-security chain. This assumption has important consequences on the definition of cyber-security policies which are often rooted in the fear of sanctions. We argue in this paper that such policies miss the point of security because they create wrong incentives for users who make mistakes or undergo the maneuvers of social engineers. Doing so, most cyber-security policies are in fact scapegoat processes more that effective guidelines for fighting cyber attacks. We argue that alternative cyber security policies, breaking up with the "Weakest Link" paradigm, are required in order to make significant improvements in facing cyber threats, especially in times of COVID-19.
The Effect of Financial Incentive on General Aviation Vfr-Into-Imc

Two flight simulator studies explored the effects of financial incentive on general aviation pilots' willingness to proceed under visual flight rules flight into adverse weather. Study 1 assessed 60 pilots' takeoff behavior into varying degrees of adverse weather seen immediately at taxiway level. Thirty pilots received straight salary, while 30 received salary plus a bonus contingent on takeoff. Trend emerged in regression analysis for effect of incentive. Study 2 examined 45 pilots' in-flight continuation into weather degrading to zero visibility. Fifteen pilots received straight salary, 15 received salary plus a partial bonus, 15 received salary plus a full bonus. Bonuses were contingent on reaching the assigned destination. Although all pilots diverted before reaching the destination, financial incentive was a powerful stimulant to continuation into IMC (p = .001). The difference between studies involves an information contrast effect. That is, when conditions deteriorate slowly, a bad situation can develop unnoticed.
Voltage-time dilemma of pure electronic mechanisms in resistive switching memory cells

Metal/insulator/metal thin film stacks showing stable resistive switching are promising candidates for future use as a nonvolatile resistive random access memory, competitive to FLASH and DRAM. Although the switching mechanisms are not completely understood a lot of theories and models try to describe the effects. One of them postulates the trapping and detrapping of electronic charge in immobile traps as the reason for the resistance changes, also known as Simmons & Verderber model. This contribution shows that this “pure electronic” switching mechanism will face a voltage-time dilemma—general to all switching insulators—at conditions competitive to the state-of-the-art FLASH. There is an incompatibility between the long retention time (10 years) and the short READ/WRITE current pulses (tREAD/WRITE≤100 ns) at high densities (area≤100×100 nm2) at low applied voltages (≤1 V). This general dilemma is exemplified in two detailed scenarios with different electronic band and defect properties.