bluuebunny/crossref_metadata_2025 huggingface dataset:
Why Is That Relevant? Collecting Annotator Rationales for Relevance Judgments
Authors: McDonnell Tyler , Lease Matthew , Kutlu Mucahid , Elsayed Tamer
Published: October 2022

When collecting subjective human ratings of items, it can be difficult to measure and enforce data quality due to task subjectivity and lack of insight into how judges’ arrive at each rating decision. To address this, we propose requiring judges to provide a specific type of rationale underlying each rating decision. We evaluate this approach in the domain of Information Retrieval, where human judges rate the relevance of Webpages to search queries. Cost-benefit analysis over 10,000 judgments collected on Mechanical Turk suggests a win-win: experienced crowd workers provide rationales with almost no increase in task completion time while providing a multitude of further benefits, including more reliable judgments and greater transparency for evaluating both human raters and their judgments. Further benefits include reduced need for expert gold, the opportunity for dual-supervision from ratings and rationales, and added value from the rationales themselves.
Crowdsourcing Accurate and Creative Word Problems and Hints
Authors: Chen Yvonne , Mandel Travis , Liu Yun-En , Popović Zoran
Published: October 2022

The current state-of-the-art method for generating educational content, such as math word problems and hints, is manual authoring by domain experts. Unfortunately, this is costly, time consuming, and produces content that lacks diversity. Attempts to automatically address the time and diversity issues through natural language generation still do not produce content that is sufficiently creative and varied. Crowdsourcing is a viable alternative - there has been a great deal of research on leveraging human creativity to solve complex problems, such as user interface design. However, these systems typically decompose complex tasks into subtasks. Writing a single word problem or hint is a small enough problem that it is unclear how to further break it down, but also far more complex than typical microtasks like image labeling. Therefore, it is not obvious how to apply these worker improvement methods or which ones are most effective (if at all). We build upon successful task design factors in prior work and run a series of iterative studies, incrementally adding different worker-support elements. Our results show that successive task designs improved accuracy and creativity.
Toward Scalable Social Alt Text: Conversational Crowdsourcing as a Tool for Refining Vision-to-Language Technology for the Blind
Authors: Salisbury Elliot , Kamar Ece , Morris Meredith
Published: October 2022

The access of visually impaired users to imagery in social media is constrained by the availability of suitable alt text. It is unknown how imperfections in emerging tools for automatic caption generation may help or hinder blind users' understanding of social media posts with embedded imagery. In this paper, we study how crowdsourcing can be used both for evaluating the value provided by existing automated approaches and for enabling workflows that provide scalable and useful alt text to blind users. Using real-time crowdsourcing, we designed experiences that varied the depth of interaction of the crowd in assisting visually impaired users at caption interpretation, and measured trade-offs in effectiveness, scalability, and reusability. We show that the shortcomings of existing AI image captioning systems frequently hinder a user's understanding of an image they cannot see to a degree that even clarifying conversations with sighted assistants cannot correct. Our detailed analysis of the set of clarifying conversations collected from our studies led to the design of experiences that can effectively assist users in a scalable way without the need for real-time interaction. They also provide lessons and guidelines that human captioners and the designers of future iterations of AI captioning systems can use to improve labeling of social media imagery for blind users.
Lessons from an Online Massive Genomics Computer Game
Authors: Singh Akash , Ahsan Faizy , Blanchette Mathieu , Waldispühl Jérôme
Published: October 2022

Crowdsourcing through human-computing games is an increasingly popular practice for classifying and analyzing scientific data. Early contributions such as Phylo have now been running for several years. The analysis of the performance of these systems enables us to identify patterns that contributed to their successes, but also possible pitfalls. In this paper, we review the results and user statistics collected since 2010 by our platform Phylo, which aims to engage citizens in comparative genome analysis through a casual tile matching computer game. We also identify features that allow predicting a task difficulty, which is essential for channeling them to human players with the appropriate skill level. Finally, we show how our platform has been used to quickly improve a reference alignment of Ebola virus sequences.
A 10-Month-Long Deployment Study of On-Demand Recruiting for Low-Latency Crowdsourcing
Authors: Huang Ting-Hao , Bigham Jeffrey
Published: October 2022

A number of interactive crowd-powered systems have been developed to solve difficult problems out of reach for automated solutions. To work interactively, such systems need access to on-demand labor. To meet this demand, workers can be (i) recruited when needed directly from the crowd marketplace, or (ii) recruited in advance and asked to wait in a retainer pool until they are needed. Most of the evaluations of these systems have been over a short time period, even though we know that marketplaces change and adapt over time. In this paper, we present the results of a 10-month deployment of a crowd-powered system that uses a hybrid approach to fast recruitment of workers that we call Ignition. We describe the Ignition approach and the observed times required to recruit workers from the marketplace and retainer over this long period of time. Our results demonstrate that it is possible to recruit workers with low latency even over long periods, and suggest a number of opportunities for future work for recruitment strategies and modeling that may further improve on-demand recruitment for deployed systems.
Usability of Humanly Computable Passwords
Authors: Samadi Samira , Vempala Santosh , Kalai Adam
Published: October 2022

Reusing passwords across multiple websites is a common practice that compromises security. Recently, Blum and Vempala have proposed password strategies to help people calculate, in their heads, passwords for different sites without dependence on third-party tools or external devices. Thus far, the security and efficiency of these "mental algorithms" has been analyzed only theoretically. But are such methods usable? We present the first usability study of humanly computable password strategies, involving a learning phase (to learn a password strategy), then a rehearsal phase (to login to a few websites), and multiple follow-up tests. In our user study, with training, participants were able to calculate a deterministic eight-character password for an arbitrary new website in under 20 seconds.
EURECA: Enhanced Understanding of Real Environments via Crowd Assistance
Authors: Gouravajhala Sai , Yim Jinyeong , Desingh Karthik , Huang Yanda , Jenkins Odest , Lasecki Walter
Published: October 2022

Indoor robots hold the promise of automatically handling mundane daily tasks, helping to improve access for people with disabilities, and providing on-demand access to remote physical environments. Unfortunately, the ability to understand never-before-seen objects in scenes where new items may be added (e.g., purchased) or altered (e.g., damaged) on a regular basis remains an open challenge for robotics.  In this paper, we introduce EURECA, a mixed-initiative system that leverages online crowds of human contributors to help robots robustly identify 3D point cloud segments corresponding to user-referenced objects in near real-time. EURECA allows robots to understand multi-object 3D scenes on-the-fly (in ~40 seconds) by providing groups of non-expert crowd workers with intelligent tools that can segment objects more quickly (~70% faster) and more accurately (6% higher F1 score) than individuals. More broadly, EURECA introduces the first real-time crowdsourcing tool that addresses the challenge of learning about new objects in real-world settings, creating a new source of data for training robots online, as well as a platform for studying mixed-initiative crowdsourcing workflows for understanding 3D scenes.
Interpretable Image Recognition with Hierarchical Prototypes
Authors: Hase Peter , Chen Chaofan , Li Oscar , Rudin Cynthia
Published: October 2022

Vision models are interpretable when they classify objects on the basis of features that a person can directly understand. Recently, methods relying on visual feature prototypes have been developed for this purpose. However, in contrast to how humans categorize objects, these approaches have not yet made use of any taxonomical organization of class labels. With such an approach, for instance, we may see why a chimpanzee is classified as a chimpanzee, but not why it was considered to be a primate or even an animal. In this work we introduce a model that uses hierarchically organized prototypes to classify objects at every level in a predefined taxonomy. Hence, we may find distinct explanations for the prediction an image receives at each level of the taxonomy. The hierarchical prototypes enable the model to perform another important task: interpretably classifying images from previously unseen classes at the level of the taxonomy to which they correctly relate, e.g. classifying a hand gun as a weapon, when the only weapons in the training data are rifles. With a subset of ImageNet, we test our model against its counterpart black-box model on two tasks: 1) classification of data from familiar classes, and 2) classification of data from previously unseen classes at the appropriate level in the taxonomy. We find that our model performs approximately as well as its counterpart black-box model while allowing for each classification to be interpreted.
Human Evaluation of Models Built for Interpretability
Authors: Lage Isaac , Chen Emily , He Jeffrey , Narayanan Menaka , Kim Been , Gershman Samuel J. , Doshi-Velez Finale
Published: October 2022

Recent years have seen a boom in interest in interpretable machine learning systems built on models that can be understood, at least to some degree, by domain experts. However, exactly what kinds of models are truly human-interpretable remains poorly understood. This work advances our understanding of precisely which factors make models interpretable in the context of decision sets, a specific class of logic-based model. We conduct carefully controlled human-subject experiments in two domains across three tasks based on human-simulatability through which we identify specific types of complexity that affect performance more heavily than others–trends that are consistent across tasks and domains. These results can inform the choice of regularizers during optimization to learn more interpretable models, and their consistency suggests that there may exist common design principles for interpretable machine learning systems.
Effective Operator Summaries Extraction
Authors: Nimni Ido , Sarne David
Published: October 2022

This paper proposes a heuristic algorithm for effectively summarizing the work of novice robot operators, e.g., ones recruited through crowdsourcing platforms, in search and rescue-like tasks. Such summaries can be used for many purposes, perhaps most notably for monitoring and evaluating an operator’s performance in settings where information gaps preclude automatic evaluation. The underlying idea of our method is dividing the task timeline into intervals, and extracting a subset of high-scoring and low-scoring segments within, using a heuristic scoring function. This results in a short effective summary of the operator’s work, based on which several other crowdworkers can evaluate her performance. The effectiveness of the proposed method was extensively evaluated and compared to a large set of alternative methods through a series of experiments in Amazon Mechanical Turk. The analysis of the results reveals that the proposed method outperforms all tested alternatives. Finally, we evaluate the performance one may achieve with the use of machine learning for predicting the operator’s performance in our domain. While this approach manages to reach a performance level similar to the one achieved with summaries, it requires an order-of-magnitude greater effort for training (measured in terms of crowdworkers time).
Verifying Extended Entity Relationship Diagrams with Open Tasks
Authors: Sabou Marta , Käsznar Klemens , Zlabinger Markus , Biffl Stefan , Winkler Dietmar
Published: October 2022

The verification of Extended Entity Relationship (EER) diagrams and other conceptual models that capture the design of information systems is crucial to ensure reliable systems. To scale up verification processes to larger groups of experts, Human Computation techniques were used focusing primarily on closed tasks, which constrain the number and variety of reported defects in favor of easy aggregation of derived judgements. To address this limitation of closed tasks, in this paper, we investigate EER verification (as instance of a broader family of model verification problems) with open tasks to extend the range of collected results. We also address the challenge of aggregating results of open tasks by proposing a follow-up HC task for defect validation. We evaluate our approach for HC-based EER Verification with open tasks in a set of experiments conducted with junior developers and show that (1) open tasks allow collecting a variety of insights that go beyond a manually built gold standard while still leading to good performance (F1=60%) and (2) HC-based validation can be reliably used for validating the results of open tasks (F1=84% compared to expert validation).
Explaining Autonomous Decisions in Swarms of Human-on-the-Loop Small Unmanned Aerial Systems
Authors: Agrawal Ankit , Cleland-Huang Jane
Published: October 2022

Rapid advancements in Artificial Intelligence have shifted the focus from traditional human-directed robots to fully autonomous ones that do not require explicit human control. These are commonly referred to as Human-on-the-Loop (HotL) systems. Transparency of HotL systems necessitates clear explanations of autonomous behavior so that humans are aware of what is happening in the environment and can understand why robots behave in a certain way. However, in complex multi-robot environments, especially those in which the robots are autonomous and mobile, humans may struggle to maintain situational awareness. Presenting humans with rich explanations of autonomous behavior tends to overload them with lots of information and negatively affect their understanding of the situation. Therefore, explaining the autonomous behavior of multiple robots creates a design tension that demands careful investigation.
This paper examines the User Interface (UI) design trade-offs associated with providing timely and detailed explanations of autonomous behavior for swarms of small Unmanned Aerial Systems (sUAS) or drones. We analyze the impact of UI design choices on human awareness of the situation. We conducted multiple user studies with both inexperienced and expert sUAS operators to present our design solution and initial guidelines for designing the HotL multi-sUAS interface.
On the Bayesian Rational Assumption in Information Design
Authors: Tang Wei , Ho Chien-Ju
Published: October 2022

We study the problem of information design in human-in-the-loop systems, where the sender (the system) aims to design an information disclosure policy to influence the receiver (the user) in making decisions. This problem is ubiquitous in systems with humans in the loop, e.g., recommendation systems might choose whether to present others' reviews to encourage users to follow recommendations, online retailers might choose which set of product features to present to persuade buyers to make the purchase. Among the flourish literature on information design, Bayesian persuasion has been one of the most prominent efforts in formalizing this problem and has spurred various research studies in both economics and computer science. While there has been significant progress in characterizing the optimal information disclosure policies and the corresponding computational complexity, one common assumption in this line of research is that the receiver is Bayesian rational, i.e., the receiver processes the information in a Bayesian manner and takes actions to maximize her expected utility. However, as empirically observed in the literature, this assumption might not be true in real-world scenarios. In this work, we relax this common Bayesian rational assumption in information design in the persuasion setting. In particular, we develop an alternative framework for information design based on discrete choice model and probability weighting to account for this relaxation. Moreover, we conduct online behavioral experiments on Amazon Mechanical Turk and demonstrate that our framework better explains real-world user behavior and leads to more effective information design policy.
Utility of Crowdsourced User Experiments for Measuring the Central Tendency of User Performance to Evaluate Error-Rate Models on GUIs
Authors: Yamanaka Shota
Published: October 2022

The usage of crowdsourcing to recruit numerous participants has been recognized as beneficial in the human-computer interaction (HCI) field, such as for designing user interfaces and validating user performance models.
In this work, we investigate its effectiveness for evaluating an error-rate prediction model in target pointing tasks.
In contrast to models for operational times, a clicking error (i.e., missing a target) occurs by chance at a certain probability, e.g., 5%.
Therefore, in traditional laboratory-based experiments, a lot of repetitions are needed to measure the central tendency of error rates.
We hypothesize that recruiting many workers would enable us to keep the number of repetitions per worker much smaller.
We collected data from 384 workers and found that existing models on operational time and error rate showed good fits (both R^2 > 0.95).
A simulation where we changed the number of participants N_P and the number of repetitions N_repeat showed that the time prediction model was robust against small N_P and N_repeat, although the error-rate model fitness was considerably degraded.
These findings empirically demonstrate a new utility of crowdsourced user experiments for collecting numerous participants, which should be of great use to HCI researchers for their evaluation studies.
NANORECTANGULAR PRINTED GOLD ANTENNA FOR ON-HUMAN BODY WIRELESS BODY NETWORK APPLICATIONS
Authors: Moulfi Bouchra , Ferouani S. , Ziani-Kerarti D.
Published: October 2022

In this work we designed a rectangular patch antenna in the teraherk band for wireless body network (WBAN) applications using CST software. This antenna is simulated with RO4003C substrate (εr = 3.55) and has dimensions of 199 × 154 μm2 for width and length, respectively. We obtained return loss of -41.408 dB, -43.918 dB, and -29.92 dB; gain of 5.32 dB, 6.21 dB, and 4.851 Db; directivity of 6.659 dB, 7.502 dB, and 6.566 dB; in 0.74 THZ, 1.148 THZ, and 1.734 THZ frequencies, respectively. The simulation results are very satisfactory, and this antenna can be used for WBAN applications.
The Violence of the System: Production of Disposable Subjects
Authors: America Guevara
Published: October 2022

The objective of this paper is to reflect on new and increasingly subtle forms of aggression against marginalized groups. In particular, it addresses the case of immigrants who are constantly subjected to state, police, and citizen surveillance and control. The article is organized into three sections corresponding to the main and sub-themes. The first section addresses the Foucaultian notion of State Racism defined as the condition for the sovereign exercise of power to be legitimately articulated in a society. The second section refers to the critical debate proposed by the French academic Didier Bigo on the securitization of migration, understood as the one that justifies coercive and discriminatory practices towards those who cross borders. Finally, based on the proposal of the philosopher and sociologist Jean Baudrillard, the last section of the article concludes with an analysis on the violence of the current system dominated by an exclusionary productive order in which personal interest reigns and where life and the link with the other are commodified producing “disposable”
Influence of Mezzanine Financing on the Corporate Financial Profile
Authors: Городников Кирилл , Павлов Михаил , Сус Александр
Published: October 2022

Due to global changes in the global economy, the importance of financing and building an optimal capital structure is increasing. Rapid changes in the exogenous environment and the investment climate lead companies to revise their financing strategies.

Currently, there are many financial instruments that provide cash inflow, but have certain restrictions. The tool that allows to eliminate them is the mezzanine. However, the existing literature on mezzanine financing does not fully cover this financing method. The novelty of this research lies in determining the financial profile of the borrower company that utilizes mezzanine financing, and in studying the impact of the mezzanine on the market value of a company’s equity and its value. Econometric analysis confirms that mezzanine financing is more often chosen by companies with a less attractive financial profile, based on ROA, EBITDA – CapEx cash flow, and beta. In addition, the interconnection between a company’s life cycle and its desire to attract a mezzanine loan is revealed. Econometric and empirical analysis allow us to conclude that the market situation, managerial methods within the company and the operational strategy increase the chances of the effective use of the mezzanine.
CONSÓRCIOS PÚBLICOS INTERMUNICIPAIS E SUA IMPORTÂNCIA PARA UMA GESTÃO PÚBLICA MAIS IGUALITÁRIA: UMA ANÁLISE DO CRESCIMENTO REGIONAL OCASIONADO NO ESTADO DA BAHIA
Authors: Barboza de Matos Elis Maria , Mendonça Morais Sant'Anna Marília
Published: October 2022

Resumo: Com a lei 11.107 de 2005, conhecida como Lei dos Consórcios Públicos, surge no Brasil a possibilidade de unir entes públicos com o intuito de melhorar a gestão pública nacional. Neste contexto entram os Consórcios Públicos Intermunicipais, os quais têm por objetivo levar direitos básicos aos habitantes de municípios de pequeno porte do país, surgem como entidades em forma de associação pública ou pessoa jurídica de direito privado, com o intuito de unir forças para adquirir um maior benefício para os entes participantes. Nesse estudo verifica-se que os consórcios Intermunicipais da Bahia estão efetivamente trazendo avanços para o Estado, refletindo positivamente na população, ocasionando assim crescimento econômico e trazendo uma melhor qualidade de vida para seus moradores. A administração Pública tem que zelar pelo princípio da eficiência, previsto na Constituição Federal de 1988 visando que os atos administrativos sejam eficazes e econômicos, proporcionando para os municípios consorciados uma melhor utilização dos recursos disponíveis e, consequentemente, promovendo a satisfação dos administrados. O presente artigo parte do questionamento: Os consórcios públicos intermunicipais podem proporcionar uma gestão pública mais igualitária? Para alcançar o objetivo proposto, foi utilizado o método dedutivo, pesquisas doutrinarias, sítios eletrônicos, bem como, legislações nacionais.
Far-Right Populism Online: Did Vox’s Community Reproduce the Party’s Discourse During the April 2019 Campaign?
Authors: Capdevila Arantxa , Moragas Fernández Carlota M. , Grau Masot Josep Maria
Published: October 2022

In April 2019, VOX, a far-right populist party, won seats for the first time in the Spanish parliament. VOX successfully used social media to participate in the electoral debate and to establish a more direct link with its followers. We investigated how the VOX online community was structured during the election campaign and to what extent the most influential profiles spread the party’s messages. We accordingly analysed two samples, one composed of tweets and retweets that used the hashtags #28A, #28Abril, and #28AbrilElecciones, and the other composed of metaphorical expressions identified in tweets by influencers. Applying social network analysis to the first sample, we studied the form and structure of the network and identified key profiles in the VOX community, i.e., influencers, builders, and bridges. Using critical metaphor analysis with the second sample, we identified the main frames used by VOX influencers to explore whether they reproduced the party’s populist discourse. We found that the VOX online community in 2019 did not only include party supporters or members but was composed of varied profiles. For this reason, the populist metaphorical framing used by the VOX leadership was only partially disseminated.
Comparative Analysis of 20-Minute Neighbourhood Policies and Practices in Melbourne and Scotland
Authors: Chau Hing-Wah , Gilzean Ian , Jamei Elmira , Palmer Lesley , Preece Terri , Quirke Martin
Published: October 2022

Twenty-minute neighbourhoods highlight the importance of well-connected and mixed-used neighbourhoods and communities with proximate access to employment, essential services, public transport, and open spaces. Shorter distances together with re-prioritised public spaces encourage more active transport choices, resulting in public health benefits and reduced environmental pollution. Higher liveability brought about by mixed-use developments enables people to have equitable access to local facilities, amenities, and employment opportunities, promoting vibrancy, social cohesion, and intergenerational connections. The attributes of 20-minute neighbourhoods also combine to create places, that are acknowledged as friendly for all ages, address changing needs across the life course, and provide better support for the ageing population. Furthermore, there are indications that 20-minute neighbourhoods may be more resilient against many of the negative impacts of stringent public health protocols such as those implemented in periods of lockdown during the Covid-19 pandemic. In this article, we evaluate and compare planning policies and practices aimed at establishing 20-minute neighbourhoods in Melbourne (Australia) and Scotland (the UK). Using case studies, we discuss similarities and differences involved in using place-based approaches of 20-minute neighbourhoods to address 21st-century challenges in key areas of health and wellbeing, equity, environmental sustainability, and community resilience.
Ovarian Cancer Metastasis to Lung Parenchyma without Peritoneal Dissemination: A Rare Case
Authors: Sonvane Shwetal , Gupta Naveen Kumar , Saikia Jyoutishman , Rathore Ruchi , Akhtar Sagir , Ray Mukurdipi
Published: October 2022

Ovarian cancer is the most lethal gynecological malignancy worldwide. Despite the advances in treatment for ovary cancer, the 5-year survival rate of advanced ovarian cancer patients with peritoneal metastasis remains as high as 30%. Clinical stage is the most important prognostic factor and most patients are at an advanced stage. There is often no clearly identifiable precursor lesion; therefore, the events which lead to metastatic disease are poorly understood. Solitary lung parenchyma metastasis is extremely rare. We report a case of 39-year-old woman who was admitted with a lung mass. She had a history of high-grade serous carcinoma ovary, which was detected and treated 6 years ago with cytoreductive surgery as well ashyperthermic intraperitoneal and adjuvant chemotherapy. During the routine follow-up, positron emission tomography computed tomography scan showed two nodules of soft-tissue density in the lung parenchyma of the left lower lobe with a dimension of 2.8 × 2.5 cm. Intraoperatively, two conglomerated lung nodules seen in lung parenchyma of the left lower lobe. Deeper nodule was in close proximity to the left lower lobe bronchus and left lower lobe pulmonary artery. Video-assisted thoracoscopic surgery was conducted to perform left lower lobectomy. Postoperatively, the patient was stable. Microscopically, the tumor was classified as a high-grade serous carcinoma, and the patient was diagnosed for having an ovarian cancer metastasis. Ovarian cancer rarely metastasizes to the lung parenchyma in a relapse. However, excision of lesion with further chemotherapy showed excellent results. Surgical excision biopsy and intraoperative frozen sectioning, followed by lobectomy or segmentectomy, are both diagnostic and therapeutic. 
Serum uric acid in first trimester as a predictor for the diagnosis of gestational diabetes mellitus-a prospective study
Authors: Srinivasan Suguna
Published: October 2022

Background: Gestational diabetes mellitus (GDM) is common worldwide. It is a disorder of carbohydrate metabolism. Indian women have increased risk of developing GDM, and leads to adverse Maternal and neonatal outcomes. Women with raised uric acid in pregnancy are interlinked with more incidence of unfavorable outcomes in pregnancy such as GDM. Hence this study is done to prove the utility of uric acid in early diagnosis of GDM by starting early treatment so as to reduce the complications in pregnant women.Methods: The antenatal women are screened for GDM by serum uric acid levels with gestational age <12 weeks. These antenatal women are followed up around 24-28 weeks and oral glucose tolerance test is done and evaluated for GDM using ADA criteria.Results: In our study, serum uric acid cut–off of 4.2 mg/dl had a positive association with the GTT values with p value less than 0.05 (p=0.018). In this study, in the raised serum uric acid category, 8 (19%) were positive for GTT and among the normal serum uric acid category, 3 (4.7%) were positive for GTT. Thus, we observe from our study that elevated levels of uric acid during the first trimester is interlinked with prediction of gestational diabetes.Conclusions: The diagnosis of serum uric acid level in first trimester as a predictor of GDM is easy and economical and it can be used as a screening test for prediction of GDM.
CSCRT Protocol with Energy Efficient Secured CH Clustering for Smart Dust Network Using Quantum Key Distribution
Authors: Rajesh Dennison , Rajanna Gowda Shankarappa
Published: October 2022

Energy efficient protocols for Mobile wireless smart dust networks are getting prominence in the present scenario. This paper describes a novel scheme for intrusion detection framework for secured clustered mobile smart dust networks which better suits the periodical data gathering. The essential objective of a battery equipped mobile wireless smart dust nodes is to upgrade the transmission energy. The proposed protocol has the favourable position that the communication and computational overheads get reduced and gives improved energy efficient routing protocol as far as energy efficient and intrusion detection system. The intrusion and interruption are fundamentally same as that it is difficult to recognize. The design becomes more complex, any security protection algorithms utilize more energy. This can be achieved by using IDS based clustering tactic, Specific Encryption algorithm with Quantum Key Distribution and Chance Succession Comparison Ratio Test protocol. Particular encryption for data based communication is carried out to low utilization of energy and also to discover attacks, when it occurs in mobile nodes. Data transmission rate is a factor for energy utilization. Simulation is done in NS2, results show that better energy efficient routing scheme for mobile wireless smart dust network.
IMPACT OF CYBER SECURITY COST ON THE FINANCIAL PERFORMANCE OF E-BANKING: MEDIATING INFLUENCE OF PRODUCT INNOVATION PERFORMANCE
Authors: Khalil Khalid , Manzoor Sheikh Raheel , Tahir Muhammad , Khan Nisar , Jamal Khalid
Published: October 2022

Purpose of Study: The study objectives are to: a) conduct a meta-analytical review to analyze the association among cybersecurity costs, such as prevention and detection costs (PDC), response costs (RC), development costs (DC), and indirect costs (IC), on the e-banking product innovation performance (PIP) and financial performance (FP), b) to evaluate the causal association of cyber security costs, i.e., (PDC, RC, DC, and IC) on PIP and FP; and c) investigate the mediating effects of PIP in a relationship between PDC, RC, DC, IC and FP. 

Methodology: The study sample was the managerial cadre employees of various electronic banks (e-banks) working in Pakistan. The survey was conducted by distributing the questionnaire among the employees of e-banks working in Pakistan. The collected data were estimated via multivariate statistical techniques.

Findings: The results of the study showed that a) the costs associated with cybersecurity, specifically PDC, RC, and DC, have a statistically significant effect on PIP and e-banking FP, whereas IC has a negative significant influence on the PIP and FP, b) the PIP has a statistically significant effect on e-banking FP, and c) the PIP partially mediates an association between PDC, RC, DC, and FP, whereas, PIP insignificantly mediates in a relationship amongst IC and e-banking FP. 

Application of Study: The study will applicable in the modern electronic banking (e-banking) systematic risk control and information security solution.

Novelty: The study is novel in the context of cyber security costs, including (PDC, RC, DC, IC) by measuring its influence on PI and e-banking FP.
Mercury Pollution in the Amazon Basin . Scientific research and related National and International control policies
Authors: Fenzl Norbert , Nascimento Fernanda S.
Published: October 2022

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Recubrimientos a base de alginato de sodio extraído de Sargassum fluitans y nanopartículas de plata para prolongar la vida de anaquel de papaya (Carica papaya L.)
Authors: Martínez Esther , Abud Archila Miguel , Freile Pelegrín Yolanda , Luján Hidalgo María Celina , Gutiérrez Miceli Federico Antonia , Ovando Chacón Sandy Luz
Published: October 2022

La papaya es un fruto climatérico que tiene una vida en anaquel corta. Una opción para prolongar la vida útil de este fruto es el uso de recubrimientos. El objetivo del presente estudio fue evaluar el efecto del recubrimiento a base de alginato extraído de Sargassum fluitans adicionado con nanopartículas de plata (NpAg) sobre la vida en anaquel de papaya (Carica papaya L. var. Maradol). Las NpAg se obtuvieron mediante síntesis verde. Las papayas, en grado de madurez 3, fueron recubiertas con tres soluciones: solución 1 (2.49 % alginato), solución 2 (2.49 % alginato y 1.1 mg NpAg/mL) y el grupo control (agua). Los frutos se pincelearon y se almacenaron 15 días a 25 °C y 75 % de humedad relativa. Los frutos recubiertos con las soluciones 1 y 2 mantuvieron valores óptimos de firmeza (6.9 y 6.6 MPa), sólidos solubles totales (11.1 y 11.06 °Brix) y contenido de ácido ascórbico (22.31 y 23.02 mg AA/g pulpa) durante 6 días más que el control. Los recubrimientos de alginato de sodio extraído de S. fluitans adicionado o no con NpAg retardaron la maduración de la papaya. Esta tecnología permite prolongar la vida en anaquel de la papaya a 25 °C sin utilizar refrigeración.
The Verification of the Validity and Reliability of the Semi-permanent Make-up Dr. Eye 4S Technique Development
Authors:   The Korean Society of Beauty and Art, Jin Hyun-Sook , Hwang Hea-Ju
Published: October 2022

The purpose of this study is to verify the validity and reliability of the semi-permanent make-up, Dr. Eye 4S Technique, which has been standardized and developed through mathematical formulation, to ensure that it is convenient for anyone to learn to use. We conducted two surveys at a two week interval. Those who participated in this study have more than 15 years of experience at plastic surgery and dermatology clinics in the Seoul metropolitan area, and 5 to 10 years of experience using semi-permanent make-up techniques. The results of compiling and analyzing data revealed the following: (i) The Correlation of Perceived Usability produced significant results in ‘convenience for the cosmetic procedure,’ ‘availability of information about the procedure’, ‘streamlining the process’, and ‘usefulness in general use’. (ii) The Correlation of Perceived Easiness produced significant results in ‘easiness to use’ ‘less effort’, and ‘easiness to perform’. (iii) The Correlation of Intention to Use produced significant results in willingness ‘to use,’ ‘to continue using’, ‘to talk positively about the 4S Technique,’ and ‘to perform the procedure using the 4S Technique’. (iv) The Correlation of Recognized Usability produced significant results in expecting ‘quick procedure,’ ‘improved result,’ and ‘to be helpful for a procedure’. (v) The Correlation of Work Efficiency produced significant results in ‘easier use,’ and ‘helpfulness in performing a procedure’. (v) The Correlation of Satisfaction Level of Training Content produced significant results in the satisfaction with the basic training about ‘drawing eyebrow sketches,’ ‘drawing eyebrow lines,’ and the ‘4S Technique.’ Lastly, (vi) The Correlation of Satisfaction Level of Training produced significant results in ‘willingness to recommend the 4S Technique’. This study verified the validity and reliability of the semi-permanent make-up, Dr. Eye 4S Technique, which is convenient for anyone to learn to use, and therefore will guide effective traning for semi-permanent make-up in the future.
Exposure assessment to pesticide residues and trace metals related to the consumption of imported onions (Allium cepa) in Senegal
Authors:   Laboratory of Analytical Chemistry and Food Sciences, Ndao SD , Ndao MS ,   Ministry of Agriculture and Rural Equipment, Diop I , Ly CO ,   African Refining Company, Diop A , Ndiaye B , Diop YM , Sarr SO
Published: October 2022

In Senegal, the onion is one of the most consumed vegetables because it is used in all salty culinary preparations. The objective of the study was to assess the contribution of imported onions to exposure to pesticide residues and metallic trace elements. Composite samples of onions were taken in the seven largest markets of Dakar: Thiaroye, Keur Massar, Castors, Cambérene, Rufisque, Tilène and Dalifort. The metallic trace elements were determined by the ICP-AES, type Agilent Technology serial number AU 14110053 of 2014, while pesticide residues were detected and quantified by gas chromatograph, type Agilent Technology 6890A serial CN10721019, equipped with an Electron Capture micro-Detector with serial number 022423. The average content of the composite samples in lead (Pb) (778.22 µg/kg) was 7 to 8 times higher, in cadmium (Cd) (12.43 µg/kg) 5 times lower than the maximum residue limits determined by the European Union and the Codex Alimentarius, while the average concentration of aluminum (Al) was 13570 µg/kg. Twenty four (24) pesticide residues were tested. The average concentrations of some pesticides banned in European Union (EU) exceeded the maximum limits set by them. In fact, they are more than hundred (100) times higher for Prophenophos (2088.16 µg/kg), 25 times for Fenthion (508.01 ppb), 7 times for Tetramethrin (72.56 µg/kg), 2.5 times for Parathion methyl (50.16 ppb), 2 times for Dichlorvos (19.12 µg/kg), and 1.4 times for Endrin (14.26 µg/kg). The Dimetoate and the Malathion, although authorized, were found in onions at concentrations 25 times (250.8 µg/kg) and 2 times (40.71 µg/kg), respectively higher than the maximum limits set by the EU. Only the average content of Chlorpyrophos (4.13 µg/kg), Bifenthrin (2.99 µg/kg), Lambda Cyhalothrin (7.30 µg/kg) and Cypermethrin (8.095 ppb) were in accordance with the EU regulations. The results of the exposure assessment reveals that the calculated daily consumption of 0.158 kg of these onion samples by a 60 kg average body weight Senegalese adult would provide 56% of the Toxicological Reference Value for lead, 25% for aluminum, 66% for Dimetoate, 63% for Dichlorvos, 28% for Dieldrin, 19% for Fenthion, 18% for Endrin and Prophenophos and 13% for Parathion-methyl. This study reveals that the imported onion contributes to the exposure of the Senegalese adult to eight (8) phytosanitary active substances and three (3) metallic trace elements. Thus, the health risk cannot be ruled out and it is important to set up a monitoring plan for the imported onion. Key words: Metallic trace elements, pesticide residues, exposure, onions, Senegal
Soil and irrigation water quality assessment for maize production in Buhle farm in Howick, Kwazulu-Natal province, South Africa
Authors:   KwaZulu-Natal Department of Agriculture and Rural Development, Zondo S , Mahlambi P ,   University of KwaZulu Natal
Published: October 2022

The continuous monitoring of soil health and irrigation water quality influences the crop yield and the quality of agricultural produce. In this study, various physicochemical parameters were measured to monitor the soil profile, irrigation water and maize quality harvested from the Buhle farm located in Howick in the KwaZulu-Natal Province of South Africa to ensure steady high quality food supply for the consumer. The maize crop was sampled from the maize stalk, the corresponding soil samples were collected from the upper surface of the soil (0-15 cm surface layer) using the soil auger and the irrigation water sample was taken from the irrigation tanks using polyethylene sample bottles. The physicochemical parameters considered for irrigation water were pH, electrical conductivity, alkalinity and chloride due to their ability to affect water quality which consequently affect crop growth and quality. The soil physicochemical parameters considered were moisture content, pH, electrical conductivity, texture, total nitrogen and nutrients (protein, fat, fibre, starch, total mineral matter and elements). These parameters determine the soil quality, water content, the ratio of absorbed and lost energy, concentration of ions and elements present which in turn affect or promote the yield and quality of crops. Maize was analysed for nutritional content and medicinal health-promoting compounds to assess the influence of soil and irrigation water on the maize quality and consequently the health of the consumers. The concentrations of total nitrogen (N), phosphorus (P) and potassium (K) in soil, which were translated into high soil fertility were 2700, 19 and 222 mg kg-1, respectively. The results obtained were within the required specification for high quality maize production. The levels of sodium, sodium adsorption ratio and electrical conductivity in the irrigation water were 0.05 mg L-1, 2 and 1.81 µS m-1, respectively, indicating safe water of low salinity. Maize was high in starch (58.6%) while fibre, protein and fat contents in the maize were 23.4, 9.01 and 4.55%, respectively, indicating suitability for consumption. Furthermore, the total anthocyanin, total flavonoids and total phenolic acid content of the maize were 8.5, 49.5 and 100 mg L-1, respectively. Overall, this study showed the presence of health-promoting compounds in the maize crop which is associated with its high quality for consumption. The validity of the analysis methods was tested using certified reference materials. The concentrations of the reference materials were not statistically different from the certified values, attesting to the validity of the analysis methods. Key words: Soil profile, water quality, soil fertility, nutrition, antioxidants
​Influence of Paper Mill Effluent Irrigated Soil Characteristics under Laboratory and Field Conditions
Authors: Devakumari M. Suguna , Katharine S. Praveena , Jeeva S. Carolin
Published: October 2022

Background: The solid wastes and the wastewater (effluent) generated in the pulp and paper industry can be used to improve the soil fertility. However, the cation concentration in these residues can influence the bioavailability of some nutrients and soil properties. The objective of this study is to experiment the availability of the cations namely Ca, Mg, Na and K in laboratory (column) and the field. Methods: An experiment with PVC column was carried out in the laboratory to study the availability of cations as influenced by 13 irrigations with papermill effluent vis-à-vis in a field experiment in the Department of Environmental Sciences, Tamil Nadu Agricultural University, Coimbatore during 2019-2020. Result: The pH, EC and the concentration of the cations were higher in the field soil compared to the column soil barring magnesium. This may be due to the clogging of pores resulting in decreased infiltration in field soil.
Formation of digital competencies of future teachers of biology in a blended learning environment
Authors: Yesmakhanova Zharkynay , Zhussipova Gulmira , Abjapparovna Kalampyr , Sumatokhin Sergey , Saparova Zhanar , Assilbekova Baktygul
Published: October 2022

The purpose of this research is to get the opinions of future biology teachers on the creation of digital competencies in a blended learning environment. This research was created with the qualitative research method. The study group of the research consists of 80 biology teacher candidates studying in biology teaching departments at various universities in Kazakhstan. The data collection tool of the research is the semi-structured interview form developed by the researchers. The descriptive analysis method was used in the analysis of the research data. As a result of the research, it has been determined that the vast majority of future biology teachers find blended learning environments useful. In addition, the majority of pre-service teachers stated that they found their digital competencies somewhat sufficient. The majority of biology teacher candidates participating in the research stated gaining the ability to use digital technologies, gaining competencies in using digital tools, preparing applications that will enable the student to reinforce the subject in the digital environment and gaining the habit of following the innovations in digital technology as their expectations regarding the digital competencies to be created in relation to the blended learning environment.

Keywords: Blended learning, digital competencies, prospective teachers
PERSEPSI PENCANTUMAN LABEL HALAL, LABEL BPOM, DAN TANGGAL KADALUARSA MEMPENGARUHI MINAT BELI KONSUMEN MINUMAN READY TO DRINK DI SURABAYA
Authors: PUTRI SUCI RAMADHANI , ANDARINI SONJA
Published: October 2022

Pertumbuhan industri minuman jadi adalah salah satu contoh pergeseran pola konsumsi konsumen di Indonesia. Minat masyarakat muslim maupun non muslim terhadap produk yang efektif dan efisien untuk dibawa berpergian, menciptakan sebuah prospek yang sangat cerah bagi perusahaan sekaligus memberikan peluang besar bagi pengusaha untuk bergabung dalam industri minuman jadi. Penelitian ini ditujukan untuk mengetahui dan menganalisa hasil uji persepsi konsumen mengenai pencantuman label halal, label BPOM, tanggal kadaluarsa pada kemasan produk minuman ready to drink (RTD) mempengaruhi minat beli di Kota Surabaya. Objek yang diteliti adalah produk minuman ready to drink (RTD) merek Ichitan. Metode pengujian yang dipilih ialah analisis regresi linier berganda dan beberapa pengujian lain yang dibantu program komputer SPSS Ver.20 for windows. Dari hasil penelitian ditemukan bahwa: adanya pengaruh secara simultan antara Label Halal, Label BPOM dan Tanggal Kadaluarsa terhadap Minat Beli ; Label Halal tidak ditemukan pengaruh secara parsial terhadap Minat Beli adanya pengaruh parsial Label BPOM terhadap Minat Beli ; adanya pengaruh parsial Tanggal Kadaluarsa terhadap Minat Beli.