bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Text Length in Crowdsourced Multiple Choice Questions
Authors: Luger Sarah
Published: October 2022

Automated systems that aid in the development of Multiple Choice Questions (MCQs) have value for both educators, who spend large amounts of time creating novel questions, and students, who spend a great deal of effort both practicing for and taking tests. The current approach for measuring question difficulty in MCQs relies on models of how good pupils will perform and contrasts that with their lower-performing peers. MCQs can be difficult in many ways. This paper looks specifically at the effect of both the number of words in the question stem and in the answer options on question difficulty. This work is based on the hypothesis that questions are more difficult if the stem of the question and the answer options are semantically far apart. This hypothesis can be normalized, in part, with an analysis of the length of texts being compared. The MCQs used in the experiments were voluntarily authored by university students in biology courses. Future work includes additional experiments utilizing other aspects of this extensive crowdsourced data set.
State Detection Using Adaptive Human Sensor Sampling
Authors: Boutsis Ioannis , Kalogeraki Vana , Gunopulos Dimitrios
Published: October 2022

With the massive prevalence of smartphones, mobile social sensing systems in which humans acting as social sensors respond to geo-located crowdsourcing tasks, became extremely popular. Such systems can provide significant benefits particularly during crisis management and emergency situations. However, not only querying users can be extremely costly but also human sensors are mobile, subjective and their response delays can highly vary. In this paper we develop a social sensing system that performs sampling on mobile social sensors to achieve accurate and real-time detection of the state of emergency events. Our contributions are two-fold: (i) our approach can capture well emergencies even in large geographical regions, and (ii) our sampling approach considers the individual characteristics of the social sensors to maximize the probability of receiving accurate responses in a timely manner. We provide comprehensive experiments that indicate that our approach accurately identifies critical real-world events, has low overhead and reduces the classification error up to 90% compared to traditional approaches.
"Is There Anything Else I Can Help You With?" Challenges in Deploying an On-Demand Crowd-Powered Conversational Agent
Authors: Huang Ting-Hao , Lasecki Walter , Azaria Amos , Bigham Jeffrey
Published: October 2022

Intelligent conversational assistants, such as Apple's Siri, Microsoft's Cortana, and Amazon's Echo, have quickly become a part of our digital life. However, these assistants have major limitations, which prevents users from conversing with them as they would with human dialog partners. This limits our ability to observe how users really want to interact with the underlying system. To address this problem, we developed a crowd-powered conversational assistant, Chorus, and deployed it to see how users and workers would interact together when mediated by the system. Chorus sophisticatedly converses with end users over time by recruiting workers on demand, which in turn decide what might be the best response for each user sentence. Up to the first month of our deployment, 59 users have held conversations with Chorus during 320 conversational sessions. In this paper, we present an account of Chorus' deployment, with a focus on four challenges: (i) identifying when conversations are over, (ii) malicious users and workers, (iii) on-demand recruiting, and (iv) settings in which consensus is not enough. Our observations could assist the deployment of crowd-powered conversation systems and crowd-powered systems in general.
Investigating the Influence of Data Familiarity to Improve the Design of a Crowdsourcing Image Annotation System
Authors: Gurari Danna , Sameki Mehrnoosh , Betke Margrit
Published: October 2022

Crowdsourced demarcations of object boundaries in images (segmentations) are important for many vision-based applications. A commonly reported challenge is that a large percentage of crowd results are discarded due to concerns about quality. We conducted three studies to examine (1) how does the quality of crowdsourced segmentations differ for familiar everyday images versus unfamiliar biomedical images?, (2) how does making familiar images less recognizable (rotating images upside down) influence crowd work with respect to the quality of results, segmentation time, and segmentation detail?, and (3) how does crowd workers’ judgments of the ambiguity of the segmentation task, collected by voting, differ for familiar everyday images and unfamiliar biomedical images? We analyzed a total of 2,525 segmentations collected from 121 crowd workers and 1,850 votes from 55 crowd workers. Our results illustrate the potential benefit of explicitly accounting for human familiarity with the data when designing computer interfaces for human interaction.
Revenue-Maximizing Stable Pricing in Online Labor Markets
Authors: Xia Chaolun , Muthukrishnan Shan
Published: October 2022

In online labor markets, millions of paid tasks are performed by workers every day. We solve the stable pricing problem, that is, given the information about tasks and workers, to find a revenue-maximizing mechanism — pricing and allocation — that is stable (where no worker or task is treated unfairly), and truthful (tasks reveal their true needs). We propose two truthful, stable mechanisms named SMUP and SMNP. In SMUP, we use randomized uniform pricing, and prove that it has (1 + log h)-guarantee on revenue where h is the maximum price of a task. In SMNP, we use randomized non-uniform pricing, and prove that it has (3+3 log h)-guarantee on revenue, slightly worse than SMUP analytically. However our experiments show, SMNP has much less variance than SMUP. For the online setting when tasks arrive over time, we present a truthful online stable mechanism with (2 + 2 log h)-guarantee on revenue.
Drafty: Enlisting Users To Be Editors Who Maintain Structured Data
Authors: Wallace Shaun , Van Kleunen Lucy , Aubin-Le Quere Marianne , Peterkin Abraham , Huang Yirui , Huang Jeff
Published: October 2022

Structured datasets are difficult to keep up-to-date since the underlying facts evolve over time; curated data about business financials, organizational hierarchies, or drug interactions are constantly changing. Drafty is a platform that enlists visitors of an editable dataset to become ``user-editors'' to help solve this problem. It records and analyzes user-editors' within-page interactions to construct user interest profiles, creating a cyclical feedback mechanism that enables Drafty to target requests for specific corrections from user-editors. To validate the automatically generated user interest profiles, we surveyed participants who performed self-created tasks with Drafty and found their user interest score was 3.2 higher on data they were interested in versus data they had no interest in. Next, a 7-month live experiment compared the efficacy of user-editor corrections depending on whether they were asked to review data that matched their interests. Our findings suggest that user-editors are approximately 3 times more likely to provide accurate corrections for data matching their interest profiles, and about 2 times more likely to provide corrections in the first place.
Crowdsourcing a Parallel Corpus for Conceptual Analysis of Natural Language
Authors: Macbeth Jamie , Grandic Sandra
Published: October 2022

Computer users today are demanding greater performance from systems that understand and respond intelligently to human language as input. In the past, researchers proposed and built conceptual analysis systems that attempted to understand language in depth by decomposing a text into structures representing complex combinations of primitive acts, events, and state changes in the world the way people conceive them. However, these systems have traditionally been time-consuming and costly to build and maintain by hand. This paper presents two studies of crowdsourcing a parallel corpus to build conceptual analysis systems through machine learning. In the first study, we found that crowdworkers can view simple English sentences built around specific action words, and build conceptual structures that represent decompositions of the meaning of that action word into simple and complex combinations of conceptual primitives. The conceptual structures created by crowdworkers largely agree with a set of gold standard conceptual structures built by experts, but are often missing parts of the gold standard conceptualization. In the second study, we developed and tested a novel method for improving the corpus through a subsequent round of crowdsourcing; In this “refinement” step, we presented only conceptual structures to a second set of crowdworkers, and found that when crowdworkers could identify the action word in the original sentence based only on the conceptual structure, the conceptual structure was a stronger match to the gold standard structure for that sentence. We also calculated a statistically significant correlation between the number of crowdworkers who identified the original action word for a conceptual structure, and the degree of matching between the conceptual structure and a gold standard conceptual structure. This indicates that crowdsourcing may be used not only to generate the conceptual structures, but also to select only those of the highest quality for a parallel corpus linking them to natural language.
Octopus: A Framework for Cost-Quality-Time Optimization in Crowdsourcing
Authors: Goel Karan , Rajpal Shreya , Mausam Mausam
Published: October 2022

We present Octopus, an AI agent to jointly balance three conflicting task objectives on a micro-crowdsourcing marketplace – the quality of work, total cost incurred, and time to completion. Previous control agents have mostly focused on cost-quality, or cost-time tradeoffs, but not on directly controlling all three in concert. A naive formulation of three-objective optimization is intractable; Octopus takes a hierarchical POMDP approach, with three different components responsible for setting the pay per task, selecting the next task, and controlling task-level quality. We demonstrate that Octopus significantly outperforms existing state-of-the-art approaches on real experiments. We also deploy Octopus on Amazon Mechanical Turk, showing its ability to manage tasks in a real-world, dynamic setting.
An Empirical Study on Short- and Long-Term Effects of Self-Correction in Crowdsourced Microtasks
Authors: Kobayashi Masaki , Morita Hiromi , Matsubara Masaki , Shimizu Nobuyuki , Morishima Atsuyuki
Published: October 2022

Self-correction for crowdsourced tasks is a two-stage setting that allows a crowd worker to review the task results of other workers; the worker is then given a chance to update his/her results according to the review.Self-correction was proposed as an approach complementary to statistical algorithms in which workers independently perform the same task. It can provide higher-quality results with few additional costs. However, thus far, the effects have only been demonstrated in simulations, and empirical evaluations are needed. In addition, as self-correction gives feedback to workers, an interesting question arises: whether perceptual learning is observed in self-correction tasks. This paper reports our experimental results on self-corrections with a real-world crowdsourcing service.The empirical results show the following: (1) Self-correction is effective for making workers reconsider their judgments. (2) Self-correction is more effective if workers are shown task results produced by higher-quality workers during the second stage. (3) Perceptual learning effect is observed in some cases. Self-correction can give feedback that shows workers how to provide high-quality answers in future tasks.The findings imply that we can construct a positive loop to improve the quality of workers effectively.We also analyze in which cases perceptual learning can be observed with self-correction in crowdsourced microtasks.
Plexiglass: Multiplexing Passive and Active Tasks for More Efficient Crowdsourcing
Authors: Rao Akshay , Kaur Harmanpreet , Lasecki Walter
Published: October 2022

Efficiently scaling continuous real-time crowdsourcing tasks — which engage crowd workers over long periods of time to complete tasks, such as monitoring video for critical events — is challenging largely because of the cost of keeping people consistently engaged. Worse, for many continuous tasks on which progress cannot be immediately made, which we term passive tasks, this engagement effort is wasted until something becomes true about the environment (e.g., the annotation of a critical event cannot happen until the event is seen). In this paper, we present the idea of passive-active task multiplexing, in which continuous tasks that involve waiting for a change in state are completed concurrently with traditional (offline/non-real time) tasks. We then implement this idea in Plexiglass, a system that answers visual queries made by blind and low-vision users more efficiently by concurrently presenting a (passive) real-time sensing task and an (active) offline visual question answering tasks to workers. We explore different approaches to accomplishing this, and validate that task multiplexing can lead to an improvement in efficiency in these settings of more than 40% in terms of overall worker time taken and 85% decrease in cost of running continuous real-time tasks. This work has implications on how real-time crowdsourcing tasks are presented to workers, and it increases the feasibility of deploying continuous real-time crowdsourcing systems in real-world settings.
Platform-Related Factors in Repeatability and Reproducibility of Crowdsourcing Tasks
Authors: Qarout Rehab , Checco Alessandro , Demartini Gianluca , Bontcheva Kalina
Published: October 2022

Crowdsourcing platforms provide a convenient and scalable way to collect human-generated labels on-demand. This data can be used to train Artificial Intelligence (AI) systems or to evaluate the effectiveness of algorithms. The datasets generated by means of crowdsourcing are, however, dependent on many factors that affect their quality. These include, among others, the population sample bias introduced by aspects like task reward, requester reputation, and other filters introduced by the task design.In this paper, we analyse platform-related factors and study how they affect dataset characteristics by running a longitudinal study where we compare the reliability of results collected with repeated experiments over time and across crowdsourcing platforms. Results show that, under certain conditions: 1) experiments replicated across different platforms result in significantly different data quality levels while 2) the quality of data from repeated experiments over time is stable within the same platform. We identify some key task design variables that cause such variations and propose an experimentally validated set of actions to counteract these effects thus achieving reliable and repeatable crowdsourced data collection experiments.
Modeling Annotator Perspective and Polarized Opinions to Improve Hate Speech Detection
Authors: Akhtar Sohail , Basile Valerio , Patti Viviana
Published: October 2022

In this paper we propose an approach to exploit the fine-grained knowledge expressed by individual human annotators during a hate speech (HS) detection task, before the aggregation of single judgments in a gold standard dataset eliminates non-majority perspectives. We automatically divide the annotators into groups, aiming at grouping them by similar personal characteristics (ethnicity, social background, culture etc.). To serve a multi-lingual perspective, we performed classification experiments on three different Twitter datasets in English and Italian languages. We created different gold standards, one for each group, and trained a state-of-the-art deep learning model on them, showing that supervised models informed by different perspectives on the target phenomena outperform a baseline represented by models trained on fully aggregated data. Finally, we implemented an ensemble approach that combines the single perspective-aware classifiers into an inclusive model. The results show that this strategy further improves the classification performance, especially with a significant boost in the recall of HS prediction.
A Checklist to Combat Cognitive Biases in Crowdsourcing
Authors: Draws Tim , Rieger Alisa , Inel Oana , Gadiraju Ujwal , Tintarev Nava
Published: October 2022

Recent research has demonstrated that cognitive biases such as the confirmation bias or the anchoring effect can negatively affect the quality of crowdsourced data. In practice, however, such biases go unnoticed unless specifically assessed or controlled for. Task requesters need to ensure that task workflow and design choices do not trigger workers’ cognitive biases. Moreover, to facilitate the reuse of crowdsourced data collections, practitioners can benefit from understanding whether and which cognitive biases may be associated with the data. To this end, we propose a 12-item checklist adapted from business psychology to combat cognitive biases in crowdsourcing. We demonstrate the practical application of this checklist in a case study on viewpoint annotations for search results. Through a retrospective analysis of relevant crowdsourcing research that has been published at HCOMP in 2018, 2019, and 2020, we show that cognitive biases may often affect crowd workers but are typically not considered as potential sources of poor data quality. The checklist we propose is a practical tool that requesters can use to improve their task designs and appropriately describe potential limitations of collected data. It contributes to a body of efforts towards making human-labeled data more reliable and reusable.
Iterative Human-in-the-Loop Discovery of Unknown Unknowns in Image Datasets
Authors: Han Lei , Dong Xiao , Demartini Gianluca
Published: October 2022

Automatic predictions (e.g., recognizing objects in images) may result in systematic errors if certain classes are not well represented by training instances (these errors are called unknowns). When a model assigns high confidence scores to these wrong predictions (this type of error is called unknown unknowns), it becomes challenging to automatically identify them. In this paper, we present the first work on leveraging human intelligence to discover unknown unknowns (UUs) in an iterative way. The proposed methodology first differentiates the feature space generated by crowd workers labelling instances (e.g., images) in an active learning fashion from the space learned by the prediction model over a batch training phase, and thus identifies the predictions most likely to be UUs. Next, we add crowd labels collected for these discovered UUs to the training set and re-train the model with this extended dataset. This process is then repeated iteratively to discover more instances of both unknown and under-represented classes. Our experimental results show that the proposed methodology is able to (1) efficiently discover UUs, (2) significantly improve the quality of model predictions, and (3) to push UUs into known unknowns (i.e., the model makes mistakes but at least its classification confidence on those instances is low so those predictions can be discarded or post-processed) for further investigation. We additionally discuss the trade-off between prediction quality improvements and the human effort required to achieve those improvements. Our results bear implications on building cost-effective systems to discover UUs with humans in the loop.
Human+AI Crowd Task Assignment Considering Result Quality Requirements
Authors: Kobayashi Masaki , Wakabayashi Kei , Morishima Atsuyuki
Published: October 2022

This paper addresses the problem of dynamically assigning tasks to a crowd consisting of AI and human workers.
Currently, crowdsourcing the creation of AI programs is a common practice.
To apply such kinds of AI programs to the set of tasks, we often take the ``all-or-nothing'' approach that waits for the AI to be good enough.
However, this approach may prevent us from exploiting the answers provided by the AI until the process is completed, and also prevents the exploration of different AI candidates.
Therefore, integrating the created AI, both with other AIs and human computation, to obtain a more efficient human-AI team is not trivial.
In this paper, we propose a method that addresses these issues by adopting a ``divide-and-conquer'' strategy for AI worker evaluation.
Here, the assignment is optimal when the number of task assignments to humans is minimal, as long as the final results satisfy a given quality requirement.
This paper presents some theoretical analyses of the proposed method and an extensive set of experiments conducted with open benchmarks and real-world datasets.
The results show that the algorithm can assign many more tasks than the baselines to AI when it is difficult for AIs to satisfy the quality requirement for the whole set of tasks. They also show that it can flexibly change the number of tasks assigned to multiple AI workers in accordance with the performance of the available AI workers.
Rapid Instance-Level Knowledge Acquisition for Google Maps from Class-Level Common Sense
Authors: Welty Chris , Aroyo Lora , Korn Flip , McCarthy Sara M. , Zhao Shubin
Published: October 2022

Successful knowledge graphs (KGs) solved the historical knowledge acquisition bottleneck by supplanting an expert focus with a simple, crowd-friendly one: KG nodes represent popular people, places, organizations, etc., and the graph arcs represent common sense relations like affiliations, locations, etc. Techniques for more general, categorical, KG curation do not seem to have made the same transition: the KG research community is still largely focused on methods that belie the common-sense characteristics of successful KGs. In this paper, we propose a simple approach to acquiring and reasoning with class-level attributes from the crowd that represent broad common sense associations between categories. We pick a very real industrial-scale data set and problem: how to augment an existing knowledge graph of places and products with associations between them indicating the availability of the products at those places, which would enable a KG to provide answers to questions like, "Where can I buy milk nearby?" This problem has several practical challenges, not least of which is that only 30% of physical stores (i.e. brick & mortar stores) have a website, and fewer list their product inventory, leaving a large acquisition gap to be filled by methods other than information extraction (IE). Based on a KG-inspired intuition that a lot of the class-level pairs are part of people's general common sense, e.g. everyone knows grocery stores sell milk and don't sell asphalt, we acquired a mixture of instance- and class- level pairs (e.g. , , resp.) from a novel 3-tier crowdsourcing method, and demonstrate the scalability advantages of the class-level approach. Our results show that crowdsourced class-level knowledge can provide rapid scaling of knowledge acquisition in this and similar domains, as well as long-term value in the KG.
The Geopolitics of Beauty
Authors: Gagnier Regenia
Published: October 2022

Building on eighteenth-century philosophical traditions, Victorian aesthetics were often posed as an antidote to the vicissitudes of the Industrial Revolution and the political and economic demands of the marketplace, and in most cultures undergoing modernization the Beautiful has often functioned in opposition to the forces of power and instrumentality and their corrosive effects on social life. Readers of 19 will be familiar with the Victorian environment — the workhouses, the poverty, the invention and technology, the urbanization, the Empire. By the last decades of the nineteenth century, the Islamic world saw the dissolution of the Ottoman Empire and the effects of European colonization, and modernizing forces in China led to the greatest rejection of a 3000-year-old tradition in world history. This Forum contribution compares Western, Islamic, and Chinese aesthetics. My argument is that since the nineteenth century, modern aesthetics have typically functioned dialectically against the constraints of scarcity, exploitation, and tyranny, and that within them Nature and the natural world play a particularly valuable role, one that is threatened today in the market failure of global warming and unsustainability.
SHInE - Simultaneous HCR, Immunohistochemistry, Nuclear staining and EdU v1
Authors: Coric Aida
Published: October 2022

This protocol allows the multiplexed use of four different molecular labelling techniques in whole-mount Platynereis tissues. In short, gene expression (via in situ HCR 3.0), cell proliferation (via EdU labelling), proteins (via Immunohistochemistry) and nuclei (DAPI/Hoechst staining) can be assessed in whole-mount tissue samples, allowing the co-visualisation of various types of molecules in the same specimen. This protocol combines knowledge from multiple sources (see below), and is being submitted in parallel with a manuscript detailing the applications of the method. (We will add the reference as soon as it's available.) We successfully applied this protocol to heads and posterior regenerates of the bristleworm Platynereis dumerilii, at various developmental stages of the animal. Given the general nature of the detected molecules, and the wide-spread use of the individual detection techniques, we anticipate that this protocol will be well applicable to a wider range of model systems. References: 1) Choi HMT, Calvert CR, Husain N, Huss D, Barsi JC, Deverman BE, Hunter RC, Kato M, Lee SM, Abelin ACT, Rosenthal AZ, Akbari OS, Li Y, Hay BA, Sternberg PW, Patterson PH, Davidson EH, Mazmanian SK, Prober DA, Rijn M van de, Leadbetter JR, Newman DK, Readhead C, Bronner ME, Wold B, Lansford R, Sauka-Spengler T, Fraser SE, Pierce NA. 2016. Mapping a multiplexed zoo of mRNA expression. Development 143:3632–3637. doi:10.1242/dev.140137 2) Choi HMT, Schwarzkopf M, Fornace ME, Acharya A, Artavanis G, Stegmaier J, Cunha A, Pierce NA. 2018. Third-generation in situ hybridization chain reaction: multiplexed, quantitative, sensitive, versatile, robust. Development 145:dev165753. doi:10.1242/dev.165753 3) Kuehn E, Clausen DS, Null RW, Metzger BM, Willis AD, Özpolat BD. 2021. Segment number threshold determines juvenile onset of germline cluster proliferation in Platynereis dumerilii. Biorxiv 2021.04.22.439825. doi:10.1101/2021.04.22.439825 4) Pende M, Vadiwala K, Schmidbaur H, Stockinger AW, Murawala P, Saghafi S, Dekens MPS, Becker K, Revilla-i-Domingo R, Papadopoulos S-C, Zurl M, Pasierbek P, Simakov O, Tanaka EM, Raible F, Dodt H-U. 2020. A versatile depigmentation, clearing, and labeling method for exploring nervous system diversity. Sci Adv 6:eaba0365. doi:10.1126/sciadv.aba0365 5) Salic A, Mitchison TJ. 2008. A chemical method for fast and sensitive detection of DNA synthesis in vivo. Proc National Acad Sci 105:2415–2420. doi:10.1073/pnas.0712168105 6) Tessmar-Raible K, Steinmetz PRH, Snyman H, Hassel M, Arendt D. 2005. Fluorescent two-color whole mount in situ hybridization in Platynereis dumerilii (Polychaeta, Annelida), an emerging marine molecular model for evolution and development. Biotechniques 39:460–464. doi:10.2144/000112023
Co-existing OSA reduce Nuss surgery efficacy v1
Authors: Yang Mei-Chen
Published: October 2022

Nuss surgery is effective for pectus excavatum (PE), with a recurrence rate of 1.2–27%. Re-do surgery is effective, but still has a 6% failure rate. Patients with obstructive sleep apnea (OSA) experience repetitive PE-associated sternal depression during sleep. As the prevalence of OSA among PE patients is higher than the average, co-existing OSA in PE patients might negatively impact the efficacy of Nuss surgery. This study aimed to evaluate the impact of co-existing OSA on Nuss surgery in patients with PE.Totally, twenty adult patients with PEonly and nine patients with PE and OSAwere analyzed. Polysomnography was performed before Nuss surgery to evaluate OSA. Sternovertebral distance (SVD) and radiographic Haller index (RHI) were recorded before surgery and at 3, 6, and 24 months postoperatively. The results showed that, post-operatively, percentage changes in SVD in patients with PE only at 3, 6, and 24 months postoperatively were significantly increased compared with those in thepatients with PE and OSA (31.1% vs. 14.1% at 3 months; 37.5% vs. 21.4% at 6 months; 42.5% vs. 19.2% at 24 months), while percentage changes in RHI were significantly lower in patients with PE only than in the patients with PE and OSA (-22.9% vs. -9.3% at 3 months; -27.9% vs. -18.7% at 6 months; -30.6% vs. -16.7% at 24 months). The study showed that co-existing OSA might reduce the efficacy of Nuss surgeryfor patients with PE. We recommended that patients with PE should be evaluated for OSA before surgery and be promptly treated for OSA until making sure the PE does not recur after bal removal.
Chromosomal instability and abnormal mitochondrial activity induced by two synthetic food colorants
Authors:   Cell and Molecular Biology Division, Department of Botany, University of Calicut, Pokkadath Aswathi , Chembrammal Reshmi ,   Cell and Molecular Biology Division, Department of Botany, University of Calicut, Thoppil John Ernest ,   Cell and Molecular Biology Division, Department of Botany, University of Calicut
Published: October 2022

The artificial colorants act as a potent cytotoxic agent at the consumer level, whose analysis is inevitable. The investigation is mainly focused to analyze the toxicity of two commonly used synthetic food colorants (Brilliant blue and Fast green) with the help of Allium cepa root tip assay. The frequency of aberrations and the concentrations of both the colorants were found to be positively correlated in the chromosome studies. The integrity of the cell membranes, which is a potent parameter to detect cellular damage was detected using Evan’s blue staining. 2,3,5-triphenyl tetrazolium chloride (TTC) method was also adopted to determine the damaging effects of the synthetic molecules on the mitochondrial oxidative properties in the root tip cells. Both food colorants showed prominent membrane damage and mitochondrial activity reduction in the test material.
A Healthy City for All? Social Services’ Roles in Collaborative Urban Development
Authors: Berglund-Snodgrass Lina , Fjellfeldt Maria , Högström Ebba , Markström Urban
Published: October 2022

There is broad consensus among policymakers about the urgency of developing healthy, inclusive, and socially sustainable cities. In the Swedish context, social services are considered to have knowledge that needs to be integrated into the broader urban development processes in order to accomplish such ends. This article aims to better understand the ways in which social service officials collaborate in urban development processes for developing the social dimensions of healthy cities. We draw from neo-institutional theories, which set out actors (e.g., social service officials) as acting according to a logic of appropriateness, which means that actors do what they see as appropriate for themselves in a specific type of situation. Based on semi-structured interviews with social services officials in 10 Swedish municipalities on their experiences of collaboration in the development of housing and living environments for people with psychiatric disabilities, we identified that they act based on (a) a pragmatic rule of conduct through the role of the problem solver, (b) a bureaucratic rule of conduct through the role of the knowledge provider, and (c) activist rule of conduct through the role of the advocator. In these roles, they have little authority in the development processes, and are unable to set the agenda for the social dimensions of healthy cities but act as the moral consciousness by looking out for everyone’s right to equal living conditions in urban development.
Laser induced thermotherapy of multiple actinic keratosis
Authors: Sukhova Tatiana Evgenievna , Molochkova Yulia Vladimirovna , Pronina Anna Igorevna
Published: October 2022

Actinic keratosis (AK) is one of the most common precancerous diseases of the skin, which is characterized by local intraepidermal atypia of keratinocytes that occurs under the influence of ultraviolet radiation, clinically manifested by typical foci of hyperkeratosis in exposed areas of the skin. This is an urgent medical and social problem due to the potential tendency of atypical keratinocytes to malignant transformation, proliferation of keratinocytes and their spread beyond the epidermis with the development of tumor progression [1]. Recently, a number of authors have established important features of the course of this precancerous tumor. First of all, we are talking about an increased risk of malignant transformation of AK into squamous cell carcinoma in the presence of a history of visceral malignancy, as well as the same changes in the lesion and the adjacent clinically unaffected skin in the form of accumulation of genetic and epigenetic mutations that form "cancerization fields" [ 33,34], indicating the need to treat AK, especially multiple foci, using the ablastic rule with the capture of 1-1.5 cm of apparently healthy skin [35,36]. For the treatment of multiple AK foci in a patient with an aggravated oncological history, for the first time, we used, in an independent version, a modern method of treatment - laser-induced thermotherapy (LITT). LITT is a non-invasive, antitumor, immunomodulatory method based on the selective death of atypical keratinocytes in the epidermis by local tissue heating to a temperature of 42.5-44℃ (hyperthermia) caused by infrared laser radiation with a wavelength of 800-1300 nm. The presented case of AK in a patient with breast cancer in history was characterized by a combination of keratotic and erythematous forms of the tumor. At the same time, LITT with an extended exposure zone by 1 cm from the visible boundaries of the lesions was not only clinically effective in terms of immediate and long-term results, but also gave an excellent cosmetic result with a completely satisfactory tolerability of the treatment procedure.
Study of the influence of fractional photothermolysis and biorevitalization on skin rejuvenation in middle aged women
Authors: Kuznetsova Evgeniya K. , Kudrevich Yuliya V. , Ziganshin Oleg R. , Zayatc Tatiana A.
Published: October 2022

BACKGROUND:There is a fairly high demand of patients for procedures to improve the appearance and rejuvenation of the skin, while the methods used have a different, often aggressive principle of action, requiring a long period of rehabilitation.
AIM:The purpose of the work was to determine the safety and effectiveness of exposure to the skin in order to improve its quality and rejuvenate such methods as biorevitalization and fractional photothermolysis using an erbium laser, to determine changes in the structural components of the skin that affect its condition, before and after exposure to various types of procedures.
MATERIALS AND METHODS:40 patients were examined, who were divided into two groups. Patients of the first group received the biorevitalization procedure, the second group of patients underwent fractional photothermolysis. A fragment of skin was taken from all patients before and after the procedures and the volumetric density of collagen types I and III, laminin, growth factors (VEGF, FGF, TGF, IGF) in the dermis and epidermis, interleukins (IL-4, IL-1) in the dermis and epidermis was assessed. We assessed the level of changes in these indicators before and after procedures in different groups, correlation analysis.
RESULTS:An increase in the volumetric density of collagens, laminin, growth factors, interleukins was recorded, but the correlations in different groups were different. The structural parameters of the skin during biorevitalization positively correlated with growth factors, and with fractional photothermolysis with indicators of local immunity, such as interleukins, TGF.
CONCLUSION:It was concluded that both biorevitalization and laser exposure have a positive effect on the quality of the skin, but in the case of revitalization, these changes occur through the stimulating action of hyaluronic acid, the entrainment of growth factors in the skin, and in the case of fractional photothermolysis, the formation of new collagen, strengthening of the dermo-epidermal connections occur through the processes of inflammation and regeneration.
Native Thiol, Total Thiol, and Dynamic Disulfide Profile in Patients with Gastrointestinal System Cancer
Authors: Çiçek Hülya , Savaş Hanım Seval , Yıldırım Mustafa , Gürbüz Hüseyin
Published: October 2022

This study aims to evaluate the use of serum native thiol (NT), total thiol (TT), and dynamic disulfide (DD) levels as biomarkers in patients with gastrointestinal system (GIS) cancer with different cancer types by comparing with healthy controls. A total of 108 subjects consisting of68 patients with GIS cancer and 40 healthy individuals as a control group were included in the study. Serum NT, TT, and DD levels were measured by an automated method developed by Erel. There was a statistically significant difference between NT levels of GIS cancer and the control group (P = 0.001). However, there were no significant differences between male and female patients in terms of serum NT levels (P = 0.08). Similarly, no significant difference was observed when comparing serum NT levels among GIS cancer types (P = 0.886). The serum TT levels were statistically significant difference (P = 0.013) in GIS cancer, 141.82 ± 48.24 μmol/l (12.7-243.9) compare to the control group, 166.03 ± 56.23 μmol/l (12.7-326.8). When the serum TT and DD levels of the patients were compared according to gender, no significant difference was found (P = 0.243 and P = 0.362, respectively). In addition, the TT levels were not significantly difference among GIS malignancies (P = 0.765). When the patient and control groups were compared in terms of DD levels, no statistically significant difference was found (P = 0.378). In conclusion, it was determined that some parameters differ statistically between patients with GIS cancer and healthy controls. Therefore, there is a significant relationship between the thiol/disulfide balance with GIS cancer. This result suggests that oxidative stress may play a role in the development of the GIS cancer, consistent with the findings in this study, but not in terms of DD levels.
Role of magnetic resonance imaging in the evaluation of seizures
Authors: Dhar Namrita , Magotra Vipan
Published: October 2022

Background: A seizure is a clinical condition caused by a transitory event of unusual unrestrained or recurring neuronal activity in the brain.Repeated unprovoked seizures are described as epilepsy. Seizures and epilepsy are major public health problems in developing countries like India with a serious impact on patients and society. The objective of the present study is to evaluate the magnetic resonance imaging (MRI) findings in patients with seizures.Methods: This cross-sectional observational study was conducted in the Department of Radiodiagnosis and Imaging, Government Medical College, Jammu on 125 patients referred with clinical features of seizures.Results: In the present study, MRI findings were normal in 58 (46.4%) cases and revealed a spectrum of abnormalities in 67 (53.6%) cases. Out of 67 abnormal MRI findings, the common abnormalities noted were – neurocysticercosis (NCC) in 11 patients(8.8%), tuberculoma in 9 patients (7.2%), tumors in 7 patients (5.6%), hypoxic ischemic insult in 8 patients (6.4%), developmental cortical malformations in 6 patients (4.8%), encephalitis in 4 patients (3.2%), phakomatosis in 5 patients (4.0%), chronic infarct in 4 patients (3.2%), traumatic brain injury in 3 patients (3.2%), cavernoma in 2 patients (1.6%), mesial temporal sclerosis in 2 patients (1.6%), cerebral abscess in 2 patients (1.6%), and metabolic cause, multiple sclerosis, arterial infarct, and venous thrombosis, in one patient each respectively.Conclusions: From our study, it could be concluded that MRI has an outstanding place in the evaluation of patients presenting with seizures. The findings of the present study will be valuable in epilepsy management in developing country like ours and MRI will emerge as a beam of light amidst a storm of myth for patients with seizures.
Mexico's colonial and early postcolonial state-formation: A political-Marxist account
Authors: Van Rankin-Anaya Armando
Published: October 2022

This paper analyses the agrarian hacienda as the chief defining political-economic institution that shaped class composition and state formation of colonial and early postcolonial Mexico. Following the insightful theoretical framework of political Marxism, this article reviews the evolution of Mexican social property relations from the colonization (in the 16th century) to independence (in the 19th century) employing a novel methodology. Due to the highly historicist-oriented perspective of this neo-Marxist wisdom –and its concrete notion of capitalism as a property regime politically constructed– this paper argues that the agrarian hacienda was substantially precapitalist. This reexamination, in turn, challenges structural and pancapitalist accounts within neo-Marxist thought such as Wallerstein’s world-system theory that argues conversely: that European colonialism in the Americas was capitalist. This work aims to expand the application of political Marxism literature to the Latin American context.
A Multi-Layered Edge-Secured Cloud Framework for Healthcare Monitoring in Old-Age Homes Using Smart Systems Driven by Comprehensive User Interaction
Authors: Raghu Rishi , Jayaraman Vijayashree , Jayaraman Jayashree , Nukala Sai Surya Varshith , Díaz Vicente García
Published: October 2022

Most chronic diseases and health disorders at early stages are either asymptomatic or have long latency periods, especially among the older age groups. This eventually becomes difficult to handle at later stages and in some cases even becomes the cause of death. Even though cloud-based smart systems have delivered promising results in the field of healthcare monitoring, due to high latency, network congestion, poor user control, etc. smart systems fail to meet the required needs. Especially in old-age homes, where 24/7 service is required, healthcare facilities need robust, prompt, and real-time smart systems. This paper proposes a multi-layered cloud-edge architecture for old-age homes that operates on smart systems to detect anomalies, predict future risks, and process data across the doctor, patient, and the cloud in real-time. The device operates mostly on the edge layers to process patient information using neural networks and send alerts to the end-user based on predictions and anomalies before sending the aggregated data to the cloud. The proposed framework includes smart devices which are facilitated with responsive user interfaces which keep the patients and doctors in complete control of the smart system while maintaining efficient data communication and security. This paper also compares the latency delay between IoT devices and cloud, also between IoT devices and edge devices.
Synthesis and some properties of colloidal quantum dots of mercury selenide
Authors:   OOO “NPP Volga”, Tsvetkova Olga Yu. , Zhukov Nikolay D. ,   OOO “NPP Volga”, Smirnova Tatiana D. ,   Saratov State University, Shtykov Sergey N. ,   Saratov State University
Published: October 2022

The synthesis of colloidal quantum dots of mercury selenide using mercury oxide as a precursor is proposed. The proposed method is characterized by the use of a less toxic component in the reaction mixture - mercury oxide. The transmission electron microscopy method established an average diameter of 5–6 nm and the shape of quantum dots. A histogram of the size distribution of synthesized nanoparticles is presented. An important property of the synthesized nanoparticles is the crystal structure established by X-ray diffraction analysis. The established properties of the synthesized nanocrystals coincide with the literature data. The elemental composition of the nanoparticles was controlled by X-ray microanalysis. It is established that the chemical composition of quantum dots corresponds to the stoichiometric ratio of Hg elements : Se = 0,98 : 1,00. In addition, it follows from the X-ray that the oxygen content has been identified in silicon and carbon compounds, HgSe-based quantum dots do not contain traces of oxidation. The optical properties of quantum dots depend on the size of the nanoparticles. If the average diameter does not exceed 10 nm, mercury selenide particles are characterized by a monocrystalline structure with intraband absorption, the spectral energy distribution of which is subjected to dimensional quantization. As can be seen from the absorption spectra, the synthesized nanoparticles are characterized by absorption bands in the IR region, in the wavelength range up to 40 microns. The synthesized quantum dots do not possess luminescent properties, which, according to the literature data, is associated with a low probability of exciton formation for small nanoparticles (5–6 nm).
Phase tree, forecast of crystallizing phases and description of chemical interaction in the system KCl–CaCl2–BaCl2
Authors:   Samara State Technical University, Garkushin Ivan K. , Lavrenteva Olga V. ,   Samara State Technical University, Shterenberg Alexandr M. ,   Samara State Technical University
Published: October 2022

The construction of a phases tree of a ternary system with three binary compounds KCaCl3, K2BaCl4, CaBaCl4 is given. The phase tree includes four secondary phase triangles CaCl2–KCaCl3–СаBaCl4, CaBaCl4–KCaCl3–BaCl2, KCaCl3–BaCl2–K2BaCl4 and KCaCl3–CaBaCl4–KCl. These triangles are connected by three stable secants KCaCl3–СаBaCl4, KCaCl3–BaCl2, KCaCl3–K2BaCl4. Crystallizing phases in stable and secant elements correspond to the simplex tops. The presence of binary compounds on adjacent sides of the composition triangle made it possible to reveal, in addition to addition reactions, the reactions of mutual exchange. The description of the main reactions for mixtures corresponding to the intersection points of unstable and stable secants is carried out. The possibility of these reactions has been confirmed by thermodynamic calculation of thermal effects and Gibbs energies for standard conditions. Using the constructed tree of phases for any mixtures in a triangle of compositions, including 2...6 salts, a description of the chemical interaction by the ion balance method is carried out. The ion balance method allows you to determine the final composition after reaction in a secant or stable element. Complex gross-reactions are presented as a set of simpler reaction equations. The proposed method for description the chemical interaction can be used for other types of ternary systems with exchange reactions (metathesis) – with ion-exchange processes and with displacement reactions.