Important Category Research Articles

Machine learning analysis to interpret the effect of the photocatalytic reaction rate constant (k) of semiconductor-based photocatalysts on dye removal

Photocatalytic reactions with semiconductor-based photocatalysts have been investigated extensively for application to wastewater treatment, especially dye degradation, yet the interactions between different process parameters have rarely been reported due to their complicated reaction mechanisms. Hence, this study aims to discern the impact of each factor, and each interaction between multiple factors on reaction rate constant (k) using a decision tree model. The dyes selected as target pollutants were indigo and malachite green, and 5 different semiconductor-based photocatalysts with 17 different compositions were tested, which generated 34 input features and 1527 data points. The Boruta Shapley Additive exPlanations (SHAP) feature selection for the 34 inputs found that 11 inputs were significantly important. The decision tree model exhibited for 11 input features with an R2 value of 0.94. The SHAP feature importance analysis suggested that photocatalytic experimental conditions, with an importance of 59%, was the most important input category, followed by atomic composition (39%) and physicochemical properties (2%). Additionally, the effects on k of the synergy between the metal cocatalysts and important experimental conditions were confirmed by two feature SHAP dependence plots, regardless of importance order. This work provides insight into the single and multiple factors that affect reaction rate and mechanism.

Geometric and Learning-Based Mesh Denoising: A Comprehensive Survey

Mesh denoising is a fundamental problem in digital geometry processing. It seeks to remove surface noise while preserving surface intrinsic signals as accurately as possible. While traditional wisdom has been built upon specialized priors to smooth surfaces, learning-based approaches are making their debut with great success in generalization and automation. In this work, we provide a comprehensive review of the advances in mesh denoising, containing both traditional geometric approaches and recent learning-based methods. First, to familiarize readers with the denoising tasks, we summarize four common issues in mesh denoising. We then provide two categorizations of the existing denoising methods. Furthermore, three important categories, including optimization-, filter-, and data-driven-based techniques, are introduced and analyzed in detail, respectively. Both qualitative and quantitative comparisons are illustrated, to demonstrate the effectiveness of the state-of-the-art denoising methods. Finally, potential directions of future work are pointed out to solve the common problems of these approaches. A mesh denoising benchmark is also built in this work, and future researchers will easily and conveniently evaluate their methods with state-of-the-art approaches. To aid reproducibility, we release our datasets and used results at https://github.com/chenhonghua/Mesh-Denoiser .

Importance of categories of crime for predicting future violent crime among handgun purchasers in California

BackgroundProhibiting the purchase and possession of firearms by those at risk of violence is an established approach to preventing firearm violence. Prior studies of legal purchasers have focused on convictions for specific crimes, such as violent misdemeanors and driving under the influence (DUI). We broaden that line of inquiry by investigating and comparing the associations between prior arrests for most categories of crime and subsequent arrest for violent offenses among legal handgun purchasers in California.MethodsIn this longitudinal cohort study of 79,678 legal handgun purchasers in California in 2001, we group arrest charges prior to their first purchases in 2001 according to categories defined by the Uniform Crime Report (UCR) Handbook. We use a gradient boosting machine to identify categories of offenses that are most important for predicting arrest for violent crime following firearm purchase. For each category identified, we then estimate the difference in risk of subsequent arrest for a violent offense using survival regression models.ResultsWe identified eight crime categories with high predictive importance: simple assaults, aggravated assaults, vehicle violations, weapon, other crimes, theft, drug abuse, and DUI. Compared to purchasers with no prior arrests, those with a prior arrest for any one of the eight important categories and no other categories were found to be at increased risk of arrest for a Crime Index-listed violent crime (murder, rape, robbery, aggravated assault), with the greatest estimated risk corresponding to the simple assault UCR category (adjusted hazard ratio 4.0; 95% CI 2.8–5.9). Simple assault was also associated with the greatest risk for subsequent arrest for firearm violence (adjusted hazard ratio 4.6; 95% CI 2.4–9.0) and any violent offense (adjusted hazard ratio 3.7; 95% CI 2.7–5.0).ConclusionThe findings of this study suggest that prior arrests for a broad array of crimes, both violent and non-violent, are associated with risk of subsequent violent crimes, including Crime Index-listed violent crimes and firearm violence, among legal purchasers of firearms. Current policies aimed at restricting access to firearms for individuals at increased risk of violence should be re-examined considering these findings.

Platelet Metabolic Profiling Reveals Glycolytic and 1-Carbon Metabolites Are Essential for GP VI-Stimulated Human Platelets-Brief Report.

Evolving evidence suggests that besides signaling pathways, platelet activation involves a complex interplay between metabolic pathways to support thrombus growth. Selective targeting of metabolic checkpoints may inhibit platelet activation and provide a novel antiplatelet strategy. We, therefore, examined global metabolic changes that occur during the transition of human platelets from resting to an activated state to identify metabolites and associated pathways that contribute to platelet activation. We performed metabolic profiling of resting and convulxin-stimulated human platelet samples. The differential levels, pathway analysis, and PCA (principal component analysis) were performed using Metaboanalyst. Metascape was used for metabolite network construction. Of the 401 metabolites identified, 202 metabolites were significantly upregulated, and 2 metabolites were downregulated in activated platelets. Of all the metabolites, lipids scored highly and constituted ≈50% of the identification. During activation, aerobic glycolysis supports energy demand and provides glycolytic intermediates required by metabolic pathways. Consistent with this, an important category of metabolites was carbohydrates, particularly the glycolysis intermediates that were significantly upregulated compared with resting platelets. We found that lysophospholipids such as 1-palmitoyl-GPA (glycero-3-phosphatidic acid), 1-stearoyl-GPS (glycero-3-phosphoserine), 1-palmitoyl-GPI (glycerophosphoinositol), 1-stearoyl-GPI, and 1-oleoyl-GPI were upregulated in activated platelets. We speculated that platelet activation could be linked to 1-carbon metabolism, a set of biochemical pathways that involve the transfer and use of 1-carbon units from amino acids, for cellular processes, including nucleotide and lysophospholipid synthesis. In alignment, based on pathway enrichment and network-based prioritization, the metabolites from amino acid metabolism, including serine, glutamate, and branched-chain amino acid pathway were upregulated in activated platelets, which might be supplemented by the high levels of glycolytic intermediates. Metabolic analysis of resting and activated platelets revealed that glycolysis and 1-carbon metabolism are necessary to support platelet activation.

Abstract 19037: Metabolomics Reveals Aerobic Glycolysis and 1-Carbon Metabolism as Major Metabolic Signature During Human Platelet Activation

Introduction: Evolving evidence suggests that besides signaling pathways, platelet activation involve a complex interplay between metabolic pathways to support thrombus growth. Selective targeting of metabolic checkpoints may inhibit platelet activation and provide a novel antiplatelet strategy. We examined global metabolic changes that occur during the transition of human platelets from resting to an activated state to identify metabolites and associated pathways that contribute to platelet activation. Methods: We performed metabolic profiling (through Metabolon Inc.) of resting and stimulated human platelet samples. The differential levels analysis, pathway analysis, and PCA were performed using Metaboanalyst. Metascape was used for metabolite network construction. Results: Of the 401 metabolites identified, 202 metabolites were significantly upregulated, and two metabolites were downregulated in activated platelets. Of all the metabolites, lipids scored highly and constituted ~50% of the identification. During activation, aerobic glycolysis supports energy demand and provides glycolytic intermediates required by metabolic pathways. Consistent with this, an important category of metabolites was carbohydrates, particularly the glycolysis intermediates that were significantly upregulated compared to resting platelets. We found that lysophospholipids such as 1-palmitoyl-GPA, 1-stearoyl-GPS, 1-palmitoyl-GPI, 1-stearoyl-GPI, 1-oleoyl-GPI were upregulated in activated platelets. We speculated that platelet activation could be linked to One-carbon (1C) metabolism, a set of biochemical pathways that involve transfer and use of 1C units from amino acids, for cellular processes, including nucleotide and lysophospholipid synthesis. In alignment, based on pathway enrichment and network-based prioritization, the metabolites from amino acid metabolism, including serine, glutamate, and branched-chain amino acids pathway were upregulated in activated platelets, which might be supplemented by the high levels of glycolytic intermediates. Conclusions: Metabolic analysis of resting and activated platelets revealed that aerobic glycolysis and 1-C carbon metabolism are vital to support platelet activation.

The Typical tRNA Co-Expresses Multiple 5' tRNA Halves Whose Sequences and Abundances Depend on Isodecoder and Isoacceptor and Change with Tissue Type, Cell Type, and Disease.

Transfer RNA-derived fragments (tRFs) are noncoding RNAs that arise from either mature transfer RNAs (tRNAs) or their precursors. One important category of tRFs comprises the tRNA halves, which are generated through cleavage at the anticodon. A given tRNA typically gives rise to several co-expressed 5'-tRNA halves (5'-tRHs) that differ in the location of their 3' ends. These 5'-tRHs, even though distinct, have traditionally been treated as indistinguishable from one another due to their near-identical sequences and lengths. We focused on co-expressed 5'-tRHs that arise from the same tRNA and systematically examined their exact sequences and abundances across 10 different human tissues. To this end, we manually curated and analyzed several hundred human RNA-seq datasets from NCBI's Sequence Run Archive (SRA). We grouped datasets from the same tissue into their own collection and examined each group separately. We found that a given tRNA produces different groups of co-expressed 5'-tRHs in different tissues, different cell lines, and different diseases. Importantly, the co-expressed 5'-tRHs differ in their sequences, absolute abundances, and relative abundances, even among tRNAs with near-identical sequences from the same isodecoder or isoacceptor group. The findings suggest that co-expressed 5'-tRHs that are produced from the same tRNA or closely related tRNAs have distinct, context-dependent roles. Moreover, our analyses show that cell lines modeling the same tissue type and disease may not be interchangeable when it comes to experimenting with tRFs.

Poromechanical modeling of fluid penetration in chemo-responsive gels: Parameter optimization and applications

As an important category of smart materials, stimuli-responsive hydrogels are highly concerned due to their extensive application possibilities and their outstanding biocompatibilities. The ability of responsive hydrogels about significant volume change by external stimuli inspires the design of electronic devices, for example, as sensors and actuators. The modeling of the hydrogel behavior enables the optimization of corresponding applications. In the present research, on the basis of the experimentally determined material parameters, a chemo-poromechanical model was implemented in COMSOL Multiphysics® to investigate the constricted swelling of hydrogels. The swelling kinetics affected by the diffusion coefficient is discussed in detail with numerical simulations.

CE Workshop 09: Cast Aside Traditional Notions of Statistical Significance, and Focus Instead on Characterizing the Magnitude of Effects that are Clinically or Scientifically Relevant

Abstract & Learning ObjectivesThere is an ongoing debate among statisticians and discipline scientists about the consequences of our persistent, dogmatic reliance on evaluating all statistical results as meaningful if and only if "p<0.05," regardless of context. This was never the intended goal of Ronald Fisher, nevertheless scientists have adopted it as a convenience, and the decades long dependence on "p<0.05" has had important negative consequences. In this presentation, I review common misconceptions about interpreting p-values, why we should consider de-emphasizing p-values, and why scientists should rely more on practical, clinical, or scientifically meaningful differences over arbitrary cut-offs. I will present several different metrics for evaluating and reporting effect magnitude, and whether or not data support the null vs. alternative hypothesis, under the frequentist paradigm, how Bayesian methods can augment or replace frequentist analyses, and a few options that help to clarify how important a finding may be. Throughout this talk, I advocate that discipline scientists take charge of sharing scientific results that are not based merely on arbitrary p-value cutoffs and other default logic, but instead based on their content expertise, in light of all of the specific relevant aspects of experimental design and experimental data, balancing the consequences of Type I vs Type II errors appropriately, and focusing on characterizing effects, rather than dichotomizing research into only two categories of importance (significant vs. not).Upon conclusion of this course, learners will be able to: 1.Discuss what p-values mean and how they are commonly misinterpreted.2.Explain the leading arguments promoted by the American Statistical Association with regard to why science should carefully reconsider if and how p-values should continue to dominate our decisions about what research should be published, and how scientists should be evaluating its worth.3.Apply new practices in how to evaluate and publish their own research, as well as how to evaluate research appearing in peer-reviewed journals, whether as consumers, reviewers, or editors.

Роман В. Скотта «Пуритане» в контексте романа И.А. Гончарова «Обломов»

The article describes the study of typological connections between the novel Puritans by Walter Scott and Oblomov by Ivan Goncharov. For the first time, these literary texts are considered through the prism of depiction as an artistic and aesthetic category, based on the genre system of fine arts. The name of the “Scottish sorcerer” is found in every novel of Goncharov’s trilogy (Ordinary History (1847), Oblomov (1859), The Precipice (1869). Most often, numerous landscapes can be found both on the pages of Scott’s and Goncharov’s novels. These landscape paintings are brought together by the plasticity of the image, decorativeness, careful detailing, epic manner and coloristic features. When creating idyllic landscapes, the Russian writer is guided by Scott’s style, combining both “high” poetic and everyday life within the framework of one image. Important in this regard are the landscapes of the famous ninth chapter of Oblomov’s Dream and as well as the pictures of Scott’s nature scattered throughout the text. In addition to the interdisciplinary genre of landscape, the authors have similar portrait descriptions (Oblomov and Milnwood). A special place in these novels is occupied by everyday scenes that convey the color of everyday life, the poeticization of reality , which is an important aesthetic category for both Russian and Scottish writers. They are in the spirit of the Flemish tradition. In addition, both novels are related by the typological similarity of storylines and characters (main and secondary).

CTM and QFD analysis: Framework for fintech adoption priority in commercial banks.

As financial technology (fintech) is developing rapidly, many commercial banks experience difficulty deciding what kind of fintech to primarily focus on when managing their business. Owing to limited resources and assets, there is a practical need for guidelines for banks' investments in fintech. This study provides a systemic procedure to identify promising fintech groups and their investment priorities. We propose a QFD-based decision support framework for banks by considering both aspects of the emerging fintech push identified using patent topic modeling and the market pull of banking services obtained from a survey of the literature and experts. An empirical application of the proposed QFD framework to major South Korean banks shows that transaction support technology, secure transactions, and trading platforms are the three most important fintech categories. The QFD results are utilized to guide individual banks for further investment strategies such as mergers and acquisitions, strategic partnerships, and spin-off operations. The proposed framework can be generalized and applied to other financial service firms.

Cloning, expression, and characterization of a surfactant-stable alkaline serine protease (KNBSSP1) from Bacillus safensis PRN1 with remarkable applications in laundry and leather industries

Proteases represent an important category of proteolytic enzymes with vast biotechnological applications in various industries like detergent, leather, agriculture, poultry, pharmaceutical, food, etc. The present study proposes an eco-friendly enzyme-mediated approach as opposed to conventional chemical approaches in detergent and laundry industries that are hazardous to human health and the environment. Accordingly, the knbsSP1gene, which encodes the trypsin-like serine protease KNBSSP1, from Bacillus safensis PRN1 was isolated, cloned into an expression vector (PET-28a), and expressed in the Escherichia coli cells BL21 (DE3). A single Ni-NTA affinity chromatography step was utilized to purify the recombinant protease (rKNBSSP1). The molecular weight of the rKNBSSP1 was approximately ∼33 kDa determined in Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE). The rKNBSSP1 showed optimal activity at 60 °C and pH 8. It retained above 70% of its enzyme activity at pH 10 and 70 °C. The protease was strongly inhibited by phenylmethylsulfonyl fluoride (PMSF) and diisopropyl fluorophosphate suggesting its inclusion in the serine family of protease. The rKNBSSP1 demonstrated outstanding compatibility and stability with metal ions, commercial detergents, and surfactants, exhibiting 97.8 ± 2.5% stability with Surf Excel, a commercial laundry detergent, and 96.9 ± 2.0% stability with SDS. Interestingly, the protease demonstrated blood-stained removal and goat skin dehairing (8 h) properties. All these remarkable characteristics make this protease a potential eco-friendly candidate in the detergent formulation and leather processing industries.

Analysis of the Key Factors Influencing Automation Transformation in Container Terminals Based on the Dempster–Shafer Evidence Interval Method

The steady growth of container volume and aggressive shipping alliances have intensified competition among terminals. With the rapid development and application of modern information and communication technology, automation is a great way to promote terminals’ sustainable development. The objectives of this study are to analyze the key factors influencing automation transformation and provide theoretical guidelines for implementing automation transformation. Based on the literature review, the main factors influencing the automation transformation of container terminals are characterized and analyzed. They are divided into four categories: technical feasibility, external promotion, self-constraints, and goals/demand. Thereafter, a novel multi-source data fusion method, the Dempster–Shafer evidence interval method (DSIM) based on Dempster–Shafer evidence theory and interval value, is proposed to fuse conflicting and uncertain opinions among experts. This method is effective for expert opinion elicitation. Using DSIM, the key factors’ relative importance and their relationship are examined based on the opinions of experts in China. The results show that technical feasibility is the most important factor category in the foundation of automation transformation. Finally, a generalized planning framework for constructing automation transformation schemes is established, providing references and suggestions for terminals’ decision-makers.

Financial indicators analysis using machine learning: Evidence from Chinese stock market

This study employs machine learning models to explore the predictive power of 10 categories of financial indicators on the Chinese stock market. We examine whether influential financial indicators fall into distinct categories of greater importance for predicting stock returns. The findings demonstrate that financial indicators across 10 categories hold predictive power for stock returns on Chinese market, with neural network models outperforming linear ones. Profitability and growth indicators are among the most influential indicators. This study contributes to a better understanding of financial indicators and demonstrates the effectiveness of machine learning models in the Chinese stock market.

Consumer engagement with sustainable wine: An application of the Transtheoretical Model

Sustainable wine is an important emergent wine category for which there is limited research on levels of consumer engagement and the multifaceted drivers of that engagement. Here, I extend prior research largely limited to organic wine, and apply the Transtheoretical Model of Behavioural Change (TTM) for the first time to determine consumer engagement around eight sustainable wine behaviours, and the role of purchase motivators, wine involvement and demographic factors in predicting those behaviours. The online survey of 727 Canadian wine consumers determined the action stage for each sustainable wine behaviour (precontemplation, contemplation, preparation, or action), and multinomial logistic regressions assessed the drivers of both action and inaction (precontemplation). Results show that most consumers are in a change stage with respect to sustainable wine behaviours (i.e., contemplation or preparation), suggesting the need for both education and sustainable certification initiatives. Generally, neither gender, income, province of residence, education nor the importance of price in wine purchase decisions associated with action stage for behaviours. In contrast, wine involvement and the importance of sustainability cues in wine purchase were the strongest and most consistent predictors of both action and inaction, while age and the importance of both taste expectation and perceived quality were predictive for some behaviours. I conclude that TTM is a very useful construct for assessing the nuances of consumer behaviour toward sustainable products, and the findings provide guidance for stakeholders interested in promoting greater sustainability in the wine industry through influencing consumer choice behaviour.

A two-stage chance constrained stochastic programming model for emergency supply distribution considering dynamic uncertainty

This paper presents a comprehensive approach to addressing the challenges of designing a reliable emergency logistics network under the dynamic uncertainty of natural disasters. The proposed multimodal transportation strategy based on level assignments can effectively mitigate the risk of facility disruptions and network uncertainty and enhance the adaptability of the system to diverse emergency supplies. The established two-stage chance constrained stochastic programming model and improved evolutionary algorithm are powerful tools for optimizing the network design and improving its resilience. Based on the real-world case of the Ya’an earthquake in China, the impacts of various practical constraints are analyzed. Several insights into the decision-making process of emergency logistics management are provided: managers should prioritize time utility over cost utility and use multiple aircraft and helicopters, supplies should be sorted into fewer and more important categories and placed in smaller packages for efficient transportation, multimodal transportation should be considered based on geographical and traffic conditions.

Adaptation to sentences and melodies when making judgments along a voice/non-voice continuum

Perceptual contrastive adaptation effects can be used to identify important perceptual features or categories. Our previous work revealed contrastive adaptation effects between voice and non-voice categories when adapting with repeated single vowels or musical tones. The current study investigated whether the effect generalizes to adaptors with higher ecological validity—sentences and melodies. Ten-step continua between a “voice” (female /a/, /o/, or /u/ vowels) and an “instrument” (bassoon, horn, or viola) were generated for each possible pair. A sentence spoken by a female voice, or a melody played on bassoon or horn, was presented, followed by a test stimulus from along the continuum. Contrastive adaptation effects were observed, with the test stimulus more likely to be identified as a voice following a musical melody and vice versa. Pilot data showed similar trends when the female voice adaptors were replaced with their male counterparts, suggesting that the effects may generalize across speaker gender and fundamental frequency. The results show that contrastive adaptation to voice and non-voice stimuli is a robust effect that does not rely on the repetition of simple adaptors or on a shared frequency range between the adaptors and test stimuli. [Work supported by NIH grant R01DC005216.]

The Intensive-Image and the Poetic Film Tradition: Notes on Ruiz, Deren, Pasolini, Buñuel and Deleuze

This article analyses an important category from Deleuze's philosophy – the notion of intensity – and explores its significance for Deleuze and the ways it can be used to think about poetic cinema. I use the concept of the intensive-image to define a cinematic style that dissipates narrative action in favour of more contemplative and sensory experiences, hence films that are able to turn onscreen reality into purely affective phenomena. The notion of intensity, I argue, does not allow us to reply easily to the question about representation (i.e., “what is the film about?”), mainly because its images are indeterminate and flowing, combined in a multiple manner that excludes any simple reduction to signification. The general argument that follows, illustrated by a careful reading of key poetic texts, is that the focus on the intensive-image inspires readers to reconsider Deleuze's classification of the cinema into two separate periods as well as to understand the ways in which intensity finds expression in films that produce problems, displacements and provocations. In the words of Pasolini, this is the poetic film tradition which must be placed diachronically in relation to the language of the film narrative, a diachronism that, he says, would appear destined to be always more pronounced. In the last section of this article, I look at Luis Buñuel's Un Chien Andalou (1929) as an early case of the poetic image and draw on key theorists and filmmakers who have discussed the cinema's power of affection and intensity.

Carrying life and death: the daily routine of hospital stretcher bearers in the context of COVID-19.

This article aims to analyze the daily work of stretcher bearers in a Federal Teaching and Research Hospital in the context of COVID-19, exploring the subjective aspects related to working in constant contact with death and the invisibility to which these workers are subjected. The proposed discussion stems from a more comprehensive qualitative investigation. The main methodological resource of the empirical research was the direct observation in the daily work that allowed one to capture nuances of the work in a dialectical analysis with the workers. The data obtained were analyzed from the perspective of Social Psychology of Work. Transience and invisibility were identified as important categories of analysis of this daily work, where the process of becoming a stretcher-bearer was marked by aspects of precariousness of work and vulnerability of the worker. Working in contact with death was also understood as a factor of invisibility, where the creation of bonds and humor appeared as a collective strategy to face the harshness of work. This article concluded by examining the importance of looking at the subjective aspects of the work carried out by stretcher bearers, as well as the expansion of research on the subject.

Carregando vidas e mortes: o cotidiano de trabalho de maqueiros hospitalares no contexto da COVID-19

Abstract This article aims to analyze the daily work of stretcher bearers in a Federal Teaching and Research Hospital in the context of COVID-19, exploring the subjective aspects related to working in constant contact with death and the invisibility to which these workers are subjected. The proposed discussion stems from a more comprehensive qualitative investigation. The main methodological resource of the empirical research was the direct observation in the daily work that allowed one to capture nuances of the work in a dialectical analysis with the workers. The data obtained were analyzed from the perspective of Social Psychology of Work. Transience and invisibility were identified as important categories of analysis of this daily work, where the process of becoming a stretcher-bearer was marked by aspects of precariousness of work and vulnerability of the worker. Working in contact with death was also understood as a factor of invisibility, where the creation of bonds and humor appeared as a collective strategy to face the harshness of work. This article concluded by examining the importance of looking at the subjective aspects of the work carried out by stretcher bearers, as well as the expansion of research on the subject.

Risk identification in managing small and medium-sized enterprises in Poland

Motivation: When running a business in the form of an enterprise, we agree to take the associated risk. The ubiquitous uncertainty about the future of enterprises, especially from the SME sector, makes risk management more and more important, which includes several successive stages. One of the most important is risk identification. Its purpose is relatively early detection of possible threats that, if they occur, will affect the company and its goals. Knowledge of the factors that may disrupt the functioning of an entity, especially a small and medium one, is the foundation in the approach to the issue of risk accompanying business activity. Properly conducted risk identification should cover all levels of the company’s operation and its relations with the environment.Aim: The article will isolate events, the occurrence of which small and medium-sized entrepreneurs fear the most. The aim of this article is to develop a register of risk sources for SMEs, and to identify the risks that pose the greatest threat to the operation of SMEs. Moreover, the level of individual sources of risk will be assessed allowing to identify the key disruptors for the operation of SME’s. The relationship between the level of risk and the size of the entity will also be examined.Results: Identification of factors threatening the functioning of enterprises increases the effectiveness of risk management that accompanies the conducted activity. Empirical research allowed to recognize the most important categories and the main sources of risk associated with SME activities. The dependency between risk categories and the size of the business was confirmed, with the strength of this relationship being moderate at best.