Detecting Collusion in Public Procurement: A Comparative Study of Machine Learning Models

Detecting collusion in public procurement is critical to ensure fair and transparent practices in government acquisitions. Bid collusion in auctions poses a major challenge in public procurement by causing unfair price hikes through unlawful cooperation among competing firms, consistently affecting the overall supply chain. This study uses machine learning methods to investigate collusion in public procurement processes. It delves deeply into exploring multiple machine learning models such as random forests, extra tree classifiers, support vector classifiers, Neural Networks, Gradient Boosting, and various combinations of models for collusion detection. First, the models were trained using available data, followed by the inclusion of screening variables derived from bid information as additional features. The additional features were fed to the models, which went through fine-tuning of parameters. Additionally, comparative analyses were carried out to evaluate the merits and drawbacks of each model. Metrics including Accuracy, balanced accuracy, precision, recall, F1-score, and ROC-AUC score were evaluated, providing a comprehensive evaluation framework. Various settings were used to compare which set of inputs gives the highest accuracy in collusion detection. The ROC-AUC analysis brought forward crucial insights, particularly regarding models' abilities to minimize false positives while maximizing true positives. Models like Random Forest and Gradient Boosting demonstrated superior performance, showcasing lower false positive rates—a crucial aspect when identifying collusion in public procurement. Additionally, the study underscores the significance of feature engineering in collusion detection. Specifically, attributes like screens - CV, SPD, DIFFP, RD, SKEW, KURTO, and KS significantly aid algorithms in processing data effectively to identify collusion patterns. The outcomes of this study carry significant implications for both the specific domain under investigation and the broader field of collusion detection. Ultimately, this research provides a valuable guide for policymakers, procurement officers, and data scientists, offering valuable insights into the effective machine learning techniques tailored for detecting collusion in public procurement

AC/DC conductivity and dielectric relaxation behavior of aqueous solutions of 1-butyl-3-methylimidazolium chloride

The complex relative dielectric function ɛ*(f) = ɛ' - jɛ" of aqueous solutions of 1-butyl-3-methylimidazolium chloride [BMiM][Cl] of varying concentrations, has been measured using precision LCR meter in the frequency range 20 Hz to 2 MHz at four different temperatures 293.15, 303.15, 313.15 and 323.15 K. Complex ac conductivity σ*(f) of the liquid samples have been determined from the measured ɛ*(f). DC conductivity σdc of the samples have also been determined. Values of σdc at different concentrations have been fitted to the empirical Casteel-Amis (CA) equation. The influence of concentration and temperature variation on the complex permittivity and electrical conductivity of the solutions of [BMiM][Cl] in distilled water has been discussed. The molar conductivities and the infinite dilution conductance of these ionic liquids have also been determined. Orientational relaxation behavior of the aqueous solutions of [BMiM][Cl] has also been studied by measuring complex permittivity in the frequency range 1 GHz to 20 GHz using vector network analyzer. Various processes contributed to the electrical/dielectric properties of the solutions of [BMiM][Cl] in distilled water have been explored

Systems of Systems Engineering Thesaurus Approach: From Concept to Realisation

The developing discipline of Systems of Systems Engineering (SoSE) is gaining attention in an increasingly broad range of domains; however, each domain comes with its own set of terms and concepts so that there may be confusion between different domains ostensibly engaged in similar challenges. SoSE is faced with concept multiplicity (one term, more than one concept) and term multiplicity (one concept, more than one term). It is unrealistic to expect long-established domains to simply change ontology to match with other domains, but a means of recognising related concepts and terms across domains and across industrial sectors will enable more rapid progress to be made in the development of SoSE. The approach taken to generating a thesaurus, through which such relationships can be documented, is presented. The approach is essentially consultative among SoSE experts and the current version of the thesaurus is available online. A combination of problem statement definition and logical decomposition has been used; the method is described and application is illustrated using well-known terms

Surgical resection of a giant peripheral ossifying fibroma in mouth floor managed with fiberscopic intubation

Tracheal intubation for general anesthesia can sometimes be difficult in patients with a large mass in the mouth floor. Preoperative evaluation of the patient's airway is most important when treating large oral disease

The ties that bind: How the dominance of WeChat combines with guanxi to inhibit and constrain China’s contentious politics

Despite the market dominance of the 'WeChat' app in today's China, we currently know little about its significance for contentious politics. This paper argues that MIMAs facilitate communication within relatively strong tie networks (compared to conventional Social Network Sites) which prior research indicates is potentially consequential for patterns of contentious political engagement. Drawing on evidence from a series of Chinese WeChat-user focus groups, we reveal that these ‘chat apps’ create spaces where, although users are often connected through strong ties offline, contentious politics rarely manifests. This trend is driven by a range of dynamics, which we elaborate in a theoretically-informed thematic analysis. When contentious politics does emerge, it is reported by our focus group participants to be largely confined to matters of ‘pragmatic’ and/or ‘safe’ politics that concern defending the interests of individuals or discrete groups, but do not challenge the wider political system

Desert Farming Benefits from Microbial Potential in Arid Soils and Promotes Diversity and Plant Health

BACKGROUND: To convert deserts into arable, green landscapes is a global vision, and desert farming is a strong growing area of agriculture world-wide. However, its effect on diversity of soil microbial communities, which are responsible for important ecosystem services like plant health, is still not known. METHODOLOGY/PRINCIPAL FINDINGS: We studied the impact of long-term agriculture on desert soil in one of the most prominent examples for organic desert farming in Sekem (Egypt). Using a polyphasic methodological approach to analyse microbial communities in soil as well as associated with cultivated plants, drastic effects caused by 30 years of agriculture were detected. Analysing bacterial fingerprints, we found statistically significant differences between agricultural and native desert soil of about 60%. A pyrosequencing-based analysis of the 16S rRNA gene regions showed higher diversity in agricultural than in desert soil (Shannon diversity indices: 11.21/7.90), and displayed structural differences. The proportion of Firmicutes in field soil was significantly higher (37%) than in the desert (11%). Bacillus and Paenibacillus play the key role: they represented 96% of the antagonists towards phytopathogens, and identical 16S rRNA sequences in the amplicon library and for isolates were detected. The proportion of antagonistic strains was doubled in field in comparison to desert soil (21.6%/12.4%); disease-suppressive bacteria were especially enriched in plant roots. On the opposite, several extremophilic bacterial groups, e.g., Acidimicrobium, Rubellimicrobium and Deinococcus-Thermus, disappeared from soil after agricultural use. The N-fixing Herbaspirillum group only occurred in desert soil. Soil bacterial communities were strongly driven by the a-biotic factors water supply and pH. CONCLUSIONS/SIGNIFICANCE: After long-term farming, a drastic shift in the bacterial communities in desert soil was observed. Bacterial communities in agricultural soil showed a higher diversity and a better ecosystem function for plant health but a loss of extremophilic bacteria. Interestingly, we detected that indigenous desert microorganisms promoted plant health in desert agro-ecosystems

Large body size constrains dispersal assembly of communities even across short distances

International audienc

Virtual stimulation of the interictal EEG network localizes the EZ as a measure of cortical excitability

Introduction: For patients with drug-resistant epilepsy, successful localization and surgical treatment of the epileptogenic zone (EZ) can bring seizure freedom. However, surgical success rates vary widely because there are currently no clinically validated biomarkers of the EZ. Highly epileptogenic regions often display increased levels of cortical excitability, which can be probed using single-pulse electrical stimulation (SPES), where brief pulses of electrical current are delivered to brain tissue. It has been shown that high-amplitude responses to SPES can localize EZ regions, indicating a decreased threshold of excitability. However, performing extensive SPES in the epilepsy monitoring unit (EMU) is time-consuming. Thus, we built patient-specific in silico dynamical network models from interictal intracranial EEG (iEEG) to test whether virtual stimulation could reveal information about the underlying network to identify highly excitable brain regions similar to physical stimulation of the brain.Methods: We performed virtual stimulation in 69 patients that were evaluated at five centers and assessed for clinical outcome 1 year post surgery. We further investigated differences in observed SPES iEEG responses of 14 patients stratified by surgical outcome.Results: Clinically-labeled EZ cortical regions exhibited higher excitability from virtual stimulation than non-EZ regions with most significant differences in successful patients and little difference in failure patients. These trends were also observed in responses to extensive SPES performed in the EMU. Finally, when excitability was used to predict whether a channel is in the EZ or not, the classifier achieved an accuracy of 91%.Discussion: This study demonstrates how excitability determined via virtual stimulation can capture valuable information about the EZ from interictal intracranial EEG

Prosumers in a digital multiverse: An investigation of how WeChat is affecting Chinese citizen journalism

WeChat is China’s most popular multi-purpose messaging and social media application and has been gaining popularity globally since its first release in 2011. In this article, we examine how the use of WeChat is affecting digitally-enabled citizen journalism in China. To achieve that purpose, we gathered data from 3 focus-group interviews with Chinese WeChat users. The findings suggest that WeChat’s integration of multiple communicative networks renders it a multiversal space where citizen journalistic practice can transverse across public, semi-public, and private spheres. The diverse communicative affordances of WeChat could facilitate ‘metavoicing’ practice as a form of citizen journalism, and enable news production and consumption to converge. Consequently, users’ experiences of news and news story lifecycles have been affected. WeChat offers both opportunities and challenges to the practice of citizen journalism: it is a space where information exchange could be constantly monitored, where the tone of current affairs coverage is often sensationalized, and where the reliability of content can be difficult to discern