Similar Set Research Articles

Targeted DNA sequencing of high-grade serous ovarian carcinoma reveals association of TP53 mutations with platinum resistance when combined with gene expression.

High-grade serous ovarian carcinoma (HGSC) is the most common subtype of ovarian cancer and is among the most fatal gynecological malignancies worldwide, due to late diagnosis at advanced stages and frequent therapy resistance. In 47 HGSC patients, we assessed somatic and germline genetic variability of a custom panel of 144 known or suspected HGSC-related genes by high-coverage targeted DNA sequencing to identify the genetic determinants associated with resistance to platinum-based therapy. In the germline, the most mutated genes were DNAH14 (17%), RAD51B (17%), CFTR (13%), BRCA1 (11%), and RAD51 (11%). Somatically, the most mutated gene was TP53 (98%), followed by CSMD1/2/3 (19/19/36%), and CFTR (23%). Results were compared with those from whole exome sequencing of a similar set of 35 HGSC patients. Somatic variants in TP53 were also validated using GENIE data of 1287 HGSC samples. Our approach showed increased prevalence of high impact somatic and germline mutations, especially those affecting splice sites of TP53, compared to validation datasets. Furthermore, nonsense TP53 somatic mutations were negatively associated with patient survival. Elevated TP53 transcript levels were associated with platinum resistance and presence of TP53 missense mutations, while decreased TP53 levels were found in tumors carrying mutations with predicted high impact, which was confirmed in The Cancer Genome Atlas data (n = 260). Targeted DNA sequencing of TP53 combined with transcript quantification may contribute to the concept of precision oncology of HGSC. Future studies should explore targeting the p53 pathway based on specific mutation types and co-analyze the expression and mutational profiles of other key cancer genes.

Anecdata: children’s and adults’ evaluation of anecdotal and statistical evidence

Pseudoscientific beliefs, including vaccine-related and other types of conspiracy theories, are often formed through reliance on personal anecdotes shared by people with similar belief sets. In the present study, we explore one aspect of pseudoscientific versus scientific reasoning by studying the development of the use of anecdotal versus statistical evidence. To do so, we asked 7- and 10-year-olds and adults to help an agent solve a problem by choosing one of two potential solutions, one supported by an anecdote and one by a graph. Results revealed significant age differences, with older participants more likely to value the graphical over the anecdotal evidence. Participants who chose the anecdotal solution frequently justified their choices by referring either to an inferred causal relationship between the chosen solution and the outcome or to characteristics of the person who provided the anecdote. Participants who chose the graphical solution frequently referred to quantity. Our findings suggest that both a greater valuation of statistical information and an increased ability to reflect critically about causal relationships may be critical in resisting the persuasive power of anecdotes, and hence, making valid evidence-based decisions.

An online low-dimension fuzzy modeling method for time-varying processes

Many industrial processes are full of nonlinearity and noise. Fuzzy modeling often leads to issues with dimension disaster and poor robustness for such processes. To address these issues, an online low-dimension fuzzy method (OLDF) is proposed here. First, an explicit mapping-based low-dimension fuzzy method (EMLF) is proposed to handle intricate nonlinear and noisy processes. In this method, similar fuzzy sets are combined into larger ones using a novel similarity criterion to reduce the fuzzy rules. Then, an explicit mapping strategy is developed to represent the local nonlinearities in each enlarged fuzzy set through an explicit mapping function. Subsequently, a robust objective function is constructed to improve the robustness of EMLF model. This objective function minimizes both the mean and variance of the modeling error, ensuring robust performance even in scenarios featuring non-Gaussian noise or outliers. After that, an online update strategy is designed to account for time-varying dynamics. It designs an adaptive detection mechanism to identify changes in dynamic behaviors. Following detection, global and local updating strategies are developed to dynamically update model parameters. Further analysis and proof highlight the effectiveness of the proposed method. Experiments with time-varying processes also confirm its success.

Effects of sample pre-treatments on the analysis of liquid organic manures by visible and near-infrared spectrometry

Proper application of a fertilizer requires precise knowledge of its nutrient composition. In the case of liquid organic manures (LOM), this information is often lacking due to heterogeneous nature of these fertilizers. Published “book values” of nutrient contents present the average from a wide range of possible nutrient characteristics, but usually differ considerably from the concentration in a particular manure. Thus, chemical analyses are recommended before applying the specific LOM. Unfortunately, this is usually too costly and time-intensive in practical farming. On-farm analysis by optical spectrometry in the visible and near-infrared (Vis-NIR) range is considered as an efficient alternative. However, calibration of Vis-NIR spectrometry for LOM is challenging as shown in many studies. One reason is LOMs’ tendency to rapidly segregate into a fuzzy continuum with liquid and solid properties. By separating LOM into well-defined liquid and solid phases and measuring them separately, calibration of Vis-NIR spectrometry might be improved. In this study, the effects of four sample pre-treatment techniques on the prediction accuracy of macronutrients (N, P, K, Mg, Ca, S), micronutrients (B, Mn, Fe, Cu, Zn), dry matter and pH of LOM using visible and near infrared spectrometry were comprehensively investigated. The concentrations were referred either to wet basis or to dry matter basis. For the study, a total of 163 samples, separated in two similar LOM sets (pig, cattle, digestates), were either dried, filtered, or centrifuged and always compared to non-treated samples. The experiments demonstrate that in comparison to raw samples (Ø r2 = 0.85) neither filtering (Ø r2 = 0.76 for filtrates and Ø r2 = 0.71 for filter residues), centrifugation (Ø r2 = 0.59 for supernatants and Ø r2 = 0.79 for pellets), nor drying (Ø r2 = 0.74) revealed to be a helpful preparation step significantly improving prediction results, independent from referring to wet or dry basis concentrations.

Pathogenic variants in CRX have distinct cis-regulatory effects on enhancers and silencers in photoreceptors.

Dozens of variants in the gene for the homeodomain transcription factor (TF) cone-rod homeobox (CRX) are linked with human blinding diseases that vary in their severity and age of onset. How different variants in this single TF alter its function in ways that lead to a range of phenotypes is unclear. We characterized the effects of human disease-causing variants on CRX cis-regulatory function by deploying massively parallel reporter assays (MPRAs) in mouse retina explants carrying knock-ins of two variants, one in the DNA-binding domain (p.R90W) and the other in the transcriptional effector domain (p.E168d2). The degree of reporter gene dysregulation in these mutant Crx retinas corresponds with their phenotypic severity. The two variants affect similar sets of enhancers, and p.E168d2 has distinct effects on silencers. Cis-regulatory elements (CREs) near cone photoreceptor genes are enriched for silencers that are derepressed in the presence of p.E168d2. Chromatin environments of CRX-bound loci are partially predictive of episomal MPRA activity, and distal elements whose accessibility increases later in retinal development are enriched for CREs with silencer activity. We identified a set of potentially pleiotropic regulatory elements that convert from silencers to enhancers in retinas that lack a functional CRX effector domain. Our findings show that phenotypically distinct variants in different domains of CRX have partially overlapping effects on its cis-regulatory function, leading to misregulation of similar sets of enhancers while having a qualitatively different impact on silencers.

Motor cortex retains and reorients neural dynamics during motor imagery.

The most prominent characteristic of motor cortex is its activation during movement execution, but it is also active when we simply imagine movements in the absence of actual motor output. Despite decades of behavioural and imaging studies, it is unknown how the specific activity patterns and temporal dynamics in motor cortex during covert motor imagery relate to those during motor execution. Here we recorded intracortical activity from the motor cortex of two people who retain some residual wrist function following incomplete spinal cord injury as they performed both actual and imagined isometric wrist extensions. We found that we could decompose the population activity into three orthogonal subspaces, where one was similarly active during both action and imagery, and the others were active only during a single task type-action or imagery. Although they inhabited orthogonal neural dimensions, the action-unique and imagery-unique subspaces contained a strikingly similar set of dynamic features. Our results suggest that during motor imagery, motor cortex maintains the same overall population dynamics as during execution by reorienting the components related to motor output and/or feedback into a unique, output-null imagery subspace.

Evaluating spatially variable gene detection methods for spatial transcriptomics data

BackgroundThe identification of genes that vary across spatial domains in tissues and cells is an essential step for spatial transcriptomics data analysis. Given the critical role it serves for downstream data interpretations, various methods for detecting spatially variable genes (SVGs) have been proposed. However, the lack of benchmarking complicates the selection of a suitable method.ResultsHere we systematically evaluate a panel of popular SVG detection methods on a large collection of spatial transcriptomics datasets, covering various tissue types, biotechnologies, and spatial resolutions. We address questions including whether different methods select a similar set of SVGs, how reliable is the reported statistical significance from each method, how accurate and robust is each method in terms of SVG detection, and how well the selected SVGs perform in downstream applications such as clustering of spatial domains. Besides these, practical considerations such as computational time and memory usage are also crucial for deciding which method to use.ConclusionsOur study evaluates the performance of each method from multiple aspects and highlights the discrepancy among different methods when calling statistically significant SVGs across diverse datasets. Overall, our work provides useful considerations for choosing methods for identifying SVGs and serves as a key reference for the future development of related methods.

The social determinants of mental health and disorder: evidence, prevention and recommendations.

People exposed to more unfavourable social circumstances are more vulnerable to poor mental health over their life course, in ways that are often determined by structural factors which generate and perpetuate intergenerational cycles of disadvantage and poor health. Addressing these challenges is an imperative matter of social justice. In this paper we provide a roadmap to address the social determinants that cause mental ill health. Relying as far as possible on high-quality evidence, we first map out the literature that supports a causal link between social determinants and later mental health outcomes. Given the breadth of this topic, we focus on the most pervasive social determinants across the life course, and those that are common across major mental disorders. We draw primarily on the available evidence from the Global North, acknowledging that other global contexts will face both similar and unique sets of social determinants that will require equitable attention. Much of our evidence focuses on mental health in groups who are marginalized, and thus often exposed to a multitude of intersecting social risk factors. These groups include refugees, asylum seekers and displaced persons, as well as ethnoracial minoritized groups; lesbian, gay, bisexual, transgender and queer (LGBTQ+) groups; and those living in poverty. We then introduce a preventive framework for conceptualizing the link between social determinants and mental health and disorder, which can guide much needed primary prevention strategies capable of reducing inequalities and improving population mental health. Following this, we provide a review of the evidence concerning candidate preventive strategies to intervene on social determinants of mental health. These interventions fall broadly within the scope of universal, selected and indicated primary prevention strategies, but we also briefly review important secondary and tertiary strategies to promote recovery in those with existing mental disorders. Finally, we provide seven key recommendations, framed around social justice, which constitute a roadmap for action in research, policy and public health. Adoption of these recommendations would provide an opportunity to advance efforts to intervene on modifiable social determinants that affect population mental health.

The Urinary Metabolome of Newborns with Perinatal Complications.

Maternal pathological conditions such as infections and chronic diseases, along with unexpected events during labor, can lead to life-threatening perinatal outcomes. These outcomes can have irreversible consequences throughout an individual's entire life. Urinary metabolomics can provide valuable insights into early physiological adaptations in healthy newborns, as well as metabolic disturbances in premature infants or infants with birth complications. In the present study, we measured 180 metabolites and metabolite ratios in the urine of 13 healthy (hospital-discharged) and 38 critically ill newborns (admitted to the neonatal intensive care unit (NICU)). We used an in-house-developed targeted tandem mass spectrometry (MS/MS)-based metabolomic assay (TMIC Mega) combining liquid chromatography (LC-MS/MS) and flow injection analysis (FIA-MS/MS) to quantitatively analyze up to 26 classes of compounds. Average urinary concentrations (and ranges) for 167 different metabolites from 38 critically ill NICU newborns during their first 24 h of life were determined. Similar sets of urinary values were determined for the 13 healthy newborns. These reference data have been uploaded to the Human Metabolome Database. Urinary concentrations and ranges of 37 metabolites are reported for the first time for newborns. Significant differences were found in the urinary levels of 44 metabolites between healthy newborns and those admitted at the NICU. Metabolites such as acylcarnitines, amino acids and derivatives, biogenic amines, sugars, and organic acids are dysregulated in newborns with bronchopulmonary dysplasia (BPD), asphyxia, or newborns exposed to SARS-CoV-2 during the intrauterine period. Urine can serve as a valuable source of information for understanding metabolic alterations associated with life-threatening perinatal outcomes.

Volumetric thermo-convective and stratified prandtl fluid magnetized flow over an extended convectively inclined surface with chemically reactive species

Substantive applications of stratified flows have been observed in various industrial operating systems. Stratified flows driven by gravity differences possess pervasive significance in the performance of nuclear reactors along with the management of safety problems due to pressurized thermal shock and induced water condensation. In addition, thermos-gravitational stratified regimes also play an exclusive role in multiphase processes in diversified engineering disciplines. Therefore, this artifact investigates the thermal and solutally stratified Prandtl fluid flow over an inclined extendable surface with magnetic field aspects. Convective boundary constraints are prescribed at the surface of the sheet and chemical reaction of first-order is also accounted. Firstly, problem formulation is conceded in the form of PDEs which are later transformed into ODEs by employing a similar set of variables. Then these ODEs are solved by employing the shooting method in collaboration with the Runge–Kutta scheme. A comparison of results in a restrictive sense with outcomes attained from an analytical approach to analyze the robustness and accuracy of currently employed schemes is also executed. The results expressing the behavior of the involved parameters on flow distributions are revealed in graphical and tabular formats. It is revealed that the heat and mass flux coefficients increase by up to 41% and 22%, respectively, in the presence of stratification in comparison to the situation when it is absent. The velocity of the fluid is accelerated by uplifting the angle of inclination and buoyancy ratio parameters. By increasing the magnitude of the model flow parameters, the fluid velocity increased. The Prandtl number tends to reduce the temperature and elevate the heat-flux coefficient. The velocity distribution showed a positive trend with the change in the angle of inclination.

Investor Regret and Stock Returns

We introduce a measure of regret for stock market investors and investigate its cross-sectional asset pricing implications. According to our regret-based framework, investors experience regret due to not achieving the highest possible return from a similar set of stock investments, and equity portfolios with high regret generate 6.84% more annualized alpha than portfolios with low regret. Using investor-trading activity of 78,000 households at a large U.S.-based brokerage firm, we develop an investor-based regret index and show that this household-level regret measure predicts stock returns in a similar way to our proposed regret measure. We also show that regret is not spanned by established risk or behavioral factors that have been documented to be robust predictors of equity returns. This paper was accepted by David Sraer, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03389 .

Metaphorical events in translation: Does language type matter?

Speakers across different languagesstructure a similar set of target domains (e.g., emotions, time, ideas) as spatial motion, relying on the same metaphorical mappings (abstract concept as moving entity; abstract concept as location). These crosslinguistic similarities co-occurwith crosslinguistic differences in the lexicalization of the source domain, with some languages encoding manner more frequently than others (e.g., English vs. Spanish). But do these patterns ofsimilarities and differences extend to translations of written texts?In this study, we analyzed metaphorical motion expressions from novels written in typologically distinct (German vs. Spanish) vs. typologically similar languages (German vs. Polish) and their translations into a language from the opposite (German vs. Spanish) or the same typological group (German vs. Polish). We observed strong crosslinguistic similarities in target domains and metaphorical mappings and systematic crosslinguistic differences in the lexicalization of the source domain, with translations largely adhering to the patterns of the target language. Our findings thus suggest that translations of metaphorical motion events to a target language—be it of a similar or a different typological group—followthe same patterns in the target and source language in structure (mappings) but adhere to the patterns of the target language in the lexicalization of the metaphorical event.

To Assess the Knowledge and Determinants Associated with Blood Donor at National Medical College & Teaching Hospital, Birgunj

Introduction: In clinical practice, the two most crucial systems of blood grouping are ABO and Rh. There exist four primary blood types, namely A, B, AB and O. World Health Organization advocates for the compulsory screening of all blood donations prior to usage, with HIV, hepatitis B and C, as well as syphilis being mandatory. The aim of the study is to assess the knowledge and determinants associated with blood donors at National Medical College & Teaching Hospital, Birgunj.Materials and Methods: Proposal was reviewed by the Institutional Review Committee of National Medical College and approved on 9th July 2023. (Ref. F-NMC/662/079-080). A descriptive cross-sectional study was done in the blood donation programs organized in the premises of National Medical College. Sampling method used was census.Results: Of the total particiants, 41.3 % were overweight followed by 39.1 % who showed the normal weight and 7.6 % of the people were found to be underweight. The upper middle-class group accounted for 71.7 % of the total respondents, knowledge about how frequently a person can donate the blood were in 38(41.31%), the volume of blood collected in one pint at the time of donation was 33(35.86%), time taken nearly 5-8 minutes were 64 (69.56%). Among the donors 17(18.47%) had donated for first time in their life similarly for second time and more than three times were 38(41.31%), 38(41.31%), 26(28.26%) and 11(11.95%), respectively.Conclusion: The overall level of knowledge was satisfactory. Male participants had more practice regarding blood donation rather than females. Community shall be benefited by similar set up as made by health workers, blood bank and hospital.

CYBERSECURITY: RESEARCH ON METHODS FOR DETECTING DDOS ATTACKS

This article describes the problem of DDoS attacks, analyzing their nature and consequences. The paper covers common DDoS attack types, such as SYN flood, ICMP flood, UDP flood. Existing methods for detecting attacks from literature are reviewed, including machine learning approaches, including artificial neural networks, support vector machines and decision trees. The paper introduces a decision tree-based machine learning model for the detection of DDoS attacks. The model is trained and tested on a publicly available dataset. The dataset consists of 1,04,345 rows of data, where every row includes 23 features, such as source IP, destination IP, port number, number of bytes transferred from the switch port, etc. A similar set of characteristics can be obtained on a real network hardware using simple calculations, which makes it possible to approximate the model evaluation to real operating conditions. SYN flood, ICMP flood and UDP flood attack types are present in the data, as well as legitimate traffic. To avoid overfitting, only some columns were used, and columns such as IP addresses were discarded. The field “label” in each row of the dataset contains either 0 or 1 where 0 corresponds to legitimate traffic and 1 to malicious one. The problem of DDoS attack detection is therefore formally reduced to the task of binary classification of each row from the dataset. The constructed model achieves an average classification accuracy of 0.94 with a standard deviation at the level of 0.06 in detecting the above mentioned types of attacks. To objectively assess the effectiveness of the model and avoid distortion of the results, stratified 5-fold cross-validation was used. The developed model can be applied in the real world network hardware to filter malicious packets or as a tool for warning the administrator about an attack. This research advances cybersecurity by enhancing DDoS attack detection.

Genomic Landscape of NSCLC in the Republic of Ireland

IntroductionThe identification of genomic “targets” through next-generation sequencing (NGS) of patient’s NSCLC tumors has resulted in a rapid expansion of targeted treatment options for selected patients. This retrospective study aims to identify the proportion of patients with advanced NSCLC in the Republic of Ireland whose tumors harbor actionable genomic alterations through broad NGS panel testing. MethodsInstitutional review board approval was obtained before study initiation. Patients with NSCLC whose tumors underwent genomic testing through the largest available NGS panel at a nationally funded Cancer Molecular Diagnostics laboratory (St. James’s Hospital) between June 2017 and June 2022 were identified. Patient demographics and tumor-related data were collected by retrospective review from all cancer centers in Ireland, referring to the Cancer Molecular Diagnostics laboratory. A total of 203 (9%) tumor samples were excluded due to insufficient neoplastic cell content. Genomic data were collected through retrospective search of Ion Reporter software. The spectrum and proportion of patients with oncogenic driver mutations were evaluated using descriptive statistics (SPSS version 29.0). ResultsIn total, 2052 patients were identified. Patients were referred from 23 different hospital sites and all four geographic regions (Leinster = 1091, 53%; Munster = 763, 37.2%; Connacht = 191, 9.3%; Ulster = 7, 0.3%). Median age was 69 (range: 26–94) years; 53% were male. The most common tumor histologic subtype was adenocarcinoma (77%, n = 1577). An actionable genomic alteration was identified in 1099 cases (53%), the most common of which was KRAS (n = 657, 32%). Less frequently, NSCLC tumors harbored the following: MET exon 14 skipping (n = 53, 2.6%), MET amplification (n = 26, 1.3%), EGFR (n = 181, 8.8%), HER2 (n = 35, 1.7%), and BRAF (n = 72, 3.5%) mutations. Fusions were detected in 76 patients (3.7%) including ALK (n = 44, 58%), RET (n = 11, 14.5%), ROS1 (n = 16, 21%), and FGFR3 (n = 5, 6.6%), whereas no NTRK fusion was identified. Co-alterations were detected in 114 patients (5.6%), the most common of which was KRAS/PIK3CA (n = 19, 17%), EGFR/PIK3CA (n = 10, 8.5%), and KRAS/IDH1 (n = 9, 8%). Other co-alterations of interest identified included KRAS G12A/ROS1 fusion (n = 1) and KRAS G12C/BRAF G469A (n = 2). ConclusionsThis is the first retrospective study to comprehensively characterize the genomic landscape of NSCLC in Ireland, using the broadest available NGS panel. Actionable alterations were identified in 53.4% of the patients, and KRAS was the most common oncogenic driver alteration. Our study revealed a lower prevalence of patients whose tumor harbors ALK, ROS1, and RET fusions, compared with similar data sets.

Research on the Harmonic Prediction Method of a PV Plant Based on an Improved Kernel Extreme Learning Machine Model

The harmonics of photovoltaic power plants are affected by various factors including temperature, weather, and light amplitude. Traditional power harmonic prediction methods have weak non-linear mapping and poor generalization capability to unknown time series data. In this paper, a Kernel Extreme Learning Machine (KELM) model power harmonic prediction method based on Gray Relational Analysis (GRA) with Variational Mode Decomposition (VMD) coupled with Harris Hawk Optimization (HHO) is proposed. First, the GRA method is used to construct the similar day set in one screening, followed by further using K-means clustering to construct the final similar day set. Then, the VMD method is adopted to decompose the harmonic data of the similar day set, and each decomposition subsequence is input to the HHO-optimized KELM neural network for prediction, respectively. Finally, the prediction results of each subseries are superimposed and numerical evaluation indexes are introduced, and the proposed method is validated by applying the above method in simulation. The results show that the error of the prediction model is reduced by at least 39% compared with the conventional prediction method, so it can satisfy the function of harmonic content prediction of a photovoltaic power plant.

Protection of data under unfair competition law in Japan and Korea—a case of asymmetric convergence?

Abstract This article explores the question of overlap in unfair competition law in Japan and Korea and discusses whether the introduction of a general clause could address the problem of overlap. Positive laws regulating unfair competition in Japan and Korea have adopted a similar set of rules based on specific conduct regulation, with some variation. Notably, Korean law now prohibits the unfair use of another’s achievement based on an open clause, complementing the specific list of prohibited conduct. The article first presents an overview of unfair competition law in Japan and Korea, highlighting the requirements for protection and limitations, and then explores the problem of overlapping claims surrounding data misappropriation. Contrasting the legislative techniques used by Japan and Korea, this article notes that an open norm may provide the judiciary with an interpretative tool to dynamically address emerging unfair conduct. However, as there is a danger of limiting free competition and potential internal inconsistencies, to avoid asymmetric convergence, open norms should be carefully coordinated with specific conduct prohibitions, with clear prioritization.

Raisonnement médico-légal dans la détermination de l’incapacité totale de travail : une étude qualitative à l’unité médico-judiciaire de l’Hôtel-Dieu de Paris

ObjectivesIn French forensic medical units, medical doctors are requested to assess the functional impact of violence on its victims and to determine a total incapacity for work (ITT). Specific to French criminal law, with significant consequences in the judicial field, this practice is highly heterogeneous with considerable differences depending on the center and the assessor. The objective of this qualitative study was to describe the assessment methods of practitioners in the forensic medical unit at the Hôtel-Dieu Hospital in Paris, where both forensic practitioners and psychiatrists contribute to the evaluation of total incapacity for work. Materials and methodsSemi-structured individual interviews were conducted with four forensic medical practitioners and four psychiatrists. The questionnaire addressed the evaluation methods and tools, the impact of the kinds of violence and their possible chronicity, as well as the rationale for a dual-evaluation by both a forensic practitioner and a psychiatrist. ResultsIn the absence of consensual tools, practitioners tend to take into account the judicial consequences of their assessment of total incapacity for work, while striving to establish an internal coherence between a fact, an injury and its functional repercussions. The osteoarticular system is given as a model, with determined durations of bone healing, while the field of psychotraumatology lacks a similar data set and requires the practitioners to aim to relate the traumatic impact on the daily consequences reported by patients. Forensic practitioners and psychiatrists differ in the extent to which they take into account the plaintiffs’ grievances and the assessment of chronic violence cases. The former tend to determine an incapacity for work based on a clinical lesion, either assessed during their own clinical exam or reported in a former medical certificate, while the latter establish an incapacity for work grounded in the functional consequences reported by patients, especially in cases of psychotraumatic symptoms (sleep disorders, avoidance symptoms, and social interaction limitations, for example) following a physical or sexual assault. A dual-assessment is seen as an efficient way to ensure that the psychological impact of violence is taken into account. However the question arises of the systematic recourse to a psychiatrist or another professional trained in the field of psychotraumatology. The assessment and the clinical symptoms are specific and require appropriate training. Medical certificates are also considered to be judicial material with a broader implication than the sole determination of total incapacity for work. In reporting griefs and the circumstances of the events which have an impact on the clinical situation of the patient, the practitioners also provide qualitative data that a judge may take into account. ConclusionsThis exploratory study describes certain methodological principles used by forensic practitioners and psychiatrists and the inter-specialty variability in the determination of total incapacity for work. It reflects a common expectation for consensual practices based on non-binding indicators. In civil expertise, tools and methodological principals are delineated and discussed, with scales and psychometric instruments which could usefully be relayed to practitioners in forensic medical units dealing with the evaluation of total incapacity for work, a notion that remains specific to French criminal law and whose evaluation standards may also be discussed with practitioners in the judicial field.

A Privacy-Preserving Trajectory Publishing Method Based on Multi-Dimensional Sub-Trajectory Similarities.

With the popularity of location services and the widespread use of trajectory data, trajectory privacy protection has become a popular research area. k-anonymity technology is a common method for achieving privacy-preserved trajectory publishing. When constructing virtual trajectories, most existing trajectory k-anonymity methods just consider point similarity, which results in a large dummy trajectory space. Suppose there are n similar point sets, each consisting of m points. The size of the space is then mn. Furthermore, to choose suitable k- 1 dummy trajectories for a given real trajectory, these methods need to evaluate the similarity between each trajectory in the space and the real trajectory, leading to a large performance overhead. To address these challenges, this paper proposes a k-anonymity trajectory privacy protection method based on the similarity of sub-trajectories. This method not only considers the multidimensional similarity of points, but also synthetically considers the area between the historic sub-trajectories and the real sub-trajectories to more fully describe the similarity between sub-trajectories. By quantifying the area enclosed by sub-trajectories, we can more accurately capture the spatial relationship between trajectories. Finally, our approach generates k-1 dummy trajectories that are indistinguishable from real trajectories, effectively achieving k-anonymity for a given trajectory. Furthermore, our proposed method utilizes real historic sub-trajectories to generate dummy trajectories, making them more authentic and providing better privacy protection for real trajectories. In comparison to other frequently employed trajectory privacy protection methods, our method has a better privacy protection effect, higher data quality, and better performance.

Phytoplankton assemblages under hydrochemical conditions of the Volga River Delta

In May 2021, comprehensive studies were conducted in the southeastern part of the Volga River avandelta (marine part of the delta). The work aimed to compare and identify the possible interaction of hydrochemical conditions and the structure of the phytoplankton community. Based on field observations, instrument measurements, and statistical analysis, three algaecoenoses were obtained (rapids, periphyton-pelagic, and marine), 4 types of environmental conditions identified by abiotic factors (oxygen-deficient, rapids, creak, and marine), and 2 types of biotopic conditions identified according to production-destructive characteristics (river with a prevalence of production, marine - production shifted towards equilibrium). For the marine part, an discrete phytopelagic community was identified, represented by benthopelagic aggregates with a complex trophic structure based on ribbon-like colonies of araphid diatom (Staurosira spp. и Staurosirella spp.). It is shown that such a community structure may serve as an indicator of water masses with significant destructive processes. Thus, an abiotic oxygen-deficient biotope located in the river part of the study area was characterized by a similar set of species. Both water areas were characterized by high AOU values, an increase in the contribution of mineral phosphorus to the Redfield ratio and a lack of nitrogen. At the same time, the water areas with a pronounced predominance of production processes over destructive ones were characterized by an abundance of centric diatoms. Thus, the selected groups of species can serve as indicators concerning certain biotopic conditions (in terms of production/destruction of organic matter).