Prevalence and patterns of higher-order drug interactions in Escherichia coli.

Interactions and emergent processes are essential for research on complex systems involving many components. Most studies focus solely on pairwise interactions and ignore higher-order interactions among three or more components. To gain deeper insights into higher-order interactions and complex environments, we study antibiotic combinations applied to pathogenic Escherichia coli and obtain unprecedented amounts of detailed data (251 two-drug combinations, 1512 three-drug combinations, 5670 four-drug combinations, and 13608 five-drug combinations). Directly opposite to previous assumptions and reports, we find higher-order interactions increase in frequency with the number of drugs in the bacteria's environment. Specifically, as more drugs are added, we observe an elevated frequency of net synergy (effect greater than expected based on independent individual effects) and also increased instances of emergent antagonism (effect less than expected based on lower-order interaction effects). These findings have implications for the potential efficacy of drug combinations and are crucial for better navigating problems associated with the combinatorial complexity of multi-component systems

Aspect-based Sentiment Analysis for German: Analyzing Talk of Literature" Surrounding Literary Prizes on Social Media

Since the rise of social media, the authority of traditional professional literary critics has beensupplemented – or undermined, depending on the point of view – by technological developmentsand the emergence of community-driven online layperson literary criticism. So far, relatively littleresearch (Allington 2016, Kellermann et al. 2016, Kellermann and Mehling 2017, Bogaert 2017, Pi-anzola et al. 2020) has examined this layperson user-generated evaluative “talk of literature”instead of addressing traditional forms of consecration. In this paper, we examine the layper-son literary criticism pertaining to a prominent German-language literary award: the Ingeborg-Bachmann-Preis, awarded during the Tage der deutschsprachigen Literatur (TDDL).We propose an aspect-based sentiment analysis (ABSA) approach to discern the evaluativecriteria used to differentiate between ‘good’ and ‘bad’ literature. To this end, we collected a cor-pus of German social media reviews, retrieved from Twitter, and enriched it with manual ABSAannotations:aspectsand aspect categories (e.g. the motifs or themes in a text, the jury discus-sions and evaluations, ...),sentiment expressionsandnamed entities. In a next step, the manualannotations are used as training data for our ABSA pipeline including 1) aspect term categoryprediction and 2) aspect term polarity classification. Each pipeline component is developed usingstate-of-the-art pre-trained BERT models.Two sets of experiments were conducted for the aspect polarity detection: one where only theaspect embeddings were used and another where an additional context window of five adjoiningwords in either direction of the aspect was considered. We present the classification results forthe aspect category and aspect sentiment prediction subtasks for the Twitter corpus. Thesepreliminary experimental results show a good performance for the aspect category classification,with a macro and a weighted F1-score of 69% and 83% for the coarse-grained and 54% and 73% forthe fine-grained task, as well as for the aspect sentiment classification subtask, using an additionalcontext window, with a macro and a weighted F1-score of 70% and 71%, respectivel

Response of Fresh Food Suppliers to Sustainable Supply Chain Management of Large European Retailers

This article analyses new supply chain management (SCM) strategies of the largest retail distribution chains in Europe within the context of differing sustainability concepts and approaches. An analysis is carried out of the strategic plans of such retailers, as well as recent developments in the sector. We begin by identifying the priority actions of retailers and then evaluating, by means of a survey, how small horticultural marketing firms (mainly cooperatives) in southeast Spain respond to the needs of these retailers. Subsequently, an analysis is carried out on these small marketing firm exporters to identify the relative weight which they assign to the variables assessed, while also considering the existing relationships between said weighted variables and business profits. Our results show that retailers tend to establish more simplified supply chains (that is, shorter and more vertical), essentially demonstrating their interpretation of a sustainable supply chain. In contrast, horticultural marketing firms have concentrated more on tactical and operational issues, thereby neglecting environmental, social and logistics management. Thus, their success rate in meeting the sustainability demands of their customers can be considered medium-low, requiring a more proactive attitude. Improved and collaborative relations, and the integration of sustainability concepts between suppliers (marketing firms) and their clients could contribute to successfully meeting sustainability demands. From the point of view of the consumer, close supplier–retail relationships have solved food safety issues, but the implementation of sustainability in other supply chain activities and processes is a pending issue. We propose strategic approximation and collaboration to bridge the gap between the varying sustainability demands in the supplier–retail relationship within perishable supply chains. Although this article specifically addresses fresh vegetable supply chains, the results may be extrapolated to other agri-food chains with a similar structure

The impact of interdisciplinary code simulation on perceptions of collaboration and team performance among internal medicine residents and nursing students

• Allows for inter-disciplinary training• Provides safe environment to practice patient care with immediate feedback-quality improvement• Results in better adherence to protocols• Well received by learners• In one study, almost half of IM residents surveyed felt ill- equipped to lead code teams even after ACLS training Crisis Resource Management (CRM) • Communication and cooperation• Leadership and management• Situational awareness• Decision-makin

Medical textiles as vascular implants and their success to mimic natural arteries

Vascular implants belong to a specialised class of medical textiles. The basic purpose of a vascular implant (graft and stent) is to act as an artificial conduit or substitute for a diseased artery. However, the long-term healing function depends on its ability to mimic the mechanical and biological behaviour of the artery. This requires a thorough understanding of the structure and function of an artery, which can then be translated into a synthetic structure based on the capabilities of the manufacturing method utilised. Common textile manufacturing techniques, such as weaving, knitting, braiding, and electrospinning, are frequently used to design vascular implants for research and commercial purposes for the past decades. However, the ability to match attributes of a vascular substitute to those of a native artery still remains a challenge. The synthetic implants have been found to cause disturbance in biological, biomechanical, and hemodynamic parameters at the implant site, which has been widely attributed to their structural design. In this work, we reviewed the design aspect of textile vascular implants and compared them to the structure of a natural artery as a basis for assessing the level of success as an implant. The outcome of this work is expected to encourage future design strategies for developing improved long lasting vascular implants

Antidepressant Use Amongst College Students: Findings of a Phenomenological Study

Background: Depression among college students is an escalating problem and could have serious consequences such as suicide. There has been an increase in use of antidepressants on college campuses in United States. However, an in depth understanding of this phenomenon from the college student’s perspective is lacking in the literature. Objective: This study examined college students’ experiences and treatment decision making during their depression treatment. Methods: A longitudinal, phenomenological research methodology was completed. The participants were nine students who were taking antidepressants for diagnosis of depression. Recruitment was done via brochures placed at University bulletin boards, and a mental health clinic. Three audio taped, unstructured interviews were conducted with each participant over four months. The central question asked was: What has the experience of treating depression been for you? Analysis of text was done using Van Manen’s lifeworld existentials of lived body, lived time, lived relation and lived space as the organizing framework. Results: Thirteen themes were identified within the four lifeworlds. The results showed that lived relation with providers was important for college students’ decision to both initiate and continue antidepressant use. Students’ role was defined in conjunction with provider’s role by them as wanting to be a ‘player’ in their treatment decisions and needing to be ‘acknowledged’ as such by their providers. Conclusions: Overall, the underlying essential theme of ‘autonomy’ was portrayed by the students’ experiential accounts of their depression treatment and treatment decision making

Anti-Persistence on Persistent Storage: History-Independent Sparse Tables and Dictionaries

International audienceWe present history-independent alternatives to a B-tree, the primary indexing data structure used in databases. A data structure is history independent (HI) if it is impossible to deduce any information by examining the bit representation of the data structure that is not already available through the API. We show how to build a history-independent cache-oblivious B-tree and a history-independent external-memory skip list. One of the main contributions is a data structure we build on the way—a history-independent packed-memory array (PMA). The PMA supports efficient range queries, one of the most important operations for answering database queries. Our HI PMA matches the asymptotic bounds of prior non-HI packed-memory arrays and sparse tables. Specifically, a PMA maintains a dynamic set of elements in sorted order in a linear-sized array. Inserts and deletes take an amortized O(log^2 N) element moves with high probability. Simple experiments with our implementation of HI PMAs corroborate our theoretical analysis. Comparisons to regular PMAs give preliminary indications that the practical cost of adding history-independence is not too large. Our HI cache-oblivious B-tree bounds match those of prior non-* HI cache-oblivious B-trees. Searches take O(log_B N) I/Os; inserts and deletes take O((log^2 N)/B + log_B N) amortized I/Os with high probability; and range queries returning k elements take O(log_B N + k/B) I/Os. Our HI external-memory skip list achieves optimal bounds with high probability, analogous to in-memory skip lists: O(log_B N) I/Os for point queries and amortized O(log_B N) I/Os for in-serts/deletes. Range queries returning k elements run in O(log_B N + k/B) I/Os. In contrast, the best possible high-probability bounds for inserting into the folklore B-skip list, which promotes elements with probability 1/B, is just Θ(log N) I/Os. This is no better than the bounds one gets from running an in-memory skip list in external memory

Robust detection of real-time power quality disturbances under noisy condition using FTDD features

To improve power quality (PQ), detecting the particular type of disturbance is the foremost thing before mitigation. So monitoring is needed to detect the PQ disturbance that occurs in a short duration of time. Classification of real-time PQ disturbances under noisy environment is investigated in this method by selecting an appropriate signal processing tool called fusion of time domain descriptors (FTDD) at the feature extraction stage. It’s a method of extracting power spectrum characteristics of various PQ disturbances. Few advantages like algorithmic simplicity and local time-based unique features makes the FTDD algorithm ahead of other techniques. PQ events like voltage sag, voltage swell, interruption, healthy, transient and harmonics mixed with different noise conditions are analysed. multiclass support vector machine and Naïves Bayes (NB) classifiers are applied to analyse the performance of the proposed method. As a result, NB classifier performs better in noiseless signal with 99.66%, wherein noise added signals both NB and SVM are showing better accuracy at different signal to noise ratios. Finally, Arduino controller-based hardware tool involved in the acquisition of real-time signals shows how our proposed system is applicable for industries that make detection simple