Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational methods for the identification and quantification of microbial organisms in metagenomes

Metagenomics allows analyzing genomic material taken directly from the environment. In contrast to classical genomics, no purification of single organisms is performed and therefore the extracted genomic material reflects the composition of the original microbial community. The possible applications of metagenomics are manifold and the field has become increasingly popular due to the recent improvements in sequencing technologies. One of the most fundamental challenges in metagenomics is the identification and quantification of organisms in a sample, called taxonomic profiling. In this work, we present approaches to the following current problems in taxonomic profiling: First, differentiation between closely related organisms in metagenomic samples is still challenging. Second, the identification of novel organisms in metagenomic samples poses problems to current taxonomic profiling methods, especially when there is no suitable reference genome available. The contribution of this thesis comprises three major projects. First, we introduce the Genome Abundance Similarity Correction (GASiC) algorithm, a method that allows differentiating between and quantifying highly similar microbial organisms in a metagenomic sample. The method first estimates the similarities between the available reference genomes with a simulation approach. Based on the similarities, GASiC corrects the observed abundances of each reference genome using a nonnegative lasso approach. In several experiments we showed that the abundance estimates are highly accurate and reduce the error compared to current approaches by 5% to 60%. The approach was also successfully applied to metaproteomics. In the second project, we developed a statistical framework to fit mixtures of discrete distribution functions to the histograms of sequencing coverage depth after mapping metagenomic reads to reference genomes. We tailored a family of distributions for this particular application and modified the expectation-maximization algorithm to also fit discrete distributions when maximum likelihood estimation of the distribution parameters is not directly possible. The most important application of our framework is the genome validity score that measures how suitable a reference genome is for a particular (metagenomic) dataset. In the third project, we developed a taxonomic profiling tool, called MicrobeGPS. In contrast to previous approaches, MicrobeGPS identifies and characterizes organisms in a metagenome even if there are no suitable reference genomes available. Distances to existing reference genomes are measured with the genome validity score
The intelligent library

Purpose The last few years have seen a surge of interest in artificial intelligence (AI). The purpose of this paper is to capture a snapshot of perceptions of the potential impact of AI on academic libraries and to reflect on its implications for library work. Design/methodology/approach The data for the study were interviews with 33 library directors, library commentators and experts in education and publishing. Findings Interviewees identified impacts of AI on search and resource discovery, on scholarly publishing and on learning. Challenges included libraries being left outside the focus of development, ethical concerns, intelligibility of decisions and data quality. Some threat to jobs was perceived. A number of potential roles for academic libraries were identified such as data acquisition and curation, AI tool acquisition and infrastructure building, aiding user navigation and data literacy. Originality/value This is one of the first papers to examine current expectations around the impact of AI on academic libraries. The authors propose the paradigm of the intelligent library to capture the potential impact of AI for libraries.
Laboratory Learning: Hands-on versus Simulated Experiments

This study compares learning outcomes of student laboratory work in an energy storages course conducted in two different modes: first as a practical hands-on exercise and second using computer-based simulations. In order to provide reliable insights, this study implements optimized research methodology to avoid any other effect (e.g. learning synchronicity/distance learning/instructions) on the learning outcome rather than the effect of the learning mode itself. The student laboratory experiments were created in a manner that they could be conducted in both modes in the same way and using a single set of instructions. To ensure a comparable group environment for the individual student, the students were arranged into two similar groups based on the student's practical experience. In this crossover study, the groups were taught the same topics by means of interchanging learning modes. To evaluate the influence of each mode on student learning, short written tests regarding the previous experiment were conducted at the beginning of the subsequent laboratory session. Overall learning results of hands-on experiments were slightly better than those of simulated laboratories (Cohen's d=0.25), the difference in performance was statistically significant (p<0.02). Through solicited feedback on each laboratory session, in hands-on mode more students expressed they have acquired new insights/comprehensions (76% vs. 66%, Cohen's d=0.23, small effect, p<0.07). Following the strategy not to optimize the lessons individually to the learning mode, other influences on the learning outcome, which were usually mixed, were excluded. The students' subjective opinions show advantages of the hands-on mode. Based on the objective data, a weak, but significant outcome to better knowledge acquisition with hands-on laboratory experiments was achieved. This observation is against the trend of the literature in the last years towards better or equal learning with nontraditional labs.
Fragments of Bag Relational Algebra: Expressiveness and Certain Answers

Abstract While all relational database systems are based on the bag data model, much of theoretical research still views relations as sets. Recent attempts to provide theoretical foundations for modern data management problems under the bag semantics concentrated on applications that need to deal with incomplete relations, i.e., relations populated by constants and nulls. Our goal is to provide a complete characterization of the complexity of query answering over such relations in fragments of bag relational algebra. The main challenges that we face are twofold. First, bag relational algebra has more operations than its set analog (e.g., additive union, max-union, min-intersection, duplicate elimination) and the relationship between various fragments is not fully known. Thus we first fill this gap. Second, we look at query answering over incomplete data, which again is more complex than in the set case: rather than certainty and possibility of answers, we now have numerical information about occurrences of tuples. We then fully classify the complexity of finding this information in all the fragments of bag relational algebra.
Simulation: A complex pedagogical space

Simulation is a pedagogy that has been widely used in a number of educational settings (e.g., aviation, transport, social work, nursing education). While it can take numerous forms, it often involves an assortment of high-tech equipment (e.g., flight simulators, manikins) that seek to replicate real settings. Specifically, this paper provides an empirically driven exploration of how simulation laboratories, used in the professional education of nurses, and medical and other health professionals in higher education settings, are practised. Informed by sociomaterial understandings, the paper problematises and disrupts homogeneous understandings of the simulation space as found in much of the health sciences literature. This is done by providing a number of layers ranging from accounts of simulation in literature and empirically driven accounts of simulation in action through to more abstract discussion. The paper is attentive to both the distinct materiality of the spaces involved and the human activities the spaces engender. This dual focus enables the consideration of spatial injustices as well as new directions for the development of simulation pedagogies.
Whatsapp: su uso educativo, ventajas y desventajas

The purpose of this work is to know and describe the educational uses of the WhatsApp application, as well as its advantages and disadvantages. The information is obtained through the review and analysis of scientific texts. Among the observed results, it should be noted that higher education is the educational level in which this tool has been used for pedagogical purposes more times. Some of its advantages: fluency and effectiveness in communication, access and exchange of information at any time and place or the motivation of students. Its disadvantages: the dynamics and speed of group chats, the characteristics of mobile phones to use the application (screen and keyboard) or the commitment of time and dedication. In conclusion: most of the works highlight the positive attitude of students towards the educational use of WhatsApp and encourages its incorporation as a support tool in the teaching-learning process.
Lifetime Enhancement of Wireless Sensor Network with Data Aggregation

Nowadays wireless sensor networks (WSN) are widely used in various domains such as disaster relief operation, military applications, environmental monitoring, home applications, structural monitoring, agricultural sector, health applications etc. Energy saving is the rudimentary provocation in wireless sensor networks. The energy of the WSNs can be conserved in many ways such as: duty cycling of nodes, clustering, energy efficient routing, data energy etc. The data aggregation is one of the approach which is used to conserve the energy of the WSN nodes by removing redundant packets from the collected packets. This helps in increasing the network lifetime and on the other hand, it saves the network bandwidth as well. Data aggregation algorithms are broadly classified on the basis of their data collection strategy into three types. In this thesis we have attempted to present a broader review of the data aggregation algorithms on the basis of their categorization as discussed earlier. Moreover, we have also proposed a centralized data aggregation algorithm that is Levelling and Self Localization based Clustering(LSLC) algorithm. This algorithm allows the nodes to self-localized themselves and also the data aggregation is performed at multiple levels which reduces the energy consumption of the nodes. This also reduces the number of packets sent to the base station and thereby enhances the network lifetime. In addition to this, the LSLC algorithm is compared with different existing data aggregation algorithms in terms of network lifetime, residual energy, packet to delivery ratio, latency, packet sent to the base station. Initially, the simulation results are obtained to analyze the impact of different metrics like increasing the number of nodes in the same area, with and without data aggregation etc. Then the LSLC is compared with some existing algorithm and it shows a considerable improvement in network lifetime, residual energy etc.
Editorial: Women in pharmacology of anti-cancer drugs: 2021

For years women have been underrepresented in Science, Technology, Engineering and Mathematics (STEM) university courses and occupations. At present, according to UNESCO, less than 30% of researchers worldwide are women. Similar statistics have been reported for women working in pharmacological research. A survey of the British Pharmacological Society (BPS) showed that while student members were fairly evenly split between the male and female genders (48% men, 52% women), there was a clear reduction in the numbers of female membership from graduation onwards (25% among Full Members, 15% among Fellows and 8.5% among Honorary Fellows). (https://www.bps.ac.uk/about/our-public-benefit/championingwomen-in-pharmacology). The dropping of women from the pharmacology profession peaked at the mid-career stage, when personal life/family and professional ambitions might conflict. This is in agreement with previous studies describing the “leak” in the academic pipeline for women who decide to leave science across many STEM fields (Ysseldyk et al., 2019). The BPS contacted the female pharmacologists who had left the workplace and asked them why they had taken such decision. The most common reply was the perceived inability to remain competitive in a profession where success is measured by articles published and grants awarded, with little or no consideration given to time away from work because of maternity leave or childcare. These factors have been amplified during the recent COVID-19 pandemic, when submissions of scientific articles to the medical journals by men has significantly increased, while decreasing for women researchers. Additionally, the number of grant submissions during the first year of the COVID-19 pandemic increased for male but not for female researchers, and female researchers were requesting lower amounts of funds in their applications (Davis et al, 2022). OPEN ACCESS
TIME VARYING LOAD MODELS APPLICATION FOR OPTIMAL ALLOCATION AND SIZING OF PV SYSTEMS IN DISTRIBUTION NETWORK

Distribution Generation (DG) is widely used in distribution systems to enhance the dynamic characteristics of the network such as improving the voltage profile, minimizing active and reactive power losses. A variable voltage load model is assumed in many distribution systems. Therefore, the results are more reliable and accurate. This paper proposes an analytical technique to size and site a photovoltaic based DG unit to minimize a multi objective function that depends on active and reactive power losses and voltage deviation taking into consideration the variable load model and mixed load between residential, commercial and industrial.
CREATING A SOFTWARE SYSTEM WITH FUNCTIONALITY TO HELP MAKE IT ACCESSIBLE FOR PEOPLE WITH A VISUAL DEFICIT

The software systems that millions of users use everyday around the world are mainly targeted at the main and the largest average group of people - people without disabilities. However, software systems are often inaccessible and unusable for another group of people - people with congenital or acquired disabilities. For a system to be accessible to people with special needs, it must be designed to take account of and be geared to their specific needs, opportunities for using the software systems and the hardware that provides them. This paper presents a model for creating a software system (for a physiological data analysis) that takes into account the needs of people with disabilities and in particular people with visual deficits. This model will ensure the assibilites of the software system and its easy use by both this target group and people without disabilities.
Prevalence of depression and its potential contributing factors in patients with enterostomy: A meta-analytical review

Objective In patients with intestinal pathologies, the placement of a stoma bag affects multiple aspects of their perceived quality of life. This meta-analysis aims to evaluate the prevalence of depression among patients with enterostomy and to determine the underlying factors that could explain the potential heterogeneity of this prevalence. Methods Relevant published studies were identified by searching PubMed, Embase, PsycINFO, Cochrane, CINAHL, Scopus, and Web of Science until May 2022. The random-effects model was used to determine the pooled prevalence of depression among patients with enterostomy using cross-sectional studies from various countries. Meta-regression and subgroup analysis were performed to identify factors contributing to heterogeneity. Quality assessment of the included studies was conducted using the Newcastle-Ottawa scale for nonrandomized studies. Results The pooled prevalence of depressive symptoms among patients with enterostomy, as calculated using the random-effects model, was 41.6% (95% confidence interval [CI]: 25.4–59.7%, Q-value = 145.794, df = 8, p < 0.001, tau∧2 = 1.124, I∧2 = 94.513). The meta-regression found that mean age and gender were not significant moderators for the observed heterogeneity in prevalence. Subgroup analysis according to the indications for enterostomy formation showed that the prevalence of depression was highest in patients with colorectal cancer, at 34.4% (95% CI: 27.2–42.4%). Subgroup analysis by region showed that patients in Africa had the highest prevalence of depression, at 88.2% (95% CI: 76.1–94.6%), compared to other regions. Subgroup analysis by stoma indication was not significant. Conclusion This meta-analysis reports that the pooled prevalence of depression among patients with enterostomy is 41.6%. Indications for enterostomy formation, as well as geographical region, were identified as potential sources of heterogeneity. These findings highlight the need for appropriate psychosocial support and interventions at different stages of enterostomy placement.
Diagnostic properties of the Frontal Assessment Battery (FAB) in Huntington’s disease

Background This study aimed at assessing the diagnostic properties of the Frontal Assessment Battery (FAB) as to its capability to (1) discriminate healthy controls (HCs) from patients with Huntington’s disease (HD) and (2) identify cognitive impairment in this population. Materials Thirty-eight consecutive HD patients were compared to 73 HCs on the FAB. Patients further underwent the Montreal Cognitive Assessment (MoCA) and the Unified Huntington’s Disease Rating Scale (UHDRS). Receiver-operating characteristics (ROC) analyses were run to assess both intrinsic—i.e., sensitivity (Se) and specificity (Sp), and post-test diagnostics, positive and negative predictive values (PPV; NPV) and likelihood ratios (LR+; LR–), of the FAB both in a case–control setting and to identify, within the patient cohort, cognitive impairment (operationalized as a below-cut-off MoCA score). In patients, its diagnostic accuracy was also compared to that of the cognitive section of the UHDRS (UHDRS-II). Results The FAB and UHDRS-II were completed by 100 and 89.5% of patients, respectively. The FAB showed optimal case–control discrimination accuracy (AUC = 0.86–0.88) and diagnostic properties (Se = 0.68–0.74; Sp = 0.88–0.9; PPV = 0.74–0.8; NPV = 0.84–0.87; LR+ = 5.6–7.68; LR– = 0.36–0.29), performing even better (AUC = 0.9–0.91) at identifying cognitive impairment among patients (Se = 0.73–1; Sp = 0.86–0.71; PPV = 0.79–0.71; NPV = 0.82–1; LR+ =5.13–3.5; LR– = 0.31–0) and comparably to the UHDRS-II (89% vs. 85% of accuracy, respectively; p = 0.46). Discussion In HD patients, the FAB is highly feasible for cognitive screening aims, being also featured by optimal intrinsic/post-test diagnostics within both case-control and case-finding settings.
Efficacy and safety of hypoglycemic drugs in improving cognitive function in patients with Alzheimer's disease and mild cognitive impairment: A systematic review and network meta-analysis

Objective The purpose of this study was to compare the effects of oral hypoglycaemic drugs (HDs) on cognitive function and biomarkers of mild cognitive impairment (MCI) and Alzheimer's disease (AD) through a network meta-analysis of randomized controlled trials (RCTs). Methods We conducted systematic searches for English- and Chinese-language articles in the PubMed, Medline, Embase, Cochrane Library and Google Scholar databases, with no date restrictions. We performed a network meta-analysis, which we report here according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The 16 studies included a total of 3,081 patients. We selected the Mini-Mental State Examination (MMSE), the Alzheimer's Disease Assessment Scale-Cognitive section (ADAS-Cog), the Alzheimer's Disease Cooperative Study Activities of Daily Living section (ADCS-ADL) and amyloid beta (Aβ) 42 as the outcome measures for analysis and comparison. Result We selected seven treatments and assessed the clinical trials in which they were tested against a placebo control. Of these treatments, intranasal insulin 20 IU (ITSN20), glucagon-like peptide-1 (GLP-1), and dipeptidyl peptidase 4 inhibitor (DPP-4) were associated with significantly improved MMSE scores (7 RCTs, 333 patients, 30≥MMSE score≥20: mild) compared with placebo [standardized mean difference (SMD) 1.11, 95% confidence interval (CI) (0.87, 1.35); SMD 0.75, 95% CI (0.04, 1.41); and SMD 4.08, 95% CI (3.39, 4.77), respectively]. Rosiglitazone 4 mg (RLZ4), rosiglitazone 10 mg (RLZ10), intranasal insulin 40 IU (ITSN40), and ITSN20 significantly decreased ADAS-Cog scores (11 RCTs, 4044 patients, 10 ≤ ADAS-Cog scores ≤ 30: mild and moderate) compared with placebo [SMD −1.40, 95% CI (−2.57, −0.23), SMD −3.02, 95% CI (−4.17, −1.86), SMD −0.92, 95% CI (−1.77, −0.08), SMD −1.88, 95% CI (−3.09, −0.66)]. Additionally, ITSN20 and ITSN40 significantly improved ADCS-ADL scores (2 RCTs, 208 patients, ADCS-ADL scale score ≤ 10: mild) compared with placebo [SMD 0.02, 95% CI (0.01, 0.03), and SMD 0.04, 95% CI (0.03, 0.05), respectively]. In the 16 included studies, the degree of AD was classified as mild or moderate. For mild cognitive impairment, DPP-4 performed best, but for mild to moderate impairment, ITSN40 had excellent performance. Conclusion Various HDs can improve the cognitive function of MCI and AD patients. Different drug regimens brought different degrees of improvement, which may be related to their dosage, duration, and mechanism of action. Systematic review registration www.crd. york.ac. uk/prospero.
Exploring the Space Between Good and Poor Spelling: Orthographic Quality and Reading Speed

ABSTRACT Variations in the accuracy and stability of a word’s spelling can be used to gauge the quality of its underlying orthographic representation. The Lexical Quality Hypothesis (LQH) contends that words with higher quality cognitive representations should be accessed more efficiently than those with lower quality representations. If this is the case, deviations in spelling accuracy and stability should be reflected in differences in reading times. Here, 90 teenage participants read 30 words; reading times were recorded. After a 2-week delay, the students spelled these same words 3 times each to gain a measure of orthographic quality. In line with the LQH, faster reading speeds were observed for words with higher spelling accuracy and stability, even for words that were not always spelled perfectly. To our knowledge, our findings provide the first empirical support for the notion that orthographic quality exists along a continuum, both within and across individuals.