Miracle-dz/UniFAR-FTUs huggingface dataset:
Comprehensive analysis of insertion sequences within rRNA genes of CPR bacteria and biochemical characterization of a homing endonuclease encoded by these sequences

The Candidate Phyla Radiation (CPR) represents an extensive bacterial clade comprising primarily uncultured lineages and is distinguished from other bacteria by a significant prevalence of insertion sequences (ISs) within their rRNA genes. However, our understanding of the taxonomic distribution and characteristics of these ISs remains limited. In this study, we used a comprehensive approach to systematically determine the nature of the rRNA ISs in CPR bacteria. The analysis of hundreds of rRNA gene sequences across 65 CPR phyla revealed that ISs are present in 48% of 16S rRNA genes and 82% of 23S rRNA genes, indicating a broad distribution across the CPR clade, with exceptions in the 16S and 23S rRNA genes of Saccharibacteria and the 16S rRNA genes of Peregrinibacteria. Over half the ISs display a group-I-intron-like structure, whereas specific 16S rRNA gene ISs display features reminiscent of group II introns. The ISs frequently encode proteins with homing endonuclease (HE) domains, centered around the LAGLIDADG motif. The LAGLIDADG HE (LHE) proteins encoded by the rRNA ISs of CPR bacteria predominantly have a single-domain structure, deviating from the usual single- or double-domain configuration observed in typical prokaryotic LHEs. Experimental analysis of one LHE protein, I-ShaI from Ca. Shapirobacteria, confirmed that its endonuclease activity targets the DNA sequence of its insertion site, and chemical cross-linking experiments demonstrated its capacity to form homodimers. These results provide robust evidence supporting the hypothesis that the explosive proliferation of rRNA ISs in CPR bacteria was facilitated by mechanisms involving LHEs. IMPORTANCE Insertion sequences (ISs) in rRNA genes are relatively limited and infrequent in standard bacteria. With a comprehensive bioinformatic analysis, we show that in CPR bacteria, which are characterized by a high frequency of ISs, these ISs occur in 48% of 16S rRNA genes and 82% of 23S rRNA genes. We also report the systematic and biochemical characterization of the LAGLIDADG homing endonucleases (LHEs) encoded by these ISs in the first such analysis of the CPR bacteria. This study significantly extends our understanding of the phylogenetic positions of rRNA ISs within CPR bacteria and the biochemical features of their LHEs.
Subcellular thermal profiling enables the deep functional exploration of the mitochondrial proteome

Mitochondria are membrane-bound organelle hubs of cellular metabolism and signaling. The dysregulation of mitochondria is related to the genesis of several highly prevalent diseases, including cancer and cardiovascular disorders, urging the development of novel technologies to systematically study this organelle and its dynamics. Thermal proteome profiling (TPP) allows the unbiased study of the interactions of proteins with drugs, metabolites, and other proteins, providing a unique understanding of the state of the proteome. Here, we develop and introduce an optimized TPP workflow, mito-TPP, for the direct and extensive study of this organelle. We demonstrate that our approach detects both direct mitochondrial small molecule-protein and metabolite-protein interactions, as well as indirect downstream effects. We also show that mito-TPP preserves features from whole-cell systems, such as the coaggregation of interacting proteins. Finally, we explore the mitochondrial proteoform map, detecting more than 180 proteins with multiple proteoform groups. Overall, we demonstrate that mito-TPP is a powerful new tool for the functional study of the mitochondrial proteome.
A SNP-based honey bee paternity assignment test for evaluating the effectiveness of mating stations and its application to the Ataun valley, Basque Country, Spain

Geographically isolated mating stations are deployed across Europe to facilitate controlled mating with selected drone-producing colonies. To assess the reliability of these stations, we developed a paternity assignment test using a custom Illumina genotyping chip with 6457 SNPs based on two metrics (number of mismatch alleles and kinship). The method demonstrated remarkable accuracy during validation with an independent dataset of known parent-offspring pairs, with an accuracy rate of 97.7%. We then applied the developed paternity assignment test to the Apis mellifera iberiensis mating station in the Ataun valley, Basque Country, Spain, in 2021. Drone-producing colonies in the valley were sampled and genotyped, as well as 156 worker offspring of queens mated at the station, and 56 drones collected in the drone congregation area. Out of the 156 worker samples, we could assign paternity of 120 (76.9%) to one of the drone-producing colonies in the valley, while 23.1% were of unknown patriline. Out of the 56 drones collected in the air, 52 (92.9%) were assigned to drone-producing colonies. We were also able to determine the colonies and apiaries that made the most significant contributions to the matings. This information aids in effective apiary management, including the selection of suitable mating station locations and the positioning of drone-producing colonies therein. Overall, our SNP-based paternity assignment test offers a valuable tool for evaluating mating station effectiveness across Europe, crucial for advancing breeding objectives in honey bee populations.
A mediating framework in resting-state connectivity between the medial prefrontal cortex and anterior cingulate in mild cognitive impairment

Mild cognitive impairment (MCI) is recognized as the prodromal phase of dementia, a condition that can be either maintained or reversed through timely medical interventions to prevent cognitive decline. Considerable studies using functional magnetic resonance imaging (fMRI) have indicated that altered activity in the medial prefrontal cortex (mPFC) serves as an indicator of various cognitive stages of aging. However, the impacts of intrinsic functional connectivity in the mPFC as a mediator on cognitive performance in individuals with and without MCI have not been fully understood. In this study, we recruited 42 MCI patients and 57 healthy controls, assessing their cognitive abilities and functional brain connectivity patterns through neuropsychological evaluations and resting-state fMRI, respectively. The MCI patients exhibited poorer performance on multiple neuropsychological tests compared to the healthy controls. At the neural level, functional connectivity between the mPFC and the anterior cingulate cortex (ACC) was significantly weaker in the MCI group and correlated with multiple neuropsychological test scores. The result of the mediation analysis further demonstrated that functional connectivity between the mPFC and ACC notably mediated the relationship between the MCI and semantic working memory. These findings suggest that altered mPFC-ACC connectivity may have a plausible causal influence on cognitive decline and provide implications for early identifications of neurodegenerative diseases and precise monitoring of disease progression.
Experimental evolution in maize with replicated divergent selection identifies plant-height associated SNPs

Experimental evolution studies are common in agricultural research, where they are often deemed “long term selection”. These are often used to perform selection mapping, which involves identifying markers which were putatively under selection based on finding signals of selection left in the genome. A challenge of previous selection mapping studies, especially in agricultural research, has been the specification of robust significance thresholds. This is in large part because long term selection studies are rarely replicated. Usually, significance thresholds in long term selection experiments are based on outliers from an empirical distribution or based on drift simulations. Both of these approaches are prone to missing true positives or including false positives. Under laboratory conditions with model species, replicated selection has been shown to be a powerful tool, especially for the specification of significance thresholds. In this study, we conducted divergent, replicated selection for short and tall plant-height in a random mating maize population under real field conditions. Selection of the 5% tallest or shortest plants was conducted for three generations. Significance thresholds were specified using the false discovery rate for selection (FDRfS) based on a single marker-based statistic leveraging replicated selection (FSTSum). Overall, we found 44 significant SNPs. Thirty-four were located within a region of 1.02 Mb comprising the coding region of the plant-height genes Dwarf1 and iAA8. We applied a window-based analysis and haplotype block analysis to further dissect the pattern of selection in significant regions of the genome. We observed patterns of strong selection in the subpopulations selected for short plant height.
Studies on the performance of some ARQ schemes

This thesis consists of a summary part and seven published articles. All the articles are about performance analysis of ARQ schemes. Two of the publications study the performance of an ARQ scheme with packet combining, called the EARQ (extended ARQ) scheme. In the packet combining algorithm, the bitwise modulo-2 sum of two erroneous copies of a packet is computed to locate the errors. The packet combining algorithm involves a straightforward search procedure, the computational complexity of which easily becomes prohibitive. As a solution to this, a modified scheme is proposed, where the search procedure is attempted only when there are at most Nmax 1s at the output of the modulo-2 adder. In one article, time diversity was utilized, whereas space diversity reception was considered in the other work. The remaining five publications study the throughput performance of adaptive selective-repeat and go-back-N ARQ schemes, where the switching between the transmission modes is done based on the simple algorithm proposed by Y. -D. Yao in 1995. In this method, α contiguous NACKs or β contiguous ACKs indicate changes from ‘good’ to ‘bad’ or from ‘bad’ to ‘good’ channel conditions, respectively. The numbers α and β are the two design parameters of the adaptive scheme. The time-varying forward channel is modelled by two-state Markov chains, known as Gilbert-Elliott channel models. The states are characterized by bit error rates, packet error rates or fading parameters. The performance of the adaptive ARQ scheme is measured by its average throughput over all states of the system model, which is a Markov chain. A useful upper bound for the achievable average throughput is provided by the performance of an (assumed) ideal adaptive scheme which is always in the ‘correct’ transmission mode. The optimization of α and β is done based on minimizing the mean-square distance between the actual and the ideal performance curves. Methods of optimizing the packet size(s) used in the adaptive selective-repeat scheme are also proposed.
Environmental Innovation and Societal Transitions

,interface,designandinfor-mational content to examine how technological affordances of digital platforms’ structure social interaction. In order to carry out the research we designed a netnographic protocol that systematised data collection across four dimensions of platforms’ technological structure and informational content: functionality and usability ; trust and virtual reputation ; codes of conduct and community footprint . Data was collected on ﬁfty-ﬁve platforms, including forty-seven across Belgium, Italy, Portugal and Spain, as well as eight international platforms. Following factor and cluster analysis, and on the basis of the theoretical understandings of the sharing and collaborative economy, we developed a typology that grouped platforms into three groups: network, transaction and community oriented .
Can the Philippines attain 6.5–8 Percent Growth During 2023–28? An Assessment Based on the Estimation of the Balance-of-Payments–Constrained Growth Rate

We expand the standard balance-of-payments–constrained (BOPC) growth rate model in three directions. First, we take into account the separate contributions of exports in goods, exports in services, overseas remittances, and foreign direct investment (FDI) inflows. Second, we use state-space estimation techniques to obtain time-varying parameters of the relevant coefficients. Third, we test for the endogeneity of output in the import equation. We apply this framework to assess the feasibility of the target set by the new Philippine administration of President Marcos (elected in 2022) to attain an annual GDP growth rate of 6.5–8 percent during 2024–28. We obtain an estimate of the growth rate consistent with equilibrium in the basic balance of the Philippines of about 6.5 percent in 2021 (and declining during the years prior to it). This BOPC growth rate is below the 6.5–8 percent target. We also find that exchange-rate depreciations will not lead to an improvement in the BOPC growth rate. The Philippines must lift the constraints that impede a higher growth of exports. In particular, it must shift its export structure toward more sophisticated products with a higher income elasticity of demand.
Optimizing the Enrollment Funnel with Decision Trees and Rule Based List

In this paper, an analysis is presented of the enrollment funnel for prospective graduate school students, predicting application sub-mission and enrollment. Eﬃcient university outreach is critical to optimizing a positive interaction cadence for prospective students, reducing costs, and strengthening academic program revenue streams. Models employing rules, decision lists, and tree-based algorithms assessed the impact of a prospect’s characterization and university outreach methods on application and enrollment probabilities. A novel two-stage modeling workﬂow, applied to each prediction problem, mirrored steps taken by a prospective candidate to become a future enrollee. This analysis could help a graduate school decide what communication mechanisms would be best utilized. Compared models were Gradient Boosted Machines (GBM), XGBoost, Random Forest, and Certiﬁably Optimal Rule Lists (CORELS). Application submission prediction using XGBoost achieved an ROC of 99.7%, while predicting enrollment with GBM had an ROC of 92.3%. The analysis concluded that there was insuﬃcient university out-reach activity to convert admitted applicants to enrollees. The modeling results support the notion that features related to prospect demographics and prospect-driven actions were more important as predictors for application submission and enrollment than the available university outreach activity volumes included in this analysis.
An electromyographic investigation of abdominal exercises and the effects of fatigue

Abdominal exercises are widely used to develop the anterior muscles of the trunk. These exercises can be undertaken without the aid of equipment, but increasingly manufacturers are developing equipment which purportedly enhances the training effect for abdominal muscles. As there are many different products and exercises used for abdominal muscle development, it is likely that some are more effective than others. This study aimed to investigate the effectiveness of five commonly performed abdominal exercises. A second aim was to investigate the effects of fatigue on these exercises. Five different types of abdominal exercise [standard crunch (sit-up) with bent knees, gym ball crunch, crunch with 5 kg weight held behind the head, legs raised crunch and a commercially manufactured roller crunch] were examined using integrated surface electromyography (IEMG). The lower rectus abdominis (LRA), upper rectus abdominis (URA) and obliquus externus abdominis (EO) of 15 healthy male participants [age (mean ± SD) 22.2 ± 6.8 years; height 1.77 ± 0.06 m; mass 79.3 ± 10.7 kg] were monitored using a four-channel special purpose EMG data logger. Three trials of each exercise were performed in random order and normalized to enable comparisons between muscles and exercises. At a later date, ten participants were then re-tested when fresh and after a 30 min whole-body fatigue protocol that specifically targeted the abdominal muscles. Two exercises were evaluated, the abdominal roller crunch and legs raised crunch, which were judged to be the least and most effective, respectively, of the five exercises previously used. The normalized IEMG showed significant (p < 0.001) differences between exercises (gym ball crunch = 86.0 ± 7.5%; legs raised crunch = 79.9 ± 5.1%; 5 kg weight crunch = 65.1 ± 13.4%; standard crunch = 56.2 ± 3.2%; and roller crunch = 45.0 ± 11.4%). Post-fatigue, the normalized mean IEMG for both exercises increased significantly (p < 0.05) for LRA and URA muscles but not for the EO (p > 0.05). It was concluded that exercises can be constructed to provide a greater challenge to abdominal muscles, commercially available roller-type equipment appears to be little different from the standard abdominal crunch with bent knees, and fatiguing exercise results in the LRA and URA being more highly activated. These findings provide more detailed knowledge and understanding of the effects of different forms of abdominal exercise.
Persons or Data Points? Ethics, Arti ﬁ cial Intelligence, and the Participatory Turn in Mental Health Research

This article identi ﬁ es and examines a tension in mental health researchers ’ growing enthusi-asm for the use of computational tools powered by advances in arti ﬁ cial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research speci ﬁ cally, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data points. The imperatives of the “ participatory turn ” in mental health research may be at odds with the (often unquestioned) assumptions and data collection methods of AI/ML approaches. This article aims to show why this is a problem and how it might be addressed.
DYNAMIC EFFECT OF POPULATION GROWTH ON UNEMPLOYMENT RATE IN NIGERIA

The paper examined the dynamic effect of population growth on unemployment rate in Nigeria. The paper is of the highest import as it discourses one of the strategic phases of the Nigerian economy and also bearing in mind that the country has been subjected to a slow growth rate and alarming unemployment rate. A dynamic ordinary least square (DOLS) was used to analyze the link between population growth and unemployment rate. Meanwhile, both the Augmented Dickey-Fuller unit root test and Johansen cointegration preceded the DOLS test in order to ascertain both the stationarity and long run equilibrium relationship of the variables. The empirical results showed that the variable was stationary at I(0) and I(1) and have long run equilibrium relationship. It was hypothesized from the DOLS result that the coefficient of determination is 61%, thus, the model is a good fit. Also, a direct relationship exists between population growth and unemployment rate. While an indirect relationship exists between per capital income and unemployment rate. Based on these findings, the study recommended amongst others that there should be population control in such a way that the population matches the available resources. Also, government should use the available resources with a well-coordinated fiscal and monetary policies in a manner to engage the teeming population that will make them be efficient in productivity which in the long run will trigger growth of the Nigerian economy as a result of reduction in unemployment.
Real-Time Randomized Path Planning for Robot Navigation

Robotic articulated systems for mobility Robotic articulated structures other then humanoids robots, for instance in vehicle design. There has been a lot of research done in humanoid robotic systems for the obvious challenge of replicating some, or all of our human motorist and perceptual skills largely driven by the interest to replace or assist humans in dangerous or demanding task from fighting wars to assisted living. Sports often act as catalyst in pushing technologic development in relation to human activity forward. Sort equipment also often acts as an extension of the body augmenting human movement and reach or interacting with the body.
Time Series Forecasting using CCA and Kohonen Maps-Application to Electricity Consumption

A general-purpose useful parameter in time series forecasting is the regressor, corresponding to the minimum number of variables necessary to forecast the future values of the time series. If the models used are non linear, the choice of this regressor becomes very difficult. We will show a quasiautomatic method using Curvilinear Component Analysis to build it. This method will be applied to electric consumption of Poland.
M a r k e dp r o o f

Discriminative training of language models has been the focus of renewed research interest recently, and signiﬁcant improvements to high accuracy large vocabulary continuous speech recognition have been demonstrated through the use of such models. In this chapter, we review past and present work on this topic, and focus in particular on three key issues: training data, learning algorithms and features. We will show how simple models trained under standard approaches can provide signiﬁcant accuracy gains with negligible impact on decoding time, and how richer models can provide further accuracy gains. We will argue that while the published results are promising, many practical issues remain under-explored, so that further improvements might be expected as the best practices become more developed.
Basic Cardiology

Aim of this study was to develop a convenient calculation of dose-response curves (DRCs) including those of theoretical model effects of combinations, using a commercial computer program which enables a clear visualization of confidence interval statistics and high quality graphs. The usefulness of this approach is exemplified by reevaluation of data from interaction experiments with nicorandil. Combination experiments were performed on bovine coronary artery strips in classical organ bath design. For the computerized calculation of DRCs, a “program package” was developed for SigmaPlot, consisting of user-defined worksheet/graph and program files (curve fits and transforms). Visualization of statistical deviations of experimental from dose-additive = competitive interaction was achieved by showing bars of 95 % confidence intervals (CIs) and DRCs with CIs of dose-additive combinations. Non-overlapping CI-ranges were considered significantly different. Dual relaxant effects of nicorandil could be split into single components of action by using combination experiments. The comparison of experimental with theoretical model effects of combinations allows conclusions with respect to the molecular sites of drug action and gives an indication as to the mechanisms of