Miracle-dz/UniFAR-FTUs huggingface dataset:
Disruption of the bacterial OLE RNP complex impairs growth on alternative carbon sources

Abstract Ornate, large, extremophilic (OLE) RNAs comprise a class of large noncoding RNAs in bacteria whose members form a membrane-associated ribonucleoprotein (RNP) complex. This complex facilitates cellular adaptation to diverse stresses such as exposure to cold, short-chain alcohols, and elevated Mg2+ concentrations. Here, we report additional phenotypes exhibited by Halalkalibacterium halodurans (formerly called Bacillus halodurans) strains lacking functional OLE RNP complexes. Genetic disruption of the complex causes restricted growth compared to wild-type cells when cultured in minimal media (MM) wherein glucose is replaced with alternative carbon/energy sources. Genetic suppressor selections conducted in glutamate MM yielded isolates that carry mutations in or near genes relevant to Mn2+ homeostasis (ykoY and mntB), phosphate homeostasis (phoR), and putative multidrug resistance (bmrCD). These functional links between OLE RNA, carbon/energy management, and other fundamental processes including protein secretion are consistent with the hypothesis that the OLE RNP complex is a major contributor to cellular adaptation to unfavorable growth conditions.
Natural Killer Cells as a Further Insight into the Course of Chronic Obstructive Pulmonary Disease

The role of natural killer (NK) cells in chronic obstructive pulmonary disease (COPD) pathogenesis has been discussed but is not yet clearly understood. This current study aimed to evaluate the associations between immunophenotypes, degrees of maturity, and the expression level of functional receptors of NK cells in the lung environment present in bronchoalveolar lavage fluid (BALF), and an attempt was made to determine their relationship in the course and progression of COPD. A total of 15 COPD patients and 14 healthy smokers were included. The clinical parameters of COPD were evaluated. In both groups, NK cells using monoclonal antibodies directly conjugated with fluorochromes in flow cytometry were assessed in the peripheral blood. Additionally, NK cells using the same method were assessed in BALF in the COPD subgroup. The blood’s NK cells differed from the estimated group’s maturity and receptor expression. Functional receptors CD158b+, CD314+, and CD336+ expressed by NK cells were significantly interlinked with age, RV, TLC, 6MWT, smoking, and the number of exacerbations. These results confirm the essential role of NK cells in COPD pathogenesis. Additionally, the relationship between clinical parameters and NK cell expression may indicate its participation in the disease progression and exacerbation and allow for a better understanding of NK cell biology in COPD.
Power Imbalance Analysis of Modular Multilevel Converter With Distributed Energy Systems

The modular multilevel converter (MMC) can integrate distributed energy systems (DES), such as a battery energy storage system, to expand its functionalities and carry out multiple simultaneous tasks. However, a DES induces power imbalances within the MMC, which affects the operating currents and voltages of the converter. This phenomenon has been partially covered in recent works, but an analytical analysis has not yet been carried out to see the behavior and implications in different MMC-DES applications. This article introduces a novel analytical analysis of the power imbalances between MMC clusters. It pioneers the development of general equations and imbalance capability metrics, enabling the assessment of maximum currents and voltages supported by the MMC clusters. The developed tools allow the evaluation of any MMC-DES application regarding the current and voltage rating requirements of MMC clusters. The analysis shows that the MMC operating mode can substantially restrain or enlarge its imbalance capacity, affecting its suitability for different DES applications. While it needs around 33% current overrating in the worst imbalances, under some operating modes it can reach most imbalances without requiring current overrating. The ac compensation mode is much more capable of achieving imbalances than the dc compensation mode, reaching 88.37% and 16.74% of the imbalance points, respectively, without requiring any overrating.
Flexural Performance of Mono-material and Multimaterial Fused Filament Fabrication Honeycomb Structures

Additive manufacturing, specifically Fused Filament Fabrication is a widely used and affordable layer-based manufacturing process that is also capable of multi-material printing. The honeycomb sandwich structures can be fabricated by multi-material fused filament fabrication to acquire desirable material properties and minimize weight which is essential in the automotive and aerospace industry. This study aims to examine the flexural properties of the mono-material and multi-material sandwich structures, particularly Honeycomb, Rectangular Horizontal, and Rectangular Vertical. The materials selected for the experiment are polylactic acid (Ultimaker PLA Green) and acrylonitrile butadiene styrene (Ultimaker ABS Red). According to the results of the three-point bending test, the highest flexural strength and elastic modulus were achieved by the Honeycomb configuration for mono-material PLA and ABS as well as ABSPLA-ABS structures. As for the PLA-ABS-PLA sandwich parts, the best flexural performance was exhibited by the Rectangular Vertical configuration.
Developing numeric nutrient criteria for streams on the Delmarva Peninsula

Title of Thesis: DEVELOPING NUMERIC NUTRIENT CRITERIA FOR STREAMS ON THE DELMARVA PENINSULA. Lindsay Ayn Tempinson, Master of Science, 2016 Directed By: Professor, Dr. Thomas R. Fisher, University of Maryland Center for Environmental Sciences, Horn Point Laboratory To better address stream impairments due to excess nitrogen and phosphorus and to accomplish the goals of the Clean Water Act, the U.S. Environmental Protection Agency (EPA) is requiring states to develop numeric nutrient criteria. An assessment of nutrient concentrations in streams on the Delmarva Peninsula showed that nutrient levels are mostly higher than numeric criteria derived by EPA for the Eastern Coastal Plain, indicating widespread water quality degradation. Here, various approaches were used to derive numeric nutrient criteria from a set of 52 streams sampled across Delmarva. Results of the percentile and y-intercept methods were similar to those obtained elsewhere. Downstream protection values show that if numeric nutrient criteria were implemented for Delmarva streams they would be protective of the Choptank River Estuary, meeting the goals of the Chesapeake Bay Total Maximum Daily Load (TMDL). DEVELOPING NUMERIC NUTRIENT CRITERIA FOR STREAMS ON THE DELMARVA PENINSULA
PORE PRESSURE GENERATION IN SATURATED SAND INDUCED BY ONE- AND TWO-DIMENSIONAL SHAKINGS

The test data obtained from shaking table tests at the National Center for Research on Earthquake Engineering were processed and analyzed to study the effect of one- and two-dimensional shakings on soil liquefaction. The measured pore water pressures generated under one- and two-dimensional shakings at various locations within the sand specimens were compared. It was found that the ratios of the maximum excess pore water pressure generated in the sand specimens under two-dimensional shakings to that generated under one-dimensional shakings were always larger than 1.0 and the values were about the same at all different piezometer locations in the same shaking table test series. The ratio of the maximum pore pressure ratio, (ru)max  (u/v')max, under two-dimensional shakings to that under one-dimensional shakings is approximately 5.0, and 3.0 for Vietnam sand and Mailiao sand, respectively. Analyses based on these findings showed that the liquefaction resistance of sand under two-dimensional shakings is approximately 0.75 to 0.85 of that under one-dimensional shakings.
Seguimiento del Desarrollo Psicomotor en un Caso con Microdeleción Distal 1q21.1

espanolEl sindrome de microdelecion 1q21.1 es una enfermedad rara, provocado por una diminuta delecion 1.35 Mb recurrente en la region 1q21. Los individuos con esta alteracion genetica pueden tener una amplia gama de manifestaciones clinicas. Algunos de los casos estudiados no presentan sintomas, mientras que otros muestran caracteristicas fenotipicas como pueden ser microcefalia, retraso en el desarrollo, rasgos dismorficos y convulsiones. Este trabajo reporta el caso de un nino de 40 meses de edad, al que se le detecta esta alteracion, a la edad aproximada de 12 meses, mediante estudio genetico Microarray; basado en la hibridacion genomica comparada (Comparative Genomic Hybridization) ( a- CGH en adelante). Presenta rasgos dismorficos faciales, microcefalia asi como retraso en su desarrollo psicomotor. No se han encontrado estudios de caso unico en la literatura cientifica centrados en el funcionamiento psicomotor, por lo que son necesarias mas aportaciones a fin de esclarecer esta cuestion. El presente estudio se encamina en esa vertiente, teniendo como objetivos principales analizar de forma detallada las caracteristicas de su desarrollo psicomotor empleando el Inventario de Desarrollo Battelle y realizar el seguimiento de la intervencion neuropsicologica. English1q21.1 Microdeletion syndrome is a rare disorder, caused by a tiny and recurrent 1.35 Mb deletion in the 1q21.1 region. Individuals with this genetic alteration may have a wide range of clinical manifestations. Some cases have no symptoms, while others show a wide range of phenotypic characteristics such as microcephaly, developmental delay, seizures and dysmorphic features. This paper reports the case of a 40 month old child, whose alteration was detected by means of genetic studies, based on Microarray-based comparative genomic hybridization (a- CGH onwards), when he was 12 months old. He has facial dysmorphic features, microcephaly and delayed psychomotor development, as well. There is no evidence of single case study through scientific literature on psychomotor functioning, so more contributions to clarify this issue are needed. The present study is focused on this aspect with the main objectives of analysing in detail the characteristics observed in his psychomotor development, using the Battelle Developmental Inventory and perform monitoring of the neuropsychological treatment.
Distributed matching theory-based task re-allocating for heterogeneous multi-UAV edge computing

Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle (UAV) edge computing. However, the heterogeneity of UAV computation resource, and the task re-allocating between UAVs have not been fully considered yet. Moreover, most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function (SF). In this backdrop, this paper formulates the task scheduling problem as a multi-objective task scheduling problem, which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks' completion time and energy consumption. Optimizing three coupled goals in a real-time manner with the dynamic arrival of tasks hinders us from adopting existing methods, like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process, or heuristic-based ones that usually incur along decision-making time. To tackle this problem in a distributed manner, we establish a matching theory framework, in which three conflicting goals are treated as the preferences of tasks, SFs and UAVs. Then, a Distributed Matching Theory-based Re-allocating (DiMaToRe) algorithm is put forward. We formally proved that a stable matching can be achieved by our proposal. Extensive simulation results show that DiMaToRe algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.
Hope amidst crisis: exploring perinatal mental health and family dynamics in out-of-home care through virtual assessments during the UK COVID-19 response

Caring for a young child exposed to early trauma, along with caregiving stress and heightened by the impact of lockdowns as a result of the COVID-19 response, may compromise the development of the parent-child relationship. Understanding a foster carer's attachment history and considering relational dynamics through an attachment lens may shed light on areas they need support in, to enhance their parenting capacity for vulnerable children. The feasibility of collecting and coding observational data and attachment interviews of foster carers and their children, when conducted remotely during COVID-19, needs to be explored. This perspective piece considers the impact on infant and perinatal health in the context of COVID-19 with particular emphasis on relational dynamics and attachment assessments, using a case study of a foster carer and her child in an out-of-home-care placement. Understanding these dynamics is crucial for safeguarding the well-being of both caregivers and vulnerable children during this challenging time.
Empowering Secondary Education Through AI-Supported E-Learning

The research paper offers a revolutionary web application for reshaping education that consists of four essential AI-driven elements. These elements include story generation, short note generation, auto essay grading, and multiple-choice question generation. The MCQ generation uses NLP to quickly produce a variety of MCQs, assisting educators in assessments and giving students a variety of practice. Concise summaries are produced by short note generation, which improves understanding, and lengthy assignments are objectively graded by auto essay grading, which lessens the stress on instructors. Through AI-crafted narratives, the story generation component encourages innovation with support from actual examples and user feedback. The article describes each tool's design, implementation, and effectiveness. This study supports cutting-edge educational practices by advancing learning, evaluation, and engagement while integrating technology's changing role.
Research progress, challenges and perspectives of phospholipids metabolism in the LXR-LPCAT3 signaling pathway and its relation to NAFLD (Review)

Phospholipids (PLs) are principle constituents of biofilms, with their fatty acyl chain composition significantly impacting the biophysical properties of membranes, thereby influencing biological processes. Recent studies have elucidated that fatty acyl chains, under the enzymatic action of lyso-phosphatidyl-choline acyltransferases (LPCATs), expedite incorporation into the sn-2 site of phosphatidyl-choline (PC), profoundly affecting pathophysiology. Accumulating evidence suggests that alterations in LPCAT activity are implicated in various diseases, including non-alcoholic fatty liver disease (NAFLD), hepatitis C, atherosclerosis and cancer. Specifically, LPCAT3 is instrumental in maintaining systemic lipid homeostasis through its roles in hepatic lipogenesis, intestinal lipid absorption and lipoprotein secretion. The liver X receptor (LXR), pivotal in lipid homeostasis, modulates cholesterol, fatty acid (FA) and PL metabolism. LXR's capacity to modify PL composition in response to cellular sterol fluctuations is a vital mechanism for protecting biofilms against lipid stress. Concurrently, LXR activation enhances LPCAT3 expression on cell membranes and elevates polyunsaturated PL levels. This activation can ameliorate saturated free FA effects in vitro or endoplasmic reticulum stress in vivo due to lipid accumulation in hepatic cells. Pharmacological interventions targeting LXR, LPCAT and membrane PL components could offer novel therapeutic directions for NAFLD management. The present review primarily focused on recent advancements in understanding the LPCAT3 signaling pathway's role in lipid metabolism related to NAFLD, aiming to identify new treatment targets for the disease.
A Lightweight Bridge Surface Damage Detection Method Based on YOLOv7

In response to the shortcomings of traditional bridge damage detection algorithms in terms of accuracy, real-time performance, and small target damage detection, this paper proposes a lightweight bridge damage detection model based on Yolov7. In order to improve the detection accuracy and real-time performance, we use the lightweight MobileNet network to replace the original backbone network and use depth-separable convolution instead of traditional convolution. At the same time, we embed the CA (Coordinate Attention) module in the feature enhancement network to enhance the feature extraction ability of damage. To verify the effectiveness of the proposed algorithm, we have established a dataset containing 3018 bridge surface damage images and trained it through manual labeling and data augmentation. The experimental results show that compared with the original model, our proposed algorithm improves accuracy by 0.24%, while reducing computation by 72.80% and parameters by 49.36%. This indicates that our algorithm can significantly reduce computation and parameters while ensuring detection accuracy.
Competences and the Digital Transformation: Case Study of a German Management Consultancy

Digital transformation (DT) has become a challenge for social, business and education systems, as it requires sophisticated ways of management in comparison to traditional, well-established project management methods. In addition, certain competences, as well as new competence profiles, emerge during this transformation. Following the case study method based on a well-established German management consultancy, a series of interviews, a focus group discussion, and analysis of competences and DT management approaches were conducted to answer the following research questions: (1) what are people-related challenges in DT projects? (2) how people enable success of DT projects? (3) are there specific competences relevant for DT projects’ success? Application of the qualitative research methods resulted in such findings as: the biggest challenge in the DT management is a lack of the right set of competences, the “Number 1” factor of the successful DT is a change management, and the right problem-solving mindset, empathy, and ability to learn are above all needed for DT skills.
Extracellular Vesicles in Flaviviridae Pathogenesis: Their Roles in Viral Transmission, Immune Evasion, and Inflammation

The members of the Flaviviridae family are becoming an emerging threat for public health, causing an increasing number of infections each year and requiring effective treatment. The consequences of these infections can be severe and include liver inflammation with subsequent carcinogenesis, endothelial damage with hemorrhage, neuroinflammation, and, in some cases, death. The mechanisms of Flaviviridae pathogenesis are being actively investigated, but there are still many gaps in their understanding. Extracellular vesicles may play important roles in these mechanisms, and, therefore, this topic deserves detailed research. Recent data have revealed the involvement of extracellular vesicles in steps of Flaviviridae pathogenesis such as transmission, immune evasion, and inflammation, which is critical for disease establishment. This review covers recent papers on the roles of extracellular vesicles in the pathogenesis of Flaviviridae and includes examples of clinical applications of the accumulated data.
Arsenic Impairs Wound Healing Processes in Dermal Fibroblasts and Mice

Inorganic arsenic (NaAsO2) is a naturally occurring metalloid found in water resources globally and in the United States at concentrations exceeding the U.S. Environmental Protection Agency Maximum Contamination Level of 10 ppb. While exposure to arsenic has been linked to cancer, cardiovascular disease, and skin lesions, the impact of arsenic exposure on wound healing is not fully understood. Cultured dermal fibroblasts exposed to NaAsO2 displayed reduced migration (scratch closure), proliferation, and viability with a lowest observable effect level (LOEL) of 10 µM NaAsO2 following 24 h exposure. An enrichment of Matrix Metalloproteinase 1 (MMP1) transcripts was observed at a LOEL of 1 µM NaAsO2 and 24 h exposure. In vivo, C57BL/6 mice were exposed to 10 µM NaAsO2 in their drinking water for eight weeks, then subjected to two full thickness dorsal wounds. Wounds were evaluated for closure after 6 days. Female mice displayed a significant reduction in wound closure and higher erythema levels, while males showed no effects. Gene expression analysis from skin excised from the wound site revealed significant enrichment in Arsenic 3-Methyltransferase (As3mt) and Estrogen Receptor 2 (Esr2) mRNA in the skin of female mice. These results indicate that arsenic at environmentally relevant concentrations may negatively impact wound healing processes in a sex-specific manner.
Video-Based Fruit Detection and Tracking for Apple Counting and Mapping

Automatic fruit counting systems have garnered interest from farmers and agronomists to monitor fruit production, predict yields in advance, and identify production variability across orchards. However, accurately counting fruits poses challenges, particularly due to occlusions. This study proposes a multi-view sensing approach using continuous motion videos captured by a camera moved along the row of trees, followed by fruit detection in all video frames and application of Multi-Object Tracking (MOT) algorithms to prevent double-counting. Three tracking methods, namely SORT, DeepSORT, and ByteTrack, are compared for fruit counting using the YOLOv5x object detector. The methodology is applied to map fruit production in an experimental apple orchard at two different dates: four weeks and one week before harvest. The results demonstrate that ByteTrack (MOTA=0.682; IDF1=0.837; HOTA=0.689) outperforms SORT and DeepSORT, indicating its superior tracking performance. Computational efficiency analysis reveals similar processing times between SORT and ByteTrack (about 15 ms), while DeepSORT requires significantly more processing time per image (128 ms). Fruit counting evaluation shows reasonably accurate yield predictions on both dates, with reduced errors and improved performance closer to the harvest date (MAPE=7.47 %; $R^{2}$=0.70). The system proves effective in estimating orchard fruit production using computer vision technology, offering valuable insights for yield forecasting. These findings contribute to optimizing fruit production and supporting precision agriculture practices. The code and the dataset have been made publicly available and a video visualization of results is accessible at http://www.grap. udl.cat/en/publications/video_fruit_counting.