Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiscale characterization of the mechanics of curved fibered structures with application to biological materials

Curved fibered structures are ubiquitous in nature and this organization is found in the majority of biological tissues. Indeed, the mechanical behavior of these materials is of pivotal importance in biomechanics and mechanobiology fields. In this paper, we develop a multiscale formulation to characterize the macroscopic mechanical nonlinear behavior from the microstructure of fibered matrices. From the analysis of the mechanics of a randomly curved single fiber, a fibered matrix model is built to determine the macroscopic behavior following a homogenization approach. The model is tested for tensile, compression and shear loads in a number of applications reminiscent to collagen extracellular matrices. However, any other fibered microstructures can be studied following the proposed formulation. The presented approach naturally recovers instabilities at compression as well as the strain stiffening regime, which are observed experimentally in the mechanical behavior of collagen matrices. Indeed, it was found that the bending energy associated to fiber unrolling, is the most important source of energy developed by fibers for the analyzed cases in tensile and shear in all deformation regions (except the strain stiffening region), whereas bending energy dominates at compression too during buckling. The proposed computational framework can also be used to perform multiscale simulations in the referred applications. As a result, the developed methodology may be an interesting and complementary tool to characterize the nonlinear behavior and evolution of curved fibered structures present in biology and engineered materials.
Partial Evaluation of Reversible Flowchart Programs

Flowchart languages are traditionally used to study the foundations of partial evaluation. This article presents a systematic and formal development of a method for partial evaluation of a reversible flowchart language. The results confirm that partial evaluation in this unconventional computing paradigm shows effects consistent with traditional partial evaluation. Experiments include specializing a symmetric encryption algorithm and a reversible interpreter for Bennett's reversible Turing machines. A defining feature of reversible languages is their invertibility. This study reports the first experiments composing program inversion and partial evaluation. The presented method is fully implemented. It is potentially of interest because reversible computing has found applications in areas as diverse as low-power computing, debugging, robotics, and quantum-inspired computing.
CD271 restrains the B1b cell antibody response in a T cell dependent manner

Co-signaling molecules modulate T cell function and are essential to control the duration and amplitude of immune responses. These molecules belong to the immunoglobulin and tumor necrosis factor receptor (TNFR) superfamilies and have been extensively studied; however, the immunomodulatory role of several family members remains unknown. We show that CD271 (also known as p75 or NGFR), a TNFR superfamily member, is highly expressed on peritoneal B1 B cells, but not on conventional (B2) B cells at steady state. CD271 expression by B cells specifically restrains the response to T cell-independent type 2 antigens (TI-2). B1 cell-expressed CD271 maintains peritoneal CD4+ T cell quiescence, and augmented antibody responses to TI-2 antigens in CD271-deficient mice are dependent on CD4+ T cells. This increase in antibody production correlates with improved bacterial neutralization in vitro and survival after bacterial challenge in vivo. Further, our results suggest that CD271 can directly inhibit mouse and human T cell activity to the same extent as PD-L1, a known, negative regulator of T cell function. These results establish CD271 as a co-inhibitory molecule that could be targeted to improve the efficacy of vaccines against pathogenic encapsulated bacteria and to broadly modulate the T cell response in therapeutic contexts. eTOC summary Lebel et al. identify an unexpected role for CD271, a neurotrophin receptor, in directly inhibiting T cell function. B1 cell-expressed CD271 maintains CD4+ T cell quiescence; in the absence of CD271, T cells bolster antibody production to T-independent antigens, enhancing the response to encapsulated bacteria.
PRogramAR: Augmented Reality End-User Robot Programming

The field of end-user robot programming seeks to develop methods that empower non-expert programmers to task and modify robot operations. In doing so, researchers may enhance robot flexibility and broaden the scope of robot deployments into the real world. We introduce PRogramAR (Programming Robots using Augmented Reality), a novel end-user robot programming system that combines the intuitive visual feedback of augmented reality (AR) with the simplistic and responsive paradigm of trigger-action programming (TAP) to facilitate human-robot collaboration. Through PRogramAR, users are able to rapidly author task rules and desired reactive robot behaviors, while specifying task constraints and observing program feedback contextualized directly in the real world. PRogramAR provides feedback by simulating the robot’s intended behavior and providing instant evaluation of TAP rule executability to help end-users better understand and debug their programs during development. In a system validation, 17 end-users ranging from ages 18 to 83 used PRogramAR to program a robot to assist them in completing three collaborative tasks. Our results demonstrate how merging the benefits of AR and TAP using elements from prior robot programming research into a single novel system can successfully enhance the robot programming process for non-expert users.
The Role of Bacterioplankton in Lake Erie Ecosystem Processes: Phosphorus Dynamics and Bacterial Bioenergetics

The effects of labile dissolved organic carbon (LDOC) on phosphorus dynamics of plankton were studied at diverse stations during synoptic surveys of Lake Erie aboard the CCGS Limnos in August of 2003 and June, July, and August of 2004. The sites represented diverse LDOC regimes, trophic states, and basin locations. LDOC values ranged from 13.7 to 126.5 μM. At higher LDOC concentrations, a greater portion of the phosphorus pool was distributed to algae, and at lower LDOC concentrations, a greater portion of the phosphorus pool is distributed to bacteria. Bacterial P-quota was greatest at stations with the lowest LDOC concentrations. Phosphate uptake by bacteria was greater at lower LDOC sites and lower at higher LDOC sites. LDOC concentration was not related to trophic state index (TSI), calculated based on chlorophyll a concentrations. These observations support the microbial shunt hypothesis (MSH). Phosphate apportionment to bacteria was consistent and independent of LDOC concentrations. This observation varies from the MSH.
Sesquiterpene Lactones and Phenols from Polyfollicles of Magnolia vovidessi and their Antimicrobial Activity

Bioassay-guided fractionation of an active crude extract (EtOAc) of polyfollicles of Magnolia vovidessi, an endemic medicinal plant of the cloud forest of Mexico, led to the isolation and identification of shizukolidol (1), an eudesmane-type sesquiterpenoid lactone that showed antibacterial activity against the economically important phytopathogenic bacterium Chryseobacterium sp. (MIC= 400 μg/mL). In addition, 4α,8β-dihydroxy-5α(H)-eudesm-7(11)-en-8,12-olide 8 (2), rutin, scopoline and scopoletine were also isolated as were mexicanin, parthenolide, costunolide, astragalin, quercetin, hesperidin, p-coumaric acid, chlorogenic acid, vanillin, vanillic acid, 4-hydroxybenzoic acid, protocatechuic acid and shikimic acid identified by a dereplication-like procedure using LC-ESI-MS/MS. Rutin displayed mild anti-oomicite activity against phytopathogen Phytophthora cinnamomi.
TransResU-Net: A Transformer based ResU-Net for Real-Time Colon Polyp Segmentation

Colorectal cancer (CRC) is one of the most common causes of cancer and cancer-related mortality worldwide. Performing colon cancer screening in a timely fashion is the key to early detection. Colonoscopy is the primary modality used to diagnose colon cancer. However, the miss rate of polyps, adenomas and advanced adenomas remains significantly high. Early detection of polyps at the precancerous stage can help reduce the mortality rate and the economic burden associated with colorectal cancer. Deep learning-based computer-aided diagnosis (CADx) system may help gastroenterologists to identify polyps that may otherwise be missed, thereby improving the polyp detection rate. Additionally, CADx system could prove to be a cost-effective system that improves long-term colorectal cancer prevention. In this study, we proposed a deep learning-based architecture for automatic polyp segmentation called Transformer ResU-Net (TransResU-Net). Our proposed architecture is built upon residual blocks with ResNet-50 as the backbone and takes advantage of the transformer self-attention mechanism as well as dilated convolution(s). Our experimental results on two publicly available polyp segmentation benchmark datasets showed that TransResU-Net obtained a highly promising dice score and a real-time speed. With high efficacy in our performance metrics, we concluded that TransResU-Net could be a strong benchmark for building a real-time polyp detection system for the early diagnosis, treatment, and prevention of colorectal cancer. The source code of the proposed TransResU-Net is publicly available at https://github.com/nikhilroxtomar/TransResUNet.
Engineering Pichia pastoris to improve S‐adenosyl‐
l‐methionine production using systems metabolic strategies

S‐adenosyl‐l‐methionine (SAM) is a highly valued chemical that can be used as a dietary supplement and has been used to treat depression, osteoarthritis, and liver problems as well. We adopted systems metabolic engineering strategies to improve SAM production in a high‐producing strain (GS115/DS56). First, the cystathionine β‐synthase gene CYS4 was downregulated using a weak promoter PG12 to reduce the removal of homocysteine from SAM cycle, thus leading to a 48.8% increase in the SAM titer (1.68 g/L) from the strain G12‐CBS, while preventing cysteine auxotrophy induced by deletion of this essential gene. Subsequently, the SAM titer of G12‐CBS was improved to 13.01 g/L in 15‐L fed‐batch fermentation using the optimal l‐methionine feeding strategy. Finally, based on comparative transcriptomics, five genes were chosen and overexpressed for further enhancement of SAM production. Among them, GDH2 and ACS2 exhibited positive effects, and the additional overexpression of GDH2 led to a 52.3% increase of titer (2.71 g/L) in shake flask culture. Therefore, the engineered Pichia pastoris strains can be utilized in industrial production of SAM using a simple and cost‐effective process, and these approaches could be employed for improving the production of other chemicals by P. pastoris.
The catalytic activity of microRNA Argonautes plays a modest role in microRNA star strand cleavage in C. elegans

Many Argonaute proteins can cleave RNA (“slicing”) as part of the microRNA-induced silencing complex (miRISC), even though miRNA-mediated target repression is generally independent of target cleavage. Here we use C. elegans to examine the role of miRNA-guided slicing in organismal development. We find that unwinding and decay of the miRNA star strand is weakly defective in the absence of slicing, with the largest effect observed in embryos. Argonaute-Like Gene 2 (ALG-2) is more dependent on slicing for unwinding than ALG-1. The miRNAs that displayed the greatest (albeit very minor) dependence on slicing for unwinding tend to form stable duplexes with their star strand, and in some cases, lowering duplex stability alleviates dependence on slicing. While a few miRNA guide strands are reduced in slicing mutants, the basis of this is unclear since changes were not dependent on EBAX-1, a factor in the Target-Directed miRNA Degradation (TDMD) pathway. Gene expression and gross phenotype were wild type in slicing mutants, indicating that 1) slicing is not required for target regulation and 2) the weak unwinding defect does not significantly reduce the pool of functional miRISC. Thus, in contrast to previous work, miRISC slicing in C. elegans is dispensable in standard laboratory conditions.
Endoscopy International Open Deep Learning and Capsule Endoscopy: Automatic Multi-brand and Multi-de-vice Panendoscopic Detection of Vascular Lesions

Introduction: Capsule endoscopy (CE) is commonly used as the initial exam for suspected mid-gastrointestinal bleeding after normal upper and lower endoscopy. Although the assessment of the small bowel is the primary focus of CE, detecting upstream or downstream vascular lesions may also be clinically significant. This study aimed to develop and test a Convolutional Neural Network (CNN)-based model for panendoscopic automatic detection of vascular lesions during CE. Methods: A multicentric AI model development study was based on 1022 CE exams. Our group used 34655 frames from seven types of CE devices, of which 11091 were considered to have vascular lesions (angiectasia or varices) after triple validation. We divided data into a training and a validation set, and the latter was used to evaluate the model’s performance. At the time of division, all frames from a given patient were assigned to the same dataset. Our primary outcome measures were sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and an area under the precision-recall curve (AUC-PR). Results: Sensitivity and specificity were 86.4% and 98.3%, respectively. PPV was 95.2%, while the NPV was 95.0%. Overall accuracy was 95.0%. The AUC-PR value was 0.96. The CNN processed 115 frames per second. Conclusion: This is the first proof-of-concept AI deep learning model developed for pan-endoscopic automatic detection of vascular lesions during CE. The diagnostic performance of this CNN in multi-brand devices addresses an essential issue of technological interoperability, allowing it to be replicated in multiple technological settings
RECENT INSIGHTS INTO THE VAGINAL MICROBIOTA

– Research on the vaginal microbiome and its relation to women’s health has steadily gained momentum in recent years. Traditionally, vaginal microbiome studies have focused on the pathogenesis of various diseases. Recent publications focus more on health and support a key role for Lactobacillus species and their dominance in maintaining a healthy state in the human vagina. In this narrative review, we synthesize promising novel insights related to vaginal microbiota published from April 2021 to March 2022. Hereby, we focus specifically on advances in understanding the vaginal microbiota composition by using innovative sequencing and detection tools. In addition, microbiota composition-influencing factors, potential microbe-based diagnostics and therapies are discussed.
Visible-Near-Infrared Spectroscopy Can Predict the Clay/Organic Carbon and Mineral Fines/Organic Carbon Ratios

The ratios of mineral fines (<0.02 mm, clay + fine silt) to organic carbon (OC), consisting of the n-ratio (i.e., the clay/OC ratio) and m-ratio (i.e., the fines/OC ratio) have recently been used to analyze and predict soil functional properties such as tilth conditions, clay dispersibility, degree of preferential flow, water repellency, and chemical adsorption. Conventional texture and OC measurements are time consuming and expensive, and visible–near-infrared (vis-NIR) spectroscopy may provide a fast and inexpensive alternative for obtaining the n- and m-ratios. In this study, a total of 480 soil samples from seven Danish and one Greenlandic fields, with a large textural range (clay: 0.027–0.355 kg kg⁻¹; OC: 0.011–0.084 kg kg⁻¹; n-ratio: 0.49–16.80; m-ratio: 1.46–32.14), were analyzed for texture and OC and subsequently scanned with a vis-NIR spectrometer from 400 to 2500 nm. The spectral data were correlated to reference values of the n-ratio, m-ratio, clay, fine silt, fines, and OC with partial least squares regression. The vis-NIR models were developed on a regional dataset comprising the 480 soil samples divided into calibration and validation subsets. Further, we tested vis-NIR models developed on the individual eight fields using full cross-validation. Validation results from the regional models showed high predictive abilities with a root mean square error of prediction (RMSEP) of 0.64 and R² of 0.97 for the n-ratio and RMSEP = 1.43 and R² of 0.97 for the m-ratio. The regional clay, fine silt, fines, and OC models also yielded successful predictions (R² = 0.88–0.95). The higher prediction accuracy for the n- and m-ratios compared with predictions of basic soil properties was confirmed from the field-specific models. Our results suggest vis-NIR spectroscopy as a precise, easily applicable, and fast method for simultaneously obtaining an ensemble of key parameters for soil structure and health.
A Shared Vision? Exploring the Perceptions of A Shared Vision? Exploring the Perceptions of Principals and Teachers Regarding the Middle Principals and Teachers Regarding the Middle School Concept School Concept

From decades of recommendations, middle school advocates have recommended various organizational structures and instructional practices to meet the specific educational needs of young adolescents. Several notable national studies have sought to assess and report the status of implementation of these recommended practices, though largely from the perspective of the building principal. The purpose of this study was to examine both teacher s’ and principals’ perceptions concerning the middle school concept. Based on responses of over 1,600 teachers and principals from all 50 states, findings indicate support for components of the middle school concept related to curriculum and instruction as well as school culture; however, support for components related to middle school philosophy and organizational structures received the lowest levels of support from principals and teachers. While reported support for middle school students was encouraging, the waning support for the philosophical and organizational components often considered foundational to the middle school concept was concerning.
Learning of Nonnegative Matrix Factorization Models for Inconsistent Resolution Dataset Analysis

SUMMARY Due to the need to protect personal information and the impracticality of exhaustive data collection, there is increasing need to deal with datasets with various levels of granularity, such as user-individual data and user-group data. In this study, we propose a new method for jointly analyzing multiple datasets with di ﬀ erent granularity. The proposed method is a probabilistic model based on nonnegative matrix factorization, which is derived by introducing latent variables that indicate the high-resolution data underlying the low-resolution data. Experiments on purchase logs show that the proposed method has a better performance than the existing meth-ods. Furthermore, by deriving an extension of the proposed method, we show that the proposed method is a new fundamental approach for analyzing datasets with di ﬀ erent granularity.
Assessment of User Satisfaction in an Outdoor Gym as a Tool for Improvements and Increased Adherence

The study aimed to assess the satisfaction of Outdoor Gym (OG) users to identify areas for improvement that could enhance adherence to the practice. It is an exploratory and descriptive study involving 38 OG users. Participants completed a questionnaire to characterize the sample and profile, followed by the System Usability Scale to evaluate satisfaction with the equipment. The results revealed that users had an average age of 48 ± 13.3 years, with the majority being women (71%). They had been attending OG for approximately 12 ± 7.8 months, with the majority (61%) going at least 5 times a week. The proximity of OG to their homes (47%) was the primary reason for practicing, mainly with the goal of promoting health (71%). Areas for improvement identified included the need for a Physical Education Professional (PEF) and a space for children. Regarding satisfaction, the double diagonal rotation equipment obtained the highest score (90.1 ± 13.7), followed by the leg pressure equipment (84.3 ± 18.3), horse riding simulator (81.3 ± 16.9), skiing (77.6 ± 18.5), and surfing (73.9 ± 19.6). The proximity of the OG to the residence appears to be a significant factor in initiating the practice. It is suggested that the presence of a PEF and a space for children can complement satisfaction and encourage adherence and regular practice. However, additional studies with diverse populations are needed to target strategies that promote adherence.
Does the Hartz IV Reform have an Eﬀect on Matching Eﬃciency in Germany? A Stochastic Frontier Approach

In the course of a comprehensive labor market reform started in 2002 and ﬁnished through the implementation of the most radical measure Hartz IV in 2005, I exploit its impact on matching processes in Germany. I use disaggregated data for 178 local employment agencies to examine the eﬀects of stocks and ﬂows of vacancies and unemployed on the hiring rate as well as on the matching eﬃciency. Building on the work of Ibourk et al. (2004) and Fahr and Sunde (2006), I employ a stochastic frontier analysis. As a functional framework I choose the translog function to address the interactions of stocks and ﬂows in generating new hires. Furthermore, the twofold structure of a stochastic frontier allows for a modeling of potential sources (e.g. Hartz IV) expected to induce an increased or decreased matching eﬃciency. My results suggest that Hartz IV exhibits a signiﬁcantly positive impact on the hiring rate and the matching eﬃciency. Compared to 1998, on average matching eﬃciency experienced an increase in 2007.
Using Problem-Based Learning and Gamiﬁcation as a Catalyst for Student Engagement in Data-Driven Engineering Education: A Report

: This report explores the integration of problem-based learning, gamiﬁcation, and data-driven approaches in engineering education. With a focus on the course “GeoGovernment 1”, this framework aimed to engage students actively and foster self-directed learning. By tackling real-world issues like automated teller machine (ATM) burglaries in Rhineland-Palatinate (Germany), students gained experience in data analyses and geoinformatics technology. This approach not only motivated students but also enhanced their prospects in science, technology, engineering
…::KENT AKADEMİSİ | URBAN ACADEMY

This study aims to empirically examine the causality nexus between carbon emissions (CO2) and economic growth in Türkiye in the post - Republican period between 1923-2018. The main objective of the study is to shed light on Türkiye's sustainable development efforts from the past to the present by analyzing the nexus between carbon emissions and economic growth, taking into account the periodic factors in this period. In this way, the study aims both to learn from the experiences of the past and to support future policy decisions. According to the results of the Hacker and Hatemi-J (2006) causality test, there is bidirectional causality between the two variables. According to the results of Rolling Window Causality Analysis, there is a direct causality nexus between CO2 emissions and GDP in the sub-periods 1955-1959, 1974-1975, 1987-1989, 1993-1997 and 2008-2010, and between economic growth and carbon emissions in the sub-period 1981-1988. This study aims to contribute to the understanding of the complex interaction between the environment and the economy in shaping the next 100 years of the Republic of Türkiye .