Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Transcript Variant 6 of TPD52L2 as a Prognostic and Predictive Biomarker in Basal-Like MDA-MB-231 and MDA-MB-453 Cell Lines for Breast Cancer

Background Basal-like breast cancer (BLBC) exhibits worse pathological features than other breast cancer subtypes, and patients diagnosed with BLBC have short disease-free and overall survival times. Thus, the identification of novel biomarkers and therapeutic targets for BLBC is of upmost importance. Although TPD52L2 is upregulated in multiple cancers, little is known about its roles in BLBC. Methods RNA levels were analyzed between breast cancer tissues and paired adjacent normal tissues using RNA-seq data from The Cancer Genome Atlas (TCGA). TPD52L2 stable knockdown and inducible knockout cell lines were established using basal-like MDA-MB-231 and MDA-MB-453 cell lines. Cell proliferation assays in vitro and tumor growth analysis in vivo were performed to determine the function of TPD52L2 during BLBC progression. Transwell assays were used to estimate the regulatory effect of TPD52L2 on BLBC cell migration. The expression profile of all tpd52l2 transcripts was analyzed to assess the functional protein isoform. Association of transcript variant 6 (V6) expression with pathological parameters was carried out using the clinical data of the BRCA cohort. Results We identified V6 of TPD52L2 as a novel biomarker and regulator of BLBC progression. TPD52L2 is upregulated in BLBCs and associated with patient outcomes. TPD52L2 knockdown suppresses tumor growth, and V6 correlates with cancer-related phenotypes in BLBC. Clinical data further proved that V6 is associated with different pathological features, such as pathological stage and pathological tumor status, and independently predicts patient outcomes and responses to therapies. Conclusions Our findings demonstrate that V6 of TPD52L2 is a novel biomarker for BLBC patients. V6 promotes cell proliferation and migration and has marked oncogenic roles in determining the malignant phenotypes of BLBC.
Leaf spot disease of groundnut: A review of existing research on management strategies

Abstract The early and late leaf spot disease (ELS and LLS) caused by the Cercospora arachidicola and Cercosporidium personatum is one of the most important economic diseases in groundnut production. The effect of the disease can lead to up to 70% yield loss under severe conditions. Even though there are an array of management approaches in curbing the menace of the disease, these seem not to be enough to completely control the disease. It is therefore important to develop additional and more improved strategies via the implementation of sustainable approaches. Around the globe, several researches have been conducted on this topic, with most of them leading to prosperous and dynamic outcomes that could lead to a lasting solution to the disease, and hence improving farmers’ income. It is therefore important to know what work has been done in order to identify gaps that needs to be filled. The objective of this review is to discuss recent research findings on the management of the leaf spot disease on groundnut. This will include cultural control, chemical control, the use of antagonistic organisms, and host plant resistance. These areas unabatedly continue to be an active research area, and current information on their efficacy will continuously be available. In this review, we have discussed some of the mechanisms involved and also suggested some ways to maximize the outcomes for further interventions.
Using Listener Gaze to Refer in Installments Benefits Understanding

Listener gaze can predict reference resolution as it reﬂects listeners’ understanding. Further, speakers commonly refer in installments to co-present objects by providing a description incrementally. Here, we investigate whether listener gaze could be utilized to refer incrementally, in spoken installments. Speciﬁcally, we implemented a system that generates instructions, describes objects, and reacts to listener gaze with verbal feedback. We compared unambiguous vs. ambiguous instructions supplemented by two levels of feedback speciﬁcity: either underspeciﬁed (“No, not that one! ”) or more informative, contrastive responses (“Further left! ”). Our ﬁndings show that ambiguous instructions with underspeciﬁed feedback did not beneﬁt task performance. In contrast, ambiguous instructions with contrastive feedback (referring in installments) resulted in more efﬁcient interactions. Moreover, this strategy even out-performed the one providing unambiguous instructions.
Constitutive modeling for hydrogel with chain entanglements and application to adaptive hydrogel composite structures

Abstract Hydrogel is one of typical smart materials and has been used in many engineering applications, such as flexible electronics, flexible robots, and biomedical engineering. Modern industries with complex working environments require hydrogel to have higher strength without losing flexibility. Many published experimental studies focus on the preparation technique of hydrogel composite with high strength and toughness. However, the theoretical investigation into the influence of entanglements on the hydrogel deformation is rarely reported for the structure analysis and deformation mechanism of hydrogel composite, as a purpose to design of hydrogel devices. In this paper, the constitutive model is developed for thermal responsive hydrogel with chain entanglements, based on Flory-Rehner theory and slip-link model, and numerically solved by a user subroutine in ABAQUS. The uniaxial tensile and compressive simulations of standard specimens are carried out to validate the proposed model and demonstrate the applicability of the hydrogel composite, in which a great agreement is obtained by comparing the simulation results to the experimental data from published work. Subsequently, the hydrogel composites with three types of structure, such as hydrogel grippers, scaffolds and skins, are designed to improve the overall strength and maintain the flexibility of the devices, inspired by the deformation mismatch characteristics of multilayer hydrogels. The results show that the properties of composite hydrogels are closely related to the level of entanglements, cross-link and composite structures. This work may contribute to the preparation of reinforced hydrogels and provide insights for the design of hydrogel multifunctional devices.
Neutronic and burnup characteristics of potential dual‐cooled annular (Th‐233U‐235U)O2 fuel for the advanced pressurized water reactors: An assembly‐level analysis

Many efforts are now being made to ensure nuclear power plant safety and efficiency. One of these is the use of dual‐cooled annular fuel, which is an internally and externally cooled annular fuel with many advantages in heat transfer characteristics and neutron thermalization. Another is the tendency to use thorium‐containing fuel to extend the fuel cycle and reduce plutonium production. Hence, in this study, the performance of dual‐cooled annular fuel fueled by a new suggested thorium‐based fuel, namely (Th‐233U‐235U)O2, has been presented and investigated from a neutronic point of view in an AP1000 reactor assembly. The neutronic and safety properties of the envisaged dual‐cooled annular assemblies are compared to those of two hypothetical reference assemblies fueled with UO2 and (Th‐233U)O2. The primary neutronic goal is to achieve a longer cycle length than the proposed reference assemblies while retaining or improving safety parameters over the reference assemblies. The obtained results show that the studied dual‐cooled annular assemblies have a longer criticality period than the reference designs. Other safety parameters, such as the power peaking factor, the delayed neutron fraction, and the moderator and fuel temperature coefficients, demonstrate that dual‐cooled annular assemblies have favorable safety parameters compared to UO2 or (Th‐233U)O2. However, this analysis would benefit from a more detailed burnup simulation based on a full core modeling, as well as a comprehensive thermal‐hydraulic analysis in conjunction with a neutronic analysis.
Planning for wooden multistorey construction – insights from Finland's municipal civil servants

ABSTRACT Municipalities across Finland are promoting wooden multistorey construction as a low-carbon alternative for building construction. However, do attitudes towards implementing these alternatives stem from the opportunity to reduce carbon emissions or because these alternatives are perceived to improve local economies? This research employs a survey to collects the attitudes of Finnish municipal civil servants towards implementing wooden multistorey buildings in their municipalities. The respondents represent a mix of administrative professionals such as planners, real estate managers, building inspectors and other strategic managerial professionals (n = 273, 8% response rate). Their responses reflect views from approximately 8% of all municipal civil servants working on municipal land use and planning issues during 2019. The findings reveal attitudes towards implementing wooden multistorey buildings are engendered by fulfilling ecological development, economic development, technical quality and output efficiency goals. Furthermore, comparing municipal planners to other municipal administrators reveals dissimilar planning logics. Municipal planners holistically prioritize the project's ecological and economic development outcomes. Other administrators chiefly prioritize economic development outcomes. Hence, some municipal administrators may value wooden multistorey construction primarily as an activity to improve municipal vitality rather than as a holistic spatial planning solution. Future research should identify whether these divergences lead to planning tensions within municipal administrations.
Development of a Multi-Scale Tomato Yield Prediction Model in Azerbaijan Using Spectral Indices from Sentinel-2 Imagery

This paper presents the development and update of a multi-scale yield prediction model for processing tomatoes. The study was carried out under the EU-funded programme “Support to Development of a Rural Business Information System (RBIS)”, and the performance of the updated crop-specific yield prediction models and their generated predictions at regional and national levels are presented. The model was built using Sentinel-2 satellite imagery to obtain cumulative values of six (6) selected vegetation indices (VIs). The data were collected on five (5) different dates for processing tomato fields in the Khachmaz region of Azerbaijan during summer 2021 (June to August) at 10- to 13-day intervals. In addition, a targeted field sampling campaign was conducted on selected Khachmaz pilot fields towards the end of the growing season to assess the potential of Sentinel-2 data to determine yield variability in tomato fields. Finally, actual recorded yields were collected at the field level to build the yield prediction regression model and evaluate its performance at different spatial scales, ranging from single field to national level, as well as under different data availability scenarios (number of consecutive Sentinel-2 images used). The results showed a high degree of correlation between all implemented VIs and processing tomato yield, with a coefficient of determination of up to 0.89 for the NDVI, providing valuable information for future estimates of tomato production across multiple spatial scales. The developed prediction model could also be used in the agri-food sector for national yield estimates to support policy and regulatory decisions at the national level.
Information Freshness in Multihop Wireless Networks

We consider the problem of minimizing age of information in multihop wireless networks and propose three classes of policies to solve the problem - stationary randomized, age difference, and age debt. For the unicast setting with fixed routes between each source-destination pair, we first develop a procedure to find age optimal Stationary Randomized policies. These policies are easy to implement and allow us to derive closed-form expression for average AoI. Next, for the same unicast setting, we develop a class of heuristic policies, called Age Difference, based on the idea that if neighboring nodes try to reduce their age differential then all nodes will have fresher updates. This approach is useful in practice since it relies only on the local age differential between nodes to make scheduling decisions. Finally, we propose the class of policies called Age Debt, which can handle 1) non-linear AoI cost functions; 2) unicast, multicast and broadcast flows; and 3) no fixed routes specified per flow beforehand. Here, we convert AoI optimization problems into equivalent network stability problems and use Lyapunov drift to find scheduling and routing schemes that stabilize the network. We also provide numerical results comparing our proposed classes of policies with the best known scheduling and routing schemes available in the literature for a wide variety of network settings.
DIAGNOSIS KESALAHAN SISWA BERBASIS PENSKORAN POLITOMUS MODEL PARTIAL CREDIT PADA MATEMATIKA

Penelitian ini bertujuan untuk menemukan informasi diagnostik dari kesalahan jawaban peserta pada Ujian Nasional (UN) Matematika. Informasi diagnostik yang ditemukan meli-puti atribut yang mendasari butir soal, ketidaktuntasan atribut, dan jenis kesalahan yang dilakukan oleh peserta. Penelitian ini merupakan diagnosis post-hoc, yang digambarkan sebagai pende-katan retrofitting. Analisis butir soal dan respons butir pada UN mata pelajaran matematika untuk menemukan informasi diag-nostik pada kategori isi, proses, dan keterampilan siswa SMP di Bantul Yogyakarta 2007/2008. Hasil penelitian (1) atribut yang mendasari butir soal pada matematika ada 47 atribut, meliputi 4 atribut isi, 36 atribut proses, dan 7 atribut keterampilan, (2) ketidaktuntasan atribut isi, proses, dan keterampilan yang ter-tinggi pada geometri dan pengukuran, (3) jenis kesalahan ter-tinggi pada bilangan, aljabar, dan geometri dan pengukuran adalah kesalahan konsep, dan jenis kesalahan tertinggi pada sta-tistika dan peluang adalah kesalahan interpretasi bahasa, dan (4) penemuan informasi diagnostik data UN Matematika dapat dilakukan melalui mekanisme identifikasi atribut, pengembang-an rubrik penskoran politomus, perhitungan ketidaktuntasan atribut, dan diagnosis kesalahan peserta tes. Kata kunci : diagnostik , matematika , partial credit model ______________________________________________________________ A DIAGNOSIS OF STUDENTS’ MISTAKES BASED ON POLYTOMOUS SCORNG PARTIAL CREDIT MODELS IN MATHEMATICS Abstract This study aims to reveal diagnostic information from the participants’ incorrect answers in the National Examination (NE) of Mathematics. The diagnostic information includes the attributes underlying test items, the attribute exhaustiveness, and the types of mistakes that the participants made. This study was a post-hoc diagnostic study, described as the retrofitting approach. The analysis of test items and item responses in the NE of Mathematics aimed to reveal the diagnostic information in the Junior High School students’ content, process, and skill categories. The results are that (1) there are 47 attributes underlying the mathematics test items, consisting of 4 content attributes, 36 process attributes, and 7 skill attributes, (2) the highest inexhaustiveness of the content, process, and skill attributes is in the topics of geometry and measurement, (3) most mistakes in the topics of numbers, algebra, geometry, and measurement are those of concepts, and most mistakes in statistics and probability are those of language interpretation, and (4) the findings of diagnostic information in the data on the NE of Mathematics can be revealed through the mechanism of identifying the attributes, developing a polytomous scoring rubric, finding out the attribute inexhaustiveness, and diagnosing mistakes the test participants. Keywords : diagnosis, mathematics, partial credit model
Baobab-Fruit Shell and Fibrous Filaments Are Sources of Antioxidant Dietary Fibers

Since 2008, baobab-fruit dried pulp is listed as an ingredient on the European Union′s Novel Food Catalogue. By pulp production, 80% of the baobab fruit is discarded, forming side streams, namely, shell, fibrous filaments, and seeds. This study explored pulp and side-stream functional properties, including total dietary fiber (TDF), total antioxidant capacity (TAC), polyphenols, and water- (WHC) and oil-holding capacities (OHC), along with endocannabinoids (ECs) and N-acylethanolamines (NAEs) in pulp, seeds, and seed oil. Shell excelled in TDF (85%), followed by fibrous filaments (79%), and showed the highest soluble and direct TAC (72 ± 0.7 and 525 ± 1.0 µmol eq. Trolox/g, respectively). Pulp was the richest in polyphenols, followed by shell, fibrous filaments, and seeds. Quercetin predominated in shell (438.7 ± 2.5 µg/g); whereas epicatechin predominated in pulp (514 ± 5.7 µg/g), fibrous filaments (197.2 ± 0.1 µg/g), and seeds (120.1 ± 0.6 µg/g); followed by procyanidin B2 that accounted for 26–40% of total polyphenols in all the products. WHC and OHC ranged between 2–7 g H2O-Oil/g, with fibrous filaments showing the highest values. ECs were not found, whereas NAEs were abundant in seed oil (2408.7 ± 11.1 ng/g). Baobab shell and fibrous filaments are sources of polyphenols and antioxidant dietary fibers, which support their use as functional food ingredients.
Linear and segmented linear trend detection for vegetation cover using GIMMS normalized difference vegetation index data in semiarid regions of Nigeria

Abstract. Quantitative analysis of trends in vegetation cover, especially in Kogi state, Nigeria, where agriculture plays a major role in the region’s economy, is very important for detecting long-term changes in the phenological behavior of vegetation over time. This study employs the use of normalized difference vegetation index (NDVI) [global inventory modeling and mapping studies 3g (GIMMS)] data from 1983 to 2011 with detailed methodological and statistical approach for analyzing trends within the NDVI time series for four selected locations in Kogi state. Based on the results of a comprehensive study of seasonalities in the time series, the original signals are decomposed. Different linear regression models are applied and compared. In order to detect structural changes over time a detailed breakpoint analysis is performed. The quality of linear modeling is evaluated by means of statistical analyses of the residuals. Standard deviations of the regressions are between 0.015 and 0.021 with R2 of 0.22–0.64. Segmented linear regression modeling is performed for improvement and a decreasing standard deviation of 33%–40% (0.01–0.013) and R2 up to 0.82 are obtained. The approach used in this study demonstrates the added value of long-term time series analyses of vegetation cover for the assessment of agricultural and rural development in the Guinea savannah region of Kogi state, Nigeria.
Construction of a Ground-Motion Logic Tree through Host-to-Target Region Adjustments Applied to an Adaptable Ground-Motion Prediction Model

The purpose of a median ground-motion logic tree is to capture the center, body, and range of possible ground-motion amplitudes for each earthquake scenario considered in a seismic hazard analysis. For site-specific hazard analyses, the traditional approach of populating the logic tree branches with ground-motion prediction models (GMPMs) selected and weighted on the basis of vaguely defined applicability to the target region is rapidly being abandoned in favor of the backbone GMPM approach. In this approach, the selected backbone model is first adjusted to match the earthquake source and path characteristics of the target region, and then it is separately adjusted to account for the site-specific geotechnical profile. For a GMPM to be amenable to such host-to-target adjustments, the magnitude scaling of response spectral ordinates should be consistent with the theoretical scaling of Fourier amplitude spectra. In addition, the influence of individual source and path parameters should be clearly distinguished in the model to allow the adjustments to be applied individually, and reliable estimates of the source and path parameters from the host region of the GMPM should be available, as should a reference rock profile for the model. The NGA-West2 project GMPM of Chiou and Youngs (2014; hereafter, CY14) has been identified as a very suitable backbone model. Moreover, rather than adopting generic source and path parameters and a rock site profile from the host region for CY14, which is not easily defined because the data from which it was derived came from several geographical locations, recent studies have inverted the model to obtain a CY14-consistent reference rock profile and CY14-compatible source and path parameters. Using these host-region characteristics, this study illustrates the process of building a ground-motion logic tree through the sequential application of multiple host-to-target-region adjustments, each represented by a node on the logic tree to achieve a tractable model for the total epistemic uncertainty.
A new tsunami hazard assessment for eastern Makran subduction zone by considering splay faults and applying stochastic modeling

ABSTRACT Tsunami hazard imposed by possible rupture of splay faults is important as it may significantly intensify tsunami heights locally. The Makran Subduction Zone (MSZ) in the northwestern Indian Ocean can generate large thrust earthquakes that could trigger significant tsunamis. In this paper, the effects of possible rupture of splay faults on the tsunami hazards of eastern MSZ are studied by developing a framework that uses stochastic earthquake rupture models and considers uncertainties related to rupture location, rupture geometry, seismic moment split ratio, earthquake slip asperity location within a fault plane, and earthquake slip heterogeneity. To quantify these uncertainties, 484 different parameter combinations of tsunami sources are considered systematically. The geometry of splay faults is developed using the most recent marine seismic surveys of the tectonic structure of the MSZ. A moment magnitude of 8.6 is considered as a scenario magnitude. The results of this study are generated in two parts, by considering average sources and stochastic sources. Results show significant local amplification of the maximum tsunami heights due to splay faults. For instance, the maximum wave height in Pasni, Pakistan can be amplified by a factor of four due to a single splay fault rupture scenario of average sources.
Deep Learning Architectures for Automated Image Segmentation

Image segmentation is widely used in a variety of computer vision tasks, such as object localization and recognition, boundary detection, and medical imaging. This thesis proposes deep learning architectures to improve automatic object localization and boundary delineation for salient object segmentation in natural images and for 2D medical image segmentation. First, we propose and evaluate a novel dilated dense encoder-decoder architecture with a custom dilated spatial pyramid pooling block to accurately localize and delineate boundaries for salient object segmentation. The dilation offers better spatial understanding and the dense connectivity preserves features learned at shallower levels of the network for better localization. Tested on three publicly available datasets, our architecture outperforms the state-of-the-art for one and is very competitive on the other two. Second, we propose and evaluate a custom 2D dilated dense UNet architecture for accurate lesion localization and segmentation in medical images. This architecture can be utilized as a stand alone segmentation framework or used as a rich feature extracting backbone to aid other models in medical image segmentation. Our architecture outperforms all baseline models for accurate lesion localization and segmentation on a new dataset. We furthermore explore the main considerations that should be taken into account for 3D medical image segmentation, among them preprocessing techniques and specialized loss functions.