Miracle-dz/UniFAR-FTUs huggingface dataset:
Federal Reserve Bank of Dallas Globalization and Monetary Policy Institute Default and the Maturity Structure in Sovereign Bonds

During emerging market crises, government interest rate spreads rise, the debt maturity shortens and the spread on short-term bonds is higher than on long-term bonds. This paper studies the maturity composition of debt in a dynamic model with endogenous default, in which the price of debt compensates for the risk-adjusted losses from default. Short-term debt is better at inducing repayment because it does not require savings in the near future for repaying in the far future. Hence, short-term debt can raise more resources than long-term debt. However, issuing long-term debt provides a hedge against the need to roll-over short-term debt at high interest rate spreads. The trade-off between these two benefits is quantitatively important for understanding the maturity composition in emerging markets. When calibrated to data from Brazil, the model matches the dynamics in the maturity of debt issuances and its comovement with the level of spreads across maturities. Valderrama for many useful comments. The views in this paper are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Dallas or the Federal Reserve System.
IMPROVING THE ENTREPRENEURIAL SKILLS OF WOMEN PRODUCING KULI-KULI IN BIDA NIGER STATE: A PLOT STUDY

: This study is conducted to explore ways to improve the entrepreneurial skills of women producing Kuli-Kuli in Bida Town, Niger State of Nigeria with the view to contributing towards their revenue generation and standard of living. It will also improve the tax base and tax revenue of Bida Town, Niger State of Nigeria, with ultimate goal of improving the Gross Domestic Product (GDP). A designed questionnaire will be distributed across the target population of 30 women producing Kuli-Kuli in Bida Town, Niger State of Nigeria; the study adopted the Partial Least Squares-Structural Equation Modelling (PLS-SEM). The finding reveals the instruments to be valid and reliable. Path coefficient results that entrepreneurial skills and the socio-economic status of the women producing kuli-kuli will be enhanced.
Aldehyde-functionalized chitosan and cellulose:chitosan composites: application as drug carriers and vascular bypass grafts

In this work, aldehyde-functionalized chitosan was produced by the reaction of chitosan in the solid state with nitrogen oxide gases, generated in situ from a HNO3/H3PO4 NaNO2 mixture. This reaction is more advantageous than the existing methods to produce aldehyde-functionalized chitosan, since the depolymerization was slower and the purification process of the products was easy and straightforwa rd. The appearance of characteristic peaks in the Fourier transform infrared and ca rbon-13 nuclear magnetic resonance spectra (1733 cm -1 and 183.4 ppm, respectively) of the product confirms the presence of the aldehyde functionality in the modified chitos ans. The pH-dependent H-NMR spectra also revealed the presence of aldehyde groups. However, as the pH increased from 2.0 to 6.0, the resonance due to the aldehyde gradually disappeared and a new resonance appeared at 8.05 ppm, which is attributable to the formation of Schiff base between the aldehyde and the free amine groups. Thi s aldehyde-derivative of chitosan formed a gel in situ by simply dissolving it in water at a concentration of 6% (w/w) without any added external crosslinker. This gel show potential use as drug carrier and as scaffold for vascular tissue engineeri ng. In addition, cellulose:chitosan composites were prepared with the main purpose of obtaining a compliant hollow tube for vascular bypass application. Elastic properti es of membranes made of this composite with different ratios between each polymer were determined using uniaxial tests and the ratio that yielded the less stiff me mbrane was chosen to prepare a small diameter hollow tube. The presence of chitosan had a favo rable
Influence Of The External And Internal Factors Towards Online Impulsive Buying

Online Impulsive buying behaviour might well be characterized as a means for marketers to increase their profits. Nowadays, the ubiquity of internet commerce has attracted the interest of both scholars and marketers. As a result, investigating the reasons of online impulsive buying behaviour is essential, as such research may produce certain novel ideas or techniques for marketers to improve profits from the online market. In this study, the author focuses on both internal (e.g., Hedonic Shopping Motivation & Personality Traits) and external (e.g., Marketing Factors and Website factors ) constituents in exploring impulsive purchase behaviour. External elements internal (e.g., Hedonic Shopping Motivation & Personality Traits) and external (e.g., Marketing Factors and Website factors ) that promote impulsive purchases are connected in certain ways and difficult to separate separately.
EXPERIMENTAL STUDY OF SIFCON CORBELS

In the current paper, results of testing four SIFCON corbel specimens under the effect of vertical load are reported. The shear span to effective depth ratio (a/d) was varied (0.35 to 1.0) and the fractional volume of the steel fibers was constant at 6% by volume of concrete. Two of the SIFCON corbels were reinforced with main reinforcement steel bars. The ultimate load, cracking load, deflection, failure mode, and crack patterns are negatively affected by the increased value of (a/d) and improved as the main steel bars are included in the SIFCON corbels.
The horizon of hope for L. Vesijärvi, southern Finland: 30 years of water quality and phytoplankton studies

L. Vesijãrvi (Fig. l) is a formerly severely eutrophied lake in southern Finland (61°00'N, 25°30'E) with a surface area of 111 km2 and a mean depth of 6.0 m. After decades of urban and industria! sewage pollution, the sewage inflow to the lake was diverted in 1976 and the Enonselkã basin was artificially aerated in 1979-1984 (KETO & SAMMALKORPI 1988). The initially promising recovery ofthe 1ake (KEro 1982) was disturbed by the return o f noxious cyanobacterial blooms in the beginning of the 1980s, due to roach-stock mediated interna! nutrient loading (KETO & SAMMALKORPI 1988, HORPPILA & KAIRESALO 1990, HORPPILA & PELTONEN 1994).
Impact of Political Instability on Financial Development of Pakistan

This study analyzed the impact of political instability on financial development of Pakistan. OLS regression is used for the estimation of data. Time series data is used for the study. 40 years are included in the time series from 1972 to 2011. The variable of interest is political instability controlling the effects of trade openness, legal protection and GDP/capita. The regression results showed that political instability has negative significant impact on financial development of Pakistan. Trade openness is positive but insignificant with financial development. Legal protection and GDP/capita showed positive and significant impact on the financial development of Pakistan.
Derivation of chromophore concentrations in turbid media using the rate of change of optical attenuation with respect to wavelength

: A spectroscopic method is investigated for estimating the concentrations of absorbers in highly scattering media using measurements of the rate of change of optical attenuation with wavelength. Such measurements are independent of absolute intensity and thus may be significantly less influenced by changes in coupling which often cause artefacts in medical applications of near-infrared spectroscopy. The method has been explored using a combination of stochastic (Monte Carlo) and analytical (diffusion-based) models and experiments on samples of turbid fluids. Results suggest that the method is highly tolerant of changes in the measurement geometry. The accuracy of the derived concentrations of absorbers can be strongly influenced by the wavelength dependence of scattering, and an ad-hoc , empirically-derived correction for this dependency has been investigated and implemented with some success.
Differences in Lower Extremity Electromyographic Responses Based on Foot Position and Swing Phase in Golf Driver Swings

The purpose of this study was to investigate the muscle activity of the lower extremity during driver swing in three-foot positions (Feet Open Stance, Feet Straight Stance, Lead Foot Open Stance). The electromyograms of gastrocnemius, tibialis anterior, and vastus lateralis during swing were measured and analyzed in three sections (take away - back swing, back swing - down swing, and down swing - follow swing). There was no significant difference in muscle activity according to foot position. Muscle activity according to phase was significantly higher in right gastrocnemius and tibialis anterior, and the left and right vastus lateralis in down swing - follow swing. In conclusion, the difference in muscle activity according to foot position is insignificant, and it is considered that the muscle activity to maintain the balance of the body increases toward the end of swing.
L ABEL M AKER 3D: Automatic Semantic Label Generation from RGB-D Trajectories

Semantic annotations are indispensable to train or evaluate perception models, yet very costly to acquire. This work introduces a fully automated 2D/3D labeling framework that, without any human intervention, can generate labels for RGB-D scans at equal (or better) level of accuracy than comparable manually annotated datasets such as ScanNet. Our approach is based on an ensemble of state-of-the-art segmentation models and 3D lifting through neural rendering. We demonstrate the effectiveness of our La-belMaker3D pipeline by generating significantly better labels for the ScanNet datasets and automatically labelling the previously unlabeled ARKitScenes dataset. Code and models are available at http://labelmaker3d.github. io.
Diffusion-based Zero-Shot 3D Human Pose Estimation

Learning-based methods have dominated the 3D human pose estimation (HPE) tasks with signi ﬁ cantly better performance in most benchmarks than traditional optimization-based methods. Nonetheless, 3D HPE in the wild is still the biggest challenge for learning-based models, whether with 2D-3D lifting, image-to-3D, or diffusion-based meth-ods, since the trained networks implicitly learn camera intrinsic parameters and domain-based 3D human pose distributions and estimate poses by statistical average. On the other hand, the optimization-based methods estimate results case-by-case, which can predict more diverse and sophisticated human poses in the wild. By combining the advantages of optimization-based and learning-based methods, we propose the Ze ro-shot D iffusion-based O ptimization ( ZeDO ) pipeline for 3D HPE to solve the problem of cross-domain and in-the-wild 3D HPE. Our multi-hypothesis ZeDO achieves state-of-the-art (SOTA) performance on Human3.6M, with minMPJPE 51 . 4 mm, without training with any 2D-3D or image-3D pairs. Moreover, our single-hypothesis ZeDO achieves SOTA performance on 3DPW dataset with PA-MPJPE 40 . 3 mm on cross-dataset evaluation, which even outperforms learning-based methods trained on 3DPW. Our code is available here: https: //github.com/ipl-uw/ZeDO-Release .
Ethnobotanical Properties of Akçakoca District in Düzce (Turkey)

Turkey has a rich flora because of its geographical and climatic properties. Anatolia (Asia Minor) is a bridge between continentals of Asia and Europe. A lot of people have moved to Turkey from various lands, cultures, religions and customs along centuries. As a result of the cultural diversity and the richness of flora, traditional names and uses of plants as medicine, food and for the other aims have improved in Anatolia. The study area is located at the northwest of Turkey, on the coast of Black Sea. Kaplandede Mount (1168 m) which lies parallel to the sea is the highest mount in the district [1]. The most significant feature of study area is its wet climate which continues all the year. The whether rains intensively in Autumn, then winter, summer and spring. Kaplandede Mount is Hersinyen solid and included sandstones and schists. Akçakoca’s soil is consist of black and brown soil, alluvion and sand at the seashore [2].
L 2 5GC+ : An Improved, 3GPP-compliant 5G Core for Low-latency Control Plane Operations

—While 5G offers fast access networks and a high-performance data plane, the control plane in 5G core (5GC) still presents challenges due to inefficiencies in handling control plane operations (including session establishment, handovers and idle-to-active state-transitions) of 5G User Equipment (UE). The Service-based Interface (SBI) used for communication between 5G control plane functions introduces substantial overheads that impact latency. Typical 5GCs are supported in the cloud on containers, to support the disaggregated Control and User Plane Separation (CUPS) framework of 3GPP. L 2 5GC is a state-of-the-art 5G control plane design utilizing shared memory processing to reduce the control plane latency. However, L 2 5GC has limitations in supporting multiple user sessions and has programming language incompatibilities with 5GC implementations, e.g., free5GC, using modern languages such as GoLang. To address these challenges, we develop L 2 5GC+ , a significant enhancement to L 2 5GC. L 2 5GC+ re-designs the shared-memory-based networking stack to support synchronous I/O between control plane functions. L 2 5GC+ distinguishes different user sessions and maintains strict 3GPP compliance. L 2 5GC+ also offers seamless integration with existing 5GC microservice implementations through equivalent SBI APIs, reducing code refactoring and porting efforts. By leveraging shared memory I/O and overcoming L 2 5GC’s limitations, L 2 5GC+ provides an improved solution to optimize the 5G control plane, enhancing latency, scalability, and overall user experience. We demonstrate the improved performance of L 2 5GC+ on a 5G testbed with commercial basestations and multiple UEs.
DIFFERENTIAL PRIVACY GUARANTEES FOR ANALYTICS AND MACHINE LEARNING ON GRAPHS: A SURVEY OF RESULTS

We study differential privacy (DP) in the context of graph-structured data and discuss its formulations and applications to the publication of graphs and their associated statistics, graph generation methods, and machine learning on graph-based data, including graph neural networks (GNNs). Interpreting DP guarantees in the context of graph-structured data can be challenging, as individual data points are interconnected (often non-linearly or sparsely). This differentiates graph databases from tabular databases, which are usually used in DP, and complicates related concepts like the derivation of per-sample gradients in GNNs. The problem is exacerbated by an absence of a single, well-established formulation of DP in graph settings. A lack of prior systematisation work motivated us to study graph-based learning from a privacy perspective. In this work, we systematise different formulations of DP on graphs, and discuss challenges and promising applications, including the GNN domain. We compare and separate works into methods that privately estimate graph data (either by statistical analysis or using GNNs), and methods that aim at generating new graph data. We conclude our work with a discussion of open questions and potential directions for further research in this area
Characterising the RNA-binding protein atlas of the mammalian brain uncovers RBM5 misregulation in mouse models of Huntington's disease

RNA-binding proteins (RBPs) are key players regulating RNA processing and are associated with disorders ranging from cancer to neurodegeneration. Here, we present a proteomics work ﬂ ow for large-scale identi ﬁ cation of RBPs and their RNA-binding regions in the mammalian brain identifying 526 RBPs. Analysing brain tissue from males of the Huntington ’ s disease (HD) R6/2 mouse model uncovered differential RNA-binding of the alternative splicing regulator RBM5. Combining several omics work ﬂ ows, we show that RBM5 binds differentially to transcripts enriched in pathways of neurodegeneration in R6/2 brain tissue. We further ﬁ nd these transcripts to undergo changes in splicing and demonstrate that RBM5 directly regulates these changes in human neurons derived from embryonic stem cells. Finally, we reveal that RBM5 interacts differently with several known huntingtin interactors and components of huntingtin aggregates. Collectively, we demonstrate the applicability of our method for capturing RNA interactor dynamics in the contexts of tissue and disease.
Large Scale Metric Learning for Distance-Based Image Classification

: This paper studies large-scale image classiﬁcation, in a setting where new classes and training images could continuously be added at (near) zero cost. We cast this problem into one of learning a low-rank metric, which is shared across all classes and explore k-nearest neighbor (k-NN) and nearest class mean (NCM) classiﬁers. We also introduce an extension of the NCM classiﬁer to allow for richer image representations. Experiments on the ImageNet 2010 challenge dataset —which contains more than 1M training images of 1K classes— shows, surprisingly, that the NCM classiﬁer compares favorably to the more ﬂexible k-NN classiﬁer. Moreover, the NCM performance suggests that 256 dimensional features is comparable to that of linear SVMs, which were used to obtain the current state-of-the-art performance. Experimentally we study the generalization performance to classes that were not used to learn the metrics, and show how a zero-shot model based on the ImageNet hierarchy can be combined effectively with small training datasets. Using a metric learned on 1K classes of the ImageNet 2010 Challange, we show results for the ImageNet-10K dataset, and obtain performance that is competitive with the current state-of-the-art, while requiring signiﬁcant less training time.
in translation collaborative practices and cooperation

This study explores collaboration practices among English-French subtitlers in the audiovisual translation (AVT) industry in France. By adopting a human-centred approach, the study identifies two types of collaboration: formal and informal, and examines subtitlers’ communication with colleagues, clients, and external agents in the subtitling production network. The research sheds light on the impact of collaborative practices on the subtitlers’ workflows and roles, as well as on the profession’s working conditions and its sustainability. The data were collected with seven subtitlers who each participated in two interviews and a direct non-participant observation of their workday. The participants were affiliated to ATAA, the association for audiovisual translators in France, and as such, benefited from opportunities for collaboration provided by this well-established community. This study contributes to a better understanding of collaboration in the French subtitling industry, highlighting its benefits and limitations.
Journal of International Women's Studies Journal of International Women's Studies

The objectives of this quantitative study were to identify factors associated with contraceptive use by Jordanian Muslim women; to estimate factors that predict the variance in contraceptive use; and recommend appropriate health and social policies to enhance quality of life of Jordanian women. A cross -sectional design was used to collect data from 487 married non-pregnant women aged 18 to 49 years who resided in three southern governorates in Jordan using a structured interview guide. Results showed that 63.2% of women used some form of contraceptive method; IUD was the most frequently used method (44.2%). The percentage of women exposed to violence was 5% and 9.2% for physical and verbal abuse respectively. Findings also showed that there was a significant relationship between psychological wellbeing of women and contraceptive use. Furthermore, no relationship between women’s perceived religious stance towards contraceptives and their use. Predictors of contraceptive use were: women aged 40-45 years explained 23.3% of the variance in contraceptive use; and the woman’s approval of contraceptive use for birth spacing explained 21.4% of the variance in contraceptive use. The Islamic stance towards contraceptive use was not significant in these women; however further studies are needed to confirm these findings as well as the generalizability to Muslim women in other countries. The study findings have implications for health and social policies relevant to family planning services in order to enhance and increase the use of contraceptives to reduce the TFR in Jordan. Furthermore,
Seasonal variation of infiltration capacities of soils in western Oregon.

Infiltration capacities were 50 percent greater during fall than during summer for forest soils of western Oregon. These results contrast with those measured in other studies. In forested areas, investigators should be aware of potentially large seasonal changes in infiltration capacities. Such seasonal changes may exceed effects due to applied treatments (logging, slash disposal, burning, etc.) and can confound study
Lessons from Neuroimaging Functional Anatomy of Essential Tremor:

SUMMARY: The neuropathogenetic processes underlying essential tremor appear to cause subtle morphologic changes in neural networks that include multiple brain structures, primarily the cerebellum, brain stem, frontal lobes, and thalamus. One of the main challenges of neuroimaging in essential tremor is differentiating disease-speciﬁc markers from the spectrum of structural changes that occur due to aging. This review discusses recent neuroimaging studies in the light of current knowledge of the neuropsychology and pathology of the disease. We suggest that the application of multiple macroscopic and microscopic neuroimaging modalities, combined with personalized information relative to cognitive and behavioral symptoms, is the prerequisite for a comprehensive classiﬁcation and correct diagnosis of essential tremor
Diversity statistics in the OECD

Data on ethnic, racial and indigenous identity can help render certain minorities statistically visible, and expose potential discrimination and inequalities. This paper systematically reviews diversity data collection practices in OECD countries and selected key partners and identifies three common challenges: the legal treatment of ‘sensitive’ data and concerns around privacy; the use of different data sources for different policy purposes; and issues of comparability over time since identities are dynamic and multiple constructs. When relevant, recommendations and best practices to improve diversity data are put forward. These include: expanding the collection of data on ethnic and racial identities where legal frameworks permit; ensuring the representation of hard-to-reach populations such as indigenous communities; developing national diversity statistical standards to standardise information and allow linking data across sources; raising the timeliness and policy relevance of diversity data by including questions in both regular sample surveys and population censuses; and involving communities in the data collection process.