Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Prior-Based Audio Inpainting Using Multi-Resolution Harmonic Convolutional Neural Networks

In this manuscript, we propose a novel method to perform audio inpainting, i.e., the restoration of audio signals presenting multiple missing parts. Audio inpainting can be interpreted in the context of inverse problems as the task of reconstructing an audio signal from its corrupted observation. For this reason, our method is based on a deep prior approach, a recently proposed technique that proved to be effective in the solution of many inverse problems, among which image inpainting. Deep prior allows one to consider the structure of a neural network as an implicit prior and to adopt it as a regularizer. Differently from the classical deep learning paradigm, deep prior performs a single-element training and thus it can be applied to corrupted audio signals independently from the available training data sets. In the context of audio inpainting, a network presenting relevant audio priors will possibly generate a restored version of an audio signal, only provided with its corrupted observation. Our method exploits a time-frequency representation of audio signals and makes use of a multi-resolution convolutional autoencoder, that has been enhanced to perform the harmonic convolution operation. Results show that the proposed technique is able to provide a coherent and meaningful reconstruction of the corrupted audio. It is also able to outperform the methods considered for comparison, in its domain of application.
Experiences of soil fertility management through legume based farmer participatory experimentation in Malawi.

Soil fertility, participatory research, green manure, Best bet. Soil infertility is the most outstanding threat to agricultural productivity in Malawi. This is mainly due to low use of organic and inorganic materials to restore fertility. Consequently, farmers and researchers are developing alternative interventions to manage soil productivity. The Risk management project in Malawi is one such initiative that has recently joined in the search of soil fertility management technologies in Malawi. The overall objective of the project is to empower farmers to gain experience in experimenting and providing feedback of best bet legume technologies to rehabilitate degraded soils. This study was conducted in Chisepo in Central Malawi during the 2001/ 2002 and 2002/2003 seasons. Soils are mostly sandy and sand loamy soils. Annual rainfall is between 600-800mm. The study used the mother-baby trial approach in implementing the farmer and researcher managed trials. The legumes were grown on either sandy soils or sandy loam soils to compare soil rehabilitation benefits of the different technologies. Farmers were encouraged to incorporate the legume crop residues in order to maximize the residual nitrogen benefit to the cereal crop. Finally, feedback sessions were held with farmers to elicit farmer perceptions on the performance of the different legumes.
Petrological and geochemical variations along Iceland's Neovolcanic Zones

Petrological, geochemical, and geophysical gradients along the SE volcanic zone in Iceland imply systematic variations in melting and crystallization conditions and in magma supply and eruption rates. At the southern tip of the zone, in Vestmannaeyjar, alkali basalt magmas are generated by small degrees of melting under a thick lithosphere. Farther north, in the Hekla-Katla region, greater degrees of melting result in the generation of transitional basalt magmas. Magma supply rates exceed eruption rates, and melts begin to accumulate at the base of the crust, as indicated by magnetotelluric evidence. Uniform rare earth element patterns in the Hekla-Katla basalts may be explained by homogenization in the melt accumulation zone or by uniform melting conditions. Infrequent replenishment of magma reservoirs in this region leads to mixing of compositionally diverse magmas and, consequently, to basalts with diverse phenocryst compositions and textures. Even farther north, in central Iceland, the melting anomaly associated with the SE zone has developed to the same degree as it has beneath the SW axial rift zone, leading to similar magmatic conditions. High magma supply rates and low cooling rates inhibit fractionation and lead to the eruption of voluminous olivine tholeiites. In these areas a broad spectrum of melt compositions is generated by variable degrees of melting over a wide depth range. The compositional diversity, e.g., in large ion lithophile element enrichment, is masked somewhat by reequilibration and mixing of melts on ascent and in the melt accummulation zone. Compositional diversity may be preserved, however, in the melt accummulation zone in a lateral direction away from the rift axis since distal parts of the melt zone are fed only by melts segregating at greater depths. The variations in magmatic conditions along the SE zone, which are analogous to those inferred along propagating rifts, may be related to a mantle blob that ascended beneath central Iceland 2–3 m.y. ago, spread out laterally and triggered a southward propagating rift.
Enhanced expression of natural cytotoxicity receptors on cytokine-induced memory-like natural killer cells correlates with effector function

Introduction Natural killer (NK) cells are a key component of the innate immune system, involved in defending the host against virus-infected cells and tumor immunosurveillance. Under in vitro culture conditions, IL-12/15/18 can induce a memory-like phenotype in NK cells. These cytokine-induced memory-like (CIML) NK cells possess desirable characteristics for immunotherapies, including a longer lifespan and increased cytotoxicity. Methods In this study, NK cells were isolated from peripheral blood of healthy donors and stimulated with IL-12/15/18 to induce a memory-like phenotype or with IL-15 alone as a control. After seven days of culture, multiparametric flow cytometry analysis was performed to evaluate the phenotypic and functional profiles of CIML and control NK cells. Results Our results showed a significantly higher expression of CD25, CD69, NKG2D, NKp30, NKp44, NKp46, TACTILE, and Granzyme B in CIML NK cells compared to control NK cells. In contrast, KIR2D expression was significantly lower in CIML NK cells than in control NK cells. Moreover, functional experiments demonstrated that CIML NK cells displayed enhanced degranulation capacity and increased intracellular IFN-γ production against the target cell line K562. Interestingly, the degranulation capacity of CIML NK cells was positively correlated with the expression of the activating receptors NKp46 and NKp30, as well as with the inhibitory receptor TACTILE. Discussion In conclusion, this study provides a deep phenotypic characterization of in vitro-expanded CIML NK cells. Moreover, the correlations found between NK cell receptors and degranulation capacity of CIML NK cells allowed the identification of several biomarkers that could be useful in clinical settings.
Transfer of nonsorbing solutes to a streambed with bed forms: Laboratory experiments

Experiments were performed to determine the mechanisms and rates of solute exchange between a flowing stream and porous streambed. Mass balance, flow visualisation, and depth profiles of concentration were used to investigate the exchange of an inert tracer in a laboratory flume. The measured mass transfer was compared to the exchange predicted by models of exchange related to bed forms, which are presented in a companion paper. For the initial stages with stationary bed forms or slowly moving bed forms the net exchange was predicted satisfactorily and was dominated by bed form‐induced interstitial flows (pumping). In the initial stages with rapidly moving bed forms the exchange was dominated by scour/deposition as bed forms propagated (turnover). At later times the models of bed form‐related exchange significantly underpredicted the measured exchange. The additional exchange, and the exchange to a flat bed, may be related to bed inhomogeneity or irregular variations in pressure at the bed surface which are not related to bed forms. Such effects are likely to be more pronounced in the field situation.
Towards a Revolutionary Info-Geometric Control Theory with Potential Applications of Fokker Planck Kolmogorov(FPK) Equation to System Control, Modelling and Simulation

An exposition of a ground-breaking Info-Geometric approach to FPK probability density function (PDF) is undertaken in this paper. The results extend to finding the FPK Geodesic equations (GEs) of motion. Exact analytic solutions of these GES are derived. the Some potential applications of FPK to system control, modelling and simulation are provided. Challenging Open problems are given combined with conclusion and next phase research.
Evaluation of oxidative stress in foals with Rhodococcus equi infection–induced pneumonia for the judgment of therapeutic effect

Forty-five foals with Rhodococcus equi infection and pneumonia symptoms were classified into a surviving group and a dead group. Using serum samples, the oxidative stress index (OSI) was determined at the first visit and the follow-up visit. The OSI of the surviving group was significantly lower at the follow-up than that at the first visit. No significant difference was observed between the OSI of the dead group at the first and follow-up visits. In the surviving group, treatment at the first visit mitigated inflammation and reduced OSI. However, in the dead group, poor response to the treatment provided at the first visit led to continued inflammation, and no change was observed the OSI.
Model-Based Fitting of EEG Signals With Uncertainty Quantification for Robust Alpha Wave Identification

Electroencephalography (EEG) is a noninvasive technique widely used to assess the brain’s electrical activity, suitable for a variety of applications in clinical and nonclinical environments. However, the reliable identification of specific EEG features still remains a challenge, especially if the signals are recorded from wearable devices, notably less accurate than their hospital counterparts. The uncertainty analysis can help to address this challenge, by providing a robust and rigorous tool to assess the validity of the information extracted from the signals. This is particularly important in automated processes, such as brain–machine interfaces (BMIs), to avoid misclassifications and misinterpretation. This article proposes the use of a model-based fitting of prefiltered EEG signals, combined with uncertainty quantification, to extract the alpha amplitude oscillation with an optimal trade-off between accuracy and time resolution and, importantly, to allow the identification of those parts of the signal that do not follow the expected alpha dynamics, e.g., because affected by artifacts. This is achieved through a metrology-sound analysis of compatibility between measurement and model, taking their respective uncertainties into consideration. The proposed method has been successfully tested on real EEG signals and shown to have significant advantages in terms of time resolution and interpretability, compared with more traditional techniques, such as the independent component analysis (ICA) by temporal decorrelation, especially when applied to single-channel signals.
Community And The Northwestern Logger: Continuities And Changes In The Era Of The Spotted Owl

Community and the northwestern logger community as an idea: a conceptual issue with practical implications the historical context overview of the northwestern loggers social world the attributes of the loggers social world - identity, friendship patterns, and shared reality finding work the logger and the spotted owl the future of northwestern loggers and their communities.
Towards General Single-Utensil Food Acquisition with Human-Informed Actions

: Food acquisition with common general-purpose utensils is a necessary component of robot applications like in-home assistive feeding. Learning acquisition policies in this space is difﬁcult in part because any model will need to contend with extensive state and actions spaces. Food is extremely diverse and generally difﬁcult to simulate, and acquisition actions like skewers, scoops, wiggles, and twirls can be parameterized in myriad ways. However, food’s visual diversity can belie a degree of physical homogeneity, and many foods allow ﬂexibility in how they are acquired. Due to these facts, our key insight is that a small subset of actions is sufﬁcient to acquire a wide variety of food items. In this work, we present a methodology for identifying such a subset from limited human trajectory data. We ﬁrst develop an over-parameterized action space of robot acquisition trajectories that capture the variety of human food acquisition technique. By mapping human trajectories into this space and clustering, we construct a discrete set of 11 actions. We demonstrate that this set is capable of acquiring a variety of food items with ≥ 80% success rate, a rate that users have said is sufﬁcient for in-home robot-assisted feeding. Furthermore, since this set is so small, we also show that we can use online learning to determine a sufﬁciently optimal action for a previously-unseen food item over the course of a single meal.
Application of diffraction tomography to fracture detection

Two diffraction tomography techniques are applied to crosshole field data to detect fractures in granitic rock. The techniques used are the conventional back‐propagation method and a new quadratic programming method incorporating constraints. In this formulation, the Born approximation is used for linearization of the inverse problem. Two dimensional (2-D) pseudo spectral finite‐difference synthetic data are generated to demonstrate the inversion methods and justify use of the Born approximation. Also, using 2-D Born synthetic data, the velocity sensitivity of the inversion algorithm and reduction of fracture generated tube waves and S‐waves are investigated. The inversion methods are applied to field data from the Grimsel test site in Switzerland. The data are collected from a 10×21.5m rectangular area where fractures are known to exist. Data acquisition with 0.5 m spacing of three component receivers and a piezoelectric source is carried out so as to obtain a nearly complete coverage of the region. Cros.
The Interface of Leadership Development and Extracurricular Activity: Exploring the Effects of Involvement in Extracurricular Activity on Community Leadership

This study informs the field of education of the importance of providing a wide variety of extracurricular activities for students and its effect on students’ community leadership development. Data were collected from college students ( N = 705) and analyzed using quantitative methodology. Results indicate that high involvement level students indicated relatively high citizenship in leadership outcomes. Also, students’ self-perception of leadership skills was the most significant predictor of community values of leadership development outcomes. This study highlights the need for higher education institutions to encourage students to participate in extracurricular activities involving groups to enhance community leadership that advances positive social change.
Enterprise policies and R&D support for high-tech SMEs: a multi-perspective approach

This article examines the role of enterprise policy and R&D subsidy schemes in supporting high-tech Small-and Medium-sized Enterprises, by examining a case study of South Korea. A qualitative approach is used to analyse the perspectives of three stakeholder groups, entrepreneurs, national policymakers and policy-practitioners (including street-level bureaucrats working in bodies directly supporting the SMEs), based on semi-structured interviews with 35 participants. The ﬁ ndings suggest, ﬁ rst, that there was a mismatch in the conceptualizations of entrepreneurship, with policymakers and policy-practitioners focusing on entrepreneurship as the event of starting-up a business and entrepreneurs more on innovation. Second, while all groups feel the policy was bene ﬁ cial, policymakers and policy-practitioners argue it was necessary to have a strict implementation process so-as-to deliver the subsidy fairly across many SMEs. In contrast, entrepreneurs considered such stringent and complicated policy implementation, and policy discontinuities, as impeding the R&D performance of SMEs. Third, although perspectives varied, all believed that ﬂ exibility in the policy implementation process is required to improve policy e ﬃ cacy. The study highlights the critical role of “ bottom-up ” policy approaches to improve policy e ﬃ cacy; especially policy-practitioners ’ interactions and networking with entrepreneurs in the policy development and implementation processes. This study contributes to understanding the roles and perspectives of stakeholder groups in developing and implementing enterprise policies.
Determinantes de la divulgación de información previsional en España: un análisis de las empresas del IBEX 35

A pesar de que se considera que la información previsional presenta importantes ventajas que ayudan a mejorar la toma de decisiones, en España la normativa es escueta respecto a la publicación de este tipo de información, y sólo exige su divulgación en apartados muy concretos de las cuentas anuales y en otros documentos obligatorios. Dado que la gran mayoría de la información previsional divulgada por las compañías españolas es de carácter voluntario, las prácticas de divulgación de esta información son muy dispares entre estas empresas. El conocimiento de cuáles son estas prácticas ayudaría a orientar al regulador en los futuros desarrollos normativos al respecto. El objetivo de este trabajo es observar el nivel de publicación de información previsional divulgada por las empresas del IBEX 35, y examinar la posible influencia de ciertas características empresariales en la publicación de esta información. Los resultados muestran que el nivel de publicación de información previsional es bajo, y es destacable el hecho de que factores como el tamaño, el endeudamiento y el crecimiento de las compañías parecen influir en las prácticas de divulgación de información previsional llevadas a cabo por éstas.
Analysis of Artificial Intelligence Based Human Expression

Facial Emotion Recognition (FER) is a current area of research in computer vision and machine learning. This study looks into how well Convolutional Neural Networks (CNNs) can identify face expressions of human emotion. CNNs have proven to perform exceptionally well in a range of computer vision applications, including image categorization, object recognition, and face recognition. To categorize the seven fundamental human emotions-anger, disgust, fear, happiness, sadness, surprise, neutral- a deep learning model is suggested utilizing CNNs. Convolutional and pooling layers are interspersed with fully connected layers for classification in the proposed model. The FER2013 dataset, which includes more than 35,000 photos, is the one utilized for training and evaluation. The performance of the proposed model was evaluated and compare it with the state-of-the-art approaches in terms of accuracy, precision, recall, and F1 score. The experimental findings show that the state-of-the-art performance in facial emotion recognition achieved by the proposed CNN-based model.
Comparing Vegetation and Substrate Performances on Nutrient Removal and Biomass Establishment Using a Natural Swimming Pool Experiment

Natural swimming pools (NSPs) rely on the interaction of bog vegetation, bacteria, and substrate to maintain water quality. Nitrogen (N) and phosphorus (P) levels in NSPs are critical because of their involvement in eutrophication. We conducted a 15-week greenhouse study to address the significant literature gap regarding nutrient removal capabilities of substrates and vegetation in the low-nutrient environment of NSPs. We used mass balance analyses to compare the performances of four substrates [river gravel (control), recycled glass, expanded clay, expanded shale] and two plant species [blue flag iris (Iris versicolor) and lizard’s tail (Saururus cernuus)] under two flow conditions: free water surface and subsurface flow. At the end of the experiment, except for the recycled glass group, all other substrate groups reduced water nitrate (NO3) levels to less than 30 mg⋅L−1, the standard of the 2011 Forschungsgesellschaft Landschaftsentwicklung Landschaftsbau (FLL) guidelines. However, only the expanded clay group closely approached the P standard (≤0.01 mg⋅L−1). Expanded clay and expanded shale demonstrated potential as substrates for NSP bogs. The final aboveground biomass dry weight was strongly negatively correlated with the final NO3 and P water concentrations. However, direct plant uptake proved insufficient to remove all nutrient inputs, especially for P. Except for the recycled glass group (34%), a significant portion of N (79%–90%) from total N added was removed by aboveground biomass. However, P uptake by biomass was substantially lower (18%–37%). With acceptable vigor and biomass accumulation, blue flag iris may be a suitable species for vegetated NSPs, whereas lizard’s tail is not because of uncertain establishment. Compared with controlling N, managing P for FLL standards in NSPs will be more challenging. Our work begins to fill the essential gap in the NSP literature regarding nutrient removal capabilities of substrates and vegetation. Future work should continue to study alternative substrates and plant species for P removal, particularly in field conditions and over longer periods.
Expression of PD-1 and PD-L1 in Endometrial Cancer: Molecular and Clinical Significance

The landscape of diagnosing and treating endometrial cancer is undergoing a profound transformation due to the integration of molecular analysis and innovative therapeutic approaches. For several decades, the cornerstone treatments for endometrial cancer have included surgical resection, cytotoxic chemotherapy, hormonal therapy, and radiation therapy. However, in recent years, the concept of personalised medicine has gained momentum, reshaping the way clinicians approach cancer treatment. Tailoring treatments based on specific biomarkers has evolved into a standard practice in both initial and recurrent therapy protocols. This review aims to provide an in-depth exploration of the current state of molecular analysis and treatment strategies in the context of endometrial cancer, focusing on the immunological aspect of the PD-1/PD-L1 axis. Furthermore, it seeks to shed light on emerging and innovative approaches that hold promise for the future modulation of endometrial cancer treatments. In essence, as researchers delve into the complex molecular landscape of endometrial cancer and harness the understanding of the PD-1/PD-L1 axis, we are paving the way for more targeted, effective, and personalised therapies that have the potential to significantly improve the outcomes and quality of life for patients with this challenging disease.