Miracle-dz/UniFAR-FTUs huggingface dataset:
Permeability of active layer sediments and groundwater runoff in Brattegg River catchment, SW Spitsbergen

: This paper presents the permeability of the permafrost active layer determined in the Brattegg River catchment (SW Spitsbergen) for the 6-years interval of 2005–2010. The field permeability measurements technique of weathered rocks on various geomorphological forms allows to assess the value of their hydraulic conductivity ( k ). High variability of k values, ranging from 6.37 10 −9 to 4.0 10 −3 m s −1 , indicates the permeability of rocks from very low in clay to very high in gravel-rock rubble. Among the geomorphological forms, the best permeability was observed in boulder covers and rock debris, and the lowest one in patterned ground. The obtained results were used to determine the groundwater runoff ( q tot ), assuming the unit thickness of the active layer aquifer. The q tot value from the Brattegg River catchment was calculated at 130 L s −1 , which is from 15% to 47% of the average surface runoff.
Increasing accuracy of measuring functioning parameters of agricultural units

The paper substantiates the ways of increasing the accuracy of measuring the parameters of agricultural units (AU) functioning. It has been noted that agricultural machines and units work in conditions of vibrations and noises created by the environment and technological tools. Features of the movement of these systems and their compliance with their functional purpose are factors that determine the degree of perfection of AU. The study of the dynamics of AU operation requires new research methods and means, therefore a measuring system of the dynamics and energy of mobile machines was created. Increasing the accuracy of measuring parameters of AU operation is achieved by substantiating the data processing algorithm of the sensors of the measuring system. The main component of the measurement system is an inertial measurement unit (IMU), which consists of an accelerometer, a gyroscope, and a magnetometer. It was established that the signal measured by IMU consists of four components: real acceleration; angles of inclination of the AU element relative to the horizon; vibration and inherent noise of the sensor. The IMU installed on the tractor frame determined that the main spectrum of oscillations is in the range from 0 to 3 Hz. The maximum vibration energy corresponds to a frequency of 0.4 Hz. The second harmonic of the oscillations is at a frequency of 25 Hz for the three axes of the accelerometer. An algorithm for data processing by the measuring system has been developed, including processing with the Butterworth filter, compensation of centrifugal velocities, tilt angles, free fall acceleration. The Butterworth low-pass filter with a cut-off frequency of 3 Hz was used to compensate for the real acceleration. The speed and position data of the GPS receiver included in the measuring system must be processed by the Butterworth frequency filter with a cut-off frequency of 1 Hz. It was determined that the maximum traction power of the tractor is 108.0 kW. It was established that the power determined by the measuring system due to acceleration and data processing by the developed method is 101.3 kW. The error of measuring the traction power of the tractor is 6.2%.
Wavefront sensing for anisotropic turbulence using digital holography

We report on digital holographic imaging through atmospheric turbulence. Data recorded with aberrations is corrected during post processing using an iterative sharpness-metric maximization algorithm. Assuming the correction cancels the actual wavefront error, this process is equivalent to wavefront sensing. Much of our past work focused on imaging through isotropic turbulence with phase corrections using a Zernike-polynomial expansion. Here, we describe algorithm modifications for imaging through anisotropic turbulence, similar to what is seen when looking through the aero-optic boundary layer surrounding a moving aircraft. Specifically, we explore tradeoffs associated with switching from a Zernike representation to Karhunen-Loève basis functions. In some cases, the dimensionality of the phase correction estimation algorithm can be reduced significantly by this change. This reduces the computational burden
Highly polarized single mode nanobelt laser

We demonstrate a highly polarized single mode nanobelt laser with a low threshold. Different from the traditional nanobelt lasers, the laser cavity is formed along the lateral direction of the nanobelt and the wavelength is centered at 712.6 nm with a linewidth of about 0.18 nm. The single mode lasing emission is highly polarized with a polarization ratio of about 0.91. Moreover, the threshold is as low as 18 μJ/cm2 which is about an order of magnitude lower than that of the traditional CdSe nanobelt lasers. These low threshold high polarization single mode nanobelt lasers offer great potential as a low cost and energy efficient choice of technology for applications in visible light communications, displays, optical sensing, and environmental monitoring.
Short Carbon Nanotube-Based Delivery of mRNA for HIV-1 Vaccines

Developing a safe and effective preventive for HIV-1 remains the hope for controlling the global AIDS epidemic. Recently, mRNA vaccines have emerged as a promising alternative to conventional vaccine approaches, primarily due to their rapid development and potential for low-cost manufacture. Despite the advantages of mRNA vaccines, challenges remain, especially due to the adverse effects of the delivery vehicle and low delivery efficiency. As a result, Luna Labs is developing a short carbon nanotube-based delivery platform (NanoVac) that can co-deliver mRNA and HIV-1 glycoproteins to the immune system efficiently with negligible toxicity. Surface chemistries of NanoVac were optimized to guide antigen/mRNA loading density and presentation. Multiple formulations were engineered for compatibility with both intramuscular and intranasal administration. NanoVac candidates demonstrated immunogenicity in rabbits and generated human-derived humoral and cellular responses in humanized mice (HIS). Briefly, 33% of the HIV-1–infected HIS mice vaccinated with NanoVac–mRNA was cleared of virus infection by 8–weeks post-infection. Finally, NanoVac stabilized the loaded mRNA against degradation under refrigeration for at least three months, reducing the cold chain burden for vaccine deployment.
Intrinsic motivation and learning dynamics

We investigate the eﬀects of intrinsic motivation on the dynamics of learning processes. We construct a simple model of a single agent adapting to unknown environment. Performing a repeated choice between a number of initially unexplored alternatives, the agent gains rewards for each selected alternative and in doing so gradually comprehends the environment. In our model the agent choice is governed by two stimuli. The traditional extrinsic motive inclines the agent to maximize the cumulative payoﬀ throughout the process, while the second, intrinsic one, biases the agent towards the novel options that she inherently likes. We show that the intrinsic motivation can induce an instability and periodic dynamics of the learning process which is always stationary in the case of self-ish, rational agent. Interestingly, the opposite effect can arise as well: when the impact of intrinsic motivation on the agent choice is strong, the equiprobable choice equilibrium strategy becomes stable. Based on the presented results we argue that the eﬀects of human intrinsic motivation in particular and bounded rationality in general may appear to contribute greatly to the dynamics of complex socio-economic systems and therefore de-serve much attention in the formal models of such systems.
Structural analysis of dynamical networks: BDC-decomposition and influence matrix

Dynamical networks, composed of dynamical subsystems that interact according to a given interconnection topology, can model several complex systems, ranging from natural systems to engineering applications. Dynamical networks admit a graph representation, where nodes represent subsystems and arcs represent interconnections, and have a peculiar feature: the global behaviour is the outcome of an ensemble of local interactions. A structural analysis of dynamical networks aims at providing parameterindependent results, based on the topology of the interconnection graph (i.e., the system structure); a structural approach is particularly well suited to explain the extraordinary robustness of natural systems in spite of intrinsic uncertainties and variability. We present the BDC-decomposition, which describes the structure of a wide class of dynamical networks: we show that it provides not only a local, but also a global description of the system, and that it can help structurally assess many relevant properties. In particular, we focus on a BDC-based vertex algorithm that allows us to analyse the system steady-state input-output behaviour and to compute the system influence matrix, representing the structural steady-state effect on each of the variables of a persistent input applied to each of the system equations.
Statistics of continuous weak linear measurement

One of the pillars of the scientific method is the fact that all scientific predictions and explanations of phenomena in the universe are testable. Testing in the context of physics involves the action of measuring. Thus, the measurement process plays an important role in physics. While classically we all understand the idea of measurement in a very straightforward fashion, in quantum mechanics the concept of measurement departs fromour everyday experience in physics. In fact, although the quantum measurement obeys rather simple rules, its interpretation has been a subject of discussion since the beginning of the 20th century. Some of the physics involved in the process of a quantum measurement have no classical analogues, challenging in this way our intuition: the famous paradox of a cat in a box is a clear example of this.
Performance of a Multiuser Cooperative IoT NOMA Network With Battery-Assisted Energy Harvesting

This article investigates a cooperative nonorthogonal multiple access (Co-NM)-based network consisting of a multiantenna source, a full-duplex energy harvesting (EH) near user (NU) Internet of Things (IoT) node, and multiple distant user (DU) IoT nodes. The source shares a direct link to the NU, while the NU augments the harvested energy by a limited amount of its battery energy to relay the information to the selected DU. Considering time-switching (TS) or power-splitting (PS) protocol, practical nonlinear EH, successive interference cancellation error, and opportunistic Co-NM/orthogonal multiple access (OMA) (OM) switching, closed-form expressions are derived for the outage probability and throughput of both DU and NU. We demonstrate that the proposed opportunistic Co-NM/OM switching can ensure a performance similar to OM at the NU without loss in DU throughput. Also, a joint optimal choice of battery energy and PS/TS parameter helps in attaining a maximum energy efficiency (EE). Moreover, Co-NM/OM switching ensures higher EE as compared with Co-NM and OM.
Linguistic Fuzzy Trust Model over Oscillating Wireless Sensor Networks

Simulation of the Linguistic Fuzzy Trust Model (LFTM) over oscillating Wireless Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Networks (BTRM-WSN) in terms of the accuracy and the average path length suggested by each model is presented. Both models give quite good and accurate outcomes over oscillating WSNs. Also it must be mentioned that the evaluation environment used here is Trust and Reputation Model Simulator for WSN.
Exceptional Field Theory and Supergravity

In this thesis, recent developments in Double Field Theory (DFT) and Exceptional Field Theory (EFT) are presented. They are reformulation of supergravity in which duality symmetries are made manifest before dimensional reduction. This is achieved through the definition of an extended spacetime that “geometrises” the T-duality group O(d,d) in DFT and exceptional U-duality groups in EFT. All functions on this extended space are subject to a covariant `section constraint', whose solutions then restrict the coordinates dependency of the fields. There exist different solutions to the section constraint that correspond to different theories. In this sense, different theories are unified within the formalism of extended field theories. Moreover, extended field theories possess a powerful tool to study compactifications: the generalised Scherk-Schwarz ansatz.Here, we present several examples of the effectiveness of the generalised Scherk-Schwarz ansatz. In particular, we proved two conjectures regarding consistent truncations: the so-called Pauli reduction of the bosonic string on group manifolds and type IIB supergravity on AdS5 x S5. Another application is presented on the embedding of generalised type IIB within the E6(6) EFT, which recently appeared in the study of integrable systems.Finally, we present the supersymmetric completion of the bosonic E8(8) EFT.
Tissue Inhibitor of Metalloproteinases-1 Overexpression Mediates Chemoresistance in Triple-Negative Breast Cancer Cells

Triple-negative breast cancer (TNBC) is among the most aggressive breast cancer subtypes. Despite being initially responsive to chemotherapy, patients develop drug-resistant and metastatic tumors. Tissue inhibitor of metalloproteinases-1 (TIMP-1) is a secreted protein with a tumor suppressor function due to its anti-proteolytic activity. Nevertheless, evidence indicates that TIMP-1 binds to the CD63 receptor and activates noncanonical oncogenic signaling in several cancers, but its role in mediating TNBC chemoresistance is still largely unexplored. Here, we show that mesenchymal-like TNBC cells express TIMP-1, whose levels are further increased in cells generated to be resistant to cisplatin (Cis-Pt-R) and doxorubicin (Dox-R). Moreover, public dataset analyses indicate that high TIMP-1 levels are associated with a worse prognosis in TNBC subjected to chemotherapy. Knock-down of TIMP-1 in both Cis-Pt-R and Dox-R cells reverses their resistance by inhibiting AKT activation. Consistently, TNBC cells exposed to recombinant TIMP-1 or TIMP-1-enriched media from chemoresistant cells, acquire resistance to both cisplatin and doxorubicin. Importantly, released TIMP-1 reassociates with plasma membrane by binding to CD63 and, in the absence of CD63 expression, TIMP-1-mediated chemoresistance is blocked. Thus, our results identify TIMP-1 as a new biomarker of TNBC chemoresistance and lay the groundwork for evaluating whether blockade of TIMP-1 signal is a viable treatment strategy.
An Extensive Review on SISL-based Antennas with Hexagonal Shaped SISL-Antenna

Substrate-integrated suspended line (SISL) is a quasi-planar, multi-layered platform for designing antennas with embedded cavities. The SISL antenna shows good radiation performance, low loss, and self-packaging characteristics, which are more suitable for modern communication systems. A SISL-based hexagonal patch antenna, different types of SISL-based antennas in the literature, their advantages, and their performance are discussed in this paper.
Systemic Review of Clot Retraction Modulators

Through a process termed clot retraction, platelets cause thrombi to shrink and become more stable. After platelets are activated via inside-out signaling, glycoprotein αIIbβIII binds to fibrinogen and initiates a cascade of intracellular signaling that ends in actin remodeling, which causes the platelet to change its shape. Clot retraction is also important for wound healing. Although the detailed molecular biology of clot retraction is only partially understood, various substances and physiological conditions modulate clot retraction. In this review, we describe some of the current literature pertaining to clot retraction modulators. In addition, we discuss compounds from Cudrania trucuspidata, Arctium lappa, and Panax ginseng that diminish clot retraction and have numerous other health benefits. Caffeic acid and diindolylmethane, both common in plants and vegetables, likewise reduce clot retraction, as do all-trans retinoic acid (a vitamin A derivative), two MAP4K inhibitors, and the chemotherapeutic drug Dasatinib. Conversely, the endogenous anticoagulant Protein S (PS) and the matricellular protein secreted modular calcium-binding protein 1 (SMOC1) both enhance clot retraction. Most studies aiming to identify mechanisms of clot retraction modulators have focused on the increased phosphorylation of vasodilator-stimulated phosphoprotein and inositol 1,4,5-triphosphate receptor I and the decreased phosphorylation of various phospholipases (e.g., phospholipase A2 (PLA2) and phosphatidylinositol-specific phospholipase Cγ2 (PLCγ2), c-Jun N-terminal kinase, and (PI3Ks). One study focused on the decreased phosphorylation of Sarcoma Family Kinases (SFK), and others have focused on increased cAMP levels and the downregulation of inflammatory markers such as thromboxanes, including thromboxane A2 (TXA2) and thromboxane B2 (TXB2); prostaglandin A2 (PGE2); reactive oxygen species (ROS); and cyclooxygenase (COX) enzyme activity. Additionally, pregnancy, fibrinolysis, and the autoimmune condition systemic lupus erythematosus all seem to affect, or at least have some relation with, clot retraction. All the clot retraction modulators need in-depth study to explain these effects.
Incidence of Carpal Tunnel Syndrome and Other Coexisting Brachial Plexus Neuropathies in Bullseye Shooters—A Pilot Retrospective Clinical and Neurophysiological Assessment

Shooting may impact the frequency of neuropathies in the upper extremity nerves or of cervical disc–root conflicts. This study was undertaken to assess whether shooting sports trained with a handgun by civilians may influence the risk factor for carpal tunnel syndrome (CTS) and other neuropathies of the brachial plexus nerve fibers. Neurophysiological studies using surface electromyography (rEMG at rest and mcEMG during maximal contraction), electroneurography (ENG), and motor-evoked potential recordings (MEPs) were performed in a select population of nine shooters, which were rigorously screened as positive through a clinical examination for carpal tunnel syndrome and other brachial plexus neuropathies among a population of forty-two subjects, to confirm the existence of pathologies in the upper extremities. Increased muscle tension in rEMG and a simultaneous decrease in motor unit activity in mcEMG were recorded both in the proximal and distal muscles of the upper extremities more frequently in the shooters than in the healthy controls—volunteers. An ENG examination confirmed CTS in the shooting hand of four subjects (4/42; 9.5%), additionally revealing a significantly decreased F-wave at the C6–C7 levels in the dominant extremities of the shooting group in comparison to the control population (p = 0.05). All the examined subjects had revealed brachial plexus pathologies on both sides according to the results of the MEP recordings upon stimulation at the C4–C8 levels (various significant differences between the shooters and control group were found), and two had ulnar neuropathy in the wrist on the shooting side. It was concluded that shooting sports are a moderate risk factor for carpal tunnel syndrome and that they significantly influence the development of other brachial plexus neuropathies.
Constraints and Suggestions Regarding Entrepreneurial Behavior of SHGs Member under National Rural Livelihood Mission (NRLM) in Khanpur Block of Samastipur District in Bihar

The present study was undertaken to assess the constraints and suggestions regarding entrepreneurial behaviour of SHG members under the National Rural Livelihood Mission in Khanpur block of Samastipur district in Bihar during the year 2022. The data were collected through a pre-tested schedule from 120 respondents who were selected randomly. The collected data were tabulated, analysed, and interpreted with the help of appropriate statistical tools. The descriptive research design was followed for the current study. It was found that more than half of the respondents, i.e., 48.33 percent, were middle-aged, a large proportion of the members (83.33 percent) were literate, and in the case of size of family, the majority of respondents of small families (up to 4 members) (55.83% and 86.67%) had a nuclear family, and a higher percentage (40.00%) of the respondents had semi-cemented houses. The majority of the respondents depend on agriculture for their livelihood. The major constraints faced by the respondents were the low price of products (67.5%), ranked I, followed by a lack of knowledge about the market trend of SHG products (65.83%), ranked II. The major suggestions given by the respondents were the increase in the price of products (68.34%), ranked I, followed by organising various types of entrepreneurial development programmes (65.83%), ranked II.
The Generalised Gaussian Process Convolution Model

This thesis formulates the Generalised Gaussian Process Convolution Model (GGPCM), which is a generalisation of the Gaussian Process Convolution Model presented by Tobar et al. [2015b]. The GGPCM provides a theoretical framework for nonparametric kernel models of multi-dimensional signals defined on multidimensional input spaces. We show that the GGPCM generalises and connects existing work; most notably, we derive a dual formulation of the cross-spectral mixture kernel presented by Ulrich et al. [2015]. Finally, we use the GGPCM to develop the Deep Kernel Model, which presents a new network structure for unsupervised learning.
Estrategias de las empresas del sector agroalimentario en las redes sociales. Las empresas malagueñas en Instagram

El objeto de este trabajo es analizar cómo comunican las empresas del sector agroalimentario en Instagram. Se analizan 1000 publicaciones descargadas a través de Fanpage Karma de 25 empresas malagueñas especializadas en este ámbito que tienen cuenta oficial en esta red. Se aplica la técnica del análisis de contenido, partiendo de una visión cuantitativa -reacciones, me gusta y comentarios-, junto con una perspectiva cualitativa, basada en el estudio de las estrategias, los formatos narrativos predominantes, el tono y el tema que más interacción generan entre los grupos de interés. El tema que más reacciones genera en los seguidores es el evento online; mientras que la estrategia con más interacción es el sorteo o concurso. En cuanto al tono que más moviliza a los stakeholders es la recomendación, y la emoción, el deseo. No obstante, no siempre se da el caso de que, a más publicaciones mayor impacto en la audiencia.