Miracle-dz/UniFAR-FTUs huggingface dataset:
BDNF Influence on Adult Terminal Axon Sprouting after Partial Deafferentation

BDNF is a neurotrophin family member implicated in many different neuronal functions, from neuronal survival during development to synaptic plasticity associated with processes of learning and memory. Its presence in the oculomotor system has previously been demonstrated, as it regulates afferent composition of extraocular motoneurons and their firing pattern. Moreover, BDNF expression increases after extraocular motoneuron partial deafferentation, in parallel with terminal axon sprouting from the remaining axons. To elucidate whether BDNF could play an active role in this process, we performed partial deafferentation of the medial rectus motoneurons through transection of one of the two main afferents, that is, the ascending tract of Deiters, and injected BDNF into the motoneuron target muscle, the medial rectus. Furthermore, to check whether BDNF could stimulate axon sprouting without lesions, we performed the same experiment without any lesions. Axon terminal sprouting was assessed by calretinin immunostaining, which specifically labels the remaining afferent system on medial rectus motoneurons, the abducens internuclear neurons. The results presented herein show that exogenous BDNF stimulated terminal axon growth, allowing the total recovery of synaptic coverage around the motoneuron somata. Moreover, calretinin staining in the neuropil exceeded that present in the control situation. Thus, BDNF could also stimulate axonal sprouting in the neuropil of intact animals. These results point to an active role of BDNF in plastic adaptations that take place after partial deafferentation.
EVAA—Exchange Vanishing Adversarial Attack on LiDAR Point Clouds in Autonomous Vehicles

In addition to red-green-blue (RGB) camera sensors, light detection and ranging (LiDAR) plays an important role in autonomous vehicles (AVs) to perceive their surroundings. Deep neural networks (DNNs) are able to achieve cutting-edge 3-D object detection and segmentation performance using LiDAR point clouds. LiDAR-enabled AVs provide human perception by segmenting LiDAR point clouds into meaningful regions and providing semantic context to the AV user. However, the generation of point clouds to provide semantic segmentation in AVs is not reliable and secure, which may result in traffic accidents. We propose a novel adversarial attack against LiDAR point clouds in AVs in this article. We devised an exchange vanishing adversarial attack (EVAA) to deceive LiDAR point clouds by introducing targeted noise on specific objects (e.g., vehicles and driveways). In two autonomous driving datasets with 3-D object annotations, NuScenes and PandaSet, we evaluate the performance of our proposed attack framework. We achieve an attack success rate (ASR) of <inline-formula> <tex-math notation="LaTeX">$\approx 63$ </tex-math></inline-formula>% and ASR of <inline-formula> <tex-math notation="LaTeX">$\approx 29$ </tex-math></inline-formula>% on both NuScenes and PandaSet datasets, respectively.
El impacto de las TIC en la educación

Las tecnologías de la información y la comunicación tienen una gran importancia en la vida de la sociedad, pero sobre todo en el sector de la educación proporcionado cambios y transformaciones que afectan al ser humano. Sus efectos se manifiestan de manera muy especial en las actividades laborales y el mundo educativo, donde todo debe ser revisado, desde la razón de ser de la escuela y demás instituciones educativas, hasta la formación básica que precisamos las personas en la forma de enseñar y de aprender y que nos permite utilizar una estructura organizativa.
Laplacian Filtered Loop-Star Decompositions and Quasi-Helmholtz Filters: Definitions, Analysis, and Efficient Algorithms

Quasi-Helmholtz decompositions are fundamental tools in integral equation modeling of electromagnetic problems because of their ability of rescaling solenoidal and non-solenoidal components of solutions, operator matrices, and radiated fields. These tools are however incapable, per se, of modifying the refinement-dependent spectral behavior of the different operators and often need to be combined with other preconditioning strategies. This article introduces the new concept of filtered quasi-Helmholtz decompositions proposing them in two incarnations: 1) the filtered Loop-Star functions and 2) the quasi-Helmholtz filters. Because they are capable of manipulating large parts of the operators’ spectra, new families of preconditioners and fast solvers can be derived from these new tools. A first application to the case of the frequency and $h$ -refinement preconditioning of the electric field integral equation (EFIE) is presented together with numerical results showing the practical effectiveness of the newly proposed decompositions.
Training dictionary by granular computing with L∞-norm for patch granule–based image denoising

Considering the objects by different granularity reflects the recognition common law of people, granular computing embodies the transformation between different granularity spaces. We present the image denoising algorithm by using the dictionary trained by granular computing with L∞-norm, which realizes three transformations, (1) the transformation from image space to patch granule space, (2) the transformation between granule spaces with different granularities, and (3) the transformation from patch granule space to image space. We demonstrate that the granular computing with L∞-norm achieved the comparable peak signal to noise ratio (PSNR) measure compared with BM3D and patch group prior based denoising for eight natural images.
Noise emission from wind turbines in wake - Measurement and modeling

The influence of the wake of an upstream turbine impinging another one located further downstream is studied focusing on the latter’s noise emission. Measurement data are investigated in the form of surface pressure fluctuations acquired using microphones flush-mounted in a wind turbine blade near its tip, characterizing the noise sources. Numerical results from a wind turbine noise model are also included in the analysis. The wind speed deficit and increased turbulence levels of the wake flow are clearly observed. Surface pressure measurements strongly support the fact that turbulent inflow noise is increased. However, numerical results show that the wake velocity deficit reduces noise in certain circumtances. This can compensate, or even sometime more than compensate, the additional noise emission expected as a result of the wake turbulence. Furthermore, noise amplitude modulation appears to increase when the turbine is impacted by the wake flow.
Does Loan Size Matter in How Collateral Characteristics Relate to Credit Access?

The study examined the moderating role of loan size on the relationship between collateral characteristics and access to credit by micro, small, and medium-sized enterprises (MSMEs) in the agricultural sector of the Ashanti Region of Ghana. In the agricultural sector, MSMEs engaged in crop, livestock, and fish farming constituted the population for the study. The study employed a quantitative research method alongside a causal research design. The Pearson multiple regression was employed to analyze the relationships among the study variables. The study found that collateral costs, registration, and insurance positively and significantly contribute to MSMEs’ credit access. Whereas loan size does not moderate the effect of collateral cost on farmers’ credit access, it negatively and significantly moderates the effect of collateral registration and insurance on credit access. Furthermore, loan size positively and significantly moderates the effect of collateral age on farmers’ access to credit. The study was restricted to MSMEs in crop, livestock, and fish farming in the Ashanti Region of Ghana, thus making generalization to the country and beyond difficult. This study is important for decision-making concerning how farmers could take advantage of their collateral to secure appreciable loans in the Ashanti Region of Ghana. No empirical study has examined the moderating role of loan size on the relationship between collateral characteristics and credit access, aside from the fact that empirical studies dominate other sectors other than the agricultural sector.
The Impact Of Corporate Governance To Financial Performance Of Takaful In Indonesia

Takaful industry plays an essential role in answering significant issue in the society such as social, economic and environment. The presence of corporate governance become crucial to every Takaful firm in promoting and raising the public trust in one of the Islamic finance ecosystem whom currently to be called as the sleeping giant. Unfortunately, although the regulation has been established by the Financial Services Authority (OJK), certain cases of malpractices and failure of insurance currently rise to the surface. This study contributes to the literature by investigating corporate governance factors that influenced financial performance of Takaful listed in Indonesian Sharia Insurance Association (AASI). Panel Data regression analysis will be used in analyzing the data over the period 2017 – 2021. The data is collected from insurance statistic report published by Financial Services Authority also from annual report and sustainability report of every insurance. Corporate governance variables will be used as independent variables and Return on Asset will be used as a financial performance’s dependent variable. This study provides several corporate governance upon takaful performance from the perspective of a developing country. It also provides an empirical examination of current structures of takaful firms and suggestion to the decision makers and the stakeholders to be adopted in boosting firm performance. This study also gives a recommendation to the policymakers in assessing and reviewing corporate governance policies.
The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review

Background Artificial intelligence (AI) is a broad outlet of computer science aimed at constructing machines capable of simulating and performing tasks usually done by human beings. The aim of this scoping review is to map existing evidence on the use of AI in the delivery of medical care. Methods We searched PubMed and Scopus in March 2022, screened identified records for eligibility, assessed full texts of potentially eligible publications, and extracted data from included studies in duplicate, resolving differences through discussion, arbitration, and consensus. We then conducted a narrative synthesis of extracted data. Results Several AI methods have been used to detect, diagnose, classify, manage, treat, and monitor the prognosis of various health issues. These AI models have been used in various health conditions, including communicable diseases, non-communicable diseases, and mental health. Conclusions Presently available evidence shows that AI models, predominantly deep learning, and machine learning, can significantly advance medical care delivery regarding the detection, diagnosis, management, and monitoring the prognosis of different illnesses.
In Situ Observations of Harmonic Alfvén Waves and Associated Heavy Ion Heating

Resonant ion heating by high-frequency Alfvén waves has long been believed to be the primary dissipation mechanism for solar coronal heating, and these high-frequency Alfvén waves are considered to be generated via cascade from low-frequency Alfvén waves. In this study, we report an unusual harmonic Alfvén event from in situ observations by the Van Allen Probes in the magnetosphere, having an environment similar to that in the solar corona. The harmonic Alfvén waves, which propagate almost along the wave vector of the fundamental waves, are considered to be generated due to the interaction between quasi-parallel Alfvén waves and plasma density fluctuations with almost identical frequency. These high-frequency harmonic Alfvén waves can then cyclotron resonantly heat the heavy ions. Our observations provide an important insight into solar corona heating by Alfvén waves.
A diagnostic model of nerve root compression localization in lower lumbar disc herniation based on random forest algorithm and surface electromyography

Objective This study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and establish a diagnostic model based on SEMG parameters using random forest (RF) algorithm for localization diagnosis of compressed nerve root in LDH patients. Methods Fifty-eight patients with LDH and thirty healthy subjects were recruited. The SEMG of tibialis anterior (TA) and lateral gastrocnemius (LG) were collected bilaterally during walking. The peak root mean square (RMS-peak), RMS-peak time, mean power frequency (MPF), and median frequency (MF) were analyzed. A diagnostic model based on SEMG parameters using RF algorithm was established to locate compressed nerve root, and repeated reservation experiments were conducted for verification. The study evaluated the diagnostic efficiency of the model using accuracy, precision, recall rate, F1-score, Kappa value, and area under the receiver operating characteristic (ROC) curve. Results The results showed that delayed activation of TA and decreased activation of LG were observed in the L5 group, while decreased activation of LG and earlier activation of LG were observed in the S1 group. The RF model based on eight SEMG parameters showed an average accuracy of 84%, with an area under the ROC curve of 0.93. The RMS peak time of TA was identified as the most important SEMG parameter. Conclusion These findings suggest that the RF model can assist in the localization diagnosis of compressed nerve roots in LDH patients, and the SEMG parameters can provide further references for optimizing the diagnosis model in the future.
Barcoding coffee grounds - Exploring pteropod gastropod biodiversity with dregs in collection jars

Despite their cosmopolitan occurrence and massive plankton sampling during expeditions, the genetic diversity within Pteropoda Cuvier, 1804 is still largely unexplored. In this study we present a next-generation environmental barcoding approach to zooplankton bulk samples, which were collected during the circumglobal 2010 Malaspina expedition to evaluate pteropod diversity. We introduce a technique that avoids destructive procedures and leaves material intact for further morphological investigations. We extracted DNA out of the dregs (organic material such as mucus or body parts) of 27 sample containers for molecular barcoding (average 100-260 bp of COI). We were able to identify 7128 operational taxonomic units corresponding to the species composition contained in the examined samples. Among them were three species of thecosome pteropods, Creseis acicula, Creseis virgula and Cavolinia inflexa, which are discussed with respect to their taxonomy and their geographic distribution. Unidentified gymnosomes were also present in our samples from warmer regions in oceanic waters of the southern Indian Ocean. To facilitate identification of species, it is beneficial to create a better database of pteropod COI barcodes. Furthermore, gathering environmental barcoding data on a broad global scale will help to better understand species abundance and distribution of pteropods in the world’s oceans, and potentially those of other planktonic organisms.
Amino acids, fatty acids and mineral elements composition of Roystonea regia and Ptychosperma macarthurii palm kernels

Roystonea regia and Ptychosperma macarthurii are exotic palm species widely grown in Nigeria as ornamentals. The kernels of R. regia and P. macarthurii were subjected to amino acids, fatty acids, and mineral elements analyses in this study. Glutamic acid (13. 64 and 14.00 g/100 g), aspartic acid (9.72 and 9.50 g/100 g), arginine (8.68 and 7.49 g/100 g), and leucine (7.23 and 7.98 g/100 g) were the dominant amino acids in R. regia and P. macarthurii seeds. The percentage yields of kernel oils were 13.9 and 1.7% for R. regia and P. macarthurii, respectively. Gas chromatograph facilitated the identification of thirteen fatty acids, mainly comprised of oleic acid (25.19 and 35.64%), linoleic acid (57.88 and 45.60%), and palmitic acid (9.6 and 10.03%) in R. regia and P. macarthurii, respectively. The analysis also revealed the high unsaturated nature of fixed oils of R. regia (83.63%) and P. macarthurii kernels (81.66%). Calcuim, copper, iron, zinc, magnesium, manganese, sodium, and potassium were also detected in the kernels; majorly, calcium (71.5 mg/L) and magnesium (23.1 mg/L) in P. macarthurii kernels, whereas sodium (24.6 ppm) and potassium levels (50.1 ppm) were higher in R. regia kernels. These results reveal the high amino acids, fatty acids, and mineral elements content of R. regia and P. macarthurii kernels. These unexploited palm fruits could be properly utilized as animal feed, edible oil, or for other industrial purposes with the knowledge of its nutritional value and fixed oil content.
The Effectiveness of Health Promotion Media Through Booklets and Videos on Increasing Knowledge and Attitudes

Water is an element that can transmit disease, so clean water treatment is important for the community. This study aimed to determine the effectiveness of health promotion through videos and booklets on increasing public knowledge and attitudes about clean water treatment. This research used experimental research with One Group Pretest Posttest design. The population is the people of Simpang
MODAL ANALYSIS OF MULTISTEP TIMOSHENKO BEAM WITH A NUMBER OF CRACKS

Modal analysis of cracked multistep Timoshenko beam is accomplished by the Transfer Matrix Method (TMM) based on a closed-form solution for Timoshenko uniform beam element. Using the solution allows significantly simplifying application of the conventional TMM for multistep beam with multiple cracks. Such simplified transfer matrix method is employed for investigating effect of beam slenderness and stepped change in cross section on sensitivity of natural frequencies to cracks. It is demonstrated that the transfer matrix method based on the Timoshenko beam theory is usefully applicable for beam of arbitrary slenderness while the Euler-Bernoulli beam theory is appropriate only for slender one. Moreover, stepwise change in cross-section leads to a jump in natural frequency variation due to crack at the steps. Both the theoretical development and numerical computation accomplished for the cracked multistep beam have been validated by an experimental study
Bi-temperature Euler Equations Modeling for Fusion Plasma

This work deals with the modeling of fusion plasma by bi-temperature fluid models. First, using non-dimensional scaling of the governing equations, we give the assumptions leading to a bi-temperature model. Then we describe a finite volume method on non-structured meshes to approximate the solutions of this model. The method relies on a relaxation scheme to solve the Riemann problem at the interfaces. The description of the finite volume method that uses the strong conservative form of the equations is given both in Cartesian as well as in cylindrical coordinate systems useful to compute flows inside a torus. Several numerical tests in Cartesian and cylindrical coordinate systems and in different geometries are presented in order to validate the numerical method.
Progressive Model-Driven Approach for 3D Modeling of Indoor Spaces

This paper focuses on the 3D modeling of the interior spaces of buildings. Three-dimensional point clouds from laser scanners can be considered the most widely used data for 3D indoor modeling. Therefore, the walls, ceiling and floor are extracted as the main structural fabric and reconstructed. In this paper, a method is presented to tackle the problems related to the data including obstruction, clutter and noise. This method reconstructs indoor space in a model-driven approach using watertight predefined models. Employing the two-step implementation of this process, the algorithm is able to model non-rectangular spaces with an even number of sides. Afterwards, an “improvement” process increases the level of details by modeling the intrusion and protrusion of the model. The 3D model is formed by extrusion from 2D to 3D. The proposed model-driven algorithm is evaluated with four benchmark real-world datasets. The efficacy of the proposed method is proved by the range of [77%, 95%], [85%, 97%] and [1.7 cm, 2.4 cm] values of completeness, correctness and geometric accuracy, respectively.
Study on Vibrational Power Flow Propagation Characteristics in a Laminated Composite Cylindrical Shell Filled with Fluid

The characteristics of vibrational power flow in an infinite laminated composite cylindrical shell filled with fluid excited by a circumferential line cosine harmonic force are investigated using wave propagation approach. The harmonic motions of the shell and the fluid filled in the shell are described by Love shell theory and acoustic wave equation, respectively. Under the driving force, the vibrational power flow input into the coupled system and the transmission of the power flow carried by different internal forces (moments) of the shell in the axial direction are established. Numerical computations are implemented to investigate the vibrational power flow input and its propagation. It is found that characteristics of the vibrational power flow vary with different circumferential mode orders and frequencies, and the presence of fluid in the shell significantly affects the vibration of the shell structure. Additionally, parametric investigations are carried out to study the effects of the fiber orientation, modulus ratio E11/E22, and thickness-to-radius parameter h/R on input power into the coupled system and propagation power along the shell axial direction. This work will provide some guidance for the vibration control of the laminated composite cylindrical shell.
Certain curvature conditions on Kenmotsu manifolds admitting a quarter-symmetric metric connection

We study certain curvature properties of Kenmotsu manifolds with respect to the quarter-symmetric metric connection. First we consider Ricci semisymmetric Kenmotsu manifolds with respect to a quarter-symmetric metric connection. Next, we study ξ -conformally ﬂat and ξ -concircularly ﬂat Kenmotsu manifolds with respect to the quarter-symmetric metric con- nection. Moreover, we study Kenmotsu manifolds satisfying the condition ˜ Z ( ξ,Y ) · ˜ S = 0, where ˜ Z and ˜ S are the concircular curvature tensor and Ricci tensor respectively with respect to the quarter-symmetric metric connec- tion. Then, we prove the non-existence of ξ -projectively ﬂat and pseudo-Ricci symmetric Kenmotsu manifolds with respect to the quarter-symmetric metric connection. Finally, we construct an example of a 5-dimensional Kenmotsu manifold admitting a quarter-symmetric metric connection for illustration.
Endoscopic treatment of upper gastrointestinal postsurgical leaks: a narrative review

Upper gastrointestinal postsurgical leaks are life-threatening conditions with high mortality rates and are one of the most feared complications of surgery. Leaks are challenging to manage and often require radiological, endoscopic, or surgical intervention. Steady advancements in interventional endoscopy in recent decades have allowed the development of new endoscopic devices and techniques that provide a more effective and minimally invasive therapeutic option compared to surgery. Since there is no consensus regarding the most appropriate therapeutic approach for managing postsurgical leaks, this review aimed to summarize the best available current data. Our discussion specifically focuses on leak diagnosis, treatment aims, comparative endoscopic technique outcomes, and combined multimodality approach efficacy.