Miracle-dz/UniFAR-FTUs huggingface dataset:
Berbamine Analogs Exhibit Differential Protective Effects From Aminoglycoside-Induced Hair Cell Death

Hearing loss is the third most common chronic health condition in the United States and largely results from damage to sensory hair cells. Major causes of hair cell damage include aging, noise exposure, and medications such as aminoglycoside antibiotics. Due to their potent antibacterial properties and low cost, aminoglycosides are often used for the treatment of gram-negative bacterial infections, surpassing expensive antibiotics with fewer harmful side effects. However, their use is coupled with permanent hearing loss in over 20% of patients requiring these life-sustaining antibiotics. There are currently no FDA-approved drugs that prevent hearing loss from aminoglycosides. A previous study by our group identified the plant alkaloid berbamine as a strong protectant of zebrafish lateral line hair cells from aminoglycoside damage. This effect is likely due to a block of the mechanotransduction channel, thereby reducing aminoglycoside entry into hair cells. The present study builds on this previous work, investigating 16 synthetic berbamine analogs to determine the core structure underlying their protective mechanisms. We demonstrate that nearly all of these berbamine analogs robustly protect lateral line hair cells from ototoxic damage, with ED50 values nearing 20 nM for the most potent analogs. Of the 16 analogs tested, nine strongly protected hair cells from both neomycin and gentamicin damage, while one conferred strong protection only from gentamicin. These data are consistent with prior research demonstrating that different aminoglycosides activate somewhat distinct mechanisms of damage. Regardless of the mechanism, protection required the entire berbamine scaffold. Phenolic alkylation or acylation with lipophilic groups appeared to improve protection compared to berbamine, implying that these structures may be responsible for mitigating damage. While the majority of analogs confer protection by blocking aminoglycoside uptake, 18% of our analogs also confer protection via an uptake-independent mechanism; these analogs exhibited protection when delivered after aminoglycoside removal. Based on our studies, berbamine analogs represent a promising tool to further understand the pathology of aminoglycoside-induced hearing loss and can serve as lead compounds to develop otoprotective drugs.
Visual Feedback Weakens the Augmentation of Perceived Stiffness by Artificial Skin Stretch

Tactile stimulation devices are gaining popularity in haptic science and technology – they are lightweight, low-cost, can be easily made wearable, and do not suffer from instability during closed loop interactions with users. Applying tactile stimulation in the form of stretching the skin of the fingerpads, concurrently with kinesthetic force feedback, has been shown to augment the perceived stiffness during interactions with elastic objects. However, all of the studies to date have investigated the perceptual augmentation effects of artificial skin-stretch in the absence of visual feedback. We investigated how visual displacement feedback affects the augmentation of perceived stiffness caused by the skin-stretch. We used a forced-choice paradigm stiffness discrimination task with four different conditions: force feedback, force feedback with artificial skin-stretch, force and visual feedback, and force and visual feedback with artificial skin-stretch. We found that visual displacement feedback weakens the skin-stretch induced perceptual augmentation and improves the stiffness discrimination sensitivity.
Combined transgenic expression of Δ12-desaturase and Δ12-epoxygenase in high linoleic acid seeds leads to increased accumulation of vernolic acid.

The transgenic production of unusual fatty acids in oil seed crops offers an alternative, renewable resource for industry. However, transgenic expression of genes catalysing the synthesis of unusual fatty acids has generally resulted in these fatty acids accumulating at levels significantly below the levels in the wild species from which the genes were sourced. This study reports expression of additional copies of any of three Δ12-desaturase genes (FAD2) from Crepis palaestina Bornm. , cotton (Gossypium hirsutum L.) or Arabidopsis thaliana (L.) Heynh. with C. palaestina Δ12-epoxygenase gene (Cpal2), in an Arabidopsis mutant having a significantly higher level of linoleic acid substrate. This resulted in the highest levels of vernolic acid accumulation, 21% of total fatty acids, reported so far in any transgenic plant expressing the Δ12-epoxygenase. Similarly, the co-expression of C. palaestina Cpal2 and a transgenic copy of FAD2 in cotton seed that contains large amounts of linoleic acid substrate also resulted in greater accumulation of vernolic acid in seed than did expression of C. palaestina Cpal2 alone.
The formin Fmn2 is required for the development of an excitatory interneuron module in the zebrafish acoustic startle circuit

The formin family member, Fmn2, is a neuronally enriched cytoskeletal remodelling protein conserved across vertebrates. Recent studies have implicated Fmn2 in neurodevelopmental disorders, including sensory processing dysfunction and intellectual disability in humans. Cellular characterization of Fmn2 in primary neuronal cultures has identified its function in the regulation of cell-substrate adhesion and consequently growth cone translocation. However, the role of Fmn2 in the development of neural circuits in vivo, and its impact on associated behaviours have not been tested. Using automated analysis of behaviour and systematic investigation of the associated circuitry, we uncover the role of Fmn2 in zebrafish neural circuit development. As reported in other vertebrates, the zebrafish ortholog of Fmn2 is also enriched in the developing zebrafish nervous system. We find that Fmn2 is required for the development of an excitatory interneuron pathway, the spiral fiber neuron, which is an essential circuit component in the regulation of the Mauthner cell-mediated acoustic startle response. Consistent with the loss of the spiral fiber neurons tracts, high-speed video recording revealed a reduction in the short latency escape events while responsiveness to the stimuli was unaffected. Taken together, this study provides evidence for a circuit-specific requirement of Fmn2 in eliciting an essential behaviour in zebrafish. Our findings underscore the importance of Fmn2 in neural development across vertebrate lineages and highlight zebrafish models in understanding neurodevelopmental disorders. SIGNIFICANCE STATEMENT Fmn2 is a neuronally enriched cytoskeletal remodelling protein linked to neurodevelopment and cognitive disorders in humans. Recent reports have characterized its function in growth cone motility and chemotaxis in cultured primary neurons. However, the role of Fmn2 in the development of neural circuits in vivo and its implications in associated behaviours remain unexplored. This study shows that Fmn2 is required for the development of neuronal processes in the acoustic startle circuit to ensure robust escape responses to aversive stimuli in zebrafish. Our study underscores the crucial role of the non-diaphanous formin, Fmn2, in establishing neuronal connectivity and related behaviour in zebrafish.
Sensors Fusion and Multidimensional Point Cloud Analysis for Electrical Power System Inspection

Thermal inspection is a powerful tool that enables the diagnosis of several components at its early stages. One critical aspect that influences thermal inspection outputs is the infrared reflection from external sources. This situation may change the readings, demanding that an expert correctly define the camera position, which is a time consuming and expensive operation. To mitigate this problem, this work proposes an autonomous system capable of identifying infrared reflections by filtering and fusing data obtained from both stereo and thermal cameras. The process starts by acquiring readings from multiples Observation Points (OPs) where, at each OP, the system processes the 3D point cloud and thermal image by fusing them together. The result is a dense point cloud where each point has its spatial position and temperature. Considering that each point’s information is acquired from multiple poses, it is possible to generate a temperature profile of each spatial point and filter undesirable readings caused by interference and other phenomena. To deploy and test this approach, a Directional Robotic System (DRS) is mounted over a traditional human-operated service vehicle. In that way, the DRS autonomously tracks and inspects any desirable equipment as the service vehicle passes them by. To demonstrate the results, this work presents the algorithm workflow, a proof of concept, and a real application result, showing improved performance in real-life conditions.
Selected Factors that Negatively Impact Healing

Wound healing is achieved through orchestrated phases that must occur in the proper sequence and time. Many factors impair normal healing by interfering with one or more of its phases. This chapter reviews the most important factors known to negatively affect healing and describes the mechanisms whereby they exert their detrimental effects. The factors discussed include patient-related factors (horse versus pony, age, nutritional status, disease, and tissue perfusion) and wound-related factors (causes and types of wounds, age and location of the wound, involvement of structures other than skin, nature of the wound, previous treatment, neoplastic transformation, and bioburden). A better understanding of the influence of these factors on repair may lead to a therapeutic approach that negates or diminishes their effects, thereby improving healing and resolving non-healing wounds.
Predicting Performances on Processing and Memorizing East Asian Faces from Brain Activities in Face-Selective Regions: A Neurocomputational Approach

For more than two decades, a network of face-selective brain regions has been identified as the core system for face processing, including occipital face area (OFA), fusiform face area (FFA), and posterior region of superior temporal sulcus (pSTS). Moreover, recent studies have suggested that the ventral route of face processing and memory should end at the anterior temporal lobes (i.e., vATLs), which may play an important role bridging face perception and face memory. It is not entirely clear, however, the extent to which neural activities in these face-selective regions can effectively predict behavioral performance on tasks that are frequently used to investigate face processing and face memory test that requires recognition beyond variation in pose and lighting, especially when non-Caucasian East Asian faces are involved. To address these questions, we first identified during a functional scan the core face network by asking participants to perform a one-back task, while viewing either static images or dynamic videos. Dynamic localizers were effective in identifying regions of interest (ROIs) in the core face-processing system. We then correlated the brain activities of core ROIs with performances on face-processing tasks (component, configural, and composite) and face memory test (Taiwanese Face Memory Test, TFMT) and found evidence for limited predictability. We next adopted an multi-voxel pattern analysis (MVPA) approach to further explore the predictability of face-selective brain regions on TFMT performance and found evidence suggesting that a basic visual processing area such as calcarine and an area for structural face processing such as OFA may play an even greater role in memorizing faces. Implications regarding how differences in processing demands between behavioral and neuroimaging tasks and cultural specificity in face-processing and memory strategies among participants may have contributed to the findings reported here are discussed.
Past and Present Practices of Topographic Base Map Database Update in Nepal

Topographic Base Maps (TBMs) are those maps that portray ground relief as the form of contour lines and show planimetric details. Various other maps like geomorphological maps, contour maps, and land use planning maps are derived from topographical maps. In this constantly changing world, the update of TBMs is indispensable. In Nepal, their update and maintenance are done by the Survey Department (SD) as a national mapping agency. This paper presents the history of topographical mapping and the reasons for the lack of updates. Currently, the SD is updating the TBM database using panchromatic and multispectral images from the Zi Yuan-3 (ZY-3) satellite with a resolution of 2.1 and 5.8 m, respectively. The updated methodology includes the orthorectification of images, the pansharpening of images, field data collection, digitization, change detection, and updating, the overlay of vector data and field verification, data quality control, and printing map production. A TBM in the Dang district of Nepal is presented as casework to show the changes in the area and issues faced during the update. Though the present digitizing procedure is time-consuming and labor-intensive, the use of high-resolution imagery has made mapping accurate and has produced high-quality maps. However, audit and automation can be introduced from the experiences of other countries for accurate and frequent updates of the TBM database in Nepal.
Constructing and optimizing 3D atlases from 2D data with application to the developing mouse brain

3D imaging data necessitate 3D reference atlases for accurate quantitative interpretation. Existing computational methods to generate 3D atlases from 2D-derived atlases result in extensive artifacts, while manual curation approaches are labor-intensive. We present a computational approach for 3D atlas construction that substantially reduces artifacts by identifying anatomical boundaries in the underlying imaging data and using these to guide 3D transformation. Anatomical boundaries also allow extension of atlases to complete edge regions. Applying these methods to the eight developmental stages in the Allen Developing Mouse Brain Atlas (ADMBA) led to more comprehensive and accurate atlases. We generated imaging data from fifteen whole mouse brains to validate atlas performance and observed qualitative and quantitative improvement (37% greater alignment between atlas and anatomical boundaries). We provide the methods as the MagellanMapper software and the eight 3D reconstructed ADMBA atlases. These resources facilitate whole-organ quantitative analysis between samples and across development.
Feature-Based Stitching Algorithm of Multiple Overlapping Images from Unmanned Aerial Vehicle System

This research presents a novel solution to cluster images from an Unmanned Aerial Vehicle System (UAV) using a feature-based stitching algorithm that employs a Binary Robust Invariant Scalable Keypoints (BRISK) feature detection technique. The UAV images are clustered by comparing the degree of overlaps, via the BRISK feature detection and matching, and a set threshold. The clustering serves as an essential solution in solving the stitching errors of UAV images, which are predominantly caused by inconsistent or overlapping regions. The Random Sample Consensus (RANSAC) is able to eliminate outliers on every paired keypoint and produces a precise computed homography or displacement of objects within images, thus making the stitching of multiple overlapping UAV images a success. Since the goal is to detect and cluster images qualified for image stitching. The aggregation of image smoothing is recommended. This will have a significant effect in eliminating minor problems such as the lack of color balance and seam presence, problems that slightly affect the visual appearance of the stitched UAV images.
An Evolutionary SVM Model for DDOS Attack Detection in Software Defined Networks

Software-Defined Network (SDN) has become a promising network architecture in current days that provide network operators more control over the network infrastructure. The controller, also called as the operating system of the SDN, is responsible for running various network applications and maintaining several network services and functionalities. Despite all its capabilities, the introduction of various architectural entities of SDN poses many security threats and potential targets. Distributed Denial of Services (DDoS) is a rapidly growing attack that poses a tremendous threat to the Internet. As the control layer is vulnerable to DDoS attacks, the goal of this paper is to detect the attack traffic, by taking the centralized control aspect of SDN. Nowadays, in the field of SDN, various machine learning (ML) techniques are being deployed for detecting malicious traffic. Despite these works, choosing the relevant features and accurate classifiers for attack detection is an open question. For better detection accuracy, in this work, Support Vector Machine (SVM) is assisted by kernel principal component analysis (KPCA) with genetic algorithm (GA). In the proposed SVM model, KPCA is used for reducing the dimension of feature vectors, and GA is used for optimizing different SVM parameters. In order to reduce the noise caused by feature differences, an improved kernel function (N-RBF) is proposed. The experimental results show that compared to single-SVM, the proposed model achieves more accurate classification with better generalization. Moreover, the proposed model can be embedded within the controller to define security rules to prevent possible attacks by the attackers.
Quantitative detection of sleep apnea with wearable watch device

The spread of wearable watch devices with photoplethysmography (PPG) sensors has made it possible to use continuous pulse wave data during daily life. We examined if PPG pulse wave data can be used to detect sleep apnea, a common but underdiagnosed health problem associated with impaired quality of life and increased cardiovascular risk. In 41 patients undergoing diagnostic polysomnography (PSG) for sleep apnea, PPG was recorded simultaneously with a wearable watch device. The pulse interval data were analyzed by an automated algorithm called auto-correlated wave detection with adaptive threshold (ACAT) which was developed for electrocardiogram (ECG) to detect the cyclic variation of heart rate (CVHR), a characteristic heart rate pattern accompanying sleep apnea episodes. The median (IQR) apnea-hypopnea index (AHI) was 17.2 (4.4-28.4) and 22 (54%) subjects had AHI ≥15. The hourly frequency of CVHR (Fcv) detected by the ACAT algorithm closely correlated with AHI (r = 0.81), while none of the time-domain, frequency-domain, or non-linear indices of pulse interval variability showed significant correlation. The Fcv was greater in subjects with AHI ≥15 (19.6 ± 12.3 /h) than in those with AHI <15 (6.4 ± 4.6 /h), and was able to discriminate them with 82% sensitivity, 89% specificity, and 85% accuracy. The classification performance was comparable to that obtained when the ACAT algorithm was applied to ECG R-R intervals during the PSG. The analysis of wearable watch PPG by the ACAT algorithm could be used for the quantitative screening of sleep apnea.
Age, parasites, and condition affect humoral immune response in tropical pythons

Mounting an immune response has been suggested to be physiologically costly because of metabolic requirements of immune cells specifically and upregulation of the immune system in general. We investigated such costs in free-living water pythons (Liasis fuscus), immunized with a harmless antigen, keyhole limpet hemocyanin. In the present study, we analyze the independent effects of age, blood parasite load, and body condition on the ability to mount a humoral immune response (level of antibody production to novel antigens). Python humoral immune response decreased with increasing body length/age, decreased with increasing blood parasite load, and decreased with declining body condition. The results suggest an energetic trade-off between immunocompetence and other energetically costly processes. Copyright 2006.
Model Order Selection From Noisy Polynomial Data Without Using Any Polynomial Coefficients

Given a set of noisy data values from a polynomial, determining the degree and coefficients of the polynomial is a problem of polynomial regressions. Polynomial regressions are very common in engineering, science, and other disciplines, and it is at the heart of data science. Linear regressions and the least squares method have been around for two hundred years. Existing techniques select a model, which includes both the degree and coefficients of a polynomial, from a set of candidate models which have already been fitted to the data. The philosophy behind the proposed method is fundamentally different to what have been practised in the last two hundred years. In the first stage only the degree of a polynomial to represent the noisy data is selected without any knowledge or reference to its coefficient values. Having selected the degree, polynomial coefficients are estimated in the second stage. The development of the first stage has been inspired by the very recent results that all polynomials of degree $q$ give rise to the same set of known time-series coefficients of autoregressive models and a constant term $\mu $ . Computer experiments have been carried out with simulated noisy data from polynomials using four well known model selection criteria as well as the proposed method (PTS1). The results obtained from the proposed method for degree selection and predictions are significantly better than those from the existing methods. Also, it is experimentally observed that the root-mean square (RMS) prediction errors and the variation of the RMS prediction errors from the proposed method appear to scale linearly with the standard deviations of the noise for each degree of a polynomial.
EFFECT OF ORGANIC AND MINERAL FERTILIZERS ON ESSENTIAL OIL CONTENT IN CARAWAY, ANISE AND CORIANDER FRUITS

The aim of this study, which was conducted in field conditions on three locali- ties in Serbia during two years, was to investigate the influence of the application of vari- ous types of fertilizers on the essential oil content in caraway, anise and coriander fruits. The influence of four organic fertilizers was investigated: two microbiological fertilizers (Slavol and Bactofil B-10), two specific organic fertilizers (Royal Ofert biohumus and vermicompost). Also, the chemical fertilizer was used and there was a control plot with- out any fertilization. From the results, it can be concluded that the application of different fertilizers has an influence on essential oil content only in case of anise fruits. The appli- cation of Royal Ofert biohumus shows the best results, after which follows chemical fer- tilizer. The use of these two types of fertilizers significantly increased the essential oil content in the anise fruits in comparison with other tested treatments. Although differ- ences in the essential oil content of caraway and coriander were not significant, the two above mentioned fertilizers and vermicompost show the best results.
TimelyRep: Timing deterministic replay for Android web applications

With the constantly growing and changing requirements of app users, web techniques are used in mobile application development for better cross‐platform compatibility and online update. As the embedded web contents gain complexity, debugging web apps become a critical demand. Web replay tools can record program inputs and reproduce the same execution for debugging and performance tuning. However, traditional replay approaches are largely intended for apps with desktop interaction methods (keyboard, mouse) and require modification to the browser, which limits their applicability in mobile platforms.