Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Pitch Perception With an Active Auditory Model Extended by Octopus Cells

Pitch is an essential category for musical sensations. Models of pitch perception are vividly discussed up to date. Most of them rely on definitions of mathematical methods in the spectral or temporal domain. Our proposed pitch perception model is composed of an active auditory model extended by octopus cells. The active auditory model is the same as used in the Stimulation based on Auditory Modeling (SAM), a successful cochlear implant sound processing strategy extended here by modeling the functional behavior of the octopus cells in the ventral cochlear nucleus and by modeling their connections to the auditory nerve fibers (ANFs). The neurophysiological parameterization of the extended model is fully described in the time domain. The model is based on latency-phase en- and decoding as octopus cells are latency-phase rectifiers in their local receptive fields. Pitch is ubiquitously represented by cascaded firing sweeps of octopus cells. Based on the firing patterns of octopus cells, inter-spike interval histograms can be aggregated, in which the place of the global maximum is assumed to encode the pitch.
Antidiabetic and Neuroprotective Effect of the N-Butanol Extract of Fragaria nilgerrensis Schlecht. in STZ-Induced Diabetic Mice

Diabetes has been associated with neurodegenerative disorders that are accompanied by memory loss and cognitive impairments, but there is no effective treatment for it at present. Fragaria nilgerrensis Schlecht. (FNS), a well-known Chinese materia medica, has been traditionally used for the folkloric treatment of diabetes and other diseases. However, its effects are poorly documented. Here, we investigated the antidiabetic and neuroprotective effect of FNS in diabetic mice. Thin layer chromatography (TLC) and high performance liquid chromatography (HPLC) evaluations of N-butanol extract of Fragaria nilgerrensis Schlecht. (N-FNS) showed the presence of flavonoid and its structure is similar to scutellarin. For the first time, we show the potential neuroprotective and antidiabetic effects of FNS. After 4 weeks of FNS intervention, a significant decrease in blood glucose, increase in body weight, and amelioration in glucose tolerance were observed in FNS treated diabetic mice. In the acute study, FNS enhanced motor activity in the open field task and significantly prevented spatial-learning deficits in Morris water maze tests. Besides, synapse ultrastructure of the hippocampus showed that the mitochondrial morphology was basically restored and all the synaptic structural parameters were gradually normalized after treatment with FNS. Importantly, we found that the activities of SOD and CAT in liver and hippocampus of diabetic mice significantly increased after FNS administration. In vitro, FNS and scutellarin showed high DPPH radical scavenging activity. The study suggests that FNS exerted significant antidiabetic and neuroprotective effects which may be attributed to its antioxidant property.
A meta-analysis and bioinformatics exploration of the diagnostic value and molecular mechanism of miR-193a-5p in lung cancer

Lung cancer is a leading cause of mortality worldwide and despite recent improvements in lung cancer treatments patient mortality remains high. miR-193a-5p serves a crucial role in the initiation and development of cancer; it is necessary to understand the underlying molecular mechanisms of miR-193a-5p in lung cancer, which may enable the development of improved clinical diagnoses and therapies. The present study investigated the diagnostic value of peripheral blood and tissue miR-193a-5p expression using a microarray meta-analysis. Peripheral blood miR-193a-5p was revealed to be upregulated in patients with lung cancer. The pooled area under the curve (AUC) was 0.67, with a sensitivity and specificity of 0.74 and 0.56, respectively. Conversely, the peripheral tissue miR-193a-5p expression in patients with lung cancer was significantly downregulated. The pooled AUC was 0.83, and the sensitivity and specificity were 0.65 and 0.89, respectively. Through bioinformatics analysis, three Kyoto Encyclopedia of Genes and Genomes (KEGG) terms, pathways in cancer, prostate cancer and RIG-I-like receptor signaling pathway, were identified as associated with miR-193a-5p in lung cancer. In addition, in lung cancer, six key miR-193a-5p target genes, receptor tyrosine-protein kinase erbB-2 (ERBB2), nuclear cap-binding protein subunit 2 (NCBP2), collagen α-1(I) chain (COL1A1), roprotein convertase subtilisin/kexin type 9 (PCSK9), casein kinase II subunit α (CSNK2A1) and nucleolar transcription factor 1 (UBTF), were identified, five of which were significantly upregulated (ERBB2, NCBP2, COL1A1, CSNK2A1 and UBTF). The protein expression of ERBB2, NCBP2, COL1A1, CSNK2A1 and UBTF was also upregulated. NCBP2 and CSNK2A1 were negatively correlated with miR-193a-5p. The results demonstrated that miR-193a-5p exhibited opposite expression patterns in peripheral blood and tissue. Upregulated peripheral blood miR-193a-5p and downregulated tissue miR-193a-5p may be promising diagnostic biomarkers in lung cancer. In addition, the KEGG terms pathways in cancer, prostate cancer and RIG-I-like receptor signaling pathway may suggest which pathways serve vital roles in lung cancer by regulating miR-193a-5p. In addition, six genes, ERBB2, COL1A1, PCSK9, UBTF and particularly NCBP2 and CSNK2A1, may be key target genes of miR-193a-5p in lung cancer.
Plant synthetic biology could drive a revolution in biofuels and medicine

Population growth, climate change, and dwindling finite resources are amongst the major challenges which are facing the planet. Requirements for food, materials, water, and energy will soon exceed capacity. Green biotechnology, fueled by recent plant synthetic biology breakthroughs, may offer solutions. This review summarizes current progress towards robust and predictable engineering of plants. I then discuss applications from the lab and field, with a focus on bioenergy, biomaterials, and medicine. Impact statement The plant synthetic biology field has exploded in the last five years, in part driven by techniques such as CRISPR and cheap DNA synthesis. This review summarizes the current state of research in plant synthetic biology, and how it is being applied to two topics: renewable fuels and chemicals, and medicine.
Computational Studies for Structure-Based Drug Designing Against Transmembrane Receptors: pLGICs and Class A GPCRs

Biological cell is the fundamental building block of every living system. The plasma membrane, a phospholipid bilayer consisting of two asymmetric leaflets, defines its existence by separating the interior from the exterior. This low dielectric barrier selectively prevents the passage of hydrophilic and charged compounds including small ions. Integral transmembrane proteins span the entire bilayer and take part in small-molecule transport and complex signaling pathways while functioning as receptors and/or ion channels. These proteins carry important biological functions and hence are attractive drug targets. Present review considers the members of two important protein superfamilies that provided the major pharmaceutical drug-targets, viz., Cys-loop pentameric ligand gated ion channels (pLGICs) and class A G-protein-coupled receptors (GPCRs). The crystal structures of integral membrane proteins are difficult to obtain. It limited their structural investigation and associated structure-based drug designing (SBDD). However, recent advancement in crystallographic techniques yielded some important crystal structures. While the advancement of computational science guided their study even in the absence of crystal structures through the homology/comparative modelling approaches. These proteins possess multiple ligand binding sites including both orthosteric and allosteric sites. Addressing the multidimensional problem of understanding the structure and dynamics of such big proteins, multisite-protein-ligand complexes is now possible with molecular dynamics simulation approach, enabled with highly enhanced computational power. Overall the discussion highlights the understanding of structure-function relationship that guides SBDD of these interesting and important transmembrane proteins.
A Customized Hybrid Approach to Infrastructure Maintenance Scheduling in Railroad Networks under Variable Productivities

Railroads are maintained routinely by using various types of rail‐bound machines so as to achieve the longest possible rail life and reduce the safety risks associated with unanticipated rail failures. The rail maintenance routing and scheduling problem (RMRSP), which involves routing of multiple maintenance vehicles and scheduling of hundreds of maintenance jobs over a large‐scale network, is usually subject to various types of complex constraints and extremely difficult to solve. This article proposes a vehicle routing problem with time windows (VRPTW) formulation for RMRSP and develops a customized stepwise algorithm to solve the problem. A series of numerical experiments are conducted to demonstrate that the proposed algorithm works very effectively, significantly outperforming the state‐of‐the‐art commercial solver. The results of two real‐world instances from a Class I railroad company show that the proposed model and solution algorithm enable the expensive maintenance vehicles to achieve a higher level of utilization, that is, spending more time on working and less time on deadhead traveling.
Adversarial Binaries for Authorship Identification

Binary code authorship identification determines authors of a binary program. Existing techniques have used supervised machine learning for this task. In this paper, we look this problem from an attacker's perspective. We aim to modify a test binary, such that it not only causes misprediction but also maintains the functionality of the original input binary. Attacks against binary code are intrinsically more difficult than attacks against domains such as computer vision, where attackers can change each pixel of the input image independently and still maintain a valid image. For binary code, even flipping one bit of a binary may cause the binary to be invalid, to crash at the run-time, or to lose the original functionality. We investigate two types of attacks: untargeted attacks, causing misprediction to any of the incorrect authors, and targeted attacks, causing misprediction to a specific one among the incorrect authors. We develop two key attack capabilities: feature vector modification, generating an adversarial feature vector that both corresponds to a real binary and causes the required misprediction, and input binary modification, modifying the input binary to match the adversarial feature vector while maintaining the functionality of the input binary. We evaluated our attack against classifiers trained with a state-of-the-art method for authorship attribution. The classifiers for authorship identification have 91% accuracy on average. Our untargeted attack has a 96% success rate on average, showing that we can effectively suppress authorship signal. Our targeted attack has a 46% success rate on average, showing that it is possible, but significantly more difficult to impersonate a specific programmer's style. Our attack reveals that existing binary code authorship identification techniques rely on code features that are easy to modify, and thus are vulnerable to attacks.
Second-order Guarantees of Distributed Gradient Algorithms

We consider distributed smooth nonconvex unconstrained optimization over networks, modeled as a connected graph. We examine the behavior of distributed gradient-based algorithms near strict saddle points. Specifically, we establish that (i) the renowned Distributed Gradient Descent (DGD) algorithm likely converges to a neighborhood of a Second-order Stationary (SoS) solution; and (ii) the more recent class of distributed algorithms based on gradient tracking--implementable also over digraphs--likely converges to exact SoS solutions, thus avoiding (strict) saddle-points. Furthermore, new convergence rate results to first-order critical points is established for the latter class of algorithms.
Quantified factory worker: designing a worker feedback dashboard

Factory work is changing towards knowledge work, demanding problem-solving skills and managing complexity. Providing factory workers the possibility to receive meaningful self-tracking feedback at work, could empower them to cope better with the increasing complexity of their work. We apply the Quantified Self approach to factory work by introducing the concept and prototype of a Worker Feedback Dashboard, which presents various automatically tracked well-being and work performance metrics to workers. Based on user interviews, we created user experience goals for the Dashboard, and identified the following design implications: Keep positive (but truthful), Give personal feedback, Enable reflection, and Do not disturb the worker. After designing the prototype, we studied its user acceptance. Even though the interviewed factory workers' first reactions to tracking personal metrics at work were rather negative, the attitudes became more positive after presenting the prototype. The results encourage implementing the Worker Feedback Dashboard prototype to a functional application.
Communication of information in the digital age among social sciences students: Uncovering a synthetic indicator of performance

Purpose The purpose of this paper is to analyze the informational behavior of a group of future professionals in the field of social sciences (SS), in terms of their competence in the communication–dissemination of information. Design/methodology/approach The IL-HUMASS, EVALCI/KN and EVALCI/SK tests regarding the affective (attitudes, motivations) and cognitive (knowledge, skills) dimensions are distributed to a stratified sample of five universities and eight degree courses in Spain. Infographics and non-parametric methods allow to compare the disciplinary profiles with regard to gender, academic course and academic degrees. An Information Literacy Communication synthetic indicator based on structural equation modeling includes the subjective and effective dimensions to measure the holistic learning outcomes in communication–dissemination of information. Findings Significant differences regarding the informational behavior of future professionals in SS are discovered. The synthetic indicator allows academic degrees to be ranked in order to identify those in need of initiatives aimed at improving communication–dissemination competence. Practical implications Findings must be taken into account to design effective learning programs. This methodological approach can be expanded to scientific and academic environments. Originality/value The paper puts forward the first evidence-based study on communication–dissemination competence among future SS professionals, as no similar research has been found in the scientific literature. It is also the first time that the definition of a predictive performance indicator, based on a powerful statistical methodology, has been proposed.
Prioritized Kinematic Control of Joint-Constrained Head-Eye Robots using the Intermediate Value Approach

Existing gaze controllers for head-eye robots can only handle single fixation points. Here, a generic controller for head-eye robots capable of executing simultaneous and prioritized fixation trajectories in Cartesian space is presented. This enables the specification of multiple operational-space behaviors with priority such that the execution of a low priority head orientation task does not disturb the satisfaction of a higher prioritized eye gaze task. Through our approach, the head-eye robot inherently gains the biomimetic vestibulo-ocular reflex (VOR), which is the ability of gaze stabilization under self generated movements. The described controller utilizes recursive null space projections to encode joint limit constraints and task priorities. To handle the solution discontinuity that occurs when joint limit tasks are inserted or removed as a constraint, the Intermediate Desired Value (IDV) approach is applied. Experimental validation of the controller's properties is demonstrated with the Dreamer humanoid robot. Our contribution is on (1) the formulation of a desired gaze task as an operational space orientation task, (2) the application details of the IDV approach for the prioritized head-eye robot controller that can handle intermediate joint constraints, and (3) a minimum-jerk specification for behavior and trajectory generation in Cartesian space.
Low-Dose Naltrexone (LDN)—Review of Therapeutic Utilization

Naltrexone and naloxone are classical opioid antagonists. In substantially lower than standard doses, they exert different pharmacodynamics. Low-dose naltrexone (LDN), considered in a daily dose of 1 to 5 mg, has been shown to reduce glial inflammatory response by modulating Toll-like receptor 4 signaling in addition to systemically upregulating endogenous opioid signaling by transient opioid-receptor blockade. Clinical reports of LDN have demonstrated possible benefits in diseases such as fibromyalgia, Crohn’s disease, multiple sclerosis, complex-regional pain syndrome, Hailey-Hailey disease, and cancer. In a dosing range at less than 1 μg per day, oral naltrexone or intravenous naloxone potentiate opioid analgesia by acting on filamin A, a scaffolding protein involved in μ-opioid receptor signaling. This dose is termed ultra low-dose naltrexone/naloxone (ULDN). It has been of use in postoperative control of analgesia by reducing the need for the total amount of opioids following surgery, as well as ameliorating certain side-effects of opioid-related treatment. A dosing range between 1 μg and 1 mg comprises very low-dose naltrexone (VLDN), which has primarily been used as an experimental adjunct treatment for boosting tolerability of opioid-weaning methadone taper. In general, all of the low-dose features regarding naltrexone and naloxone have been only recently and still scarcely scientifically evaluated. This review aims to present an overview of the current knowledge on these topics and summarize the key findings published in peer-review sources. The existing potential of LDN, VLDN, and ULDN for various areas of biomedicine has still not been thoroughly and comprehensively addressed.
Postsynaptic localization and regulation of AMPA receptors and Cav1.2 by β2 adrenergic receptor/PKA and Ca2+/CaMKII signaling

The synapse transmits, processes, and stores data within its tiny space. Effective and specific signaling requires precise alignment of the relevant components. This review examines current insights into mechanisms of AMPAR and NMDAR localization by PSD‐95 and their spatial distribution at postsynaptic sites to illuminate the structural and functional framework of postsynaptic signaling. It subsequently delineates how β2 adrenergic receptor (β2 AR) signaling via adenylyl cyclase and the cAMP‐dependent protein kinase PKA is organized within nanodomains. Here, we discuss targeting of β2 AR, adenylyl cyclase, and PKA to defined signaling complexes at postsynaptic sites, i.e., AMPARs and the L‐type Ca2+ channel Cav1.2, and other subcellular surface localizations, the role of A kinase anchor proteins, the physiological relevance of the spatial restriction of corresponding signaling, and their interplay with signal transduction by the Ca2+‐ and calmodulin‐dependent kinase CaMKII. How localized and specific signaling by cAMP occurs is a central cellular question. The dendritic spine constitutes an ideal paradigm for elucidating the dimensions of spatially restricted signaling because of their small size and defined protein composition.
Experiencing VOS: a visual orientation system

This demo introduces VOS - a Visual Orientation System. Since orientation without visual cues is challenging for humans, situations in which visibility is limited pose hindrance and sometimes a threat to human activities. To explore the augmentation design space that enables focusing the sense of hearing, we chose a particular application scenario: swimming in open-water. We developed augmented swimming-goggles that provide visual feedback to complement the sense of orientation. Currently, we explore different information encoding methods. The presented prototype illustrates the differences between using a continuous signal to convey absolute directions and discrete signals to indicate a relative direction.
Validation and usability of a mobile phone application for epidemiological surveillance of traumatic dental injuries

BACKGROUND/AIM Traumatic dental injuries (TDI) are a public health problem, given their prevalence and consequences. However, their epidemiology is uncertain due to a general lack of quality data capture. The aim of this study was to evaluate the validity and usability of a mobile phone-based application for community-based surveillance of traumatic dental injuries. MATERIALS AND METHODS A mobile phone-based application, Dental Trauma Tracker (DTT), was developed. This system involves a mobile application for general users to report TDIs and a Web application for researchers to generate epidemiological data. The DTT evaluation used mixed methods and was conducted in three phases: (a) validation of a trauma identification system using preselected TDI images; (b) design evaluation by experts; and (c) usability evaluation measured by the reporting of three fictitious TDI cases and using the System Usability Scale (SUS). RESULTS In the first phase, 182 participants participated. Most images showed over 95% accuracy, indicating that they adequately represented the type of dentoalveolar trauma being evaluated (κ = 0.75). The design evaluation identified nine usability problems-four of them with a "High priority" to be fixed, four with "Low priority," and one "No fix necessary. " A total of 29 volunteers participated in the usability evaluation. The mean time for users to complete all of the reports was 7.8 ± 3.0 minutes. Mean SUS score was 67.4 ± 21.9 (Range: 0-100; worst to best). The global agreement between cases registered with the gold standard was also "Substantial" (κ = 0.71). CONCLUSIONS This preliminary evaluation confirmed the App's usability, using a sample of potential users, as well as reporting on the results of an expert panel review of the DTT. These are the minimum requirements necessary before further expansion and widespread implementation occurs to confirm these results.
White Spot Syndrome Virus-Induced Shrimp miR-315 Attenuates Prophenoloxidase Activation via PPAE3 Gene Suppression

MicroRNAs (miRNAs), the small non-coding RNAs, play a pivotal role in post-transcriptional gene regulation in various cellular processes. However, the miRNA function in shrimp antiviral response is not clearly understood. This research aims to uncover the function of pmo-miR-315, a white spot syndrome virus (WSSV)-responsive miRNAs identified from Penaeus monodon hemocytes during WSSV infection. The expression of the predicted pmo-miR-315 target mRNA, a novel PmPPAE gene called PmPPAE3, was negatively correlated with that of the pmo-miR-315. Furthermore, the luciferase assay indicated that the pmo-miR-315 directly interacted with the target site in PmPPAE3 suggesting the regulatory role of pmo-miR-315 on PmPPAE3 gene expression. Introducing the pmo-miR-315 into the WSSV-infected shrimp caused the reduction of the PmPPAE3 transcript level and, hence, the PO activity activated by the PmPPAE3 whereas the WSSV copy number in the shrimp hemocytes was increased. Taken together, our findings state a crucial role of pmo-miR-315 in attenuating proPO activation via PPAE3 gene suppression and facilitating the WSSV propagation in shrimp WSSV infection.