Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-local pairwise energy-based model for the high-dynamic-range image compression problem

We present a new energy-based compression model for the display of high dynamic range images. The proposed tone mapping method tends to exploit the biologically inspired dynamic retina concept, which is herein mathematically expressed via an image representation based on the specification of the statistical distributions of the nonlocal gradient magnitude. In this framework, which also operates the notion of nonlocal gradient recently put forward by Gilboa and Osher, the detail-preserving contrast reduction problem is therefore expressed by a energy-based model with nonlocal pairwise pixel interactions defined on a complete graph whose cost function is locally minimized by a conjugate gradient descent procedure. The experiments demonstrate that the proposed compression method is efficient and provides pleasing results on various images with different scene contents and performs competitively compared to the best existing state-of-the-art tone mapping methods recently proposed in the literature.
The Design and Implementation of Lego Volleyball Robots.

The aim of the LEGO robot project was to develop a team of robots to compete in a scaled down version of volleyball. The competition was held in Sheffield, as part of the British Association for Science Annual exhibition, on the 13 th of September 1999. The robots described in this technical report won the competition.
A Proof-of-Concept for a Hypolipidemic Brown Trout Model

The impacts of hypolipidemic pharmaceuticals on fish lipid metabolism remain unexplored. However, data points to similar effects and mechanisms of action between fish and humans. Therefore, fish may be a strong model for screening hypolipidemic drug candidates and water pollution by lipid-modulating agents. This study aimed to test a new hypolipidemic model assay with juvenile brown trout using atorvastatin (ATV)—a hypolipidemic chemical. We selected 17α-ethinylestradiol (EE2), known to cause hyperlipidemia in fish, to ensure model functionality. Fish received intramuscular injections of 4 μL/g for two weeks under the following experimental conditions: control—C (0.7% NaCl), solvent control—SC (0.7% NaCl, 0.9% ethanol, 0.1% dimethyl sulfoxide), ATV (0.3 μg/g), EE2 (2 μg/g), and a mixture of both compounds—MIX (0.3 μg/g ATV and 2 μg/g EE2). Endpoints included blood lipid biochemistry, hepatic lipid droplet quantification, and liver mRNA expression of lipid-related target genes (related to lipogenesis, lipid transport, and β-oxidation pathways). ATV lowered blood total cholesterol, high-density lipoproteins (HDL), and low-density lipoproteins (LDL) levels, whilst triglycerides and very-low-density lipoproteins (VLDL) were highest under EE2. Hepatic lipid droplet deposition significantly increased in the ATV, EE2, and MIX groups. ATV and MIX caused a significant downregulation of the peroxisome proliferator-activated receptor γ (pparγ) and acetyl Co-A oxidase 3 (acox3). EE2 upregulated acyl-CoA long-chain synthetase 1 (acsl1) and downregulated both fatty acid binding protein 1 (fabp1) and acetyl Co-A oxidase 1-3I (acox1-3I). ATV caused hypolipidemic effects in juvenile brown trout and could even counteract EE2-stimulated hyperlipidemia, reinforcing the potential of fish hypo- and hyperlipidemic models.
Toward polyphonic musical instrument identification using example-based sparse representation

Musical instrument identification is one of the major topics in music signal processing. In this paper, we propose a musical instrument identification method based on sparse representation for polyphonic sounds. Such the identification has been still categorized into challenging tasks, since it needs high-performance signal processing techniques. The proposed scheme can be applied without any signal processing such as source separation. Sample feature vectors for various musical instruments are used for the base matrix of sparse representation. We conducted two experiments to evaluate the proposed method. First, the musical instrument identification is tested for monophonic sounds using five musical instruments. The average accuracy of 91.9% was obtained and it shows the effectiveness of the proposed method. Second, musical instrument composition of polyphonic sounds is examined, which contain two instruments. It is found that the estimated weight vector by sparse representation indicates the mixture ratio of two instruments.
Hippocampal-Dependent Spatial Memory in the Water Maze is Preserved in an Experimental Model of Temporal Lobe Epilepsy in Rats

Cognitive impairment is a major concern in temporal lobe epilepsy (TLE). While different experimental models have been used to characterize TLE-related cognitive deficits, little is known on whether a particular deficit is more associated with the underlying brain injuries than with the epileptic condition per se. Here, we look at the relationship between the pattern of brain damage and spatial memory deficits in two chronic models of TLE (lithium-pilocarpine, LIP and kainic acid, KA) from two different rat strains (Wistar and Sprague-Dawley) using the Morris water maze and the elevated plus maze in combination with MRI imaging and post-morten neuronal immunostaining. We found fundamental differences between LIP- and KA-treated epileptic rats regarding spatial memory deficits and anxiety. LIP-treated animals from both strains showed significant impairment in the acquisition and retention of spatial memory, and were unable to learn a cued version of the task. In contrast, KA-treated rats were differently affected. Sprague-Dawley KA-treated rats learned less efficiently than Wistar KA-treated animals, which performed similar to control rats in the acquisition and in a probe trial testing for spatial memory. Different anxiety levels and the extension of brain lesions affecting the hippocampus and the amydgala concur with spatial memory deficits observed in epileptic rats. Hence, our results suggest that hippocampal-dependent spatial memory is not necessarily affected in TLE and that comorbidity between spatial deficits and anxiety is more related with the underlying brain lesions than with the epileptic condition per se.
Effect of Maternal Multivitamin Supplementation on the Mental and Psychomotor Development of Children Who Are Born to HIV-1–Infected Mothers in Tanzania

OBJECTIVES. To determine the association between maternal multivitamin supplementation and the mental and psychomotor development of children who are born to HIV-1–infected mothers in Tanzania, as secondary endpoints in a randomized trial that investigated the effect of maternal multivitamin supplementation on HIV-1 vertical transmission and progression. METHODS. The Bayley Scales of Infant Development, 2nd Edition, were administered at 6, 12, and 18 months of age to a subset of children (N = 327). We assessed the effect of vitamin A and multivitamin (vitamins B, C, and E) supplementation using linear regression models and Cox proportional hazard models for the Mental Development Index, the Psychomotor Development Index, and raw scores separately. RESULTS. Multivitamin supplementation was associated significantly with a mean increase in Psychomotor Development Index score of 2.6 (95% confidence interval: 0.1–5.1). Multivitamins were also significantly protective against the risk for developmental delay on the motor scale (relative risk: 0.4; 95% confidence interval: 0.2–0.7) but not on the Mental Development Index. Vitamin A supplementation had no significant effect on these outcomes. CONCLUSIONS. Maternal multivitamin supplements provide a low-cost intervention to reduce the risk for developmental delays among infants who are born to HIV-positive mothers in developing countries.
Verifying Distributed Algorithms via Dynamic Analysis and Theorem Proving

We use output from dynamic analysis to assist theorem-proving of safety properties of distributed algorithms. The algorithms are written in the IOA language, which is based on the mathematical I/O automaton model. Daikon, a dynamic invariant discovery tool, generalizes from test executions, producing assertions about the observed behavior of the algorithm. We use these relatively simple run-time properties as lemmas in proving program properties. These lemmas are necessary, but easy for humans to overlook. Furthermore, the lemmas decompose complex steps into simple ones that theorem provers can manage mostly unassisted, thus reducing the human effort required to prove interesting algorithm properties. In several experiments, Daikon produced all or most of the lemmas required for correctness proofs, automating the most difficult part of the process, which usually requires human insight. This verification technique is a worthwhile alternative to using only static analysis with model checkers or theorem provers, or only dynamic analysis with simulators and runtime analyzers. Our technique combines the advantages of static and dynamic analysis: it is sound and scales to algorithms with unbounded processes and variable sizes. Further, it can suggest and verify new program properties that the designer might not have envisioned.
Increased Renal Medullary H2O2 Leads to Hypertension

Abstract—We have recently reported that exaggerated oxidative stress in the renal medulla due to superoxide dismutase inhibition resulted in a reduction of renal medullary blood flow and sustained hypertension. The present study tested the hypothesis that selective scavenging of O2·− in the renal medulla would prevent hypertension associated with this exaggerated oxidative stress. An indwelling, aortic catheter was implanted in nonnephrectomized Sprague-Dawley rats for daily measurement of arterial blood pressure, and a renal medullary interstitial catheter was implanted for continuous delivery of the superoxide dismutase inhibitor diethyldithiocarbamic acid (DETC, 7.5 mg · kg−1 · d−1) and a chemical superoxide dismutase mimetic, 4-hydroxytetramethyl piperidine-1-oxyl (TEMPOL, 10 mg · kg−1 · d−1). Renal medullary interstitial infusion of TEMPOL completely blocked DETC-induced accumulation of O2·− in the renal medulla, as measured by the conversion rate of dihydroethidium to ethidium in the dialysate and by urinary excretion of 8-isoprostanes. However, TEMPOL infusion failed to prevent DETC-induced hypertension, unless catalase (5 mg · kg−1 · d−1) was coinfused. Direct infusion of H2O2 into the renal medulla resulted in increases of mean arterial pressure from 115±2.5 to 131±2.1 mm Hg, which was similar to that observed in rats receiving the medullary infusion of both TEMPOL and DETC. The results indicate that sufficient catalase activity in the renal medulla is a prerequisite for the antihypertensive action of TEMPOL and that accumulated H2O2 in the renal medulla associated with exaggerated oxidative stress might have a hypertensive consequence.
Specificity and robustness in transcription control networks

Recognition by transcription factors of the regulatory DNA elements upstream of genes is the fundamental step in controlling gene expression. How does the necessity to provide stability with respect to mutation constrain the organization of transcription control networks? We examine the mutation load of a transcription factor interacting with a set of n regulatory response elements as a function of the factor/DNA binding specificity and conclude on theoretical grounds that the optimal specificity decreases with n. The predicted correlation between variability of binding sites (for a given transcription factor) and their number is supported by the genomic data for Escherichia coli. The analysis of E. coli genomic data was carried out using an algorithm suggested by the biophysical model of transcription factor/DNA binding. Complete results of the search for candidate transcription factor binding sites are available at http://www.physics. rockefeller.edu/∼boris/public/search_ecoli.
Dicodon monitoring of protein synthesis (DiCoMPS) reveals levels of synthesis of a viral protein in single cells

The current report represents a further advancement of our previously reported technology termed Fluorescent transfer RNA (tRNA) for Translation Monitoring (FtTM), for monitoring of active global protein synthesis sites in single live cells. FtTM measures Förster resonance energy transfer (FRET) signals, generated when fluorescent tRNAs (fl-tRNAs), separately labeled as a FRET pair, occupy adjacent sites on the ribosome. The current technology, termed DiCodon Monitoring of Protein Synthesis (DiCoMPS), was developed for monitoring active synthesis of a specific protein. In DiCoMPS, specific fl-tRNA pair combinations are selected for transfection, based on the degree of enrichment of a dicodon sequence to which they bind in the mRNA of interest, relative to the background transcriptome of the cell in which the assay is performed. In this study, we used cells infected with the Epizootic Hemorrhagic Disease Virus 2-Ibaraki and measured, through DiCoMPS, the synthesis of the viral non-structural protein 3 (NS3), which is enriched in the AUA:AUA dicodon. fl-tRNAIleUAU-generated FRET signals were specifically enhanced in infected cells, increased in the course of infection and were diminished on siRNA-mediated knockdown of NS3. Our results establish an experimental approach for the single-cell measurement of the levels of synthesis of a specific viral protein.
Automated Fault Localization Techniques ; A Survey

Fault localization is a task in software debugging to identify the set of statements in a program that cause the program to fail. As size and complexity of software grows,and the more developers participate in debugging, fault localization becomes harder than before. Automated fault localization techniques aim to facilitate this task by guiding the developers to a small portion of program that are likely to be culpable for the program failures. In this paper, we look at important techniques for automated fault localization and categorize them based on their common features. We also briefly discuss some of challenges and shortcomings in this field.
Permeabilization of the Blood-Brain Barrier via Mucosal Engrafting: Implications for Drug Delivery to the Brain

Utilization of neuropharmaceuticals for central nervous system(CNS) disease is highly limited due to the blood-brain barrier(BBB) which restricts molecules larger than 500Da from reaching the CNS. The development of a reliable method to bypass the BBB would represent an enormous advance in neuropharmacology enabling the use of many potential disease modifying therapies. Previous attempts such as transcranial catheter implantation have proven to be temporary and associated with multiple complications. Here we describe a novel method of creating a semipermeable window in the BBB using purely autologous tissues to allow for high molecular weight(HMW) drug delivery to the CNS. This approach is inspired by recent advances in human endoscopic transnasal skull base surgical techniques and involves engrafting semipermeable nasal mucosa within a surgical defect in the BBB. The mucosal graft thereby creates a permanent transmucosal conduit for drugs to access the CNS. The main objective of this study was to develop a murine model of this technique and use it to evaluate transmucosal permeability for the purpose of direct drug delivery to the brain. Using this model we demonstrate that mucosal grafts allow for the transport of molecules up to 500 kDa directly to the brain in both a time and molecular weight dependent fashion. Markers up to 40 kDa were found within the striatum suggesting a potential role for this technique in the treatment of Parkinson’s disease. This proof of principle study demonstrates that mucosal engrafting represents the first permanent and stable method of bypassing the BBB thereby providing a pathway for HMW therapeutics directly into the CNS.
Localized techniques for broadcasting in wireless sensor networks

We present three localized techniques for broadcasting in large scale ad hoc networks, i.e., for the problem of disseminating a message from a source node to all the nodes in the network. Aim of the proposed techniques is to define broadcasting mechanisms that are simple, thus generating low overhead, energy efficient, for deployment in resource-constrained networks, and reliable, in that all the nodes receive the intended message with very high probability. The three schemes follow two different approaches for data dissemination. The first approach relies on the idea of identifying local rules for sparsifying the network topology. The resulting virtual topology is the actual structure through which broadcasting is performed. While techniques for sparsifying the network topology have been proposed before, our solution makes no use of location information. The second approach follows the line of on-line algorithms for the implementation of probabilistic flooding. In this case, the proposed algorithm has been studied analytically, which lead to asymptotic proofs that all nodes are successfully reached by the broadcast message with very high probability. A comparative performance evaluation has been performed via simulations among the three proposed techniques and a previous solution for ad hoc broadcast. We have evaluated various metrics of interests versus different nodes distributions, which include the uniform and a more realistic ``Hill distribution" that takes into consideration certain characteristics of sensor nodes deployment in uneven areas.Our results show that the on-line approach and one of the proposed virtual topology-based solutions offer the desirable compromise between energy saving, network load and reliability.
Current and Future Gene Therapy for Malignant Gliomas

Malignant gliomas are the most common neoplasm in the central nervous system. When treated with conventional treatments including surgery, irradiation, and chemotherapy, the average life expectancy of the most malignant type, glioblastoma multiforme is usually less than 1 year. Therefore, gene therapy is expected to be an effective and possibly curative treatment. Many gene therapeutic approaches have demonstrated efficacy in experimental animal models. However, the current clinical trials are disappointing. This review focuses on current therapeutic genes/vectors/delivery systems/targeting strategies in order to introduce updated trends and hopefully indicate prospective gene therapy for malignant gliomas.
Modelling the lymphatic system: challenges and opportunities

The lymphatic system is a vital part of the circulatory and immune systems, and plays an important role in homeostasis by controlling extracellular fluid volume and in combating infection. Nevertheless, there is a notable disparity in terms of research effort expended in relation to the treatment of lymphatic diseases in contrast to the cardiovascular system. While similarities to the cardiovascular system exist, there are considerable differences in their anatomy and physiology. This review outlines some of the challenges and opportunities for those engaged in modelling biological systems. The study of the lymphatic system is still in its infancy, the vast majority of the models presented in the literature to date having been developed since 2003. The number of distinct models and their variants are few in number, and only one effort has been made thus far to study the entire lymphatic network; elements of the lymphatic system such as the nodes, which act as pumps and reservoirs, have not been addressed by mathematical models. Clearly, more work will be necessary in combination with experimental verification in order to progress and update the knowledge on the function of the lymphatic system. As our knowledge and understanding of its function increase, new and more effective treatments of lymphatic diseases are bound to emerge.
The Effect of Severe Varus Deformity on Clinical and Radiographic Outcomes in Mechanical Aligned Total Knee Arthroplasty with Medial Stabilizing Technique

Background: The purpose was to compare the clinical and radiographic outcomes between preoperative mild and severe varus deformity after total knee arthroplasty (TKA) with medial stabilizing technique (MST). Methods: We retrospectively analyzed 158 knees of 125 female patients with a 2-year follow-up who underwent mechanically aligned TKA with MST between April 2018 and February 2021. Patients were divided into two groups; the severe varus group was defined as one with preoperative hip-knee ankle (HKA) angle ≥ 15° and the mild varus group with HKA angle < 15°. Pre- and post-operative clinical outcomes (Western Ontario and McMaster University Osteoarthritis Index, Knee Society Knee Score) and radiographic outcomes (medial proximal tibial angle (MPTA), HKA angle, lateral distal femoral angle (LDFA), joint line distance, and femoral component rotation angle) were compared between the groups. Results: Among the 158 knees analyzed, 131 and 27 were allocated to the mild and severe varus groups, respectively. Preoperative data showed that the MPTA (84.7° ± 2.8° vs. 80.7° ± 3.2°, p < 0.001) was significantly less in the severe varus group. In postoperative data, clinical outcomes were not different between the groups. Joint line distance (18.4 mm ± 2.8 mm vs. 18.6 mm ± 2.7 mm, p = 0.676) was also not significantly different. Femoral component rotation angle (−1.7° ± 1.0° vs. −1.0° ± 1.3°, p = 0.018) was more externally rotated in the severe varus group. Conclusions: Severe varus group showed comparable clinical and radiographic outcomes to that of mild varus group after mechanically aligned TKA with MST.
A VTOL quadrotor platform for multi-UAV path planning

A four-rotor vertical takeoff and landing aerial robot known as quadrotor has been developed as a platform to validate and test various algorithm suit to the unmanned air vehicles (UAV). A path planning method base on Rapidly-exploring Random Tree (RRT) was developed to generate paths UAV for in real time. The algorithm was experimented on the quadrotor platform and was validated to be efficient.
Modeling and Optimization Techniques for Yield-Aware SRAM Post-Silicon Tuning

SRAM cell design is driven by the need to satisfy several stability and performance criteria for all cells in the array in an energy-efficient manner. Significant randomness of FET threshold voltages makes achieving this difficult and limits both the minimum cell size and minimum array supply voltage. Post-silicon adaptivity in the form of an adaptive-voltage scheme in a partitioned SRAM array can be used to reduce impact of variability despite lack of any spatial correlation in realizations. This paper develops a novel optimization flow for yield-aware cell sizing and voltage selection under variability given the availability of post-silicon voltage tuning. We formulate a two-stage stochastic optimization problem in which the first-stage decision is to select cell size and possible voltage levels, and the second-stage decision is to assign each partition to an optimal voltage after manufacturing. We develop closed-form statistical models of array margin behavior and yield as a function of Vdd, cell size, and array size. We solve the problem using dynamic programming that minimizes power while meeting yield constraints on read, write, and static noise margins. The proposed flow allows designs that are on average 8% and up to 17% more power-efficient than the designs in which voltages are selected uniformly. The results also indicate that at high-yield levels power savings can be up to 32% in the active mode and 71% in the standby mode.