Miracle-dz/UniFAR-FTUs huggingface dataset:
Surface EMG and heartbeat analysis preliminary results in surgical training: Dry boxes and live tissue

The training in the surgical practice is of paramount importance to prepare the residents in performing surgical procedures on human subject and to provide exercise on new techniques for experienced surgeons. Usually, these trainings are carried out on live animals or in virtual environments and dry boxes; the complexity of the exercises is identical in both of the case, but the pressure in operating with a living subject could change the attitude and the movements of the trainee. Until now, it has not been possible to analyze this stress in details together in the surgical animal training and dry boxes. In this work we propose an innovative portable system that can measure two physiological parameters, the heartbeat and the surface electromyography, during a session of training in both of the environment. The preliminary results, for one subject, show a bigger average power in the shoulder muscles during the living operation together with a higher but stable heartbeat rate.
Evaluation of changes in the expression of Wnt/β-catenin target genes in mouse reproductive tissues during estrous cycle: An experimental study

Background: The Wingless-type (Wnt)/β-catenin signaling pathway controls cell homeostasis. Reproductive tissues are dynamic in response to steroidal hormone changes. Steroidal hormones are known to control the Wnt/β-catenin pathway, but their role in reproductive tissues remains unknown. Objective: The present study aims to investigate the expression patterns of Wnt/β-catenin target genes in mouse reproductive tissues during the normal estrous cycle. Materials and Methods: In this experimental study, 16 adult NMRI mice were grouped as proestrus, estrus, metestrus, and diestrus according to vaginal smear and histological evaluation of uterine and ovarian tissues. Uterine horns and ovarian tissues were collected. Reverse transcription quantitative polymerase chain reaction was performed to evaluate the expression of Wnt/β-catenin target genes (Myc2, Ppard, Id2, Birc5, and Ascl2) at different stages of the estrous cycle. Results: The expression levels of Id2, Ascl2, and Pprd in uterine tissue were significantly higher at the proestrus phase than at the other stages. Meanwhile, Birc5 expression in uterine tissue was significantly higher at the metestrus stage than at the other stages. Furthermore, Myc2 expression was significantly higher at the diestrus stage than at the estrus and metestrus stages. In the ovarian tissue, the highest expression of Id2, Ascl2, and Birc5 was detected at the proestrus stage, whereas the highest expression of Myc2 and Ppard was observed at the estrus stage. Conclusion: This study showed that Wnt/β-catenin target genes profiles are different among estrous cycle. It seems that different hormonal profiles during estrous cycles play a key role in the expression pattern of Wnt/β-catenin target genes in ovarian and uterine tissue.
Antibody-Dependent Cellular Phagocytosis by Macrophages is a Novel Mechanism of Action of Elotuzumab

Elotuzumab, a recently approved antibody for the treatment of multiple myeloma, has been shown to stimulate Fcγ receptor (FcγR)-mediated antibody-dependent cellular cytotoxicity by natural killer (NK) cells toward myeloma cells. The modulatory effects of elotuzumab on other effector cells in the tumor microenvironment, however, has not been fully explored. Antibody-dependent cellular phagocytosis (ADCP) is a mechanism by which macrophages contribute to antitumor potency of monoclonal antibodies. Herein, we studied the NK cell independent effect of elotuzumab on tumor-associated macrophages using a xenograft tumor model deficient in NK and adaptive immune cells. We demonstrate significant antitumor efficacy of single-agent elotuzumab in immunocompromised xenograft models of multiple myeloma, which is in part mediated by Fc–FcγR interaction of elotuzumab with macrophages. Elotuzumab is shown in this study to induce phenotypic activation of macrophages in vivo and mediates ADCP of myeloma cells though a FcγR-dependent manner in vitro. Together, these findings propose a novel immune-mediated mechanism by which elotuzumab exerts anti-myeloma activity and helps to provide rationale for combination therapies that can enhance macrophage activity. Mol Cancer Ther; 17(7); 1454–63. ©2018 AACR.
Recent progress on monolithic fiber amplifiers for next generation of gravitational wave detectors

Single-frequency fiber amplifiers in MOPA configuration operating at 1064 nm (Yb3+) and around 1550 nm (Er3+ or Er3+:Yb3+) are promising candidates to fulfill the challenging requirements of laser sources of the next generation of interferometric gravitational wave detectors (GWDs). Most probably, the next generation of GWDs is going to operate not only at 1064 nm but also at 1550 nm to cover a broader range of frequencies in which gravitational waves are detectable. We developed an engineering fiber amplifier prototype at 1064 nm emitting 215 W of linearly-polarized light in the TEM00 mode. The system consists of three modules: the seed source, the pre-amplifier, and the main amplifier. The modular design ensures reliable long-term operation, decreases system complexity and simplifies repairing and maintenance procedures. It also allows for the future integration of upgraded fiber amplifier systems without excessive downtimes. We also developed and characterized a fiber amplifier prototype at around 1550 nm that emits 100 W of linearly-polarized light in the TEM00 mode. This prototype uses an Er3+:Yb3+ codoped fiber that is pumped off-resonant at 940 nm. The off-resonant pumping scheme improves the Yb3+-to-Er3+ energy transfer and prevents excessive generation of Yb3+-ASE.
Robust Dual View Deep Agent

Motivated by recent advance of machine learning using Deep Reinforcement Learning this paper proposes a modified architecture that produces more robust agents and speeds up the training process. Our architecture is based on Asynchronous Advantage Actor-Critic (A3C) algorithm where the total input dimensionality is halved by dividing the input into two independent streams. We use ViZDoom, 3D world software that is based on the classical first person shooter video game, Doom, as a test case. The experiments show that in comparison to single input agents, the proposed architecture succeeds to have the same playing performance and shows more robust behavior, achieving significant reduction in the number of training parameters of almost 30%.
Enhancement of RWSN Lifetime via Firework Clustering Algorithm Validated by ANN

Nowadays, wireless power transfer is ubiquitously used in wireless rechargeable sensor networks (WSNs). Currently, the energy limitation is a grave concern issue for WSNs. However, lifetime enhancement of sensor networks is a challenging task need to be resolved. For addressing this issue, a wireless charging vehicle is an emerging technology to expand the overall network efficiency. The present study focuses on the enhancement of overall network lifetime of the rechargeable wireless sensor network. To resolve the issues mentioned above, we propose swarm intelligence based hard clustering approach using fireworks algorithm with the adaptive transfer function (FWA-ATF). In this work, the virtual clustering method has been applied in the routing process which utilizes the firework optimization algorithm. Still now, an FWA-ATF algorithm yet not applied by any researcher for RWSN. Furthermore, the validation study of the proposed method using the artificial neural network (ANN) backpropagation algorithm incorporated in the present study. Different algorithms are applied to evaluate the performance of proposed technique that gives the best results in this mechanism. Numerical results indicate that our method outperforms existing methods and yield performance up to 80% regarding energy consumption and vacation time of wireless charging vehicle.
Blind recognition of linear space time block codes

The blind recognition of communication parameters is a key research issue for commercial and military communication systems. In this paper, we investigate the problem of the blind recognition of linear space-time block codes (STBC). To characterize the space time coding, we propose to compute a time-lag correlation of the received samples. Provided the number of transmitters, the noise variance and the symbol timing are well estimated, we show that the theoretical values of the correlation norm only depend on the STBC and are affected by neither the channel nor the symbol modulation. The automatic recognition of the STBC is realized by selecting the STBC which minimizes the distance between the theoretical values and the experimental ones. Simulations show that our method performs well even for low signal to noise ratio (0 dB).
Advanced Raman Spectroscopy for Bioprocess Monitoring

The Raman -effect was discovered almost 90 years ago. It took a long time until the importance of Raman spectroscopy was fully understood and accepted for process industrial applications. Still today the usage is limited to a small application area. During the last decades advances in the production of spectroscopic components have reduced the complexity of the instrumentation and further mediated a persistent decline in costs, thus making this technology available for a broader audience. The basic components of a Raman spectrometer are a monochromatic light source, typically laser, a Raman probe with optical fibres, a spectrograph and a detector which is connected to a measurementand control PC. Raman spectroscopy is increasingly becoming a choice as analytical tool in bioanalytics. Most of biological samples are handled in aqueous form which challenges many other analytical techniques (e.g., infrared spectroscopy). Raman and its enhancement techniques are able to measure quality and quantity of compounds in liquid phase with no or very little interference of water. The quantity of a compound can be determined by the peak-intensity and the quality by the position in the measured spectrum. Another advantage is that Raman spectroscopy does not rely on extensive sample preparation and measurements can be carried out non-invasively by placing an immersion probe with fibre optics directly in the liquid media. A Raman measurement is conducted fast, within milliseconds, and multiple relevant process parameters from the same sample can be measured at the same time. The measurements can be performed in continuous mode, i.e. one after the other or with a delay inbetween. The operator can determine the measurement interval and in this way the development of a process can be observed online and in real-time. Further important advantages of spectroscopic methods over many other biochemical and physical measurement tools are the robustness as they do not require assays and they are rather unsusceptible against variations of pH, temperature changes, vibrations and other process parameters. If there is no coating, colour or special treatment of the glass, some Raman set-ups allow measurements directly through the glass into the liquid phase. This option enables real process measurements without the need to disturb or contaminate the analytes. These experimental set-ups are in the focus of this thesis. Despite great advantages of spectroscopic methods, the utilization is often complicated since the threshold values are often above what is required for screening. Besides the lack of sensitivity of conventional Raman in bioprocess applications, the major drawback of this technique so far has been the disturbance of the broad fluorescence background especially in biological samples. The main objective of this thesis was to find solutions for increasing the limit of detection (LOD) for biomolecules, being capable to detect them during the course of the process reliably and being able
Insights into Parkinson’s disease from computational models of the basal ganglia

Movement disorders arise from the complex interplay of multiple changes to neural circuits. Successful treatments for these disorders could interact with these complex changes in myriad ways, and as a consequence their mechanisms of action and their amelioration of symptoms are incompletely understood. Using Parkinson’s disease as a case study, we review here how computational models are a crucial tool for taming this complexity, across causative mechanisms, consequent neural dynamics and treatments. For mechanisms, we review models that capture the effects of losing dopamine on basal ganglia function; for dynamics, we discuss models that have transformed our understanding of how beta-band (15–30 Hz) oscillations arise in the parkinsonian basal ganglia. For treatments, we touch on the breadth of computational modelling work trying to understand the therapeutic actions of deep brain stimulation. Collectively, models from across all levels of description are providing a compelling account of the causes, symptoms and treatments for Parkinson’s disease.
ANVIL: Software-Based Protection Against Next-Generation Rowhammer Attacks

Ensuring the integrity and security of the memory system is critical. Recent studies have shown serious security concerns due to "rowhammer" attacks, where repeated accesses to a row of memory cause bit flips in adjacent rows. Recent work by Google's Project Zero has shown how to leverage rowhammer-induced bit-flips as the basis for security exploits that include malicious code injection and memory privilege escalation. Being an important security concern, industry has attempted to defend against rowhammer attacks. Deployed defenses employ two strategies: (1) doubling the system DRAM refresh rate and (2) restricting access to the CLFLUSH instruction that attackers use to bypass the cache to increase memory access frequency (i.e., the rate of rowhammering). We demonstrate that such defenses are inadequte: we implement rowhammer attacks that both avoid using the CLFLUSH instruction and cause bit flips with a doubled refresh rate. Our next-generation CLFLUSH-free rowhammer attack bypasses the cache by manipulating cache replacement state to allow frequent misses out of the last-level cache to DRAM rows of our choosing. To protect existing systems from more advanced rowhammer attacks, we develop a software-based defense, ANVIL, which thwarts all known rowhammer attacks on existing systems. ANVIL detects rowhammer attacks by tracking the locality of DRAM accesses using existing hardware performance counters. Our detector identifies the rows being frequently accessed (i.e., the aggressors), then selectively refreshes the nearby victim rows to prevent hammering. Experiments running on real hardware with the SPEC2006 benchmarks show that ANVIL has less than a 1% false positive rate and an average slowdown of 1%. ANVIL is low-cost and robust, and our experiments indicate that it is an effective approach for protecting existing and future systems from even advanced rowhammer attacks.
Estimation of traversed distance in level walking using a single inertial measurement unit attached to the waist

A method for estimating step length during level walking using a single inertial measurement unit is proposed. A combination of an optimally filtered direct and reverse integration technique and a velocity update technique for the initial velocity values identification was implemented to reduce the effects of the acceleration signals drift. The method takes advantage of the cyclic nature of gait. The inertial measurement unit was placed at waist level on the right side and the method was validated on eight subjects walking for 75 m while varying their speed. The traversed distance was estimated with an average error equal to 0.8% of the total walking distance.
Retrieval, recognition and reconstruction of quadruped motions

Different techniques have been developed for capturing and retrieval, action recognition and video based reconstruction of human motion data in the past years. In this paper, we focus on how these techniques can be adapted to handle quadruped motion capture data and which new applications may appear. We discuss some particularities that must be considered during large animal motion capture. For retrieval, we derive suitable feature sets from quadrupeds motion capture data to perform fast searches for similar motions. Based on the retrieval techniques, the action recognition can be performed on the input motion capture sequences as well as on input video streams. We further present a data-driven approach to reconstruct quadruped motions from video data.
Electron microscopy of nuclear graphite: A modelling approach

Graphite acts as both a major structural component and moderator in nuclear reactors. Upon neutron irradiation, various structural and property changes occur. Property changes include; coefficient of thermal expansion (CTE), Young's modulus and thermal resistivity. This work focuses on the characterisation of irradiated graphite models using both electron energy-loss spectroscopy (EELS) and imaging techniques. A number of models of irradiated graphite have been found, whereby one or more interstitial atoms form between the hexagonal layers. In this work, density functional theory (DFT) modelling is used to predict EEL spectra (carbon K edges) at the spiro-interstitial position, and contrast those to bulk predictions. We observe that for a 'bulk-like' position in the spiro-interstitial model, the carbon K edge shape is similar to that of true bulk, thus confirming the validity of the model used. For the carbon K edge prediction at the spiro-interstitial position, although peaks in the π* region remain in approximately the same energy positions, there is considerable broadening suggesting the presence of strained sp2 bonding character. The σ* peak is significantly altered, both in energy position and intensity relative to the π* region. These observations are arguably consistent with a spiro-interstitial strained from the ideal bonding angles observed in spiro-pentane. Simulations of TEM and HAADF images of the spiro-interstitial model were also performed. These suggested that in a typical TEM, for the (100) orientation, even at a thickness of ∼15Å the interstitial would be difficult to observe. In the case of (S)TEM, a similar situation exists.
Riparian plant isotopes reflect anthropogenic nitrogen perturbations: robust patterns across land use gradients

Riparian plants incorporate nitrogen (N) from aquatic, terrestrial, and atmospheric sources, and their stable isotope compositions (δ15N) may reflect land use impacts on N sources and transformations over scales of sites to watersheds. We surveyed leaf δ15N values of 11 common riparian tree, shrub, and herbaceous species from 20 streams and rivers spanning three fifth-order watersheds in northern Utah, USA (n = 255 sites and 819 leaf samples). Streams spanned undeveloped montane forests to suburban, urban, and agricultural lands. Mean species-specific differences in leaf δ15N values were relatively small within sites (1.2 ± 2.2‰), although emergent aquatic macrophytes had higher within-site δ15N values than other growth forms. Leaf δ15N values varied significantly across land-use categories, and were lowest in undeveloped montane reaches (0.5 ± 1.9‰; mean and standard deviation), intermediate in suburban and urban reaches (2.3 ± 2.6 and 3.2 ± 3.4‰), and greatest in agricultural reaches (4.1 ± 3.1‰). The substantial variation in leaf δ15N values within a land use category often corresponded with local management differences. In an undeveloped montane canyon permitting off-leash dogs, leaf δ15N values (1.5 ± 1.3‰) exceeded similar canyons that strictly prohibited dogs (δ15N = −0.7 ± 1.1‰). Canyons with cattle grazing had leaf δ15N values enriched by 1.4 and 2.8‰ relative to similar, but un-grazed canyons. Variation in traffic between 0 and 5000 vehicles per day did not significantly affect leaf δ15N values, although a canyon with 50,000 vehicles per day showed a 5.7‰ increase relative to low-trafficked canyons. Urban leaf δ15N values were consistently enriched by 2.5 ± 0.6‰ relative to leaves in un-grazed montane reaches, and leaves in a septic-impacted suburban reach were enriched by 4.6‰ relative to upstream samples. Samples from a sewage-impacted urban river averaged 8.0 ± 4.1‰ and reached 22‰ adjacent to publicly owned treatment works (POTW). Another urban river displayed similar values in the absence of POTWs, implicating leaky sewers. Our results demonstrate the capacity of N isotopes from a diverse riparian plant community to inform our spatial understanding of watershed N-cycling perturbations, and illustrate the impact of human activities on N cycling even within protected watersheds.
VideoChef: Efficient Approximation for Streaming Video Processing Pipelines

Many video streaming applications require low-latency processing on resource-constrained devices. To meet the latency and resource constraints, developers must often approximate filter computations. A key challenge to successfully tuning approximations is finding the optimal configuration, which may change across and within the input videos because it is content-dependent. Searching through the entire search space for every frame in the video stream is infeasible, while tuning the pipeline offline, on a set of training videos, yields suboptimal results. We present VIDEOCHEF, a system for approximate optimization of video pipelines. VIDEOCHEF finds the optimal configurations of approximate filters at runtime, by leveraging the previously proposed concept of canary inputs--using small inputs to tune the accuracy of the computations and transferring the approximate configurations to full inputs. VIDEOCHEF is the first system to show that canary inputs can be used for complex streaming applications. The two key innovations of VIDEOCHEF are (1) an accurate error mapping from the approximate processing with downsampled inputs to that with full inputs and (2) a directed search that balances the cost of each search step with the estimated reduction in the run time. We evaluate our approach on 106 videos obtained from YouTube, on a set of 9 video processing pipelines with a total of 10 distinct filters. Our results show significant performance improvement over the baseline and the previous approach that uses canary inputs. We also perform a user study that shows that the videos produced by VIDEOCHEF are often acceptable to human subjects.