Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Auditory Rhythm and Music on Gait Disturbances in Parkinson’s Disease

Gait abnormalities, such as shuffling steps, start hesitation, and freezing, are common and often incapacitating symptoms of Parkinson’s disease (PD) and other parkinsonian disorders. Pharmacological and surgical approaches have only limited efficacy in treating these gait disorders. Rhythmic auditory stimulation (RAS), such as playing marching music and dance therapy, has been shown to be a safe, inexpensive, and an effective method in improving gait in PD patients. However, RAS that adapts to patients’ movements may be more effective than rigid, fixed-tempo RAS used in most studies. In addition to auditory cueing, immersive virtual reality technologies that utilize interactive computer-generated systems through wearable devices are increasingly used for improving brain–body interaction and sensory–motor integration. Using multisensory cues, these therapies may be particularly suitable for the treatment of parkinsonian freezing and other gait disorders. In this review, we examine the affected neurological circuits underlying gait and temporal processing in PD patients and summarize the current studies demonstrating the effects of RAS on improving these gait deficits.
Bidirectional Plasticity of Purkinje Cells Matches Temporal Features of Learning

Many forms of learning require temporally ordered stimuli. In Pavlovian eyeblink conditioning, a conditioned stimulus (CS) must precede the unconditioned stimulus (US) by at least about 100 ms for learning to occur. Conditioned responses are learned and generated by the cerebellum. Recordings from the cerebellar cortex during conditioning have revealed CS-triggered pauses in the firing of Purkinje cells that likely drive the conditioned blinks. The predominant view of the learning mechanism in conditioning is that long-term depression (LTD) at parallel fiber (PF)–Purkinje cell synapses underlies the Purkinje cell pauses. This raises a serious conceptual challenge because LTD is most effectively induced at short CS–US intervals, which do not support acquisition of eyeblinks. To resolve this discrepancy, we recorded Purkinje cells during conditioning with short or long CS–US intervals. Decerebrated ferrets trained with CS–US intervals ≥150 ms reliably developed Purkinje cell pauses, but training with an interval of 50 ms unexpectedly induced increases in CS-evoked spiking. This bidirectional modulation of Purkinje cell activity offers a basis for the requirement of a minimum CS–US interval for conditioning, but we argue that it cannot be fully explained by LTD, even when previous in vitro studies of stimulus-timing-dependent LTD are taken into account.
Vigilance and Sentinels in Global Health Security

ABSTRACT Global health security is increasingly reliant on vigilance to provide early warning of transnational health threats. In theory, this approach requires that sentinels, based in communities most affected by new or reemerging infectious diseases, deliver timely alerts of incipient risk. Medicalizing global safety also implies there are particular forms of insecurity that must be remedied to preempt disease spread. I examine vigilance in the context of spreading drug-resistant malaria in Southeast Asian border zones and argue that to act as sentinels, marginal groups vulnerable to infection must be able to articulate what social and behavioral factors prompt proliferating disease risks.
Reflectivity dispersion characteristics of the composite films on the metal substrate

The paper gives the results of computer simulating reflectivity of a flat structure made of composite material on the basis of Ag, Ni, Al, Cu nanoparticles and a substrate of the same metals within the visible wavelength range. The possibility of broadband optical antireflection of a metal surface using nanoparticles of the same metals by forming in the near surface layer of the metal being made anti-reflecting a composite layer is researched. Within the visible wavelength range the dispersion characteristics of the reflectivity of the composite metal-dielectric layer on a metal substrate have been calculated for different values of the filling factor and the thickness of the composite layer both for the metals having plasmon resonances (Ag, Cu) within the visible range and for the metals plasmon resonances of which do not fall in the visible wavelength range (Al, Ni).
Girls With Childhood ADHD as Adults: Cross-Domain Outcomes by Diagnostic Persistence

Objective: To ascertain adult outcomes in 10 domains reflecting symptomatology (internalizing, externalizing, self-injury, substance use), attainment (education, employment), and impairment (health, social, driving, overall) as a function of both childhood diagnosis of attention-deficit/hyperactivity disorder (ADHD) and persistence of ADHD symptoms across time. Method: We prospectively followed 140 grade-school-aged girls with rigorously diagnosed childhood ADHD and 88 age- and ethnicity-matched comparison girls for 16 years. Outcome measures were obtained via self- and parent-report questionnaires, interviews, and objective tests. Results: Childhood ADHD, whether it remitted or persisted, was a pernicious risk factor for a limited number of poor outcomes, including low educational attainment, unplanned pregnancy, body mass index (BMI), and clinician-rated impairment. Childhood ADHD that persisted over time, whether completely or partially, was associated with a number of additional detrimental outcomes in the externalizing, internalizing, self-injury, occupational, social, and overall impairment domains. Finally, in this all-female sample, ADHD was not associated with objective measures of employment, substance use, or driving outcomes. Conclusions: We discuss the considerable impairments accruing from both childhood-limited and adult-persisting ADHD, with major implications for the health and well-being of females with this neurodevelopmental disorder.
Relaxation dynamics in the gapped XXZ spin-1/2 chain

We study the dynamics of a quench-prepared domain wall state released into a system whose unitary time evolution is dictated by the Hamiltonian of the Heisenberg spin-1/2 gapped antiferromagnetic chain. Using exact wavefunctions and their overlaps with the domain wall state allows us to describe the release dynamics to high accuracy, up to the long-time limit, for finite as well as infinite systems. The results for the infinite system allow us to rigorously prove that the system in the gapped regime (Δ>1) cannot thermalize in the strict sense.
Instrumental Mechanoreceptoric Palpation in Gastrointestinal Surgery

Background and Aims Small gastric or colorectal tumours can be visually undetectable during laparoscopic surgeries, and available methods still do not provide a 100% localisation rate. Thus, new methods for further improvements in tumour localisation are highly desirable. In this study, we evaluated the usage of the Medical Tactile Endosurgical Complex (MTEC) in gastrointestinal surgery for localisation of tumours. The MTEC provides the possibility of instrumental mechanoreceptoric palpation, which serves as an analogue of conventional manual palpation. Methods Ninety-six elective surgeries were performed, including 48 open surgeries, 43 laparoscopies, and 5 robot-assisted surgeries. The 20 mm version of the MTEC tactile mechanoreceptor was used in open surgeries, and the 10 mm version in laparoscopic and robot-assisted surgeries. Results The mean time of instrumental mechanoreceptoric palpation was 3 minutes 12 seconds for open surgeries, which constituted the early stage of the learning curve, and 3 minutes 34 seconds for laparoscopic surgeries. No side effects or postoperative complications related to instrumental mechanoreceptoric palpation were observed, and this procedure provided data sufficient for tumour localisation in more than 95% of cases. Conclusion Instrumental mechanoreceptoric palpation performed using MTEC is a simple, safe, and reliable method for tumour localisation in gastrointestinal laparoscopic surgery.
New perspectives on the conservative management of osteoradionecrosis of the mandible: A literature review

Over the last decades, several therapeutic options were considered in the treatment of the osteoradionecrosis (ORN) of the mandible, including supportive measures, ultrasound therapy, corticosteroids, hyperbaric oxygen, surgical resection with reconstruction, and, more recently, drugs capable of reversing the fibroatrophic process. Once established, the ORN does not spontaneously disappear and a standard treatment has not yet been defined. The clear clinical effectiveness of hyperbaric oxygen therapy (HBOT) varies according to the literature and there are some economic/logistic issues to be considered; the triplet tocopherol/pentoxifylline/clodronate demands greater evidence from randomized clinical trials and also resilience from the patient, given the long treatment duration and its possible side effects. Controversy around the ideal treatment of the initial stage ORN of the mandible persists. More rigorous randomized prospective trials are essential. The purpose of this article was to review the relevant literature on the physiopathology of ORN of the mandible and discuss the new perspectives of its conservative treatment. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1708–1716, 2016
Ruptured secondary abdominal pregnancy after primary laparoscopic treatment for tubal pregnancy

Introduction: Most secondary abdominal pregnancies happen after spontaneous abortion of tubal pregnancy or ruptured intrauterine pregnancy. However, we presented a case of ruptured secondary abdominal pregnancy after primary laparoscopic treatment of tubal pregnancy. Case report: The ectopic pregnant lesion in the affected tube was thoroughly removed in the primary laparoscopy, and nothing abnormal was detected in abdomen or pelvis. Beta human chorionic gonadotropin levels dropped significantly after surgery, but the patient came back again for severe abdominal pain with beta human chorionic gonadotropin increasing, and free peritoneal fluid in the pouch of Douglas was detected at ultrasonography. The secondary laparoscopy was done according to the intraperitoneal hemorrhage and unstable vital signs. The secondary pregnancy was found ruptured in the splenic flexure of the colon. Although several cases of secondary abdominal pregnancies were reported in the literature, herein we describe a case secondary to the salpingotomy of the primary tubal pregnancy. Conclusion: After surgery for ectopic pregnancy, the patient's serum beta human chorionic gonadotropin levels should be closely followed until negative. When persistent ectopic pregnancy was suspected after surgery, physicians should keep in mind a rare possibility of secondary abdominal pregnancy.
On the folding of a structurally complex protein to its metastable active state

Significance Proteins usually fold to their thermodynamically stable states. The serine protease inhibitors (serpins) modulate several biological processes such as blood clotting and inflammation. These proteins are unusual because their functionally active state, and consequently the state that they need to fold to and populate, is significantly less stable than an alternate latent conformation. This metastability facilitates conformational conversion to the inactive state which irreversibly traps the protease. However, it also makes the serpins prone to disease-linked polymerization. Here, we investigate the structural basis for this conformational choice using folding simulations of the serpin, α1-antitrypsin. We find that the structure of the protease-binding reactive center loop is determined early during folding and gates kinetic accessibility to the latent conformation. For successful protease inhibition, the reactive center loop (RCL) of the two-domain serine protease inhibitor, α1-antitrypsin (α1-AT), needs to remain exposed in a metastable active conformation. The α1-AT RCL is sequestered in a β-sheet in the stable latent conformation. Thus, to be functional, α1-AT must always fold to a metastable conformation while avoiding folding to a stable conformation. We explore the structural basis of this choice using folding simulations of coarse-grained structure-based models of the two α1-AT conformations. Our simulations capture the key features of folding experiments performed on both conformations. The simulations also show that the free energy barrier to fold to the latent conformation is much larger than the barrier to fold to the active conformation. An entropically stabilized on-pathway intermediate lowers the barrier for folding to the active conformation. In this intermediate, the RCL is in an exposed configuration, and only one of the two α1-AT domains is folded. In contrast, early conversion of the RCL into a β-strand increases the coupling between the two α1-AT domains in the transition state and creates a larger barrier for folding to the latent conformation. Thus, unlike what happens in several proteins, where separate regions promote folding and function, the structure of the RCL, formed early during folding, determines both the conformational and the functional fate of α1-AT. Further, the short 12-residue RCL modulates the free energy barrier and the folding cooperativity of the large 370-residue α1-AT. Finally, we suggest experiments to test the predicted folding mechanism for the latent state.
Motion controller design for a biomimetic robotic fish

This paper investigates motion control of a biomimetic robotic fish through a general internal model (GIM)-based learning approach. By virtue of the universal function approximation ability and the temporal/spatial seal-abilities of the GIM, the learning approach is able to generate the same or similar fish swimming motion patterns. Through experimental analysis, we also find out that motion of the robot can be controlled by simply tuning two GIM parameters. To achieve desired motion, based on tuning the GIM parameters, two model-free feedback control schemes are designed. A proportional-integral-derivative (PID) controller and a Fuzzy logic controller (FLC) are employed to control the speed and the turning diameter of the robot, respectively. Finally, experiment results verify the effectiveness of the motion control approach.
Taming the Instruction Bandwidth of Quantum Computers via Hardware-Managed Error Correction

A quantum computer consists of quantum bits (qubits) and a control processor that acts as an interface between the programmer and the qubits. As qubits are very sensitive to noise, they rely on continuous error correction to maintain the correct state. Current proposals rely on software-managed error correction and require large instruction bandwidth, which must scale in proportion to the number of qubits. While such a design may be reasonable for small-scale quantum computers, we show that instruction bandwidth tends to become a critical bottleneck for scaling quantum computers. In this paper, we show that 99.999% of the instructions in the instruction stream of a typical quantum workload stem from error correction. Using this observation, we propose QuEST (Quantum Error-Correction Substrate), an architecture that delegates the task of quantum error correction to the hardware. QuEST uses a dedicated programmable micro-coded engine to continuously replay the instruction stream associated with error correction. The instruction bandwidth requirement of QuEST scales in proportion to the number of active qubits (typically < < 0.1%) rather than the total number of qubits. We analyze the effectiveness of QuEST with area and thermal constraints and propose a scalable microarchitecture using typical Quantum Error Correction Code (QECC) execution patterns. Our evaluations show that QuEST reduces instruction bandwidth demand of several key workloads by ftve orders of magnitude while ensuring deterministic instruction delivery. Apart from error correction, we also observe a large instruction bandwidth requirement for fault tolerant quantum instructions (magic state distillation). We extend QuEST to manage these instructions in hardware and provide additional reduction in bandwidth. With QuEST, we reduce the total instruction bandwidth by eight orders of magnitude. CCS CONCEPTS • Computer systems organization → Quantum computing;
Surface Frictional Resistance of Fabrics Woven from Filament Yarns

The differences in frictional forces acting between fabrics woven from filament yarns are dependent on the morphology of the fabrics and the rubbing direction. When one fabric is moved across a second stationary fabric and the projecting yarn waves of one of the fabrics is rubbed perpendicular to the yarn axes orientation, the Howell's characteristics of frictional resistance for the fabric and yarn have similar values.
The potential of AR-V7 as a therapeutic target

ABSTRACT Introduction: The androgen receptor variant AR-V7 is gaining attention as a potential predictive marker for as well as one of the resistance mechanisms to the most current anti-androgen receptor (AR) therapies in castration-resistant prostate cancer (CRPC). Accordingly, development of next-generation drugs that directly or indirectly target AR-V7 signaling is urgently needed. Areas covered: We review proposed mechanisms of drug resistance in relation to AR-V7 status, the mechanisms of generation of AR-V7, and its transcriptome, cistrome, and interactome. Pharmacological agents that interfere with these processes are being developed to counteract pan AR and AR-V7-specific signaling. Also, we address the current status of the preclinical and clinical studies targeting AR-V7 signaling. Expert opinion: AR-V7 is considered a true therapeutic target, however, it remains to be determined if AR-V7 is a principal driver or merely a bystander requiring heterodimerization with co-expressed full-length AR or other variants to drive CRPC progression. While untangling AR-V7 biology, multiple strategies are being developed to counteract drug resistance, including selective blockade of AR-V7 signaling as well as inhibition of pan-AR signaling. Ideally anti-AR therapies will be combined with agents preventing activation and enrichment of AR negative tumor cells that are otherwise depressed by AR activity axis.
Sketch Algorithms for Estimating Point Queries in NLP

Many NLP tasks rely on accurate statistics from large corpora. Tracking complete statistics is memory intensive, so recent work has proposed using compact approximate "sketches" of frequency distributions. We describe 10 sketch methods, including existing and novel variants. We compare and study the errors (over-estimation and underestimation) made by the sketches. We evaluate several sketches on three important NLP problems. Our experiments show that one sketch performs best for all the three tasks.
Multiscale thermal models of nanostructured devices

Modern electronic devices comes from a double evolution. On one hand the miniaturization techniques have reduced the traditional devices to the microscopical scales. Such approach is called top-down. On the other hand, the researching in multidisciplinary fields has created novel devices, natively nanostructured. Carbon nanotubes, nanowire and quantum dots are examples of such devices, designed following an approach called bottom-up. These two evolutive lines are converging in strongly heterogeneous devices, whose features are due to both micro and macroscopical elements. Hence, there is the need of CADs to employ models acting at different scales in the same simulation. Such a model is called multiscale model. Multiscale models involve several fields, ranging from fluid dynamics to electronic transport. In this work we deal with heating and heat dissipation in a multiscale domain. In particular, we investigate the Joule’s effect at the macro, meso and nanoscales. We start to compute the self-heating effect by modeling the electron-phonon interaction at the Born Approximation level. The heating of a molecule under bias is computed by means of an effective temperature. The transport of heat and charge is calculated within the Non Equilibrium Green’s Function (NEGF) approach whereas the ground state is obtained within the Density Functional Tight Binding (DFTB) method. We apply the method on different molecular systems. The Boltzmann Tranport Equation (BTE) for phonons is used as mesoscale model of heat dissipation. At the macroscale, the temperature map is obtained at the diffusive level with the Fourier model. Both the BTE based model and the Fourier model have been implemented within the Finite Element Method (FEM). We perform a Fourier/BTE multiscale simulation of a GaN quantum dot embedded in a AlGaN nanocolumn. All the three models have been implemented in TiberCAD, the multiscale simulator of optoelectronic devices developed by the OLAB research group at the University of Rome “Tor Vergata”.
CRYSTALS-Dilithium: A Lattice-Based Digital Signature Scheme

In this paper, we present the lattice-based signature scheme Dilithium, which is a component of the CRYSTALS (Cryptographic Suite for Algebraic Lattices) suite that was submitted to NIST’s call for post-quantum cryptographic standards. The design of the scheme avoids all uses of discrete Gaussian sampling and is easily implementable in constant-time. For the same security levels, our scheme has a public key that is 2.5X smaller than the previously most efficient lattice-based schemes that did not use Gaussians, while having essentially the same signature size. In addition to the new design, we significantly improve the running time of the main component of many lattice-based constructions – the number theoretic transform. Our AVX2-based implementation results in a speed-up of roughly a factor of 2 over the previously best algorithms that appear in the literature. The techniques for obtaining this speed-up also have applications to other lattice-based schemes.
Facing Realism in Spontaneous Emotion Recognition from Speech: Feature Enhancement by Autoencoder with LSTM Neural Networks

During the last decade, speech emotion recognition technology has matured well enough to be used in some real-life scenarios. However, these scenarios require an almost silent environment to not compromise the performance of the system. Emotion recognition technology from speech thus needs to evolve and face more challenging conditions, such as environmental additive and convolutional noises, in order to broaden its applicability to real-life conditions. This contribution evaluates the impact of a front-end feature enhancement method based on an autoencoder with long short-term memory neural networks, for robust emotion recognition from speech. Support Vector Regression is then used as a back-end for time- and value-continuous emotion prediction from enhanced features. We perform extensive evaluations on both non-stationary additive noise and convolutional noise, on a database of spontaneous and natural emotions. Results show that the proposed method significantly outperforms a system trained on raw features, for both arousal and valence dimensions, while having almost no degradation when applied to clean speech.