Rare Gain-of-Function KCND3 Variant Associated with Cerebellar Ataxia,Parkinsonism, Cognitive Dysfunction,and Brain Iron Accumulation

Loss-of-function mutations in the K_V4.3 channel-encoding KCND3 gene are linked to neurodegenerative cerebellar ataxia. Patients suffering from neurodegeneration associated with iron deposition may also present with cerebellar ataxia. The mechanism underlying brain iron accumulation remains unclear. Here, we aim to ascertain the potential pathogenic role of KCND3 variant in iron accumulation-related cerebellar ataxia. We presented a patient with slowly progressive cerebellar ataxia, parkinsonism, cognitive impairment, and iron accumulation in the basal ganglia and the cerebellum. Whole exome sequencing analyses identified in the patient a heterozygous KCND3 c.1256G>A (p.R419H) variant predicted to be disease-causing by multiple bioinformatic analyses. In vitro biochemical and immunofluorescence examinations revealed that, compared to the human K_V4.3 wild-type channel, the p.R419H variant exhibited normal protein abundance and subcellular localization pattern. Electrophysiological investigation, however, demonstrated that the K_V4.3 p.R419H variant was associated with a dominant increase in potassium current amplitudes, as well as notable changes in voltage-dependent gating properties leading to enhanced potassium window current. These observations indicate that, in direct contrast with the loss-of-function KCND3 mutations previously reported in cerebellar ataxia patients, we identified a rare gain-of-function KCND3 variant that may expand the clinical and molecular spectra of neurodegenerative cerebellar disorders associated with brain iron accumulation.     

Numerical method for the analysis of queuing models with priority jumps1

An algorithmic approach to study queuing models with common finite and infinite buffer and jump priorities is developed. It is assumed that upon arrival of a low-priority call, one call of such kind can be transferred with some probability to the end of the queue of high-priority calls. The transition probability depends on the state of the queue of heterogeneous calls. The algorithms are proposed to calculate the quality of service metrics of such queuing models.     

A deep bidirectional LSTM approach for video-realistic talking head

This paper proposes a deep bidirectional long short-term memory approach in modeling the long contextual, nonlinear mapping between audio and visual streams for video-realistic talking head. In training stage, an audio-visual stereo database is firstly recorded as a subject talking to a camera. The audio streams are converted into acoustic feature, i.e. Mel-Frequency Cepstrum Coefficients (MFCCs), and their textual labels are also extracted. The visual streams, in particular, the lower face region, are compactly represented by active appearance model (AAM) parameters by which the shape and texture variations can be jointly modeled. Given pairs of the audio and visual parameter sequence, a DBLSTM model is trained to learn the sequence mapping from audio to visual space. For any unseen speech audio, whether it is original recorded or synthesized by text-to-speech (TTS), the trained DBLSTM model can predict a convincing AAM parameter trajectory for the lower face animation. To further improve the realism of the proposed talking head, the trajectory tiling method is adopted to use the DBLSTM predicted AAM trajectory as a guide to select a smooth real sample image sequence from the recorded database. We then stitch the selected lower face image sequence back to a background face video of the same subject, resulting in a video-realistic talking head. Experimental results show that the proposed DBLSTM approach outperforms the existing HMM-based approach in both objective and subjective evaluations.     

A Constrained Line Search Optimization Method for Discriminative Training of HMMs

In this paper, we propose a novel optimization algorithm called constrained line search (CLS) for discriminative training (DT) of Gaussian mixture continuous density hidden Markov model (CDHMM) in speech recognition. The CLS method is formulated under a general framework for optimizing any discriminative objective functions including maximum mutual information (MMI), minimum classification error (MCE), minimum phone error (MPE)/minimum word error (MWE), etc. In this method, discriminative training of HMM is first cast as a constrained optimization problem, where Kullback-Leibler divergence (KLD) between models is explicitly imposed as a constraint during optimization. Based upon the idea of line search, we show that a simple formula of HMM parameters can be found by constraining the KLD between HMM of two successive iterations in an quadratic form. The proposed CLS method can be applied to optimize all model parameters in Gaussian mixture CDHMMs, including means, covariances, and mixture weights. We have investigated the proposed CLS approach on several benchmark speech recognition databases, including TIDIGITS, Resource Management (RM), and Switchboard. Experimental results show that the new CLS optimization method consistently outperforms the conventional EBW method in both recognition performance and convergence behavior.     

Novel high-speed induction motor for a commercial centrifugalcompressor

This paper describes the electrical, mechanical and metallurgical design, construction, and testing of a novel low-cost high-speed high-efficiency induction motor to drive a new type of small centrifugal compressor in industrial cooling applications. The 28-shaft-hp 50-kr/min motor features a unique laminated rotor with a multifunction high-strength copper-alloy cage brazed with a novel process. Relatively thin high-silicon steel laminations were used to achieve low losses and high mechanical strength at low cost, Different heat treatments for the stator and rotor laminations were used to optimize the mechanical and magnetic properties, The preprototype motors achieved about 94% (electromagnetic) efficiency at the rated point, including inverter harmonics, while meeting cost (less than one-tenth of aerospace practice) and produceability goals     

Broadcast scheduling in packet radio networks using mixed tabu-greedy algorithm

A two-step algorithm to solve the broadcast scheduling problem is presented. The first step employs finding a solution that has a transmission time slot for each station, while the second step attempts to maximise the throughput. Numerical examples that demonstrate the algorithm outperforms existing ones in terms of channel utilisation and packet delay are presented.     

Stochastic response sensitivity of secondary systems to primary structural uncertainties

Response characteristics of secondary systems anchored or attached to a primary structure can be strongly dependent upon parameter values assumed for the secondary and primary systems. For design and performance evaluations, it is thus of practical interest to develop sensitivity factors relating response behavior of a secondary system to structural parameter variations.

In this paper, the use of spectral moments as peak response sensitivity factors is proposed when the primary-secondary system is subjected to random loading. It is shown that they provide a consistent and quantitative measure of relative importance of parameter uncertainties in the design and performance evaluation of secondary systems. These results are particularly useful to designers in order to determine the desired dynamic characteristics of secondary systems, and to determine the degree of design response spectrum broadening needed.     

Collision-Free and Low-Latency Scheduling Algorithm for Broadcast Operation in Wireless Ad Hoc Networks

It is desirable for broadcast operation in wireless ad hoc network to prevent collision and achieve low latency at the same time. In this letter, we propose a greedy broadcast scheduling algorithm based on the graph theory of Maximum Weight Independent Set (MWIS) problem. During each broadcast wave cycle, MWIS is able to find the optimal selection of forwarders so that maximum number of untouched nodes is covered without incurring collision. Numerical results show that this algorithm could produce better performance results than recent 2-step approach.     

Therapeutic Ultrasound Halts Progression of Chronic Kidney Disease In Vivo via the Regulation of Markers Associated with Renal Epithelial–Mesenchymal Transition and Senescence

Low-intensity pulsed ultrasound (LIPUS), a therapeutic type of ultrasound, is known to enhance bone fracture repair processes and help some tissues to heal. Here, we investigated the therapeutic potential of LIPUS for the treatment of chronic kidney disease (CKD) in two CKD mouse models. CKD mice were induced using both unilateral renal ischemia/reperfusion injury (IRI) with nephrectomy and adenine administration. The left kidneys of the CKD mice were treated using LIPUS with the parameters of 3 MHz, 100 mW/cm², and 20 min/day, based on the preliminary experiments. The mice were euthanized 14 days after IRI or 28 days after the end of adenine administration. LIPUS treatment effectively alleviated the decreases in the body weight and albumin/globulin ratio and the increases in the serum renal functional markers, fibroblast growth factor-23, renal pathological changes, and renal fibrosis in the CKD mice. The parameters for epithelial–mesenchymal transition (EMT), senescence-related signal induction, and the inhibition of α-Klotho and endogenous antioxidant enzyme protein expression in the kidneys of the CKD mice were also significantly alleviated by LIPUS. These results suggest that LIPUS treatment reduces CKD progression through the inhibition of EMT and senescence-related signals. The application of LIPUS may be an alternative non-invasive therapeutic intervention for CKD therapy.     

Amniotic fluid alpha-fetoprotein levels during midtrimester of trisomy pregnancies

To investigate the association between low amniotic fluid alpha-fetoprotein (AFP) and trisomy pregnancies, we retrospectively reviewed 26 trisomy pregnancies including 18 fetuses with Down's syndrome and eight with trisomy 18. The amniotic fluid AFP median values of Down's syndrome, trisomy 18, and the study groups were 0.73 MoM, 1.15 MoM, and 0.85 MoM, respectively. There was a significant difference between the mean values of the Down's syndrome-affected fetuses (0.78 +/- 0.29 MoM) and that of the control group (p < 0.001), whereas no such difference was found for that of trisomy 18-affected fetuses (1.16 +/- 0.38 MoM). Only three patients in the study group (3/26, 11.5%) had an amniotic fluid AFP value below 0.5 MoM, including the two cases of Down's syndrome (2/18, 11.1%) and one case of trisomy 18 (1/8, 12.5%). Most of the values for the trisomy pregnancies were within the normal range, thereby precluding the possibility of using this measurement as an alternative to fetal karyotyping as a screening test for Down's syndrome or other trisomy pregnancies.