Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in the Demand for Skilled Labor within Japan's Manufacturing Sector:Effects of Skill-Biased Technological Change and Globalization

This paper examines the demand shift toward workers who are university graduates in terms of skill-biased technological change (SBTC) and globalization, both of which utilize relatively more workers with specific skills. According to the results of our empirical study, which used the major groups of Japan's manufacturing panel data from the 1988-2003, it is clear that the increase in the relative demand for university graduates is closely related to the R&D expenditures ratio (SBTC) and the import ratio from the East Asian countries or the foreign production ratio (globalization). This suggests that there has been a demand shift toward highly educated workers in Japan's manufacturing sector due to both SBTC and globalization.
Chip-Scale Continuously Tunable Optical Orbital Angular Momentum Generator

Light carrying orbital angular momentum (OAM) has potential to impact a wide variety of applications ranging from optical communications to quantum information and optical forces for the excitation and manipulation of atoms, molecules, and micro-particles. The unique advantage of utilizing OAM in these applications relies, to a large extent, on the use of multiple different OAM states. Therefore, it is desirable to have a device that is able to gen- erate light with freely adjustable OAM states in an integrated form for large- scale integration. We propose and demonstrate a compact silicon photonic integrated circuit to generate a free-space optical beam with OAM state con- tinuously tuned from a single electrical input signal, realizing both integer and non-integer OAM states. The compactness and flexibility of the device and its compatibility with complementary metal-oxide-semiconductor (CMOS) pro- cessing hold promise for integration with other silicon photonic components for wide-ranging applications.
A study of rank-constrained multilingual DNNS for low-resource ASR

Multilingual Deep Neural Networks (DNNs) have been successfully used to exploit out-of-language data to improve under-resourced ASR. In this paper, we improve on a multilingual DNN by utilizing low-rank factorization (LRF) of weight matrices via Singular Value Decomposition (SVD) to sparsify a multilingual DNN. LRF was previously used for monolingual DNNs, yielding large computational savings without a significant loss in recognition accuracy. In this work, we show that properly applying LRF on a multilingual DNN can improve recognition accuracy for multiple low-resource ASR configurations. First, only the final weight layer is factorized. Since the output weight layer needs to be trained with language specific data, reducing the number of parameters is beneficial for under-resourced languages. It is common in multilingual DNN speech recognition, to further adapt the full neural network through retraining of the multilingual DNN on target language data. Again we observe that in low-resource situations, this adaptation can bring significant improvement if LRF is applied to all hidden layers. We demonstrate the positive effect of LRF in two very different scenarios: one is a phone recognition task for two related languages and the other is a word recognition task using five different languages from the GlobalPhone dataset.
Relaying Schemes for Improving Coverage and Capacity In cellular system with Selectable User Equipment

— Relays are a promising solution being currently considered to enhance wireless communications and the performance of wireless networks. In addition, it is a promising solution to the challengingly high data rate requirements of future wireless cellular systems. In this paper we investigate the use of relays for cost-effective throughput enhancement and coverage extension. We analyze the performance of several emerging half duplex relay strategies. The strategies under investigating will be demonstrated under two cases, one with direct reception at the user equipment (UE) from the relay station (RS) and another one with UE ability to select to receive from base station (BS) or RS. The performance of each strategy in terms of capacity, coverage and performance is discussed as a function of cell radius, relay station location, relay station transmitted power and users' locations. The investigated strategies are One-Way, Two-Way and Shared Relay.
In a Model of Batten Disease, Palmitoyl Protein Thioesterase-1 Deficiency Is Associated with Brown Adipose Tissue and Thermoregulation Abnormalities

Infantile neuronal ceroid lipofuscinosis (INCL) is a fatal neurodegenerative disorder caused by a deficiency of palmitoyl-protein thioesterase-1 (PPT1). We have previously shown that children with INCL have increased risk of hypothermia during anesthesia and that PPT1-deficiency in mice is associated with disruption of adaptive energy metabolism, downregulation of peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), and mitochondrial dysfunction. Here we hypothesized that Ppt1-knockout mice, a well-studied model of INCL that shows many of the neurologic manifestations of the disease, would recapitulate the thermoregulation impairment observed in children with INCL. We also hypothesized that when exposed to cold, Ppt1-knockout mice would be unable to maintain body temperature as in mice thermogenesis requires upregulation of Pgc-1α and uncoupling protein 1 (Ucp-1) in brown adipose tissue. We found that the Ppt1-KO mice had lower basal body temperature as they aged and developed hypothermia during cold exposure. Surprisingly, this inability to maintain body temperature during cold exposure in Ppt1-KO mice was associated with an adequate upregulation of Pgc-1α and Ucp-1 but with lower levels of sympathetic neurotransmitters in brown adipose tissue. In addition, during baseline conditions, brown adipose tissue of Ppt1-KO mice had less vacuolization (lipid droplets) compared to wild-type animals. After cold stress, wild-type animals had significant decreases whereas Ppt1-KO had insignificant changes in lipid droplets compared with baseline measurements, thus suggesting that Ppt1-KO had less lipolysis in response to cold stress. These results uncover a previously unknown phenotype associated with PPT1 deficiency, that of altered thermoregulation, which is associated with impaired lipolysis and neurotransmitter release to brown adipose tissue during cold exposure. These findings suggest that INCL should be added to the list of neurodegenerative diseases that are linked to alterations in peripheral metabolic processes. In addition, extrapolating these findings clinically, impaired thermoregulation and hypothermia are potential risks in patients with INCL.
Improved Blind Channel Identiication Using a Parametric Approach Edics: Cl1.2.6 Wireless Systems

| In wireless communications, the channel has a known manifold structure due to the sensor array response, pulse-shaping function, and sampling phase. By exploiting this information, the method presented here achieves improved performance over unstructured blind channel estimation schemes. The approach is subspace-based, and can take advantage of multiple channel estimates if available, e.g., from diierent time slots in TDMA systems. Its performance is numerically simulated and compared against the original unstructured channel subspace method.
Distributed power control with double-layer Stackelberg game and utility learning in cooperative relay networks

We investigate the power control problem for multi-user and multi-relay cooperative relay networks. In order to improve the efficiency of power control in wireless networks with self-interested nodes, a double-layer Stackelberg game model with utility learning is initially proposed to jointly allocate the power consumption of both users and relays. Competition among relays and competition among users are modeled as a non-cooperative game respectively, strategies of relays are price. Given specific prices, the users compete with each other in resources. In order to reduce the complexity and communication overhead of the power control, a game-theoretic distributed utility learning algorithm is also proposed to update the game policies of both users and relays based on the local channel state information. Simulation results demonstrate the efficiency of the proposed power control algorithm.
Quality risk aversion, conjectures, and new product diffusion

In this paper, we provide a generalization of the standard models of the diffusion of a new product. Consumers are heterogeneous and risk averse, and the firm is uncertain about the demand curve: both learn from past observations. The attitude towards risk has important effects with regard to the diffusion pattern. In our model, downward-biased signals to consumers can prevent the success of the product, even if its objective quality is high: a “lock-in” result. We show, in addition, that the standard logistic pattern can be derived from the model. Finally, we discuss the steady states of the learning dynamics, with regard to the multiplicity and the local stability of equilibria, and to their welfare properties.
Bayesian analysis of ordered categorical data from industrial experiments

Data from industrial experiments often involve an ordered categorical response, such as a qualitative rating. Analysis of variance-based analyses may be inappropriate for such data, suggesting the use of generalized linear models (GLM's). When the data are observed from a fractionated experiment, likelihood-based GLM estimates may be infinite, especially when factors have large effects. These difficulties are overcome with a Bayesian GLM, which is implemented via the Gibbs sampling algorithm. Techniques for modeling data and for subsequently using the identified model to optimize the process are outlined. An important advantage in the optimization stage is that uncertainty in the parameter estimates is accounted for in the model. For robust design experiments, the Bayesian approach easily incorporates the variability of the noise factors using the response modeling approach. This approach and its techniques are used to analyze two data sets, one of which arises from a robust design experiment.
Meglumine Exerts Protective Effects against Features of Metabolic Syndrome and Type II Diabetes

Metabolic syndrome, diabetes and diabetes complications pose a growing medical challenge worldwide, accentuating the need of safe and effective strategies for their clinical management. Here we present preclinical evidence that the sorbitol derivative meglumine (N-methyl-D-glucamine) can safely protect against several features of metabolic syndrome and diabetes, as well as elicit enhancement in muscle stamina. Meglumine is a compound routinely used as an approved excipient to improve drug absorption that has not been ascribed any direct biological effects in vivo. Normal mice (SV129) administered 18 mM meglumine orally for six weeks did not display any gastrointestinal or other observable adverse effects, but had a marked effect on enhancing muscle stamina and at longer times in limiting weight gain. In the established KK.Cg-Ay/J model of non-insulin dependent diabetes, oral administration of meglumine significantly improved glycemic control and significantly lowered levels of plasma and liver triglycerides. Compared to untreated control animals, meglumine reduced apparent diabetic nephropathy. Sorbitol can improve blood glucose uptake by liver and muscle in a manner associated with upregulation of the AMPK-related enzyme SNARK, but with undesirable gastrointestinal side effects not seen with meglumine. In murine myoblasts, we found that meglumine increased steady-state SNARK levels in a dose-dependent manner more potently than sorbitol. Taken together, these findings provide support for the clinical evaluation of meglumine as a low-cost, safe supplement offering the potential to improve muscle function, limit metabolic syndrome and reduce diabetic complications.
Private Top-κ Aggregation Protocols ?

In this paper, we revisit the private top-κ data aggregation problem. First we formally define the problem’s security requirements as both data and user privacy goals. To achieve both goals, and to strike a balance between efficiency and functionality, we devise a novel cryptographic construction that comes in two schemes; a fully decentralized simple construction and its practical and semi-decentralized variant. Both schemes are provably secure in the semi-honest model. We analyze the computational and communication complexities of our construction, and show that it is much more efficient than the existing protocols in the literature.
The Information Content of Pore Fluid δ18O and [Cl−]

AbstractPaleoceanographic proxies indicate that the ocean state during the Last Glacial Maximum (LGM) differed from the modern ocean state. Depth profiles of ocean sediment pore fluid δ18O and [Cl−] have been used to reconstruct the δ18O and salinity at the LGM. Here, it is investigated whether pore fluid profiles can constrain ocean δ18O and salinity at other times and, simultaneously, their ability to constrain the LGM δ18O and salinity. An inverse framework is developed that relies on Bayesian parameter estimation, thus allowing formal separation of prior assumptions from the information in observations. Synthetic problems are used to explore the information about past ocean tracers that can be recovered from pore fluid profiles. It is concluded that prior knowledge of deep ocean mixing time scales is essential to an accurate inverse estimate of LGM ocean salinity and δ18O from modern pore fluid profiles. The most recent 10 000 years of ocean salinity and δ18O and the error in their estimates are bette.
FETAL HEART MONITOR

This research work proposes an improved algorithm or slash procedure for extracting the fetal heart rate from abdominal ECG recordings of a pregnant woman. The basic goal of this project is to detect the fetal R-R intervals as well as fetal heart rate from abdominal non-invasive records. The database of ECG recordings has been taken from physionet (www.physionet.org). This database contains a series of 55 multichannel abdominal non-invasive fetal electrocardiogram (FECG) recordings, taken from a single subject between 21 to 40 weeks of pregnancy. The records have variable durations, and were taken weekly.All data record is in . edf format( European Data Format ). The various noises can be removed from the abdominal signal by using various filtering methods. The maternal QRS segment is obtained and subtracted from the abdominal ECG signal. To evaluate the fetal's R peak, the fetal's QRS points have to obtain. The application of the algorithm to all the abdominal channels will probably allow improving the obtained results.
Topology and Organization of the Salmonella typhimurium Type III Secretion Needle Complex Components

The correct organization of single subunits of multi-protein machines in a three dimensional context is critical for their functionality. Type III secretion systems (T3SS) are molecular machines with the capacity to deliver bacterial effector proteins into host cells and are fundamental for the biology of many pathogenic or symbiotic bacteria. A central component of T3SSs is the needle complex, a multiprotein structure that mediates the passage of effector proteins through the bacterial envelope. We have used cryo electron microscopy combined with bacterial genetics, site-specific labeling, mutational analysis, chemical derivatization and high-resolution mass spectrometry to generate an experimentally validated topographic map of a Salmonella typhimurium T3SS needle complex. This study provides insights into the organization of this evolutionary highly conserved nanomachinery and is the basis for further functional analysis.
Imaging of behind the wall targets using wideband beamforming with compressive sensing

Through-the-wall radar imaging (TWRI) is a versatile application which demands the collection and processing a large number of data, both along the spatial and frequency dimensions. Compressive sensing (CS) is an attractive approach for reducing the number of data samples, without a significant degradation of the original image that is generated using the full array aperture and frequency band. In this paper, we apply CS technique to TWRI using well known Fourier-like matrices. The proposed method applies CS independently to the data samples of the radar returns of each antenna location. It then incorporates the results into the delay-and-sum beam-forming to provide a through-the-wall radar image. Simulation results show that the proposed method can provide a high-quality radar image using less than 20% of the data samples.
Multilineage Potential Research of Bovine Amniotic Fluid Mesenchymal Stem Cells

The use of amnion and amniotic fluid (AF) are abundant sources of mesenchymal stem cells (MSCs) that can be harvested at low cost and do not pose ethical conflicts. In human and veterinary research, stem cells derived from these tissues are promising candidates for disease treatment, specifically for their plasticity, their reduced immunogenicity, and high anti-inflammatory potential. This work aimed to obtain and characterize bovine amniotic fluid mesenchymal stem cells (AFMSC). The bovine AF from the amniotic cavity of pregnant gilts in the early stages of gestation (3- and 4-m-old bovine embryos) was collected. AFMSCs exhibit a fibroblastic-like morphology only starting from the fourth passage, being heterogeneous during the primary culture. Immunofluorescence results showed that AFMSCs were positive for β-integrin, CD44, CD73 and CD166, but negative for CD34, CD45. Meanwhile, AFMSCs expressed ES cell markers, such as Oct4, and when appropriately induced, are capable of differentiating into ectodermal and mesodermal lineages. This study reinforces the emerging importance of these cells as ideal tools in veterinary medicine; future studies aimed at a deeper evaluation of their immunological properties will allow a better understanding of their role in cellular therapy.
Wavelet-based lossy-to-lossless medical image compression using dynamic VQ and SPIHT coding

As the coming era of digitized medical information, a close-at-hand challenge to deal with is the storage and transmission requirement of enormous data, including medical images. Compression is one of the indispensable techniques to solve this problem. In this work, we propose a dynamic vector quantization (DVQ) scheme with distortion-constrained codebook replenishment (DCCR) mechanism in wavelet domain. In the DVQ-DCCR mechanism, a novel tree-structure vector and the well-known SPIHT technique are combined to provide excellent coding performance in terms of compression ratio and peak signal-to-noise ratio for lossy compression. For the lossless compression in similar scheme, we replace traditional 9/7 wavelet filters by 5/3 filters and implement the wavelet transform in the lifting structure. Furthermore, a detection strategy is proposed to stop the SPIHT coding for less significant bit planes, where SPIHT begins to lose its coding efficiency. Experimental results show that the proposed algorithm is supe.
Learning and Reproduction of Gestures by Imitation

We presented and evaluated an approach based on HMM, GMR, and dynamical systems to allow robots to acquire new skills by imitation. Using HMM allowed us to get rid of the explicit time dependency that was considered in our previous work [12], by encapsulating precedence information within the statistical representation. In the context of separated learning and reproduction processes, this novel formulation was systematically evaluated with respect to our previous approach, LWR [20], LWPR [21], and DMPs [13]. We finally presented applications on different kinds of robots to highlight the flexibility of the proposed approach in three different learning by imitation scenarios.
Embodied Energy at an Urban Scale: A paradigm shift in calculations

Embodied energy has long been a focus of research, and improved operational energy demands in modern structures cause the proper analyses of embodied energies to be critical for full building life cycle analysis. Many different calculation techniques exist to arrive at an embodied energy value, and literature is full of the application of these values to predominantly single or small numbers of buildings. Embodied energy at an urban scale is studied in this paper, and a new software tool for estimating embodied energy impacts at the design stage is introduced. Two case studies are discussed using the software, and embodied energies are calculated and presented in context with their operational energy savings. The importance of choosing an embodied energy value calculated according to the process-based hybrid analysis method when looking at the urban scale is discussed.
QTc and QTd in Children with Type 1 Diabetes Mellitus during Diabetic Ketoacidosis

Cardiac arrest has been described in children with diabetic ketoacidosis (DKA). Aim. To evaluate QTc and QTd in type 1 diabetic children with DKA. Methods. Twelve-lead ECG was done to 30 type 1 diabetic children with DKA at presentation and recovery. Corrected QT interval and QT dispersion (QTd) were assessed. Results. QTc and QTd mean values were significantly decreased in patients after than before DKA recovery (P < 0.01). Procedure. Sixteen patients (53, 3%) had prolonged QTc during DKA (range 451–538 ms) that dropped to one patient after recovery, his QTc (453 ms) returned to normal 5 days after hospital discharge. Nineteen patients (63.3%) had prolonged QTd (>50 ms) that dropped to three after recovery. The fact that three patients had normal QTc but prolonged QTd increases the privilege of QTd over QTc as a better marker for cardiac risk in those patients. Anion gap was significantly associated with QTc and QTd prolongation (P < 0.0001). Patients had no electrolyte abnormalities or hypoglycemia to account for QTc or QTd prolongation. Conclusion. Prolonged QTc and QTd frequently occur in DKA positively correlated to ketosis. Cardiac monitoring for patients with DKA is mandatory.
Improving Squirrel Cage Induction Motor Efficiency: Technical Review

Studying and improving of Squirrel Cage Induction Motor (SCIM) efficiency is a continuous area of interest not only among the researchers but also the industry, manufacturer and government. However, until today there are still struggles to find the most holistic environment of the SCIM which achieve its efficiency at the most lowest cost and at the same time sustaining the performance of the motor. This paper will focus on the method on improving SCIM efficiency. The first discussion presented the main importance of efficient motors and its drive systems. These are partly conceptual, partly concerning circuit topology and current commutation technique. The second discussion ooptimization of SCIM efficiency using intelligent techniques which are of particular interest. The third discussion describes the energy efficiency of SCIM standards and most effect motor parameters on SCIM efficiency.
Single-Crystal Silicon HARPSS Capacitive Resonators with Submicron Gap-Spacing

This paper reports on the fabrication and characterization of single crystal silicon (SCS) in-plane capacitive resonators with submicron gap spacing using the HARPSS process. The resonating element is made out of single crystal silicon and the drive and sense electrodes are made out of trench-refilled polysilicon, hence yielding an all-silicon microresonator with potentially better temperature and long-term stability. The capacitive gap is defined by a sacrificial oxide layer, which can be potentially reduced to the ten’s of nanometer range (700nm reported in this paper). Quality factor as high as 67,000 was measured in 1mTorr vacuum for the 40kHz fundamental resonance frequency of a clamped-clamped beam SCS HARPSS resonator. A 510µm long, 5. 5µm wide, 20µm thick clamped-clamped beam resonator was operated in its third resonance mode at 1MHz and demonstrated a Q of 11,000 under vacuum. Electrostatic tuning characteristics of the resonators have been measured and reported.