Miracle-dz/UniFAR-FTUs huggingface dataset:
Business Groups and Bankruptcy Spillovers ∗

Firms in emerging economies are often identified with particular business groups (BGs). We hypothesize that the group structure allows firms to commit to a lower likelihood of default. The notion is that BGs will not let member firms become bankrupt, if the bankruptcy results in large negative spillovers to other firms in the group. We show this to be the case for our sample of BGs in India: BGs support group firms in financial distress. Firms belonging to BGs with no bankrupt members are significantly less likely to become bankrupt compared to stand alone firms. Negative spillovers are indicated by the finding that the first bankruptcy in a group is followed by a significant and discontinuous drop in profits, in investment levels and an increase in the bankruptcy probability of other firms in the group. Business Groups and Bankruptcy Spillovers
On the stability of optical lattices

In this article, we present an analysis of the stability of optical lattices. Starting with the study of an unstable optical lattice, we establish a necessary and sufficient condition for intrinsic phase stability, and discuss two practical solutions to fulfill this condition, namely minimal and folded optical lattices. We then present a particular example of two-dimensional folded optical lattice which has the advantage of being symmetric, power recycling and having a convenient geometry. We have used this lattice for laser collimation of a continuous cesium beam in a fountain geometry.
A Transfer Learning Based Classifier Ensemble Model for Customer Credit Scoring

Customer credit scoring is an important concern for numerous domestic and global industries. It is difficult to achieve satisfactory performance by traditional models constructed on the assumption that the training and test data are subject to the same distribution, because the customers usually come from different districts and may be subject to different distributions in reality. This study combines ensemble learning and transfer learning, and proposes a clustering and selecting based dynamic transfer ensemble (CSTE) model to transfer the related source domains to target domain for assisting in modeling. The experimental results in a large customer credit scoring dataset show that CSTE model outperforms two traditional credit scoring models, as well as three existing transfer learning models.
Methodological issues in trials assessing primary prophylaxis of venous thrombo-embolism.

AIMS Many trials have been conducted to assess the efficacy of various strategies in the prevention of venous thrombo-embolism (VTE). Some of these trials have been subject to methodological criticisms. We aimed to assess the methodological issues raised by VTE trials. METHODS AND RESULTS We searched MEDLINE and the Cochrane Central Register of Controlled Trials for articles assessing primary thromboprophylaxis published between 1994 and 2003 in 60 general medical and specialty journals. A total of 77 articles were analysed by two independent reviewers using a list of items. No primary endpoint was defined in 20% of trials. Although the primary endpoint was collected before day 15 in 75% of trials, there were >/=20% missing data in 56% of articles and >/=30% in 24.2% of articles. The rate of missing data was 23.7+/-9.7% in studies using venography-detected deep-vein thrombosis as an endpoint compared with 5.6+/-6.0% in studies using other endpoints. Among the 47 superiority trials, 27 (57.4%) reported an intention-to-treat (ITT) analysis, but only 10 (21.3%) reported an analysis that complied with this principle. These results were consistent when limiting the analysis to articles published in high-impact journal (impact factor more than 5). CONCLUSION Recent randomized controlled trials assessing prophylactic regimens in VTE have important methodological limitations in terms of primary endpoints, missing data, and compliance with the ITT principle. These methodological shortcomings should be addressed when planning future trials.
Generalized Calabi-Yau structures and mirror symmetry

We use the differential geometrical framework of generalized (almost) Calabi-Yau structures to reconsider the concept of mirror symmetry. It is shown that not only the metric and B-field but also the algebraic structures are uniquely mapped. As an example we use the six-torus as a trivial generalized Calabi-Yau 6-fold and an appropriate B-field.
Noise-rejection model based on charge-transfer equation for digital CMOS circuits

Noise-rejection curve (NRC) is given by minimum noise amplitude that causes failure of digital cell as a function of noise width. It is more accurate noise failure criteria than traditional static noise margin (NM) and it becomes widely used in modern crosstalk aware designs. However, the accuracy of the NRC-based analysis is often insufficient because of inconsistencies between characterization, data representation, and modeling of the NRC. In part, it can be attributed to ambiguous definition of noise width and height. This paper presents a new noise-rejection model and describes special characterization of digital circuits to achieve high accuracy. This new model is founded on a charge-transfer equation and constrains an integral measure of the noise, rather that its amplitude and width. It provides a compact data representation and is independent on NM.
Hot mirroring: a method of hiding parity update penalty and degradation during rebuilds for RAID5

This paper proposes a storage management scheme for disk arrays, named hot mirroring. In this scheme, storage space is partitioned into two regions. One is the mirrored region, which is characterized by high performance and low storage efficiency. The other is the RAID5 region, which is characterized by low performance and high storage efficiency. Hot data blocks are stored in the former area, while cold blocks are stored in the latter. In addition, mirrored pairs and RAID5 stripes are orthogonally laid out, through which the performance degradation during rebuilding is minimized. Hot block clustering in hot mirroring achieves higher performance than conventional RAID5 arrays. The potential of hot mirroring is examined through extensive simulation.
Education Based on Precede-Proceed on Quality of Life in Elderly

Background and Objective: One of the most important challenges in public health is to improve the quality of life in elders. Aging may cause various disorders such as disabilities, high risk conditions and some chronic disease. In this study the effect of educational intervention based on precede–proceed on quality of life in elders was examined. Materials & Methods: This semi experimental study was carried out on 128 elders over 60 years in Zahedan that were randomly selected by multi-stage sampling method and divided in to control and intervention groups. Data collection tool was a triploid questionnaire that included demographic data, questions of precede-proceed constructs and SF-36 questionnaire. The validity and reliability of questionnaire confirmed by experts and Cranach’s Alpha coefficient (76%). After primary data collecting, educational intervention was performed and after nine months data was collected again and analyzed in spss.16 soft-ware using descriptive and analytical statistics. Results: The results showed that mean score of quality of life in participants was low and more than 61% of them had a mean score less than 50%. After intervention the mean score of quality of life only in experimental group significantly increased from 47.72 to 58.90. Behavior and self-rated health were the strongest predictors for quality of life in this study. Conclusion: Implementation educational intervention based on precedes-proceed model can improve quality of life in elders. Elderly women and older elderly individuals compared with elderly men and younger elderly should be considering as an important risk factor for reducing HRQOL.
Ethernet Jumbo Frames

A decade has passed since jumbo Ethernet frames were first proposed, and an IEEE standard or significant deployment are yet to be seen. This paper synthesizes the various reasons behind the lack of acceptance of jumbo frames. First, performance considerations show that jumbo frames are only useful for bulk data transfer, and may adversely impact latency sensitive applications, thereby jeopardizing the Ethernet promise of a converged network. Second, the problems faced in integrating jumbo frames within the framework of other standards are discussed, including considerations related to the pervasive TCP, as well as the existing Ethernet infrastructure. The latter effectively preclude the standardization of large frames, and therefore perpetuate the issues due to the lack of a standard. Finally, the findings of experimental studies on actual Internet links show that practically none of the links tested supported jumbo frames, preventing their use outside of a controlled local area network environment.
Joint Resource Allocation and User Association for Heterogeneous Wireless Cellular Networks

We propose a unified static framework to study the interplay of user association and resource allocation in heterogeneous cellular networks. This framework allows us to compare the performance of three channel allocation strategies: Orthogonal deployment, Co-channel deployment, and Partially Shared deployment. We have formulated joint optimization problems that are non-convex integer programs, are NP-hard, and hence it is difficult to efficiently obtain exact solutions. We have, therefore, developed techniques to obtain upper bounds on the system's performance. We show that these upper bounds are tight by comparing them to feasible solutions. We have used these upper bounds as benchmarks to quantify how well different user association rules and resource allocation schemes perform. Our numerical results indicate that significant gains in throughput are achievable for heterogeneous networks if the right combination of user association and resource allocation is used. Noting the significant impact of the association rule on the performance, we propose a simple association rule that performs much better than all existing user association rules.
Bayesian multiuser detection based on a network of NLMS filters

The Network of Kalman Filters structure was proposed, recently, to perform an optimal Bayesian symbol-by-symbol estimation in the multiuser detection context. By approximating the prediction error covariance matrix on each branch by a constant diagonal one, we show in this paper that the NKF structure can be expressed into a particular Network of normalized LMS filters exhibiting less computational complexity. The choice of the value of the step-size is also discussed. In order to overcome its heuristic choice, we, here, propose a new adaptive step size based on the second order moment of the estimated symbols. The form of the step-size still contains an information on the a priori state estimation. The performance of the resulted receiver structure is evaluated by means of computer simulations for very high asynchronous system load, in multipath fading channel, and compared to MAP, NKF, MMSE and Rake receivers.
Design patterns - From Architecture to embedded software development

Developing application software for embedded systems presents many challenges as a number of constraints need to be optimized such as strict timings, limited power usage and memory utilization. Also, successful embedded application design are the result of the combined inputs from various related disciplines such as control engineering and scheduling theory. In this regard, recycling design experience can play a substantial role by providing previously tested and proven techniques incorporated into new designs. This paper reports on the evolution of the concept of ‘Design patterns’ originated by analogy from building architectures, and now followed by a wide variety of diverse disciplines. In the field of embedded software development patterns have been found to be a useful adjunct to traditional development processes. Nowadays practitioners in the field of successfully implemented patterns are encouraged to build reliable architectures for the safety-critical applications either from scratch or to transform existing architectures into more predictable forms.
Long-term Effects of Preschool on School Performance, Earnings and Social Mobility

Children from disadvantaged families perform very poorly in school and labour market because they acquire low level of social, motivational and cognitive skills during their early childhood development. Using the NLSY data set, this paper formulates and then estimates the production processes for cognitive skills and non-cognitive skills such as social and motivational skills during early childhood development and the long-term effects of these skills on learning and lifetime earnings of an individual. Using these estimated relationships, the paper provides a calibrated intergenerational altruistic model of parental investment in children's preschool. This dynamic model is then used to estimate the effects of publicly provided preschool to the children of poor socioeconomic status (SES) as a social contract on lifetime earnings distribution, intergenerational college and social mobility, and to estimate the tax burden of such a social contract. JEL Classifications: J24, J62, O15, I21
Perceiving Collision Impacts in Alzheimer’s Disease: The Effect of Retinal Eccentricity on Optic Flow Deficits

The present study explored whether the optic flow deficit in Alzheimer’s disease (AD) reported in the literature transfers to different types of optic flow, in particular, one that specifies collision impacts with upcoming surfaces, with a special focus on the effect of retinal eccentricity. Displays simulated observer movement over a ground plane toward obstacles lying in the observer’s path. Optical expansion was modulated by varying τ˙. The visual field was masked either centrally (peripheral vision) or peripherally (central vision) using masks ranging from 10° to 30° in diameter in steps of 10°. Participants were asked to indicate whether their approach would result in “collision” or “no collision” with the obstacles. Results showed that AD patients’ sensitivity to τ˙ was severely compromised, not only for central vision but also for peripheral vision, compared to age- and education-matched elderly controls. The results demonstrated that AD patients’ optic flow deficit is not limited to radial optic flow but includes also the optical pattern engendered by τ˙. Further deterioration in the capacity to extract τ˙ to determine potential collisions in conjunction with the inability to extract heading information from radial optic flow would exacerbate AD patients’ difficulties in navigation and visuospatial orientation.
The Mind Anchor: Peran Trait Rumination dalam Struktur Pengalaman Afektif

This study aimed to investigate whether trait rumination has a role in individual’s structure of current affect, specifically on valence and arousal dimension. Within-subject experiment design was used as a study design which involved eighty-one undergraduate students of Department of Psychology, Universitas Brawijaya as participants. Images from International Affective Picture System (IAPS) were used to evoke participant’s affect and measured by Self Assessment Manikin’s (SAM) rating while trait rumination was measured using Ruminative Response Scale (RRS). Statistical analysis using one-way repeated measures ANOVA technique found that trait rumination has a significant role in participant’s structure of current affect on relation between valence stimulus and rating valence (F=5.276, p 0.05). Penelitian ini bertujuan untuk mengetahui apakah trait rumination memiliki peran dalam struktur pengalaman afektif individu, yaitu dimensi valence dan arousal . Penelitian ini menggunakan desain within-subject experiment dengan melibatkan delapan puluh satu orang mahasiswa baru Prodi Psikologi Universitas Brawijaya sebagai partisipan. Afek partisipan dibangkitkan menggunakan stimulus gambar dari International Affective Picture System (IAPS) yang diukur melalui Self Assessment Manikin (SAM) dan trait rumination diukur menggunakan Ruminative Response Scale (RRS). Hasil analisis statistik menggunakan teknik one-way repeated measures ANOVA menunjukkan bahwa trait rumination memiliki peran signifikan dalam hubungan antara valence stimulus dan rating valence ( F =5.276, p 0.05).
Statistical properties of information processing in neuronal networks

Information processing and coding were analysed in dissociated hippocampal cultures, grown on multielectrode arrays. Multisite stimulation was used to activate different neurons and pathways of the network. The neural activity was binned into firing rates and the variability of the firing of individual neurons and of the whole population was analysed. In individual neurons, the timing of the first action potential (AP) was rather precise from trial to trial, whereas the timing of later APs was much more variable. Pooling APs in an ensemble of neurons reduced the variability of the response and allowed stimuli varying in intensity to be distinguished reliably in a single trial. A similar decrease of variability was observed pooling the first evoked APs in an ensemble of neurons. The size of the neuronal pool (∼ 50–100 neurons) and the time bin (∼ 20 ms) necessary to provide reproducible responses are remarkably similar to those obtained in in vivo preparations and in small nervous systems. Blockage of excitatory synaptic pathways mediated by NMDA receptors improved the mutual information between the evoked response and stimulus properties. When inhibitory GABAergic pathways were blocked by bicuculline the opposite effect was obtained. These results show how ensemble averages and an appropriate balance between inhibition and excitation allow neuronal networks to process information in a fast and reliable way.
Untold Stories; A phenomenological enquiry into why Six Swedish seniors wish not to tell their stories.

Emphasis is being placed on how life narratives can be incorporated into caring for the elderly based on the assumption that aged health care should be grounded on narrative perspectives in order to reduce ageist behaviours. The success of this however depends on the willingness of the elderly to share their stories. The aim of this study was to explore the reasons why Swedish elders decline to share their life stories. Using semi-structured interviews, data was collected from six participants and analysed using interpretative phenomenological analysis. Findings suggest that Swedish elders’ refusal to share their life stories or excerpts of it reflects their need for privacy. The elders seemed to be naturally motivated to reflect and talk about their past, but their personal and interpersonal experiences have caused them to feel less inclined to share. Understanding the reasons why Swedish elders decline to share their stories may help families, and health practitioners to provide a supportive environment for sharing. This may contribute to a better psychological health and provide the opportunity for them to share their stories and enhance transmitting their knowledge and experiences to the younger generation. (Less)
Comparison of VADER and LSTM for Sentiment Analysis

Sentiment analysis is one of the trending topics at present. It has a vast scope from analysing the mood of the person based on his tweet, to predicting the stock prices. But this field is quite challenging. It is not easy to make a machine understand what exactly the person is saying. In this paper, we are going to demonstrate two different methods that can be used in sentiment analysis and its comparison. The two methods used in this paper are: i) VADER-Valence Aware Dictionary for sEntiment Reasoning ii) LSTM model (Long Short-Term Memory). VADER uses a lexicon-based approach, where the lexicon contains the intensity of all the sentiment showing words. The intensities are fetched, the sentiment score is calculated and based on this sentiment score, the review is classified as either positive or negative. We used VADER from NLTK module of python for our study. Recurrent Neural Network has proved its results in a variety of problems like speech recognition, language modelling, and translation. We used LSTM which is an extension of RNN for our study. LSTM networks are very effective for sequential data like texts because they can relate the context of the sentence very well. We preferred LSTM over RNN as LSTM supports Long-term dependency which will help us predict our reviews better. We implemented the LSTM model using keras
An investigation of augmenting speaker representations to improve speaker normalisation for DNN-based speech recognition

The conventional short-term interval features used by the Deep Neural Networks (DNNs) lack the ability to learn longer term information. This poses a challenge for training a speaker-independent (SI) DNN since the short-term features do not provide sufficient information for the DNN to estimate the real robust factors of speaker-level variations. The key to this problem is to obtain a sufficiently robust and informative speaker representation. This paper compares several speaker representations. Firstly, a DNN speaker classifier is used to extract the bottleneck features as the speaker representation, called the Bottleneck Speaker Vector (BSV). To further improve the robustness of this representation, a first-order Bottleneck Speaker Super Vector (BSSV) is also proposed, where the BSV is expanded into a super vector space by incorporating the phoneme posterior probabilities. Finally, a more fine-grain speaker representation based on the FMLLR-shifted features is examined. The experimental results on the WSJ0 and WSJ1 datasets show that the proposed speaker representations are useful in normalising the speaker effects for robust DNN-based automatic speech recognition. The best performance is achieved by augmenting both the BSSV and the FMLLR-shifted representations, yielding 10.0% - 15.3% relatively performance gains over the SI DNN baseline.
Energy Efficient Routing in Zigbee Wireless Sensor Network- A Review

As we distinguish, the data communication in the wireless networks is more untrustworthy than it is in the wired network environment. Even though the virtual carrier sensing scheme can be used in the wireless unicast transmission, the multicast and broadcast still not exploit the acknowledgement instrument for reliable transmission. This is due to the acknowledgement packets of broadcast programme will cause much sophisticated communication traffic and overhead. Since reliable data broadcast is critical and obligatory in many applications in the wireless sensor networks, our study focuses on the ZigBee network which is a new industrial standard for sensor networks. Some previous related papers improved the broadcast reliability by introducing redundant transmission and increasing coverage ratio of every receiver node, but there still exists probability of packet loss and extra communication cost due to redundant broadcast. Wireless sensor networks are functioning in several applications, including military, medical, environmental and domestic. In all these applications, energy usage is the determining factor in the performance of wire- less sensor networks. As a result, methods of zigbee based data routing and transferring to the base station are very important because the sensor nodes run on battery power and the energy available for sensors is limited. This Paper reviews all the aspects and constraints related to data routing within zigbee wireless sensor network.