Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance evaluation of image restoration methods for comparative analysis with and without noise

As the picture worth thousands words, it is necessary to restore the degraded images degraded because of blur, motion or noise in applications like satellite imaging, medical imaging, military and survivalance applications. Restorations techniques are either nonblind methods where the point spread function (PSF) is available or blind deconvolution. This paper presents the implementation and comparison of Weiner filter, Constrained Lease Square, Lucy Richerdson and Blind deconvolution methods in the presence of different artifacts. Performance measures like Peak signal to noise ratio (PSNR), Mean square error (MSE) and Correlation index (CI) are used to quantify the performance of the restoration filters. Results and analysis shows that CLS filter is comparatively better in restoring the degraded image.
Evaluation of magnetic field from varied permutation power transmission line at high technology nano-Fab

We present optimal permutation of power transmission lines to reduce electro-magnetic influence at high technology nano-Fab. In this study, the magnetic field was lessened by mirror array power cable system, and simulation of results predicted the best permutations to decrease electromagnetic influence (EMI) value below 0.4 mG at working space without any shielding. Furthermore, this innovative method will cost down at high technology nano-Fab especially for 28 nanometer process.
Localized interleukin-12 delivery for immunotherapy of solid tumours

Interleukin (IL)‐12 is the key cytokine in the initiation of a Th1 response and has shown promise as an anti‐cancer agent; however, clinical trials involving IL‐12 have been unsuccessful due to toxic side‐effects. To address this issue, lentiviral vectors were used to transduce tumour cell lines that were injected as an autologous tumour cell vaccine. The focus of the current study was to test the efficacy of this approach in a solid tumour model. SCCVII cells that were transduced to produce IL‐12 at different concentrations were then isolated. Subcutaneous injection of parental SCCVII cells results in tumour development, while a mixture of IL‐12‐producing and non‐producing cells results in tumour clearance. Interestingly, when comparing mice injected a mixture of SCCVII and either high IL‐12‐producing tumour cells or low IL‐12‐producing tumour cells, we observed that mixtures containing small amounts of high producing cells lead to tumour clearance, whereas mixtures containing large amounts of low producing cells fail to elicit protection, despite the production of equal amounts of total IL‐12 in both mixtures. Furthermore, immunizing mice with IL‐12‐producing cells leads to the establishment of both local and systemic immunity against challenge with SCCVII. Using depletion antibodies, it was shown that both CD4+ and CD8+ cells are crucial for therapy. Lastly, we have established cell clones of other solid tumour cell lines (RM‐1, LLC1 and moto1.1) that produce IL‐12. Our results show that the delivery of IL‐12 by cancer cells is an effective route for immune activation.
Rethinking How We Think About Cognitive Interventions for Depression: An Example From Research on Second-Language Acquisition

One of the primary goals of cognitive therapy for depression is to teach an individual a new, more adaptive way of thinking about stressful life experiences. We argue that this process of supplanting a deeply engrained way of negative thinking with a more adaptive style of thinking is similar to learning a second language. The purpose of this article was to use a second-language acquisition framework to evaluate the strategies typically used in cognitive therapy for changing depressogenic cognitive patterns and to propose new strategies that may make the therapy more effective.
Overview of Swallow - A Scalable 480-core System for Investigating the Performance and Energy Efficiency of Many-core Applications and Operating Systems

We present Swallow, a scalable many-core architecture, with a current configuration of 480 x 32-bit processors. Swallow is an open-source architecture, designed from the ground up to deliver scalable increases in usable computational power to allow experimentation with many-core applications and the operating systems that support them. Scalability is enabled by the creation of a tile-able system with a low-latency interconnect, featuring an attractive communication-to-computation ratio and the use of a distributed memory configuration. We analyse the energy and computational and communication performances of Swallow. The system provides 240GIPS with each core consuming 71--193mW, dependent on workload. Power consumption per instruction is lower than almost all systems of comparable scale. We also show how the use of a distributed operating system (nOS) allows the easy creation of scalable software to exploit Swallow's potential. Finally, we show two use case studies: modelling neurons and the overlay of shared memory on a distributed memory system.
Associations of P16INK4a promoter hypermethylation with squamous intra-epithelial lesion, cervical cancer and their clinicopathological features: a meta-analysis

To assess the associations of P16INK4a methylation status with low-grade squamous intra-epithelial lesion (LSIL), high-grade squamous intra-epithelial lesion (HSIL), cervical cancer (CC) and their clinicopathological features, a meta-analysis with 29 eligible studies was conducted. Pooled odds ratios (ORs) with their 95% confidence intervals (CIs) were estimated to assess the strength of the associations. Heterogeneity, sensitivity of pooled results and publication bias were also evaluated. Overall, there was an increasing trend of P16INK4a hypermethylation rates among LSIL (21.4%), HSIL (30.9%) and CC (35.0%) specimens. P16INK4a hypermethylation was significantly associated with the increased risk of LSIL, HSIL and CC, with the pooled ORs of 3.26 (95% CI: 1.86-5.71), 5.80 (95% CI: 3.80-8.84) and 12.17 (95% CI: 5.86-25.27), respectively. A significant association was also found between P16INK4a hypermethylation and smoking habit (OR = 3.88, 95% CI: 2.13-7.08). Taken together, meta-analysis results support P16INK4a hypermethylation as an epigenetic marker for the progression of cervical carcinogenesis.
Navigation in Social Networks: Inspired by Kleinberg's Model and Human Travel Behavior Research

Though the phenomenon of ’six degrees of separation’ always attracts many scientists’ attention, yet we haven’t thoroughly understood why our social network has such highly efficient decentralized search ability. Inspired by Kleinberg’s model and the fact that human travel behavior obeying power law distribution in the sense of geographical distance, we constructed a new social network model and investigated its search ability. A L × L square lattice is also employed as the ground regular network. Then for each node in the lattice, we randomly add long-range connections according to power law distribution in the lattice distance. We find that for any k-dimensional lattice, only when the exponent of the power law distribution of long-range connection is −1 will the small world network search ability reach the maximum for sufficiently large lattice, and the time complexity is O(ln(L)). This model not only presents a deeper insight of ’six degrees of separation’, but also provides potential applications for the future Internet, WWW, and P2P network etc.
MuR-DPA: Top-Down Levelled Multi-Replica Merkle Hash Tree Based Secure Public Auditing for Dynamic Big Data Storage on Cloud

Cloud computing that provides elastic computing and storage resource on demand has become increasingly important due to the emergence of “big data”. Cloud computing resources are a natural fit for processing big data streams as they allow big data application to run at a scale which is required for handling its complexities (data volume, variety and velocity). With the data no longer under users' direct control, data security in cloud computing is becoming one of the most concerns in the adoption of cloud computing resources. In order to improve data reliability and availability, storing multiple replicas along with original datasets is a common strategy for cloud service providers. Public data auditing schemes allow users to verify their outsourced data storage without having to retrieve the whole dataset. However, existing data auditing techniques suffers from efficiency and security problems. First, for dynamic datasets with multiple replicas, the communication overhead for update verifications is very large, because each update requires updating of all replicas, where verification for each update requires O(log n ) communication complexity. Second, existing schemes cannot provide public auditing and authentication of block indices at the same time. Without authentication of block indices, the server can build a valid proof based on data blocks other than the blocks client requested to verify. In order to address these problems, in this paper, we present a novel public auditing scheme named MuR-DPA. The new scheme incorporated a novel authenticated data structure (ADS) based on the Merkle hash tree (MHT), which we call MR-MHT. To support full dynamic data updates and authentication of block indices, we included rank and level values in computation of MHT nodes. In contrast to existing schemes, level values of nodes in MR-MHT are assigned in a top-down order, and all replica blocks for each data block are organized into a same replica sub-tree. Such a configuration allows efficient verification of updates for multiple replicas. Compared to existing integrity verification and public auditing schemes, theoretical analysis and experimental results show that the proposed MuR-DPA scheme can not only incur much less communication overhead for both update verification and integrity verification of cloud datasets with multiple replicas, but also provide enhanced security against dishonest cloud service providers.
Register spilling for specific application domains in ASIPs

An Application Specific Instruction set Processor (ASIP) is an important component in designing embedded systems. One of the problems in designing an instruction set for such processors is determining the number of registers is needed in the processor that will optimize the computational time and the cost. The performance of a processor may fall short due to register spilling, which is caused by the lack of available registers in a processor. In the design perspective, it will result in processors with great performance and low power consumption if we can avoid register spilling by deciding a value for the number of registers needed in an ASIP. However, as of now, it has not clearly been recognized how the number of registers changes with different application domains. In this paper, we evaluated whether different application domains have any significant effect on register spilling and therefore the performance of a processor so that we could use different number of registers when building ASIPs for different application domains rather than using a constant set of registers. Such utilization of registers will result in processors with high performance, low cost and low power consumption.
A novel uplink data transmission scheme for small packets in massive MIMO system

Intelligent terminals often produce a large number of data packets of small lengths. For these packets, it is inefficient to follow the conventional medium access control (MAC) protocols because they lead to poor utilization of service resources. We propose a novel multiple access scheme that targets massive multiple-input multiple-output (MIMO) systems based on compressive sensing (CS). We employ block precoding in the time domain to enable the simultaneous transmissions of many users, which could be even more than the number of receive antennas at the base station. We develop a block-sparse system model and adopt the block orthogonal matching pursuit (BOMP) algorithm to recover the transmitted signals. Conditions for data recovery guarantees are identified and numerical results demonstrate that our scheme is efficient for uplink small packet transmission.
Reliability and validity of Korean version of modified: Yale preoperative anxiety scale

Purpose The modified Yale Preoperative Anxiety Scale (mYPAS) was developed for evaluating the level of preoperative anxiety in children. The purpose of this study was to develop a Korean version of the mYPAS (K-mYPAS) and to establish its validity and reliability based on the Korean preoperative pediatric patients. Methods K-mYPAS was made through stringent back-translation procedure. Total enrolled 102 patients answered questionnaires of Korean version of State-Trait Anxiety Inventory for Children (K-STAIC), and were videotaped for 2 to 5 minutes before induction of anesthesia. Three observers of experienced psychiatrist, surgeon, and nurse analyzed videotape with K-mYPAS comparing to K-STAIC. The inter- and intraobservers reliability, concurrent and construct validity, sensitivity, specificity, and predictive value were analyzed. Results The value of Cronbach α for interobservers reliability was 0.939 and intraobserver reliability was statistically significant (P < 0.001). Concurrent and construct validity were also statistically significant (P < 0.001 and P < 0.001, respectively). Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 81.3%, 91.4%, 81.3%, 91.4%, and 88.2%, respectively. Conclusion The K-mYPAS had good psychometric properties and can be used as a reliable and valid instrument for the assessment of preoperative anxiety in children.
A theorem on the quantum evaluation of Weight Enumerators for a certain class of Cyclic Codes with a note on Cyclotomic cosets

This note is a stripped down version of a published paper on the Potts partition function, where we concentrate solely on the linear coding aspect of our approach. It is meant as a resource for people interested in coding theory but who do not know much of the mathematics involved and how quantum computation may provide a speed up in the computation of a very important quantity in coding theory. We provide a theorem on the quantum computation of the Weight Enumerator polynomial for a restricted family of cyclic codes. The complexity of obtaining an exact evaluation is $O(k^{2s}(\log q)^{2})$, where $s$ is a parameter which determines the class of cyclic codes in question, $q$ is the characteristic of the finite field over which the code is defined, and $k$ is the dimension of the code. We also provide an overview of cyclotomic cosets and discuss applications including how they can be used to speed up the computation of the weight enumerator polynomial (which is related to the Potts partition function). We also give an algorithm which returns the coset leaders and the size of each coset from the list $\{0,1,2,. ,N-1\}$, whose time complexity is soft-O(N). This algorithm uses standard techniques but we include it as a resource for students. Note that cyclotomic cosets do not improve the asymptotic complexity of the computation of weight enumerators.
Capability-based delegation model in RBAC

For flexible and dynamic resource management in environments where users collaborate to fulfill their common tasks, various attempts at modeling delegation of authority have been proposed using the role-based access control (RBAC) model. However, to achieve a higher level of collaboration in large-scale networked systems, it is worthwhile supporting cross-domain delegation with low administration cost. For that purpose, we propose a capability-role-based access control (CRBAC) model, by integrating a capability-based access control mechanism into the RBAC96 model. Central to this scheme is the mapping of capabilities to permissions as well as to roles in each domain, thereby realizing the delegation of permissions and roles by capability transfer. By taking this approach of capability-based access control, our model has the advantages of flexibility and reduced administration costs. We also demonstrate the effectiveness of our model by using examples of various types of delegation in clinical information systems.
Evaluating Ortholog Prediction Algorithms in a Yeast Model Clade

Background Accurate identification of orthologs is crucial for evolutionary studies and for functional annotation. Several algorithms have been developed for ortholog delineation, but so far, manually curated genome-scale biological databases of orthologous genes for algorithm evaluation have been lacking. We evaluated four popular ortholog prediction algorithms (MultiParanoid; and OrthoMCL; RBH: Reciprocal Best Hit; RSD: Reciprocal Smallest Distance; the last two extended into clustering algorithms cRBH and cRSD, respectively, so that they can predict orthologs across multiple taxa) against a set of 2,723 groups of high-quality curated orthologs from 6 Saccharomycete yeasts in the Yeast Gene Order Browser. Results Examination of sensitivity [TP/(TP+FN)], specificity [TN/(TN+FP)], and accuracy [(TP+TN)/(TP+TN+FP+FN)] across a broad parameter range showed that cRBH was the most accurate and specific algorithm, whereas OrthoMCL was the most sensitive. Evaluation of the algorithms across a varying number of species showed that cRBH had the highest accuracy and lowest false discovery rate [FP/(FP+TP)], followed by cRSD. Of the six species in our set, three descended from an ancestor that underwent whole genome duplication. Subsequent differential duplicate loss events in the three descendants resulted in distinct classes of gene loss patterns, including cases where the genes retained in the three descendants are paralogs, constituting ‘traps’ for ortholog prediction algorithms. We found that the false discovery rate of all algorithms dramatically increased in these traps. Conclusions These results suggest that simple algorithms, like cRBH, may be better ortholog predictors than more complex ones (e.g., OrthoMCL and MultiParanoid) for evolutionary and functional genomics studies where the objective is the accurate inference of single-copy orthologs (e.g., molecular phylogenetics), but that all algorithms fail to accurately predict orthologs when paralogy is rampant.
Social influence and the evolution of long-tailed distributions

Studies of collective human behaviour in the social sciences, often grounded in details of actions by individuals, have much to offer 'social' models from the physical sciences concerning elegant statistical regularities. Drawing on behavioural studies of social influence, we present a parsimonious, stochastic model, which generates an entire family of real-world right-skew socio-economic distributions, including exponential, winner-take-all, power law tails of varying exponents and power laws across the whole data. The widely used Albert-Barabasi model of preferential attachment is simply a special case of this much more general model. In addition, the model produces the continuous turnover observed empirically within those distributions. Previous preferential attachment models have generated specific distributions with turnover using arbitrary add-on rules, but turnover is an inherent feature of our model. The model also replicates an intriguing new relationship, observed across a range of empirical studies, between the power law exponent and the proportion of data represented.
Mujeres Supporting: How Female Family Members Influence the Educational Success of Latino Males in Postsecondary Education

The purpose of this multi-institutional qualitative study was to understand the educational pathways of Latino males by underscoring the unique role female family members play in their academic pursuits—through the voice of these young men. Findings demonstrate female family members were identified as being primary supporters of their educational pursuits, and actively leveraged different sources of cultural capital to help Latino males enroll and persist through postsecondary education. This study reinforces extant literature on the importance of family in the educational pathways of Latina/o students. Furthermore, it makes a unique contribution by highlighting the important role female family members hold in the Latino family as educational advocates.
Generalised T-duality and non-geometric backgrounds

We undertake a systematic analysis of non-geometric backgrounds in string theory by seeking stringy liftings of a class of gauged supergravity theories. In addition to conventional flux compactifications and non-geometric T-folds with T-duality transition functions, we find a new class of non-geometric backgrounds with non-trivial dependence on the dual coordinates that are conjugate to the string winding number. We argue that T-duality acts in our class of theories, including those cases without isometries in which the conventional Buscher rules cannot be applied, and that these generalised T-dualities can take T-folds or flux compactifications on twisted tori to examples of the new non-geometric backgrounds. We show that the new class of non-geometric backgrounds and the generalised T-dualities arise naturally in string field theory, and are readily formulated in terms of a doubled geometry, related to generalised geometry. At special points in moduli space, some of the non-geometric constructions become equivalent to asymmetric orbifolds which are known to provide consistent string backgrounds. We construct the bosonic sector of the corresponding gauged supergravity theories and show that they have a universal form in any dimension, and in particular construct the scalar potential. We apply this to the supersymmetric WZW model, giving the complete non-linear structure for a class of WZW-model deformations.
One-time Programs with Cloud Storage and Its Application to Electronic Money

A One-time Program (OTP) is a program, proposed by Goldwasser et al., in which the number of executions is restricted to once. The OTP uses a Garbled Circuit (GC), a circuit which does not leak the information except the execution result, as a building block. However, we need to use a special hardware called One-time Memory (OTM) to permit access to only one of two labels necessary for the execution of the GC. When the OTM does not exist or it is expensive, the realistic realization of the OTP is difficult. Furthermore, the OTM needs to be transported to a program executor and needs the production cost. Instead of using OTMs, we propose a way to distribute inputs to multiple cloud storages by using Shamir's secret sharing. In addition, we apply the proposed method to electronic money. Existing electronic money schemes do not prevent double-spending itself, but detect it and identify the double-spender. Therefore, one can double-spend the same electronic money illegally in a short time. Then we can detect the double-spending and identify the double-spender after delivering a product, but the double-spender can abscond with it. To tackle such a problem, we construct an electronic money scheme which prevents double-spending itself based on the OTP that generates a digital signature during a transaction. Combining the proposed electronic money scheme with an existing electronic money scheme, we can also construct another electronic money scheme which can detect double-spending even if the security of the OTP is broken.