Miracle-dz/UniFAR-FTUs huggingface dataset:
Pancreatic stump closure techniques and pancreatic fistula formation after distal pancreatectomy: Meta-analysis and single-center experience

Background Pancreatic fistula/PF is the most frequent and feared complication after distal pancreatectomy/DP. However, the safest technique of pancreatic stump closure remains an ongoing debate. Here, we aimed to compare the safety of different pancreatic stump closure techniques for preventing PF during DP. Methods We performed a PRISMA-based meta-analysis of all relevant studies that compared at least two techniques of stump closure during DP with regard to PF rates/PFR. We further performed a retrospective analysis of our institutional PFR in correlation with stump closure techniques. Results 8301 studies were initially identified. From these, ten randomized controlled trials/RCTs, eleven prospective and 59 retrospective studies were eligible. Stapler closure (26%vs.31%, OR:0.73, p = 0.02), combination of stapler and suture (30%vs.33%, OR:0.70, p = 0.05), or stump anastomosis (14%vs.28%, OR:0.51, p = 0.02) were associated with lower PFR than suture closure alone. Spleen preservation/splenectomy, or laparoscopic/open DP, TachoSil®, fibrin-like glue-application, or bioabsorbable-stapler-reinforcements (Seamguard®) did not influence PFR after DP. In contrast, autologous patches (falciform ligament/seromuscular patches) resulted in lower PFR than no patch application (21.9%vs.25,8%, OR:0.60, p = 0.006). In our institution, the major three techniques of stump closure resulted in comparable PFR (suture:27%, stapler:29%, or combination:24%). However, selective suturing/clipping of the main pancreatic duct during pancreatic stump closure prevented severe PF (p = 0.02). Conclusion After DP, stapler closure, pancreatic anastomosis, or falciform/seromuscular patches lead to lower PFR than suture closure alone. However, the differences are rather small, and further RCTs are needed to test these effects. Selective closure of the main pancreatic duct during stump closure may prevent severe PF.
Demonstration of On-chip 640-Gbit/s Throughput, Granularity-flexible Programmable Optical Filtering and Reconfigurable Optical Add/drop Multiplexing on Silicon Platform

By integrating cascaded arrayed-waveguide gratings with array switches on silicon platform, we design and fabricate an on-chip multi-functional photonic signal processor. 640-Gbit/s throughput, granularity-flexible programmable optical filtering and reconfigurable optical add/drop multiplexing are demonstrated experimentally.
Randomized online CP decomposition

CANDECOMP/PARAFAC (CP) decomposition has been widely used to deal with multi-way data. For real-time or large-scale tensors, based on the ideas of randomized-sampling CP decomposition algorithm and online CP decomposition algorithm, a novel CP decomposition algorithm called randomized online CP decomposition (ROCP) is proposed in this paper. The proposed algorithm can avoid forming full Khatri-Rao product, which leads to boost the speed largely and reduce memory usage. The experimental results on synthetic data and real-world data show the ROCP algorithm is able to cope with CP decomposition for large-scale tensors with arbitrary number of dimensions. In addition, ROCP can reduce the computing time and memory usage dramatically, especially for large-scale tensors.
Simultaneous position and reflector estimation (SPRE) by single base-station

Accurately estimating user's location is an important functionality in mobile communications. In this paper, we propose SPRE algorithm that can simultaneously estimate the positions of both user and reflectors with single base-station (BS). Different from previous work, the BS knows nothing about the surrounding environment and the motion model of the user. All BS knows is the measured time-of-arrivals (TOAs) and angle-of-arrivals (AOAs) of multiple paths. Since signals from different propagation paths are received by the same receiver, the TOA differences between the direct path and the reflection paths have nearly no errors, which provides SPRE with high-accuracy information. The SPRE takes an iterative procedure to estimate the user's location and reflectors' locations. Simulation results show that reflectors can be accurately estimated after couples of iterations, and in return they improve the estimation accuracy of user position. The proposed SPRE method can localize a mobile user with sub-meter accuracy in indoor cases and meter accuracy in outdoor cases. If the locations of reflectors are known a priori, the SPRE method can realize centimeter-level accuracy of positioning.
Integrating Feature Selection and Feature Extraction Methods With Deep Learning to Predict Clinical Outcome of Breast Cancer

In many microarray studies, classifiers have been constructed based on gene signatures to predict clinical outcomes for various cancer sufferers. However, signatures originating from different studies often suffer from poor robustness when used in the classification of data sets independent from which they were generated from. In this paper, we present an unsupervised feature learning framework by integrating a principal component analysis algorithm and autoencoder neural network to identify different characteristics from gene expression profiles. As the foundation for the obtained features, an ensemble classifier based on the AdaBoost algorithm (PCA-AE-Ada) was constructed to predict clinical outcomes in breast cancer. During the experiments, we established an additional classifier with the same classifier learning strategy (PCA-Ada) in order to perform as a baseline to the proposed method, where the only difference is the training inputs. The area under the receiver operating characteristic curve index, Matthews correlation coefficient index, accuracy, and other evaluation parameters of the proposed method were tested on several independent breast cancer data sets and compared with representative gene signature-based algorithms including the baseline method. Experimental results demonstrate that the proposed method using deep learning techniques performs better than others.
Optimizing robot model parameters for highly dynamic tasks

This work addresses the problem of designing a robot to perform dynamic tasks, like running, strictly through changes to the physical model. We find that this problem is formulable as an optimal control problem. We also find that if the motion can be prescribed for the robotic system as a function of its physical parameters, then that optimal control problem can be solved quickly. We demonstrate an implementation used to get a manually adjustable quadrupedal robot to run.
Scattering function approach for modeling time-varying sea clutter returns

Historically radar returns from the sea surface have generally been modeled in one of two ways-either a) a quasi-deterministic fashion using electromagnetic scattering theory combined with a random realization of physical sea surface based on insights from hydrodynamics or b) using a statistical model of the amplitude envelope based on assumptions about the distribution of scatterers within a resolution cell visible from a given observation angle. However, these models usually suffer from either excessive computational and/or conceptual complexity or have highly restrictive regimes of applicability. In this work we present an alternative characterization of sea clutter returns utilizing statistical linear time-varying system theory in an attempt to provide a more general model that works in a wider variety of circumstances while retaining a competitively low computational burden. It is hoped that the compactness of this mathematical representation will facilitate more rapid development of effective clutter mitigation techniques in the future.
A novel generated method for high quality images

Thanks to the diversity and popularity of image acquisition technique, data driven methods for image analysis and edit become popular. However, the explosive growth of images also presents challenges. To help users retrieve expected images quickly and effectively is one of the hardest tasks. It is difficult to express the user's intention completely for a single cue, thus combining multiple cues becomes necessary. Another problem is that the content-based matching process takes a long time in the case of massive image data. In this dissertation, we propose a progressive retrieval method for high quality images, targeting on the problems that the existed retrieval methods cannot guarantee the image quality and the time consuming of the feature matching for the massive material. We start from the fastest text matching and a progressive strategy is used to evaluate the image quality from both the clarity and independence. Finally, the scene elements of these object is extracted, and the contours are matched between the user sketch and the contours of the candidate scene elements. We parallelize the whole framework in a MapReduce framework to further improve the performance. We validate the performance, accuracy of the algorithm and quality of retrieval result in various experiments. The results show that our method can improve the efficiency of the retrieval and control the image quality of the retrieve results better. Then we can rapidly create a high quality image through simple line sketch.
Prognostic, predictive, and pharmacogenomic assessments of CDX2 refine stratification of colorectal cancer

We aimed to refine the value of CDX2 as an independent prognostic and predictive biomarker in colorectal cancer (CRC) according to disease stage and chemotherapy sensitivity in preclinical models. CDX2 expression was evaluated in 1045 stage I–IV primary CRCs by gene expression (n = 403) or immunohistochemistry (n = 642) and in relation to 5‐year relapse‐free survival (RFS), overall survival (OS), and chemotherapy. Pharmacogenomic associations between CDX2 expression and 69 chemotherapeutics were assessed by drug screening of 35 CRC cell lines. CDX2 expression was lost in 11.6% of cases and showed independent poor prognostic value in multivariable models. For individual stages, CDX2 was prognostic only in stage IV, independent of chemotherapy. Among stage I–III patients not treated in an adjuvant setting, CDX2 loss was associated with a particularly poor survival in the BRAF‐mutated subgroup, but prognostic value was independent of microsatellite instability status and the consensus molecular subtypes. In stage III, the 5‐year RFS rate was higher among patients with loss of CDX2 who received adjuvant chemotherapy than among patients who did not. The CDX2‐negative cell lines were significantly more sensitive to chemotherapeutics than CDX2‐positive cells, and the multidrug resistance genes MDR1 and CFTR were significantly downregulated both in CDX2‐negative cells and in patient tumors. Loss of CDX2 in CRC is an adverse prognostic biomarker only in stage IV disease and appears to be associated with benefit from adjuvant chemotherapy in stage III. Early‐stage patients not qualifying for chemotherapy might be reconsidered for such treatment if their tumor has loss of CDX2 and mutated BRAF.
A statistical method for measuring activation of gene regulatory networks

Abstract Motivation: Gene expression data analysis is of great importance for modern molecular biology, given our ability to measure the expression profiles of thousands of genes and enabling studies rooted in systems biology. In this work, we propose a simple statistical model for the activation measuring of gene regulatory networks, instead of the traditional gene co-expression networks. Results: We present the mathematical construction of a statistical procedure for testing hypothesis regarding gene regulatory network activation. The real probability distribution for the test statistic is evaluated by a permutation based study. To illustrate the functionality of the proposed methodology, we also present a simple example based on a small hypothetical network and the activation measuring of two KEGG networks, both based on gene expression data collected from gastric and esophageal samples. The two KEGG networks were also analyzed for a public database, available through NCBI-GEO, presented as Supplementary Material. Availability: This method was implemented in an R package that is available at the BioConductor project website under the name maigesPack.
Performance analysis and optimization for LDPC coded OFDM systems with pulse blanking

Pulse blanking is a common approach for impulsive interference mitigation in orthogonal frequency division multiplexing (OFDM) systems. The blanking threshold that decides whether a received signal is blanked or not, shows a crucial effect on the mitigation performance. Considering the influence of error correcting codes, we investigate the threshold optimization of pulse blanking for low-density parity-check (LDPC) coded OFDM systems. The protograph based extrinsic information transfer (PEXIT) charts and system simulations are used to tackle the optimization problem of blanking threshold with various LDPC coding schemes, which include different proto-graph structures, code lengths, code rates and the number of iterations. The simulation results show that the optimal blanking threshold changes with the code rate, whereas it remains the same regardless of the protograghs, code lengths and decoding iterations.
Outage probability of single carrier NOMA systems under I/Q imbalance

Non-orthogonal multiple access (NOMA) has been recently proposed as a viable technology that has the potential to improve the spectral efficiency of fifth generation (5G) wireless networks and beyond. However, in practical communication scenarios, transceiver architectures inevitably suffer from radio-frequency (RF) front-end related impairments that can lead to non-negligible degradation of the overall system performance. In this context, in-phase/quadrature-phase imbalance (IQI) constitutes a major impairment in direct-conversion transceivers. Based on this, the present contribution quantifies the effects of IQI on the performance of NOMA based systems under multipath fading conditions. This is realized by first deriving novel analytic expressions for the signal-to-interference-plus-noise ratio and the outage probability of NOMA systems subject to IQI at the transmitter and/or the receiver sites. Capitalizing on these results, we demonstrate that the effects of IQI differ considerably between the different NOMA users and depending on the considered system's parameters.
Impact of Stimulated Raman Scattering on the Transverse Mode Instability Threshold

Quantum defect originating from the stimulated Raman scattering (SRS) effect is a heat source that induces refractive index grating and, thus, significantly decreases the threshold of transverse mode instability (TMI), which is the main limiting factor for the power scaling of high-power fiber lasers. A semi-analytical model that takes the TMI and SRS effects into account was developed, and the impact of the Raman content variation due to changes in the injected seed and fiber length on the TMI threshold was investigated. Experimental demonstrations of the impact of the SRS effect on the TMI threshold are presented. We proved that TMI affects the beam quality of the signal light rather than the Raman light. Taking these facts into account, the suppression of SRS could be an effective way to counter the TMI of fiber lasers.
Somatotopic Mapping of the Developing Sensorimotor Cortex in the Preterm Human Brain

Abstract In the mature mammalian brain, the primary somatosensory and motor cortices are known to be spatially organized such that neural activity relating to specific body parts can be somatopically mapped onto an anatomical “homunculus”. This organization creates an internal body representation which is fundamental for precise motor control, spatial awareness and social interaction. Although it is unknown when this organization develops in humans, animal studies suggest that it may emerge even before the time of normal birth. We therefore characterized the somatotopic organization of the primary sensorimotor cortices using functional MRI and a set of custom-made robotic tools in 35 healthy preterm infants aged from 31 + 6 to 36 + 3 weeks postmenstrual age. Functional responses induced by somatosensory stimulation of the wrists, ankles, and mouth had a distinct spatial organization as seen in the characteristic mature homunculus map. In comparison to the ankle, activation related to wrist stimulation was significantly larger and more commonly involved additional areas including the supplementary motor area and ipsilateral sensorimotor cortex. These results are in keeping with early intrinsic determination of a somatotopic map within the primary sensorimotor cortices. This may explain why acquired brain injury in this region during the preterm period cannot be compensated for by cortical reorganization and therefore can lead to long-lasting motor and sensory impairment.
Investigating university students satisfaction with on-campus cafeteria services: an empirical study in perspective of private university

The objective of the study is to investigate the relationship between food quality, food variety, price fairness, ambience, staff and student satisfaction with cafeteria food services. Respondents were current students of five private universities in Dhaka City of Bangladesh and data were accumulated through the convenience sampling method for reaching the objective of the study. A total number of 267 valid questionnaires were used for statistical analysis. Multiple regression, ANOVA, and T-test were used for data analysis. The results show that attributes such as food quality, ambience and staffs have a significant impact on students? satisfaction with the cafeteria services but the highest correlation is observed between food quality and student satisfaction followed by ambience, staff, and price fairness, respectively. Management in student food services can utilize these results to ensure student satisfaction effectively. This study contributes to existing literature by assessing student satisfaction based on five dimensions of cafeteria food services which is a rare effort in Bangladesh private university perspective.
AN-aided robust secure beamforming design in MIMO two-way relay systems with PNC

This paper investigates the artificial noise (AN)-aided robust secure beamforming design for multiple-input multiple-output (MIMO) two-way relaying (TWR) systems based on physical layer network coding (PNC). In terms of signal-to-interference-and-noise ratio (SINR), we propose two robust beamforming designs to optimize worst-case secrecy sum rate in the presence of an eavesdropper, where the eavesdropper's channel state information (ECSI) is imperfect. In low SINR regime, we give a robust joint beamforming design. Since the optimization problem is non-convex, we use a zero-forcing (ZF) constraint on AN beamforming, and after approximating the objective function, the non-convex problem is formulated into a semidefinite programming (SDP). On the other hand, in high SINR regime, we provide a quality-of-service (QoS)-based robust beamforming design, in which the optimal solution can be efficiently obtained by employing an iterative algorithm based on Taylor expansion and semidefinite relaxation (SDR) techniques. Numerical results show the efficiency of the proposed schemes.
Gallium Phosphide-on-Silicon Dioxide Photonic Devices

The development of integrated photonic circuits utilizing gallium phosphide requires a robust, scalable process for fabrication of GaP-on-insulator devices. Here, we present the first GaP photonic devices on SiO<sub>2</sub>. The process exploits direct wafer bonding of a GaP/Al<italic><sub>x</sub></italic>Ga<sub>1-</sub><italic><sub>x</sub> </italic>P/GaP heterostructure onto a SiO<sub>2</sub>-on-Si wafer followed by the removal of the GaP substrate and the Al<italic><sub>x</sub></italic>Ga<sub>1-</sub><italic><sub>x</sub></italic>P stop layer. Photonic devices such as grating couplers, waveguides, and ring resonators are patterned by inductively coupled-plasma reactive-ion etching in the top GaP device layer. The peak coupling efficiency of the fabricated grating couplers is as high as −4.8 dB. Optical quality factors of 20 000 as well as second- and third-harmonic generation are observed with the ring resonators. Because the large bandgap of GaP provides for low two-photon absorption at telecommunication wavelengths, the high-yield fabrication of GaP-on-insulator photonic devices enabled by this work is especially interesting for applications in nanophotonics, where high quality factors or low mode volumes can produce high electric field intensities. The large bandgap also enables integrated photonic devices operating at visible wavelengths.
Freshness-aware initial seed selection for traffic offloading through opportunistic mobile networks

Offloading traffic through Opportunistic Mobile Networks, also known as opportunistic offloading is a promising way to relieve the overload of cellular networks. The efficiency of such opportunistic offloading is highly determined by the selection of initial seeds. With considering both the freshness of the content and the cost of transmission from the cellular network to the initial seeds, this paper defines a novel freshness-aware seed selection optimization problem to find K initial seeds to maximize the overall content utility. To solve the optimization problem, we propose two seed selection methods: the greedy seed selection method and the decay-based seed selection method. The greedy seed selection method iteratively selects nodes with the maximum Freshness Centrality value as initial seeds. To further improve the performance, the decay-based seed selection method selects initial seeds who are far apart and important in theirs local structure. Extensive real trace-driven simulations are conducted to evaluate the performance of our proposed seed selection methods. The results show that as expected the proposed decay-based seed selection method is superior to the proposed greedy seed selection method and the random seed selection method.
Graph-Based Safe Support Vector Machine for Multiple Classes

Semi-supervised learning (SSL) utilizes limited labeled data and plenty of unlabeled data, and it has attracted attentions for its improved learning performance. However, recent studies have indicated that using unlabeled data, in some cases, could deteriorate the performance. Therefore, there’s an imminent need to develop safe semi-supervised learning methods to determine whether SSL should be applied for a given scenario. This paper proposes a safe version of multi-class graph-based semi-supervised support vector machine (SVM). At first, in order to eliminate the impact of bad label assignments, a criterion based on the cost function of semi-supervised SVM is introduced to evaluate the predicted label assignments. Then, $m$ candidate optimal label assignments are picked up by the criterion. After that, a multi-class safe strategy is designed to generate the final label assignment whose performance is never worse than that of the methods using only labeled samples. Experimental results on several benchmark data sets validate the effectiveness of the proposed technique.
An ocean clutter suppression method for OTHR by combining optimal filter and dictionary learning

In this paper, we consider the ocean clutter suppression problem for High-frequency (HF) sky-wave over-the-horizon radar (OTHR). A novel algorithm named Sparse Dictionary Represented Optimal Filter (SDROF) is proposed for target detection from strong clutter. The dictionary learning technique is used to capture the characteristics of ocean echo and to provide a better clutter estimate, while the well-known optimal filter ensures a statistically maximum output SCNR. SDROF can make use of the information of clutter in current range cell and approximate heterogeneous clutter environment more accurately. Thus, the proposed method performs better in the clutter background of OTHR, which is demonstrated by experimental data.