Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolution improvement in emission optical projection tomography

A new imaging technique called emission optical projection tomography (eOPT), essentially an optical version of single-photon emission computed tomography (SPECT), provides molecular specificity, resolution on the order of microns to tens of microns, and large specimen coverage (≈ 1 cubic centimetre). It is ideally suited to gene expression studies in embryos. Reconstructed eOPT images suffer from blurring that worsens as the distance from the axis of rotation increases. This blur is caused in part by the defocusing of the lens' point-spread function, which increases with object distance from the focal plane. In this paper, we describe a frequency space filter based on the frequency–distance relationship of sinograms to deconvolve the distance-dependent point-spread function and exclude highly defocused data from the eOPT sinograms prior to reconstruction. The method is shown to reduce the volume at half-maximum of the reconstructed point-spread function to approximately 20% the original, and the volume at 10% maximum to approximately 6% the original. As an illustration, the visibility of fine details in the vasculature of a 9.5 day old mouse embryo is dramatically improved.
Early growth of new science-based firms: the influence of institutional configurations

This paper seeks to explore the early growth phase of newly-established science-based firms, especially how they access and mobilize their ? critical resources? , in particular the early entrepreneurial abilities to run the firm and raise funds. It also explores whether and how firm set-up in the early growth phase may differ in different institutional settings. Drawing on a study of 18 biopharmaceutical firms in the UK and 17 in the Netherlands, we find that there are strong differences in how science-based firms can access critical resources at the early stage. We derive three models of early growth phase of science-based firms: immediate, gradual and arrested set-up. These are strongly influenced by the institutional environment in which firms are embedded.
An Exploratory Investigation of the Structure of the Buying Center in the Metalworking Industry

The results of an exploratory study of patterns of purchase influence in the metal-working industry are reported. The data set used was a representative sample of 2151 purchase influencers in the metalworking industry. Respondents reported their involvement or noninvolvement in each of seven phases of the purchasing decision process. The authors show the presence of identifiable patterns of reported involvement in the organizational buying process and suggest an approach for analyzing those patterns.
Calculation analysis of circumferencial surface settlement of soft soil foundation pit

On the basis of analyzing and summarizing the method to calculate the ground surface settlement around the soft soil foundation pit and in the light of the deformation law of the soft soil foundation pit,the circumferencial ground surface settlement deformation of the pit is fitted in terms of exponential curves and the method is deduced to calculate the settlement deformation of the ccrcumferential ground surface of a deep foundation pit in soft soil regions that is caused by the deflection of the supporting system during excavation.Prediction is made for surface settlement through analysis and comparison of practical cases.A reliable method is put forword for the calculation of the settlement of the foundation pit projects having serious requirement on surrounding environments,which is of signifcance to enviromental protection.
Analyses of Bcl-2, Survivin, and CD44v6 expressions and human papillomavirus infection in cervical carcinomas

Infection with human papillomaviruses (HPV), and suppression of apoptosis and cell adhesion are putative aetiological factors to cervical carcinogenesis. However, controversial results have been reported with respect to their relationships with cervical carcinomas. Here we analysed papillomavirus infection, apoptotic index (AI), expressions of the anti-apoptotic proteins Bcl-2 and Survivin, and expression of the cell-adhesion protein CD44 in cervical tissue samples from individuals with and without cervical carcinomas. Although both HPV16 and HPV18 are reportedly important aetiological factors, we found that cervical carcinomas were highly associated with HPV16 but not HPV18 infection. Immunohistochemistry showed that the percentages of cells expressing Bcl-2, Survivin, and CD44v6 were greatly increased in samples of cervical carcinomas. Furthermore, the expression rates of Survivin and CD44v6 increased whereas that of Bcl-2 declined as cervical cancers developed into more advanced clinical or histopathological stages. Surprisingly, there was little difference in AI between control and cervical cancer samples. These observations provide further evidence that HPV infection, apoptosis and cell adhesion abnormalities are related to cervical cancers. They also suggest that Bcl-2, Survivin and CD44v6 expressions, and HPV16 infection could be useful indices in screening of cervical carcinomas.
A highly miniaturized patch antenna based on zeroth-order resonance

A highly miniaturized antenna with electrical length 0. 036λ<sub>0</sub>×0. 044λ<sub>0</sub>×0. 005λ<sub>0</sub> was implemented based on the zeroth-order resonance metamaterial approach, in which the resonance frequency becomes independent of the physical length of the antenna. The simulated gain is -12.75dBi in the 960MHz frequency, and the experimental return loss is also shown. The design methodology is carefully presented.
The Reporting of Nonresponse Analyses in Survey Research

Because survey respondents may not be representative of the population being studied, the external validity of many research conclusions may be of concern. Nonresponse analyses helps address this concern. The purpose of this article is to identify how frequently nonresponse analyses are reported and what variables are related to these rates. The authors find that less than one third of the survey studies include nonresponse analyses. A number of journal and article quality measures and sample characteristics were found to be related to the reporting of nonresponse analyses.
Defeating Smart and Reactive Jammers with Unlimited Power

Among all wireless jammers, dealing with reactive ones is most challenging. This kind of jammer attacks the channel whenever it detects transmission from legitimate radios. With recent advances in self-interference suppression or in-band full-duplex radios, a reactive jammer can jam and simultaneously sense/discern/detect the legitimate transmission. Such a jammer is referred to as a smart reactive jammer. However, all existing solutions, e.g., frequency hopping and rate adaptation, cannot effectively deal with this type of jammer. This is because a smart reactive jammer with sufficient power budget can theoretically jam most, if not all, frequency channels at sufficiently high power. This work proposes to augment the transmitter with an ambient backscatter tag. Specifically, when the jammer attacks the channel, the transmitter deceives it by continuing to transmit data to attract the jammer while the tag backscatters data based on both the jamming signals and active signals from the jammer and transmitter, respectively. However, backscattering signals from multiple radio sources results in a high bit error rate (BER). Thus, we propose to use multiple antennas at the receiver. The theoretical analysis and simulation results show that by using multiple antennas at the receiver, the BER and hence the throughput of the system can be significantly improved. More importantly, we demonstrate that with our proposed solutions, the average throughput increases and the BER decreases when the jammer attacks with higher power levels. We believe that this is the first anti-jamming solution that can cope effectively with a high- or even unlimited-power jammers.
Finite Length Coding in Edge Computing Scenarios

—Future cellular networks are expected to have resources for data processing at the edge of the network, providing the beneﬁts of cloud computing without long routing delays. Such computing resources may for example be used in a control scenario, where wireless sensors upload data to a controller running at the edge of the mobile network. The controller computes an actuation command that is then sent back on the downlink to a wireless device. The delay in such a system not only depends on the processing time of the controller, but also on the uplink and downlink channels where fading and packet losses can result in a queuing delay. In this work, we present a probabilistic upper bound on the total delay of such systems when the channels are subject to Nakagami-m fading. Our method takes the effect of channel coding at ﬁnite blocklength in the uplink and downlink channels into account. Using several series expansions, the probabilistic delay bounds can be computed analytically, providing guidelines for resource allocation without the need for extensive simulations.
Fast object recognition based on corner geometric relationship

The general object recognition algorithm which uses corner descriptions based on SIFT (Scale Invariant Feature Transform) and PCA (Principal Components Analysis) for patch matching and then eliminate the false matching pairs by RANSAC (RANdom SAmple Consensus) would have very heavy computation load. In this paper, we re-arrange the operating sequence of SIFT, PCA and RANSAC and utilizes the corner geometry relationships to pick up the robust initial pairs. Then, the parameters of the transformation matrix between the recognized image and the template image can be solved and all matching pairs can be obtained by the transformation matrix without SIFT-PCA calculation. Only very few SIFT and PCA calculation is required in our algorithm so that it is much faster than the traditional algorithms. From the experimental results, our algorithm shows very significant advantage over the traditional object recognition algorithm in computation time. Our algorithm only spent around one sixth to seventh computation time comparing to traditional algorithm.
Interrater Reliability of the Active-Knee-Extension Test for Hamstring Length in School-Aged Children

Purpose The purpose of this study was to determine the interrater reliability of the active knee-extension test (AKET) using a stabilizing apparatus to measure hamstring length. Methods One hundred one subjects (53 girls, 48 boys) ranging in age from 10 to 13 years with no known neuromuscular problems participated. The AKET was performed with subjects lying supine with the hip flexed to 90 degrees with a stabilization device attached to a plinth. Next, subjects were instructed to actively extend the knee until the rater detected myoclonus. Then, the rater flexed the knee until myoclonus subsided and the knee angle was measured with a blinded goniometer. This procedure was repeated by each of three raters. Results Data were analyzed using ICC (2,1) demonstrating good interrater reliability of 0.79. Conclusion Our results suggest that the AKET, when used with the stabilizing apparatus, demonstrates good interrater reliability for children aged 10 to 13 years.
Multi-BS association and Pilot Allocation via Pursuit Learning

Pilot contamination (PC) interference causes an inaccurate user equipment’s (UE) channel estimations and significant signal-to-interference ratio (SINR) degradations. To combat the PC effect and to maximize network spectral efficiency, pilot allocation can be combined with multi-Base Station (BS) association and then solved by using learning algorithm efficiently. However, current methods separate the pilot allocation and multi-BS association in the network. This results in suboptimal network spectral efficiency performance and can cause an outage where some UEs are not allocated pilots due to the limited availability of pilots at each BS. In this paper, we propose a multi-BS association and pilot allocation optimization via pursuit learning. Here, we design a parallel pursuit learning algorithm that decomposes the optimization function into smaller entities called learning automata. Each learning automaton computes the joint pilot allocation and BS association solution in parallel, by using the reward from the environment. Simulation results show that our scheme outperforms the existing schemes and does not cause an outage.
Multisized Object Detection Using Spaceborne Optical Imagery

This article addresses the highly challenging problem of vehicle detection from high-resolution remote sensing imagery by introducing a novel medium size annotated dataset named satellite imagery multivehicles dataset (SIMD) along with an adapted single pass deep multiscale object detection framework with the aim to detect multisized/type objects for catering above-ground perspective of vehicles. The dataset images are acquired from multiple locations in the EU/US regions available in the public Google Earth satellite imagery. Specifically, it comprises 5000 images of resolution 1024 × 768 and collectively contains 45 096 objects in 15 different classes of vehicles including cars, trucks, buses, long vehicles, various types of aircrafts, and boats. In the proposed architecture, we demonstrate the relevant modifications needed to translate the state-of-the-art object detection frameworks to solve the object detection problem from remote sensing imagery. The proposed architecture has been evaluated on SIMD and a public dataset VEDAI. The comparative analysis has been performed with existing off-the-shelf single-shot object detection models including YOLO and YOLT yielding superior performance measured with standard evaluation strategies. To ignite further research in this domain, the introduced SIMD dataset and the corresponding architecture is publicly available at this link: http://vision.seecs. edu.pk/simd.
A SURROGATE METHOD FOR DISCRETE MOVEMENT DATA

Sample entropy can be an effective tool for the investigation of human movement variability. However, before applying the method, it can be beneficial to employ an analysis to confirm that observed data is not solely the result of stochastic processes. This can be achieved using surrogate methods. Previous investigations have used surrogate methods within human gait data, yet no appropriate method has been applied to discrete human movement. This article proposes a surrogate method for discrete movement data. The technique reliably generated surrogates for discrete joint angle time series, effectively destroying fine-scale dynamics of the observed signal and maintaining macro structural characteristics (e.g., Mean, SD). Comparison of entropy estimates indicated that observed signals contained deterministic dynamics.
Nonlinear Periodic Systems with the p-Laplacian: Existence and Multiplicity Results

We study second-order nonlinear periodic systems driven by the vector p-Laplacian with a nonsmooth, locally Lipschitz potential function. Under minimal and natural hypotheses on the potential and using variational methods based on the nonsmooth critical point theory, we prove existence theorems and a multiplicity result. We conclude the paper with an existence theorem for the scalar problem, in which the energy functional is indefinite (unbounded from both above and below).
Maximization of Con-current Links in V2V Communications Based on Belief Propagation

In this paper, spectrum resource allocation in vehicle-to-vehicle (V2V) communications network is studied. Multiple V2V links can share one resource block (RB) for maximizing con-current links with the satisfaction of quality of service (QoS). The resource allocation problem is transformed into an inferential problem on a factor graph model. To solve this problem, the Belief Propagation based on Real-time Update of Messages (BPRUM) algorithm is proposed. In this method, the information matrix is updated after each message passing procedure is completed rather than after once iteration. From the simulation results, the proposed method achieves a significant increment in spectrum utilization compared to the existing algorithms.
Spontaneous and Pharmacologically Induced Remissions in Patients With Premature Ovarian Failure

&NA; To determine the fertility potential of patients with apparent ovarian failure, a retrospective analysis of 86 ovarian failure patients in the Norfolk oocyte donation program was performed. None of the 23 patients with primary ovarian failure ovulated. Seven of 63 (11.1%) with secondary ovarian failure did ovuiate, and three of 63 (4.8%) conceived and delivered normal, healthy infants. Of patients whose etiology for ovarian failure was partial ovarian resection or chemotherapy, the ovulation rate and pregnancy rate were 30.8 and 15.4%, respectively, compared with 5.0 and 1.7%, respectively, for the other patients with secondary ovarian failure. Serum estradiol and FSH obtained during hormone replacement were not predictive of the resumption of normal reproductive functions. Therefore, it is recommended that patients with secondary ovarian failure, especially in the better‐prognosis group, be treated with a trial of estradiol replacement and have close monitoring for ovulation before oocyte donation.
Centralized Scheduling with Sum-Rate optimization in Flexible Half-Duplex Networks

In this paper, we focus on maximization of the instantaneous sum-rate in flexible half-duplex networks, where nodes have the flexibility to choose to either transmit, receive or be silent in a given time slot. Since the corresponding optimization problem is NP-hard, we design low-cost algorithms that give sub-optimal solutions with good performance. We first consider two existing approximation techniques to simplify the sum-rate optimization problem: arithmetic-geometric means inequality and another utilising the tight lower bound approximation. We then propose a novel pattern search algorithm that performs close to exhaustive search but with significantly lower complexity. Comparing the performance of the proposed algorithm with respect to existing resource allocation techniques, we observe that our proposed algorithm provides significant sum-rate gains.
Advanced Hardware Architectures for Turbo Code Decoding Beyond 100 Gb/s

In this paper, we present two new hardware architectures for Turbo Code decoding that combine functional, spatial and iteration parallelism. Our first architecture is the first fully pipelined iteration unrolled architecture that supports multiple frame sizes. This frame flexibility is achieved by providing a set of interleavers designed to achieve a hardware implementation with a reduced routing overhead. The second architecture efficiently utilizes the dynamics of the error rate distribution for different decoding iterations and is comprised of two stages. First, a fully pipelined iteration unrolled decoder stage applied for a pre-determined number of iterations and a second stage with an iterative afterburner-decoder activated only for frames not successfully decoded by the first stage. We give post place & route results for implementations of both architectures for a maximum frame size of K = 128 and demonstrate a throughput of 102.4 Gb/s in 2S nm FDSOI technology. With an area efficiency of 6.19 and 7.15 Gb/s/m$m^{2}$ our implementations clearly outperform state of the art.
Novel QoS Control Framework for Automotive Safety-Related and Infotainment Services

Autonomous driving will rely on a multitude of connected applications with stringent quality of service (QoS) requirements in terms of low latency and high reliability. At the same time, passengers relieved of steering duty have the opportunity to enjoy infotainment services that are often associated with high data rates, e.g. video streaming. The simultaneous usage of such safety-related and infotainment services leads to diverse QoS requirements which are difficult to satisfy in current wireless networks. In an effort to address this issue, we propose a two-layer predictive resource allocation framework that leverages the services’ properties and incomplete channel information. First, we optimize packet transmission times by a so-called statistical look-ahead scheduling to enhance the network’s QoS and spectral efficiency based upon channel distribution information. Second, packets are forwarded to an online scheduler according to the outcome of this first optimization. Physical resources are assigned considering the services’ QoS requirements and current channel state. We present a novel heuristic that performs real-time resource assignment. Simulations show that our approach has a potential for improving transmission reliability and spectral efficiency.
The effect of market orientation on product innovation

Numerous scholars have debated whether marketing fosters or stifles innovation. The discussions, however, have been inconclusive due to limited empirical evidence. The authors investigate the relationship between two focal constructs in the debate: market orientation and product innovation. On the basis of a sample of U.S. manufacturing companies, the authors’ analysis shows that product innovation varies with market orientation. Specifically, (1) customer orientation increases the introduction of new-to-the-world products and reduces the launching of me-too products, (2) competitor orientation increases the introduction of me-too products and reduces the launching of line extensions and new-to-the-world products, and (3) interfunctional coordination increases the launching of line extensions and reduces the introduction of me-too products.
Factors Influencing The Usage Of The Tribal Land Information Management System For Land Management And Administration: The Case Of Mogoditshane Subordinate Land‐Board

Land Information Systems are touted to be critical for efficient land management and administration. If properly used and updated, they can inform decision makers in a timely fashion on land resources utilisation. The Government of Botswana has consequently implemented a Tribal Land Information Management System (TLIMS) at Mogoditshane Sub‐Land Board. This study seeks to evaluate the extent to which the TLIMS meets its intended purpose of improving land management and administration. The study also tries to establish the factors that affect usage of the TLIMS. The findings of the study show that there is no records consolidation amongst Land Boards. The main recommendation of the study is that information systems used by various Land Boards need to be standardised to ensure ease of integration of systems. This study contributes to research on information Systems in Developing Countries.