High Probability Of Success Research Articles

Temperature or competition: Which has more influence on Mediterranean ant communities?

Temperature and competition are two of the main factors determining ant community assemblages. Temperature may allow species to forage more or less efficiently throughout the day (in accordance with the maximum activity temperature of each species). Competition can be observed and quantified from species replacements occurring during resource exploitation. We studied the interspecific competitive interactions of ant communities from the Doñana Biological Reserve (southern Spain). Ants were sampled from pitfall traps and baits in three habitats with contrasted vegetation physiognomy (savin forest, pine forest, and dry scrubland). We measured the temperature during the competitive interactions between species and created a thermal competition index (TCI) to assess the relative contribution of temperature and numerical dominance to the competitive outcomes. Temperature had unequal effects on ant activity in each type of habitat, and modulated competitive interactions. The TCI showed that a species’ success during pair interactions (replacements at baits) was driven by the proportion of workers between the two competing species and by the species-specific effect of temperature (how advantageous the temperature change is for each species during bait replacement). During competitive interactions, the effect of temperature (higher values of TCI) and numeric supremacy (higher worker proportion) gave higher success probabilities. Interspecific competitive relationships in these Mediterranean ant communities are habitat dependent and greatly influenced by temperature.

Improving the teleportation of quantum Fisher information under non-Markovian environment

Quantum teleportation is designed to send an unknown quantum state between two parties. In the perspective of remote quantum metrology, one may be interested in teleporting the information that is encoded by physical parameters synthesized by quantum Fisher information (QFI). However, the teleported QFI is often destroyed by the unavoidable interaction between the system and the environment. Here, we propose two schemes to improve the teleportation of QFI in the non-Markovian environment. One is to control the quantum system through the operations of weak measurement (WM) and corresponding quantum measurement reversal (QMR). The other is to modify the quantum system based on the monitoring result of the environment (i.e., environment-assisted measurement, EAM). It is found that, in the non-Markovian environment, these two schemes can improve the teleportation of QFI. By selecting the appropriate strengths of WM and QMR, the environment noise can be completely eliminated and the initial QFI is perfectly teleported. A comprehensive comparison shows that the second scheme not only has a higher probability of success than the first one, but also has a significant improvement of the teleported QFI.

Experiential and Stochastic Learning Algorithms Based on the Probability of a Fuzzy Event and Modified Fuzzy Metric Distance in Intelligent Robotic Part Micro-Assembly

Experiential and stochastic learning algorithms for improving the time consumed in robot’s part micro-assembly procedures are presented. A comprehensive comparison of the results with other recent algorithms is described. The experiential learning algorithm unites the neighboring sections in a manner that is very similar to the larger united section based on the specified criterion. If the experiential learning algorithm is consecutively repeated, the micro-assembly dynamics analysis chart will be not only minimized in the number of sections, but also formed such that each united section will have one selected optimal plan with the lowest modified fuzzy metric distance within its own section. Thus, if the new input appertaining to the section is merely identified, the final selected plan within the section will execute the related task quickly and accurately thus resulting to a significant improvement in the time spent in the part insertion. Through the stochastic learning algorithm extended from the crisp set domain to the fuzzy set domain, based on the probability of a fuzzy event and the modified fuzzy metric distance, to deal well with the uncertainties arising during the micro-assembly procedure, if one specific plan among the feasible plans is successively selected to solve its confronting micro-assembly problems, the probability that the selected plan will be continuously chosen will increase as a consequence of compensation, namely, a higher value of membership degree is continuously allocated to the selected plan. As a result, the selected control plan with the highest probability of success and the lowest degree of uncertainty acquired by the stochastic learning facilitates the stabilization of the execution phase of the part insertion task. The degree of uncertainty, which is measured by a modified fuzzy metric distance and related to the task execution of the micro-assembly, is used as a criterion to select the most valid plan. The results demonstrate that the micro-assembly stuck problems can be successfully resolved by the experiential and stochastic learning algorithms.

Analyzing Uplink Grant-Free Sparse Code Multiple Access System in Massive IoT Networks

Grant-free sparse code multiple access (GF-SCMA) is considered to be a promising multiple access candidate for future wireless networks. In this article, we focus on characterizing the performance of uplink GF-SCMA schemes in a network with ubiquitous connections, such as the Internet-of-Things (IoT) networks. To provide a tractable approach to evaluate the performance of GF-SCMA, we first develop a theoretical model taking into account the property of multiuser detection (MUD) in the SCMA system. Then, the error rate performance of GF-SCMA in the case of codebook collision is analyzed to investigate the reliability of GF-SCMA when reusing codebook in massive IoT networks. For performance evaluation, accurate approximations for both success probability and average symbol error probability (ASEP) are derived. To elaborate further, the analytical results are utilized to discuss the impact of codeword sparse degree in GF-SCMA. After that, we conduct a comparative study between SCMA and its variant, dense code multiple access (DCMA), with GF transmission to offer insights into the effectiveness of these two schemes. This facilitates the GF-SCMA system design in practical implementation. Simulation results show that denser codebooks can help to support more user equipments (UEs) and increase the reliability of data transmission in a GF-SCMA network. Moreover, a higher success probability can be achieved by GF-SCMA with denser UE deployment at low detection thresholds since SCMA can achieve overloading gain.

Humanity extinction by asteroid impact

The risk of humanity extinction by giant asteroid impact is addressed. A 100 km sized asteroid impact may transform the Earth into an inhospitable planet, thus causing the extinction of many life forms including the human species. The exact reason for such a result remains nevertheless uncertain. Based on Moon crater history and NEA observations, the probability of a giant impact is between 0.03 and 0.3 for the next billion years. However, as the warning time would be in general relatively long, humanity could have time to settle on other planets with a high probability of success. The greatest threat could come from giant long period comets. We show that the probability of a giant comet impact is 2.2 × 10-12 for the next hundred years with a very short warning time. Many possible causes would lead to a degradation of life support and the extinction of humanity during the decades following the impact. It could be a lack of energy or important resources, other catastrophic events, conflicts and inefficient human organization and the preparatory phase could also play an important role. All in all, the extinction would be highly probable though not totally sure.

Universal Quantum Multi‐Qubit Entangling Gates with Auxiliary Spaces

AbstractUniversal quantum entangling gates are a crucial building block in the large‐scale quantum computation and quantum communication, and it is an important task to find simple ways to implement them. Here an effective quantum circuit for the implementation of a controlled‐NOT (CNOT) gate is constructed by introducing a non‐computational quantum state in the auxiliary space. Furthermore, the method is extended to the construction of a general n‐control‐qubit Toffoli gate with qubit–qudit gates and single‐qudit gates. Based on the presented quantum circuits, the polarization CNOT and Toffoli gates with linear optics are designed by operating on the spatial‐mode degree of freedom of photons. The proposed optical schemes can be achieved with a higher success probability and no extra auxiliary photons are needed.

Impacted Central Incisors in the Upper Jaw in an Adolescent Patient: Orthodontic-Surgical Treatment—A Case Report

The inclusion of both maxillary permanent central incisors is uncommon. This condition compromises face aesthetics, phonation and masticatory function. Therefore, early diagnosis is essential to avoid complications and failures. There are various reasons for inclusion, but supernumerary teeth are the leading cause. Early causes of removal and rapid expansion of the palate determine a high probability of success with the spontaneous eruption of the impacted elements. However, it is often necessary to proceed with a surgical–orthodontic treatment. The inclination of teeth in relation to the midline and the root maturation degree determine prognosis and therapeutic timing. In this case report, the orthopantomogram (OPG) X-ray of a 9-year-old boy revealed two impacted supernumerary teeth in the anterior maxillary region, preventing the eruption of the permanent upper central incisors. The impacted supernumerary teeth were surgically removed at different times. A straight wire multibrackets technique associated with a fixed palatal appliance was used. The palatal appliance featured an osteomucous resin support at the level of the retroincisal papilla. Subsequently, surgical exposure was carried out using the closed eruption technique and elastic traction, bringing 11 and 21 back into the arch.

Infographic: Four training modalities to improve functional mobility in people with Parkinson’s disease

Impairment of functional mobility is one of the most disabling symptoms in people with Parkinson’s disease (PwPD). Limitations in mobility lead to sedentarism, which may decrease the quality of life in PwPD. Several studies demonstrated that the combination of exercise with the traditional pharmacological treatment (i.e., levodopa) is effective to improve mobility in PwPD 1-5. Although the effects of traditional modalities (e.g., walking overground and cycling) are well documented, other stimuli may also induce positive responses on mobility in PwPD. However, such studies demonstrated trivial results or effectiveness in terms of functional mobility, indicating that the exercise – mainly using non-traditional stimuli – should be carefully prescribed. To avoid practical mistakes and ensure a high probability of success in mobility rehabilitation in PwPD, rehabilitation professionals must apply up-to-date and high-quality knowledge about mobility. Also, they must recognize the effects of different exercise modalities to improve functional mobility and the motivators and barriers to exercise in PwPD 1. This infographic aims to present (1) the motiving factors and barriers of training in PwPD, (2) the main effects of four exercise modalities on functional mobility (considering its underlining mechanisms), and (3) demonstrate the training evidence to improve the functional mobility. The exercise modalities were selected from the four recent meta-analyses (searched on PUBMED) that tested the exercise effects on functional mobility and presented data related to exercise prescription for PwPD. The encouragement of other persons is the most motivating factor for PwPD during exercise. The lacking of encouragement, fatigue and depression are related to exercise barriers in PwPD 1. Suárez-Iglesias et al. 2 demonstrated that Pilates was effective to improve functional mobility, improving Timed Up and Go (TUG) performances. Interventions using hydrotherapy, with or without land-based therapy, also showed positive effects on TUG values 3. Dance modality, associated with auditory cues, promoted positive effects on gait velocity, TUG, and freezing of gait 4. Finally, Robinson et al. 5 observed that treadmill training, when compared to no-exercise ones, improved the gait velocity and step length in PwPD regardless of use or not body weight support. Overall these results were observed in patients with early to moderate stages of disease (Hoehn and Yahr < 3). These main effects and the mechanism related to the positive responses were presented in the infographic. Despite the noteworthy positive effects of exercise using these modalities in PwPD, recommendations for training prescriptions are still debatable. The characteristics of the modalities were poorly described in most of the studies. For example, even with the availability of acceptable and practical tools, the exercise intensity or its increment throughout the training was not properly reported. Therefore, it is difficult to determine a specific guideline to improve functional mobility in PwPD. The discussion about prescriptions (hydrotherapy) and the program with the highest weight in the meta-analysis (dance, pilates and treadmill) were presented in the infographic. Future studies should detail, as many as, possible training characteristics, increasing the reproducibility and applicability of the results.

Identification of prophylactic drugs for oxaliplatin-induced peripheral neuropathy using big data

BackgroundDrug repositioning is a cost-effective method to identify novel disease indications for approved drugs; it requires a shorter developmental period than conventional drug discovery methods. We aimed to identify prophylactic drugs for oxaliplatin-induced peripheral neuropathy by drug repositioning using data from large-scale medical information and life science information databases. MethodsHerein, we analyzed the reported data between 2007 and 2017 retrieved from the FDA’s database of spontaneous adverse event reports (FAERS) and the LINCS database provided by the National Institute of Health. The efficacy of the drug candidates for oxaliplatin-induced peripheral neuropathy obtained from the database analysis was examined using a rat model of peripheral neuropathy. Additionally, we compared the incidence of peripheral neuropathy in patients who received oxaliplatin at the Tokushima University Hospital, Japan. The effects of statins on the animal model were examined in six-week-old male Sprague–Dawley rats and seven or eight-week-old male BALB/C mice. Retrospective medical chart review included clinical data from Tokushima University Hospital from April 2009 to March 2018. ResultsSimvastatin, indicated for dyslipidemia, significantly reduced the severity of peripheral neuropathy and oxaliplatin-induced hyperalgesia. In the nerve tissue of model rats, the mRNA expression of Gstm1 increased with statin administration. A retrospective medical chart review using clinical data revealed that the incidence of peripheral neuropathy decreased with statin use. Conclusion and relevanceThus, drug repositioning using data from large-scale basic and clinical databases enables the discovery of new indications for approved drugs with a high probability of success.

Mineralogy Sensitive Immersion Freezing Parameterization in DREAM

AbstractDust aerosols are abundant in the atmosphere and are very efficient ice nucleating particles at temperatures below −15°C. Depending on temperature, dust particles containing certain minerals (i.e., feldspar and quartz) are the most active as ice nuclei. A mineralogy‐sensitive immersion freezing parameterization for ice nucleating particle concentration (INPC) is implemented in Dust Regional Atmospheric Model (DREAM) for the first time. Additionally, four mineralogy‐indifferent parameterizations are implemented, two for immersion freezing and two for deposition nucleation. Dust concentration and its feldspar and quartz fractions are forecasted by DREAM for a dust episode in the Mediterranean in April 2016. DREAM results are compared with vertical profiles of cloud‐relevant dust concentrations and INPC from ground‐based lidar measurements in Potenza, Italy and Nicosia, Cyprus. INPC predictions are also compared with vertical profiles of ice crystal number concentration (ICNC) from satellite observations for two overpasses over the dust plume. The model successfully simulates the evolution and vertical extent of the dust plume. Mineralogy‐sensitive and mineralogy‐indifferent INPC parameterization results generally differ by about an order of magnitude. Forecasted INPC and observed ICNC values differ by an order of magnitude for all parameterizations. Feldspar fraction increase within a dust plume during transport can increase INPC by around 6% at −35°C, and up to 17% at −25°C, but sedimentation can reduce this effect. Over the Atlantic, mineralogy‐sensitive parameterization predicts horizontal distribution of clouds with higher probability of success, while in the Mediterranean; the results for different parameterizations show lower variability.

Proof-of-principle demonstration of sequential 3 → 1 quantum random access code via cascaded measurements.

Quantum random access code (QRAC) serves the communication task to encode a long message into a quantum system and allow the receiver to decode the initial information with a higher success probability than classical random access code (RAC). Here, we present an experimental demonstration of sequential 3 → 1 QRAC in the prepare-transform-measure scenario with one sender and three independent receivers. The experimental results show that, in the 3 → 1 QRAC scenario, three receivers can independently decode the initial information with an average success probability higher than the classical RAC.

Accelerating spiking neural networks using quantum algorithm with high success probability and high calculation accuracy

Spiking neural networks (SNNs) are a kind of neuromorphic computing which meticulously imitates the operations of biological nervous systems. Thus, the SNN is seen as a promising approach to further improve the level of intelligence that the legacy artificial neural networks achieved. In a spiking neuron of an SNN, it is a key step with the highest computing complexity to find out the moment when the output stimuli occur. Classic computer (i.e., electrical computer) based acceleration cannot reduce the computational complexity of the operations in the spiking neurons. As a result, the SNN suffers from scaling and deeper emulation problems. Considering these, in this paper, we propose a quantum algorithm to reduce the complexity of the key steps in the SNN and use this algorithm to build a quantum spiking neuron network (QSNN). More specifically, first, we give mathematical proof that the problem of finding the output stimuli is approximately equal to the problem of calculating the unsigned vector inner products, which can transfer to a quantum operation. Second, we design a scalable quantum circuit of QSNN for data of any dimension and evaluate its basic success probability and calculation accuracy. Third, to improve the QSNN performance, we propose a method to improve the minimum success probability to 99.8%, by repeatedly performing the quantum circuit only 11 times. Fourth, we prove that the computational complexity of the QSNN is a log-polynomial relationship with the data dimension, which is much lower than that of the linear complexity of the classic SNN. Finally, we apply the QSNN to solve classification tasks on two real-world datasets, i.e., MNIST and fashion MNIST which both have two noise levels (i.e., no noise and 50% of the noise). The experiment results show that in addition to the acceleration, QSNN and SNN have equal classification accuracy, which suggests the feasibility and robustness of the QSNN.

Drivers of cadmium accumulation in Theobroma cacao L. beans: A quantitative synthesis of soil-plant relationships across the Cacao Belt.

Elevated cadmium (Cd) concentrations in cacao and cocoa-based products (e.g., chocolate) present a potentially serious human health risk. While recent regulatory changes have established a threshold of 0.8 mg kg-1 for Cd content of cocoa-based products, the biophysical factors (e.g., climatic or edaphic conditions) that determine the amount of soil-derived Cd in the cacao bean are poorly understood and have yet to be quantitatively assessed across diverse production contexts. To determine the primary drivers of cacao bean Cd, we used the scientific literature to systematically compile a database of climatic, edaphic, and plant data from across the Cacao Belt, which is approximately 20 degrees latitude on either side of the equator. From this compiled dataset, we then used boosted regression trees to quantitatively synthesize and evaluate these drivers of cacao bean Cd. Total soil Cd concentration, soil pH, and leaf Cd were the best predictors of bean Cd content. Notably, we found that both available soil Cd and soil organic carbon (SOC) content had negligible effects on bean Cd. However, soil pH and SOC decreased the degree of bioconcentration of total soil Cd in the bean Cd concentration. Thus, given the difficulty in remediating soil Cd enriched soils, our results suggest that Cd mitigation strategies targeting plant physiology-based approaches (e.g., breeding, rootstocks) have a higher probability of success than soil-based strategies (e.g., remediation).

Variables Predicting Academic Success of Nursing Students: a Longitudinal Study in a Nursing Bachelor's Degree Program.

Academic failure can negatively impact on the student, the university and the nursing workforce in the short term. The aim of this study is to analyze the characteristics and predictors of academic success in two cohorts of students of a Nursing Bachelor's Degree program. This longitudinal study enrolled students who attended the Nursing Bachelor's Degree program. The Tor Vergata University includes 21 Nursing Bachelor's Degree programs at several Sanitary Institutions of the Rome area, with a mean annual recruitment of 800 students. We considered two cohorts of students beginning the program in the 2011-2012 and 2012-2013 academic years, respectively. The follow-up of these two cohorts ended in the 2017-2018 academic year. We considered socio-demographic and academic variables in the nursing field (pre-admission test grade, training exam grade in the first, second and third year and professional license exam grade). The outcome variable is academic success defined as gradua-tion on time; academic failure is defined as changing degree, delay in completion of the course, attrition and dismissal (failure to complete the studies). Data were collected at baseline (T0), at the end of the first year (T1), at the end of the second year (T2) and at the end of the third year (T3) of the course. A logistic regression was performed to identify predictors of academic success. 2,041 students were enrolled, with an average age of 22.0 years (± 4.6, 18-50); 67.4% were female. Regarding academic success, 30.6% of students graduated on time and so achieved academic success, while 69.4% failed to complete the course within the established time: 5.4% (110/2,041) changed the course, the attrition rate was 7.3%, 0.3% (6/2,041) overdue from the course for expiring of the terms, 18.0% (368/2,041) is attending the course and 38.4% (784/2,041) graduated after more than three years. Pre-admission test grade (OR: 10.0, 95% CI: 10.020-10.054) and training exam grade at the second and third years (OR: 10.0 95% CI: 10.027-10.139; OR: 10.2 95% CI: 10.171-10.294) predicted academic success. Some nursing students changed course during the last year of the program, while the training exam grade of the second and third years had predicted academic success; this is a brand new information derived from this study. In addition, we confirmed the association of age, gender, secondary school type and grade and preadmission test with academic success. For these reasons, clinical training should be improved and the quality of internship wards, as learning environments, should be monitored. Italian universities should undertake establishing the ideal cut-off in pre-admission tests to determine which students have a high probability of academic success.

Virtual Combinatorial Chemistry and Pharmacological Screening: A Short Guide to Drug Design.

Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as their low toxicity. On average, this process of new drug development involved, in addition to high economic costs, a period of several years before hopefully finding a drug with suitable characteristics to drive its commercialization. Therefore, the chemical synthesis of new compounds became the limiting step in the process of searching for or optimizing leads for new drug development. This need for large chemical libraries led to the birth of high-throughput synthesis methods and combinatorial chemistry. Virtual combinatorial chemistry is based on the same principle as real chemistry—many different compounds can be generated from a few building blocks at once. The difference lies in its speed, as millions of compounds can be produced in a few seconds. On the other hand, many virtual screening methods, such as QSAR (Quantitative Sturcture-Activity Relationship), pharmacophore models, and molecular docking, have been developed to study these libraries. These models allow for the selection of molecules to be synthesized and tested with a high probability of success. The virtual combinatorial chemistry–virtual screening tandem has become a fundamental tool in the process of searching for and developing a drug, as it allows the process to be accelerated with extraordinary economic savings.

Climate change or mismanagement?

Climate change and deoxygenation are affecting fish stocks on a global scale, but disentangling the impacts of these stressors from the effects of overfishing is a challenge. This study was conducted to distinguish between climate change and mismanagement as possible causes for the drastic decline in spawning stock size and reproductive success in cod (Gadus morhua) and herring (Clupea harengus) in the Western Baltic Sea, when compared with the good or satisfactory status and reproductive success of the other commercial species in the area. Available data on water temperature, wind speed, and plankton bloom during the spawning season did not reveal conclusive correlations between years with good and bad reproductive success of cod or herring. Notably, the other commercial species in the area have very similar life history traits suggesting similar resilience against stress caused by climate change or fishing. The study concludes that severe, sustained overfishing plus inappropriate size selectivity of the main fishing gears have caused the decline in spawning stock biomass of cod and herring to levels that are known to have a high probability of impaired reproductive success. It is pointed out that allowed catches were regulated by management and adhered to by the fishers, meaning that unregulated fishing did not occur. Thus, mismanagement (quotas that were too high and gears that selected too small sizes) and not climate change appears to be the primary cause of the bad status of cod and herring in the Western Baltic Sea.

A Riemannian Geometric Approach to Blind Signal Recovery for Grant-Free Radio Network Access

We propose a new nonconvex framework for blind multiple signal demixing and recovery. The proposed Riemannian geometric approach extends the well known constant modulus algorithm to facilitate grant-free wireless access for simultaneous demixing and recovery of multiple signal demixing and recovery. We formulate the problem as non-convex problem optimization problem integrated with the signal orthogonality constraint in the form of Riemannian Orthogonal CMA (ROCMA). Unlike traditional stochastic gradient solutions that require large data samples, parameter tuning, and careful initialization, we leverage Riemannian geometry and transform the orthogonality requirement of recovered signals into a Riemannian manifold optimization. Our solution demonstrates full recovery of multiple access signals without large data sample size or special initialization with high probability of success.

The use of FADN methodology to support the evaluation of business development plans in the RDP Sicily 2014-2020

Article 19(4) of Regulation (EU) No 1305/2013 provides that business start-up aid for young farmers, non-agricultural activities in rural areas and the development of small farms shall be conditional on the submission of a business plan.Therefore, this tool, also known as Farm Development Plan (FDP), is mandatory to verify the economic improvement of an investment under sub-measures 6.1 "Business start up aid for young farmers", 4.1 "Investments in agricultural holdings" and operation 6.4.a "Investments in creation and development of non-agricultural activities" so that rural development resources can be directed towards those project ideas which are consistent with the objectives and purposes of the rural development strategy and, thanks to the support, have the highest probability of success. The article presents the lesson learned from the Sicilian experience of designing a web-based tool for FDP submission, namely "PSAWeb Sicilia". This device allowed the Managing Authority (MA) of RDP Sicily 2014-2020 to make available an FDP scheme to users in compliance with EU obligations, consistent with the objectives and purposes of the Programme, as well as with the implementing and procedural provisions of regional calls. The computerised management of the FDPs ensured better coordination between the offices responsible for verifying and evaluating the proposals, while processing and analysis of aggregated data from over 8,400 business plans provided an in-depth knowledge of the investment needs in Sicilian agriculture and a better capacity to forecast the RDP potential response as well as some aspects of specific interest to the regional agricultural system. Thanks to PSAWeb Sicilia, in fact, a large amount of data at farm, sectoral, territorial and type of investment level was collected providing information of inestimable value not available from other data sources. The assessment of access requirements in terms of farms' economic size, economic-financial viability and profitability was ensured by borrowing principles and procedures from the Italian FADN. The cooperation between the MA and CREA-PB achieved several results. Firstly, the data collected combined with the monitoring data have been made available for the evaluation activity and for the communication to the public of the RDP implementation. This information will also be very useful both for better targeting interventions in 2021-22 and for reprogramming them in the future cap. Finally, as a positive externality, the use of the application has contributed to increasing accounting knowledge among operators and technicians in the agricultural sector, so that it has become a teaching tool in some university courses.

GFDM-Based Asynchronous Grant-Free Multiple-Access

For next-generation Internet-of-Things (IoT) networks, asynchronous instant transmission has attracted increasing research interest with the expectation of achieving near-zero latency without excessive initiation procedure. However, in an asynchronous multiple-access scenario, there exist significant inter-carrier interference between sub-carriers allocated to different users. To suppress out-of-band emission (OOBE) of each sub-carrier, a new generalized frequency division multiplexing (GFDM) has been proposed, which has lower OOBE than the conventional orthogonal frequency division multiplexing (OFDM). In this paper, by using GFDM, two types of receivers are proposed with the aim of reducing latency and improving throughput: a GFDM-based minimum mean square error (MMSE) receiver and a GFDM-based MMSE-successive interference cancellation (SIC) receiver. Then, we develop a lightweight scheme using an <inline-formula> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula>-conservative rate control with GFDM-based MMSE receivers and also invent a performance-focused scheme using an advanced rate control with GFDM-based MMSE-SIC receivers. In particular, the latter scheme provides higher throughput with limited increase in computational load of user equipments. Numerical results show that with a high successful transmission probability higher than 99 &#x0025;, the performance-focused scheme and the lightweight scheme achieve up to 85 &#x0025; and up to 70 &#x0025; higher throughput compared to the conventional OFDM-based asynchronous multiple-access scheme, respectively. Furthermore, since our proposal does not require any centralized user scheduling or initiation procedure, it presents a significant reduction in latency compared to the existing low-latency technologies.

The Present and Future of Discrete Logarithm Problems on Noisy Quantum Computers

The discrete logarithm problem (DLP) is the basis for several cryptographic primitives. Since Shor&#x2019;s work, it has been known that the DLP can be solved by combining a polynomial-size quantum circuit and a polynomial-time classical post-processing algorithm. The theoretical result corresponds the situation where a quantum device working with a medium number of qubits of very small errors can solve DLP. However, all the quantum devices that we can use have a limited number of noisy qubits, as of the noisy intermediate-scale quantum (NISQ) era. Thus, evaluating the instance size that the latest quantum device can solve, and give a future prediction of the size along the progress of quantum devices are emerging research topics. This paper contains two proposal to discuss the performance of quantum devices against DLP in the NISQ era. (1) A quantitative measure based on the success probability of the post-processing algorithm to determine whether an experiment on a quantum device (or a classical simulator) succeeded. (2) A procedure to modify bit strings observed from a Shor&#x2019;s circuit to increase the success probability of a lattice-based post-processing algorithm. We conducted our experiments with the <monospace>ibm_kawasaki</monospace> device and discovered that the simplest circuit (7 qubits) from a 2-bit DLP instance achieves a sufficiently high success probability to proclaim the experiment successful. Experiments on another circuit from a slightly harder 2-bit DLP instance, on the other hand, did not succeed, and we determined that reducing the noise level by half is required to achieve a successful experiment. Finally, we give a near-term prediction based on required noise levels to solve some selected small DLP and integer factoring instances.