Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of ADAS Perceptions With Development in China

Due to the growing awareness of driving safety and the development of sophisticated technologies, advanced driving/driver assistance system (ADAS) has been equipped in more and more vehicles with higher accuracy and lower price. The latest progress in this field has called for a review to sum up the conventional knowledge of ADAS, the state-of-the-art researches, novel applications and standards in real world. With the help of this kind of review, newcomers in this field can get basic knowledge easier and other researchers may be inspired with potential future development possibility. This paper makes a general introduction about ADAS by analyzing its hardware support, computation algorithms and current development state. Different types of perception sensors are introduced from their interior feature classifications, installation positions, supporting ADAS functions, and pros and cons. The comparisons between different sensors are concluded and illustrated from their inherent characters and specific usages serving for each ADAS function. The current algorithms for ADAS functions are also collected and briefly presented in this paper from both traditional methods and novel ideas. Additionally, discussions about current regulations and market state of ADAS in China are reviewed in this paper, and other open issues related to ADAS are also introduced in particular.
A GAN-Based Anti-obfuscation Detection Method for Malicious Code

To avoid detection, malicious code developers often use various obfuscation methods to evade detection by malicious code detection systems. In this paper, we propose a GAN-based anti-obfuscation training method for malicious code detection models. The method addresses the problem that the obfuscated malicious code can easily evade the malicious code detector. Based on the idea of adversarial training, the method proposes to use GAN to enhance the data of small samples of obfuscated malicious code samples and use the data-enhanced samples to train the malicious code for anti-obfuscation to improve the detection performance of the malicious code detector against the obfuscated malicious code. Finally, experiments are conducted on three different malicious code detectors, and the experiments show that the anti-obfuscation training method proposed in this paper helps to improve the anti-obfuscation capability of the malicious code detector and enhance its detection performance against the obfuscated malicious code.
Intelligent candidate recommendation system based on experimental calculation of the similarity model

This article describes a system that can significantly improve the candidate selection process for media casting. It allows the impresario company to recommend an optimal set of performers by selecting people who are most likely to fit specific role demands. Several mechanisms interoperate to provide an innovative recommendation system. These include Osgood semantic scale, various NLP techniques and searching in an embedding space. The Polish language corpus for NLP was created using PolishSubtitles, Dictionary of Synonyms, and Dictionary created from Personnel Consulting Agency Database, provided for the authors by cast recruitment company. Before artificial intelligence training, data had to be segmented, lemmatized, and disambiguated in the morph syntactic domain using the Morpheus 2.0 analyzer. The recommendation system described in the paper is very promising due to the applicability of machine learning algorithms and the intelligent user interface. A test, performed by a cast recruitment company, was performed to confirm proposed model viability. Test was concluded in comparision to manual selection process and provided more adequate set of candidates in shorter timeframe.
Dynamic Caching in a Hybrid Millimeter-wave/Microwave C-RAN

Placing popular content at the edge of the network close to users, known as caching, is a promising approach in the 5th generation (5G) of wireless communications in order to lower latency and congestion of fronthaul links. In this paper, we investigate the optimization of caching and fetching decisions to minimize a long-term network cost in a cloud radio access network. Importantly, in our model, the popularities of files vary over time and user requests are considered as arising from hidden-mode Markov decision processes. The primary fronthaul link is modeled as a millimeter-wave (mmWave) link; recognizing that mmWave links may be blocked, we allow for switching to a microwave link. The cache policy at each decision time can influence the network cost in the future, leading to coupled decision variables in time. To deal with the complexity of the resulting optimization problem, we introduce a dynamic programming approach to approximate the future cost of each cache state. The total network cost is minimized at each time-slot while also accounting for the future effects of the decisions taken. To reduce the complexity of calculating the future cost, an approximation approach is introduced and its accuracy is validated numerically. Simulation results confirm the effectiveness of our proposed algorithm to lower the total network cost while dealing with variable popularities.
Online Customer Review Platform Categorization to Identify Market Needs

Today’s globalized business environment has made business demands more dynamic and complex than ever. Accordingly, companies have confirmed that customer demands emanate from online customer review platforms, whose importance they have recognized as being important. There are many studies about extracting market needs from online customer review platforms. However, the research focuses on these processes and is limited to specific platforms. Limitations arise when diverse types of OCR platforms exist, due to processes being limited to a specific platform. Therefore, we categorized these platforms and tested the differences in their underlying market needs information with a quantitative approach. Part-of-speech tagging, named-entity recognition, and lexicon-based sentiment analysis were applied as methodologies. The academic contribution of this study is to suggest that an appropriate data source should be selected according to the market for extracting user review data. A practical contribution of this study is reduced waste of materials and human resources among companies through a basic stage of an optimized analysis process.
Towards Bat Bio-inspired Decision-making for Task Allocation in Vehicular Fogs

Technological evolutions in intelligent transportation have enabled smart and connected vehicles to support novel safety and infotainment services. The provision of such services is guaranteed with effective sharing and allocation of resources for task offloading and processing. The use of vehicular fogs also helps this process by lowering the latency in communications and the resource share among the fog members. However, allocation in Fogs introduces challenges related to the intermittency of Fog vehicle nodes, clustering, topology changes, and resource allocation problems. The use of metaheuristic algorithms has been explored in several works to solve these optimization problems, such as resource allocation, clustering, task allocation, and network communications, especially regarding efficiency. We thus propose a bat bio-inspired decision-making algorithm for task allocation in vehicular fogs called AEGIS. AEGIS uses the cluster members and task parameters to do the decision-making process in the task allocation process that helps to choose the best vehicle of the fog to allocate a determined task. The AEGIS was compared to a GWO approach (meta-heuristic), Greedy, and Random (traditional) approaches. We considered allocated, denied, and lost tasks for the simulation criteria. AEGIS lost fewer tasks than the other algorithms and allocated more tasks than the traditional algorithms.
RF Front-End Transmitting System for Agricultural Applications

In this paper, a design of an RF front-end transmitter for actuating greenhouse plant leaves with electromagnetic wave is proposed. The proposed RF front-end transmitter consists of a phase-locked loop (PLL), variable attenuator, power amplifier (PA), protector and detector circuits, and antenna. The overall circuit is designed for ISM band application with a center frequency of 2.45 GHz. The attenuation range of the variable attenuator is 20 dB. This variable attenuator is connected between PLL and driver PA to control the radiated electromagnetic wave power level for the optimum plant growing condition. The RF power higher than 20 W can be obtained at the output port of PA. The protector and detector circuits consist of the isolator, dual directional coupler, and RF detecting circuits. The isolator is used to protect the PA from the reflected power when the antenna is disconnected from the system. The RF detecting circuits are connected to the couple ports of the dual directional coupler to check long time operation. The designed PAs have been operated very well on humid operating conditions for 14 days.
A Comparison between Crisp and Fuzzy Logic in an Autonomous Driving System for Boats

The adoption of autonomous driving systems is increasingly widespread in land vehicles for private and public transportation and more standards have been defined (among which SAE and ADAS are the most complete). Although in maritime transportation automatic navigation was developed earlier with respect to similar systems developed for land vehicles, there are no standards equivalent to ADAS and SAE. Furthermore, the automation on boats is always partial and refers only to the route planning, obstacle avoiding and motion control functions. In this paper an autonomous driving system in a simulated environment for boats is presented with the attempt to help to define a standard equivalent to those mentioned above. The autonomous driving system presented takes into consideration many simulation aspects and has been developed as a single complete software solution. The design involved both classical approaches and computational intelligence techniques. We distinguish three main implementation phases relating to as many levels of control of the architecture. In this paper, we present only the simulation results related to the mid-level, giving particular attention to the tasks of boat avoidance and docks avoidance (i.e., entry and exit from ports), in which the differences between the crisp and fuzzy logic versions of the same mid-level controllers are highlighted. Results show how fuzzy controllers allow ADS to achieve a lower probability of collision and stall with the same performance as an ADS with crisp controllers. The performance indicator that has been formulated for this work is inspired by Fish Schooling Behavior, which has strong similarities with the self-driving boat problem.
Demand Side Management for Microgrids based on Fuzzy Prediction Intervals

This paper proposes a two-level hierarchical energy management system (EMS) with demand side management (DSM) capabilities for grid-connected microgrids (MGs). The proposed strategy is based on model predictive control (MPC) with prediction intervals obtained through the fuzzy numbers method. While the Main Grid level EMS aims for auto-consumption within the MG, i.e., minimise the energy drawn for the main grid, the Microgrid level tracks power and consumption references, sent from the higher level, to manage the MG resources and the load consumption. Furthermore, fuzzy prediction intervals are used to determine the best-case and worst-case scenarios of operation and modify the load profile while the overall load during the MG operation is maintained. Operation data for generation and consumption from a real urban community is used to validate the performance of the proposed EMS. The results show that the proposed hierarchical EMS with DSM and an adequate prediction case can reduce weekly costs while maintaining overall consumption and a healthy battery usage compared to an EMS that has no way to modify the load. This concludes that a microgrid can improve its performance with the correct predictions and the commitment of the consumers.
SoFIT: Self-Orienting Camera Network for Floor Mapping and Indoor Tracking

We present SoFIT, an easily-deployed and privacy-preserving camera network system for occupant tracking. Unlike traditional camera network-based systems, SoFIT does not require a person to calibrate the network or provide real-world references. This enables anyone, including non-professionals, to install SoFIT. Once installed, SoFIT automatically localizes cameras within the network and generates the floor map leveraging movements of people using the space in daily life, before using the floor map and camera locations to track occupants throughout the environment. We demonstrate through a series of deployments that SoFIT can localize cameras with less than 4.8cm error, generate floor maps with 85% similarity to actual floor maps, and track occupants with less than 7.8cm error.
Ponciri Fructus Immaturus ethanol extract attenuates septic shock through inhibition of the STAT1 signaling pathway

Sepsis is a systemic inflammatory disease to infections and results in tissue damage and multiple organ failure. Ponciri Fructus Immaturus (PFI) is widely used in traditional medicine for allergic inflammation and gastrointestinal disorders. However, the effect of PFI on sepsis is still unknown. This study investigated the anti-inflammatory and antiseptic effects of PFI ethanol extract (PFIE) in LPS-stimulated J774 macrophages and mice with CLP- or LPS-induced sepsis, respectively. PFIE attenuates the LPS-induced production of the proinflammatory mediator NO by inhibiting the expression of iNOS in J774 cells. Real-time RT-PCR data and ELISA showed that the mRNA and protein levels of TNF-α, IL-1β, and IL-6 increased in LPS-stimulated J774 cells. However, this induction was significantly suppressed in PFIE pre-treated J774 cells. We also found that PFIE administration increased the survival rate of mice with LPS- and CLP-induced sepsis. Decreased serum levels of AST, ALT, and CK were observed after administration of PFIE, which was associated with reduced production of proinflammatory factors, such as NO, TNF-α, IL-1β, and IL-6. Moreover, PFIE suppressed the phosphorylation and nuclear translocation of STAT1 in LPS-stimulated J774 cells, suggesting that PFIE can inhibit LPS- and CLP-induced septic shock by suppressing the STAT1 activation. These findings provide the potential therapeutic relevance of PFIE in treating acute inflammatory disease.
Transformational leadership and project success: The mediating role of trust and job satisfaction

Transformational leadership (TFL) impacts on project and organizational success are well established. However, many underlying factors that make TFL effective are still missing. Therefore, we formulated hypotheses and tested the mediating role of trust (TS) and job satisfaction (JS) in linking TFL to project success (PS). A time-lagged methodology was used to collect quantitative data using a structured questionnaire from 326 project manager-team member dyads working in Pakistan’s public sector. Our results showed that TS, JS, and TFL significantly impacted project success. Moreover, we found that TS and JS mediate the relationship between TFL and PS. These findings highlight the importance of trust and job satisfaction as mechanisms that translate TFL into the success of projects for organizations.
PD-1/PD-L1 immune-checkpoint blockade induces immune effector cell modulation in metastatic non-small cell lung cancer patients: A single-cell flow cytometry approach

Peripheral immune-checkpoint blockade with mAbs to programmed cell death receptor-1 (PD-1) (either nivolumab or pembrolizumab) or PD-Ligand-1 (PD-L1) (atezolizumab, durvalumab, or avelumab) alone or in combination with doublet chemotherapy represents an expanding treatment strategy for metastatic non-small cell lung cancer (mNSCLC) patients. This strategy lays on the capability of these mAbs to rescue tumor-specific cytotoxic T lymphocytes (CTLs) inactivated throughout PD-1 binding to PD-L1/2 in the tumor sites. This inhibitory interactive pathway is a physiological mechanism of prevention against dangerous overreactions and autoimmunity in case of prolonged and/or repeated CTL response to the same antigen peptides. Therefore, we have carried out a retrospective bioinformatics analysis by single-cell flow cytometry to evaluate if PD-1/PD-L1-blocking mAbs modulate the expression of specific peripheral immune cell subsets, potentially correlated with autoimmunity triggering in 28 mNSCLC patients. We recorded a treatment-related decline in CD4+ T-cell and B-cell subsets and in the neutrophil-to-lymphocyte ratio coupled with an increase in natural killer T (NKT), CD8+PD1+ T cells, and eosinophils. Treatment-related increase in autoantibodies [mainly antinuclear antibodies (ANAs) and extractable nuclear antigen (ENA) antibodies] as well as the frequency of immune-related adverse events were associated with the deregulation of specific immune subpopulations (e.g., NKT cells). Correlative biological/clinical studies with deep immune monitoring are badly needed for a better characterization of the effects produced by PD-1/PD-L1 immune-checkpoint blockade.
Placoid scales in bioluminescent sharks: Scaling their evolution using morphology and elemental composition

Elasmobranchs are characterised by the presence of placoid scales on their skin. These scales, structurally homologous to gnathostome teeth, are thought to have various ecological functions related to drag reduction, predator defense or abrasion reduction. Some scales, particularly those present in the ventral area, are also thought to be functionally involved in the transmission of bioluminescent light in deep-sea environments. In the deep parts of the oceans, elasmobranchs are mainly represented by squaliform sharks. This study compares ventral placoid scale morphology and elemental composition of more than thirty deep-sea squaliform species. Scanning Electron Microscopy and Energy Dispersive X-ray spectrometry, associated with morphometric and elemental composition measurements were used to characterise differences among species. A maximum likelihood molecular phylogeny was computed for 43 shark species incuding all known families of Squaliformes. Character mapping was based on this phylogeny to estimate ancestral character states among the squaliform lineages. Our results highlight a conserved and stereotypical elemental composition of the external layer among the examined species. Phosphorus-calcium proportion ratios (Ca/P) slightly vary from 1.8-1.9, and fluorine is typically found in the placoid scale. By contrast, there is striking variation in shape in ventral placoid scales among the investigated families. Character-mapping reconstructions indicated that the shield-shaped placoid scale morphotype is likely to be ancestral among squaliform taxa. The skin surface occupied by scales appears to be reduced in luminous clades which reflects a relationship between scale coverage and the ability to emit light. In luminous species, the placoid scale morphotypes are restricted to pavement, bristle- and spine-shaped except for the only luminescent somniosid, Zameus squamulosus, and the dalatiid Mollisquama mississippiensis. These results, deriving from an unprecedented sampling, show extensive morphological diversity in placoid scale shape but little variation in elemental composition among Squaliformes.
Are degraded karst tiankengs coupled with microclimatic underground forests the refugia of surface flora? Evidence from China’s Yunnan

Karst tiankengs, as one of the most magnificent negative topographies, are capable of forming a bank for species diversity conservation easily. More than 300 karst tiankengs have been discovered and identified worldwide. Given its treacherous terrain, although original karst tiankeng were identified as species refuges, the broader distribution of degraded karst tiankeng has not been systematically studied. Our study area comprised the degraded karst tiankeng cluster immersed in the fragmented karst forests of Yunnan, China. Fifty-eight plant samples were selected from karst tiankengs and surface. We compared species composition, and analyzed diversity indices and similarity coefficients to verify the isolation effect of karst tiankengs on floras. The results indicated that: (1) In the degraded karst tiankeng, there were 24 families, 37 genera and 48 species in the tree layer and 27 families, 43 genera and 49 species in the shrub layer. Outside the degraded karst tiankengs, 20 families, 31 genera and 39 species were in the tree layer, and the shrub layer included 26 families, 44 genera and 55 species. (2) The species composition reached significant differences within and outside degraded karst tiankeng (p < 0.05) based on the analysis of variance (ANOVA). (3) In the degraded karst tiankeng, species richness/diversity in trees were higher than those in the shrub layer, while at the surface, shrubs had higher richness and lower diversity than trees by Alpha-diversity index. And for Beta-diversity index, species similarity among degraded karst tiankengs (0.215) was extremely dissimilar, which was even lower than the contrast within and outside the degraded karst tiankengs (0.272). (4) Shared species ranged from 1 to 5 among the four habitats, with high variability in plant species across the habitat matrices. Through a comparative analysis of systematic biodiversity methods, we found that the degraded karst tiankengs, an independent type of karst tiankeng, are the unreported refugia. Species records in degraded karst tiankeng cluster will contribute to plant diversity conservation and resource management, and to the linkage with broader China’s karst floras. Karst tiankeng botanical habitats possess not only biodiversity value for in situ conservation, but will further support the ecological recovery of surface flora. While its mechanism needs to be further revealed.
The relationship between tobacco and breast cancer incidence: A systematic review and meta-analysis of observational studies

Background The effect of tobacco on breast cancer (BC) is controversial. The purpose of this study was to investigate the relationship between tobacco and BC. Methods A search was conducted in PubMed, EBSCO, Web of Science and Cochrane Library databases before February 2022. The adjusted odd ratio (OR) and corresponding 95% confidence interval (CI) were used to examine the relationship between active or passive smoking and BC risk. Results A total of 77 articles composed of 2,326,987 participants were included for this meta-analysis. Active (OR=1.15, 95% CI=1.11-1.20, p<0.001) and passive (OR=1.17, 95% CI=1.09-1.24, p<0.001) smoking increased the risk of BC in the female population, especially premenopausal BC (active smoking: OR=1.24, p<0.001; passive smoking: OR=1.29, p<0.001), but had no effect on postmenopausal BC (active smoking: OR=1.03, p=0.314; passive smoking: OR=1.13, p=0.218). Active smoking increased the risk of estrogen receptor-positive (ER+) BC risk (OR=1.13, p<0.001), but had no effect on estrogen receptor-negative (ER-) BC (OR=1.08, p=0.155). The risk of BC was positively associated with the duration and intensity of smoking, negatively associated with the duration of smoking cessation. Active smoking increased the risk of BC in the multiparous population (OR=1.13, p<0.001), but had no effect on the nulliparous population (OR=1.05, p=0.432), and smoking before the first birth (OR=1.22, 95% CI=1.17-1.27) had a greater impact on the risk of BC than smoking after the first birth (OR=1.08, 95% CI=1.04-1.12). Conclusion Smoking (active and passive) increased the risk of BC in women. The effect of smoking on BC was influenced by smoking-related factors (duration, intensity, years of quitting), population-related factors (fertility status), and BC subtypes. Systematic Review Registration identifier CRD42022322699.