Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine Intelligence at the Edge With Learning Centric Power Allocation

While machine-type communication (MTC) devices generate considerable amounts of data, they often cannot process the data due to limited energy and computational power. To empower MTC with intelligence, edge machine learning has been proposed. However, power allocation in this paradigm requires maximizing the learning performance instead of the communication throughput, for which the celebrated water-filling and max-min fairness algorithms become inefficient. To this end, this paper proposes learning centric power allocation (LCPA), which provides a new perspective on radio resource allocation in learning driven scenarios. By employing 1) an empirical classification error model that is supported by learning theory and 2) an uncertainty sampling method that accounts for different distributions at users, LCPA is formulated as a nonconvex nonsmooth optimization problem, and is solved using a majorization minimization (MM) framework. To get deeper insights into LCPA, asymptotic analysis shows that the transmit powers are inversely proportional to the channel gains, and scale exponentially with the learning parameters. This is in contrast to traditional power allocations where quality of wireless channels is the only consideration. Last but not least, a large-scale optimization algorithm termed mirror-prox LCPA is further proposed to enable LCPA in large-scale settings. Extensive numerical results demonstrate that the proposed LCPA algorithms outperform traditional power allocation algorithms, and the large-scale optimization algorithm reduces the computation time by orders of magnitude compared with MM-based LCPA but still achieves competing learning performance.
Extremal functions for a class of trace Trudinger-Moser inequalities on a compact Riemann surface with smooth boundary

In this paper, we concern trace Trudinger-Moser inequalities on a compact Riemann surface with smooth boundary. This kind of inequalities were extensively studied by Osgood-Phillips-Sarnak [24], Liu [20], Li-Liu [17], Yang [31, 32] and others. We establish several trace Trudinger-Moser inequalities and obtain the corresponding extremals via the method of blow-up analysis. The results in the current paper generalize those of Li-Liu [17] and Yang [32, 33].
Integrating Immunotherapy with Chemotherapy: A New Approach to Drug Repurposing

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype lacking the three hormonal receptors namely estrogen receptor, progesterone receptor and HER2 receptor, and the only treatment option available for TNBC is chemotherapy. Chemotherapy lacks specificity since it acts on normal healthy cells as well resulting into secondary diseases in TNBC patients. In addition chemotherapy poses recurrence and relapse issues due to the development of chemoresistance among TNBC patients. Immunotherapy remarkably immune checkpoint inhibitors show a great therapeutic potential in TNBC. As TNBC contain an increased TILs (tumor infiltrating lymphocytes) infiltration making it more suitable as a therapeutic target anti-tumor immune strategy. Moreover, evidences have indicated that chemotherapy upregulates the anti-tumor immune response in TNBC. As a result, a combination of immunotherapy with chemotherapy may increase the overall relapse and recurrence free survival of TNBC patients. Therefore, in this chapter we will focus on how the immunotherapy works in TNBC, their effects and consequences. We will further be discussing the clinical studies and the importance of immune checkpoint inhibitors (ICIs) in combination with various therapeutic agents and target. Further, we will explore the processes involved.
Identification of High-Risk Driving Behavior and Sections for Rail Systems

Risk assessment is an important process for railway safety. Current practices for assessing the risks of driving behaviors aim to inspect the driving record generated by automatic train protection systems. This paper proposes an automatic process to access detailed data contained in driving data, and identifies six high-risk driving behaviors. The modules can assess the competency of drivers and evaluate the frequency of high-risk behaviors in each section. Moreover, an integrated risk index for driving behaviors is proposed to compare each driver and section. An empirical study for drivers and sections is performed to demonstrate the feasibility of applying the proposed modules in practice. Results reveal that 20% of high-risk drivers contribute to 74% of the total risk, while 15% of high-risk sections contribute to 80% of the total risk. The proposed modules identify the drivers and sections with high risk. By enabling the operators of railway systems to take countermeasures, this methodology could enable them to improve the safety of railway systems more efficiently.
Wisata “Manyamabraya”: Paket Wisata “Ajeg Bali” Berbasis Local Genius

This research is a qualitative research that aims to describe "manyamabraya" tourism based on local genius in the Mengali Traditional Village, Sawan-Buleleng District. The research data were collected using documentation, interview, and observation techniques with research instruments in the form of interview guides and observation sheets. The data collected was then analyzed descriptively qualitatively by following the interactive analysis method proposed by Miles and Huberman (1994). This study concludes that, (1) "Manyamabraya" tourism based on local genius in the Mengali Traditional Village is a tourism concept that provides the opportunity for tourists to be directly involved in the socio-cultural life of the community in the Mengali Traditional Village, (2) This tour was developed because of the natural and cultural potential which is very suitable to be developed into a cultural-based tourist destination, as well as the weakness of the community's economy has encouraged creative ideas to develop this "manyamabraya" tourism, (3) The "manyamabraya" tourism is managed directly independently by the community of the Mengali Indigenous Village, starting from providing accommodation, tourist activities, food, drinks and entertainment
Ionic liquids for the preparation of biopolymer materials for drug/gene delivery: a review

Biopolymers are particularly suitable for drug applications due to their biocompatibility, biodegradability, and low immunogenicity. There has been growing interest in using biopolymers to achieve the controlled release of therapeutics. However, the solubility and processability of biopolymers remain challenging due to their structural heterogeneity and dense networks of inter- and intramolecular interactions. Fortunately, ionic liquids (ILs), regarded as green solvents, have been increasingly appreciated for their unparalleled power for biopolymer processing. By the dissolution of biopolymers in ILs, various materials including sponges, films, microparticles (MPs), nanoparticles (NPs), and aerogels can be generated as potential drug delivery carriers. Besides, ILs can be used as reaction media and/or catalysts for biopolymer chemical reactions, which show enhanced reaction efficiencies. In addition, because of their unique physicochemical (e.g., polarity, hydrophobicity, amphipathicity and miscibility) and biological properties (e.g., antibacterial activity), ILs can assist or participate in the formation of drug delivery carriers. To cover all these aspects of the research, this review provides an overview of the recent progress in using ILs for the engineering of next-generation drug/gene delivery carrier materials. The tunable properties of ILs as affected by their structures are highlighted. Also, the key principles, challenges and prospects of this area are presented.
Researcher Perceptions of a Self-Service Online Portal to Facilitate Volunteer Recruitment into Clinical Trials

Abstract Background Recruitment of volunteers is a major challenge for clinical trials. There has been increasing development and use of Internet-based portals in recruitment for clinical research. There has been little research on researcher use and perceptions of these portals. Objectives This study evaluated researcher perceptions of use of Rally, an Internet-based portal for clinical trial volunteer recruitment. Methods A cross-sectional survey was developed and implemented to understand researcher perceptions. From theoretical models of information technology use, the survey adopted items in four domains: ease of use, usefulness, facilitating conditions, and self-efficacy. The dependent variable was researchers' behavioral intention to use Rally. The survey captured characteristics of researchers such as gender, age, and role. It was implemented using the REDCap survey tool. An email invitation followed by three reminders was sent to researchers. A hierarchical regression model was applied to assess predictors of behavioral intention. Results The survey response rate was 35.6% (152 surveys received from 427 contacted researchers). In the hierarchical regression model, facilitating conditions and self-efficacy predicted behavioral intention (F (4,94) = 6.478; p <0.001). The model explained 21.6% of the variance in behavioral intention (R-square change = 21.3%, p <0.001). Conclusion Facilitating conditions and self-efficacy predicted researchers' behavioral intention to use Rally for volunteer recruitment into clinical trials. Future research should document best practices and strategies for enhancing researcher use of online portals for volunteer recruitment.
A Survey on Why-Type Question Answering Systems

Search engines such as Google, Yahoo and Baidu yield information in the form of a relevant set of web pages according to the need of the user. Question Answering Systems reduce the time taken to get an answer, to a query asked in natural language by providing the one most relevant answer. To the best of our knowledge, major research in Why-type questions began in early 2000's and our work on Why-type questions can help explore newer avenues for fact-finding and analysis. The paper presents a survey on Why-type Question Answering System, details the architecture, the processes involved in the system and suggests further areas of research.
Family firm succession in tourism and hospitality: an ethnographic case study approach

PurposeGrounded in stewardship theory, this study explores the motives, actions and meanings of multiple stakeholders involved in an inter-family hospitality family firm succession.Design/methodology/approachA longitudinal, ethnographic case study approach collects data from 15 in-depth interviews, one year of observation and a one-month on-site internship.FindingsResults show that a well-defined succession plan and the active involvement of the successor/s in the succession process would foster a strong stewardship commitment to the family business. Moreover, a clear and open communication strategy is required to strategically manage rivalry and competition among potential successors during an inter-family succession.Originality/valueThe succession process of family firms remains an intensely discussed phenomenon, and despite its importance to the tourism and hospitality industry, the intersection between tourism and hospitality and family business literature is sparse. Notably, the tourism and hospitality literature lacks a multiple stakeholder perspective to holistically capture the motives, actions and meanings of numerous stakeholders involved in an inter-family succession.
Kinematic analysis with motion sensors in kayakers: A study with boyacense athletes

Objective: The results of the stroke cycle kinematic analysis of a group of kayakers from a city of Colombia are presented, using a motion capture platform based on inertial and magnetic sensors. Method: Quantitative approach of a cross-sectional descriptive type. A group participated with similar anthropometric characteristics such as size, mass, and body mass index. A technological platform was used that allowed the measurement of the kinematics of their movements from the first stroke cycle until the end at a 200-metre distance. Results: With the use of inertial and magnetic sensors, a comparative study of the kayakers of the sample was carried out, verifying that the distance reached by the boat in every stroke is greater on the right side with a distance of 3.651 metres and the minimum on the left side with a distance of 0.762 centimetres. The smaller amount of strokes that were made in the 200-meter test was 81 strokes/minute and the best displacement average was 2.387 meters, data that allow the measurement of the speed, displacement of the boat and number of strokes, are the most important factors to obtain better marks in this sport discipline. Conclusions: The lack of preparation of the kayakers was demonstrated since the stroke cycle in the aerial and aquatic phases is deficient, as the paddle blade does not enter the water in its maximum amplitude and the fluctuation in the control of the rate are factors that generate a smaller displacement of the boat.
Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection

Markov blanket feature selection, while theoretically optimal, generally is challenging to implement. This is due to the shortcomings of existing approaches to conditional independence (CI) testing, which tend to struggle either with the curse of dimensionality or computational complexity. We propose a novel two-step approach which facilitates Markov blanket feature selection in high dimensions. First, neural networks are used to map features to low-dimensional representations. In the second step, CI testing is performed by applying the k-NN conditional mutual information estimator to the learned feature maps. The mappings are designed to ensure that mapped samples both preserve information and share similar information about the target variable if and only if they are close in Euclidean distance. We show that these properties boost the performance of the k-NN estimator in the second step. The performance of the proposed method is evaluated on synthetic, as well as real data pertaining to datacenter hard disk drive failures.
Across the benthic and pelagic realms: a species‐level phylogeny of Benthesicymidae (Crustacea : Decapoda)

Abstract. Benthesicymidae is a monophyletic group of Decapoda adapted to a life on the sea-floor, in the near-bottom layer, in the bathy- and in the mesopelagic, within an impressive depth range from a few hundred metres (Gennadas) to several thousand metres (Benthesicymus). Higher taxa are known to conquer all main oceanic biotopes such as the benthic, benthopelagic, and pelagic and a wide depth range but few family-level groups have clades evolved within all these oceanic realms. Therefore, the global fauna of Benthesicymidae provides a rare opportunity for an insight into phylogenetic processes favouring colonisation of all principal oceanic biotopes. The first comprehensive phylogenetic study of Benthesicymidae (all 37 valid species) is based on six molecular markers and 105 morphological characters (including 72 female and male copulatory characters). Analyses resulted in trees with similar topology and the same set of robust clades. Molecular methods based on 167 sequences (84 new) provided better resolution of deeper nodes and generally higher support of the clades, while morphological methods allowed analyses of all valid species of the global fauna. Phylogenetic analyses support the monophyly and robustness of all currently known genera except Gennadas, which was split into Gennadas Bate, 1881, Amalopenaeus Smith, 1882, and Notogennema gen. nov. We also retrieved two major clades for which we erected two new subfamilies: Benthesicyminae subfam. nov. (presumably benthic, genera Altelatipes, Bathicaris, Benthesicymus, and Benthonectes) and Gennadinae subfam. nov. (presumably pelagic, genera Amalopenaeus, Bentheogennema, Benthoecetes, Boreogennema, Gennadas, Maorrancaris, and Notogennema gen. nov.). We revealed two groups of morphological characters, that are interlinked evolutionarily: (1) petasma and thelycum; (2) body, mouthparts, and pereopods. Morphological traits within benthic and pelagic clades are different, a model explaining the differences is proposed. Along with previous studies, our results confirm the idea that the elaboration of the copulatory structures is a key to successful colonisation of the pelagic realm. These results extend our knowledge about evolution in the largest habitual biotope of our planet and phylogenetic processes favouring colonisation of all principal oceanic biotopes.
Morphological and Molecular Characterization of Trichoderma spp. from Rhizosphere Soil and Their Antagonistic Activity against Fusarium spp.

Trichoderma species are well known for their biocontrol activity which colonize many soil and tuber-borne and foliage plant pathogens. In this study, 12 native isolates of Trichiderma spp were collected from various crop rhizosphere soil samples and characterized them phenotypically based on morphological and cultural features and genotypically based on sequence analysis of internal transcribed spacer (ITS) region-PCR amplification. The results obtained from phenotypic and genotypic observation revealed that isolates were belonged to five different species namely T. asperellum, T. harzianum, T. longibrachiatum, T. koningii and T. koningiopsis. All Trichoderma isolates produced ~600 bp amplicon and phylogenetic analysis revealed that all isolates were grouped with respective species. Further, the antagonistic potential of all the isolates was evaluated against Fusarium spp. following in vitro dual culture method. The results showed that isolates of T. harzianum exhibited maximum growth inhibition activity. The highest rate of inhibition was recorded with T. harzianum isolate TBT6 (87.1%) followed by TBT7 (82.2%), while the least inhibition was observed in T. longibrachiatum isolate TBT10 (59.7%) after 7 days of incubation. The antagonistic T. harzianum isolate TBT6 can be used for development of Trichoderma based bio-formulation and served as bio-control agent against Fusaium spp. under field conditions.
PSEUDO-DYNAMIC ANALYSES OF INFILLED REINFORCED CONCRETE FRAMED STRUCTURES WITH PRIOR DAMAGES AFTER ADVANCED RETROFIT

This study investigates suitable models for the analysis of innovative retrofits in infilled (and bare) reinforced concrete frames. It focuses on the detrimental effects of prior damages and deficiencies in frames such as corroded steel reinforcements or inadequate lap-splices in columns that may lead to premature failures and structural collapses. It investigates numerically the beneficial effects of innovative interventions on deficient RC frames, through pseudo-dynamic 3-dimensional finite element analyses. The intervention involves infill wall with special thermal insulating clay brick orthoblocks, having at the boundary interface with the RC frame, an advanced seismic joint made of highly deformable polyurethane. The technique has been already validated experimentally in frames without corroded or lap-spliced bars [1] (as well as for a four-column structure in project named “INfills and MASonry structures protected by deformable POLyurethanes in seismic areas” – INMASPOL [2,3]). The analyses suggest that the 3dimensional FE models may reproduce with satisfactory accuracy the mechanical behavior of FRP retrofitted deficient columns. Further, they suggest that the deficient RC frames after the innovative composite retrofit achieve higher base shear load than the original bare RC frame without corroded or lap-spliced bars, at comparable top displacement ductility.
Green Photoluminescent Methodology for Aluminium Traces Quantification in 24-Hour Urine of Subjects with Different Exposition to Tobacco Smoke

The aim of this work has been to evaluate the aluminium (Al(III)) traces contents in 24-hour urine samples from subjects with different tobacco smoke expositions using a new methodology with 1,4-dihydroxy-9, 10-anthraquinone (Quinizarine, QZ) as a fluorosphore. Biological samples were tested using commercial reagent strips and clinical parameters. Al(III) was determined complexing with QZ followed by a solid phase extraction step using Nylon membranes as a solid support. The analyte was subsequently quantified by solid surface fluorescence (SSF, λem= 573, λexc= 490) with a detection limit of 0.88 μg L-1 and quantification limit of 2.69 μg L-1. The calibration curve was linear from 2.69 to 499.13 μg L-1 Al(III) (R2 = 0.9973). Urine samples were successfully analysed with an average recovery close to 100%. Solid phase extraction step showed efficacy to eliminate foreign ions and the highly fluorescent matrix own of urine. Results were validated by electrothermal atomic absorption spectrometry (ETAAS) with an adequate concordance. The new methodology has low operation cost with simple instrumentation and without organic solvent.
Using Data Augmentation and Time-Scale Modification to Improve ASR of Children’s Speech in Noisy Environments

Current ASR systems show poor performance in recognition of children’s speech in noisy environments because recognizers are typically trained with clean adults’ speech and therefore there are two mismatches between training and testing phases (i.e., clean speech in training vs. noisy speech in testing and adult speech in training vs. child speech in testing). This article studies methods to tackle the effects of these two mismatches in recognition of noisy children’s speech by investigating two techniques: data augmentation and time-scale modification. In the former, clean training data of adult speakers are corrupted with additive noise in order to obtain training data that better correspond to the noisy testing conditions. In the latter, the fundamental frequency (F0) and speaking rate of children’s speech are modified in the testing phase in order to reduce differences in the prosodic characteristics between the testing data of child speakers and the training data of adult speakers. A standard ASR system based on DNN–HMM was built and the effects of data augmentation, F0 modification, and speaking rate modification on word error rate (WER) were evaluated first separately and then by combining all three techniques. The experiments were conducted using children’s speech corrupted with additive noise of four different noise types in four different signal-to-noise (SNR) categories. The results show that the combination of all three techniques yielded the best ASR performance. As an example, the WER value averaged over all four noise types in the SNR category of 5 dB dropped from 32.30% to 12.09% when the baseline system, in which no data augmentation or time-scale modification were used, was replaced with a recognizer that was built using a combination of all three techniques. In summary, in recognizing noisy children’s speech with ASR systems trained with clean adult speech, considerable improvements in the recognition performance can be achieved by combining data augmentation based on noise addition in the system training phase and time-scale modification based on modifying F0 and speaking rate of children’s speech in the testing phase.