Challenging Work Research Articles

How community and organizational culture interact and affect senior clinical educator identity

Purpose The development of Educator Identity has a significant impact on well-being, motivation, productivity, and the quality of teaching. Previous research has shown that conflicting responsibilities and a challenging work environment could negatively affect the development of Clinical Educator Identity within an organization. However, there is a lack of research that identifies the factors affecting Clinical Educator Identity Formation and provides guidance on how organizations can support its development, maintenance, and advancement. Methods To examine the phenomenology of Professional Identity Development in experienced Senior Clinical Educators in Singaporean hospitals, the study utilized an exploratory qualitative approach. The data was collected from September 2021 to May 2022 through one-to-one interviews. Four investigators analyzed the data using constant comparative analysis to identify relevant themes. Results Eleven senior educators revealed that personal, relational, and organizational factors influenced the development of Clinical Educator Identity. The relational aspect was a vital enabler, while organizational culture was a strong barrier. The study also identified several ways in which organizations can support Educator Identity development. Conclusion The study findings provide insight into how organizations can support the development of Clinical Educator Identity. The results could aid organizations in understanding the areas where they can channel resources to support Clinical Educator Identity development.

Development of vanillin-based crosslinking agent with phase-locked dynamic imine bonds for shape-memory polyurethanes

Scientists have gained so much attention due to one of polyurethane's tuneable and unique characteristics, i.e., the shape-memory effect. But, the simplistic fabrication of such materials persists a challenging work. In the current work, we report the synthesis and detailed characterization of shape-memory polyurethane obtained by incorporating lower concentrations of imine bonds, which readily undergo phase-locking systems beneficial for microphase separation. A symmetric imine moiety (DIM) was designed through the simple Schiff-base reaction of naphthalene diamine and vanillin. The tensile strength of the films reached up to 30 MPa with an %elongation of 87% by tuning the hard segment content and the concentration of imine bonds. Also, in the meantime, the films showed excellent shape memory effect, where the shape could recover its original form within 2 s at the highest loading of DIM. The remarkable balance between the mechanical properties and the shape memory effect could be associated with the two main factors. Firstly, incorporating symmetrical and rigid CN along with the naphthalene promoted the microphase separation and smoothened the orientation of the chain segments at the strain-induced crystallization at lower temperatures. Secondly, the phase locking occurred at lowered temperatures due to dynamic imine exchange reaction and H-bonding. The phase recovery started, and chains settled at their original positions once the temperature was elevated.

Association between Pharmacists' Country of Qualifying Education and Practising in a Hospital Setting: A Cross-Sectional Ontario Study.

It is hypothesized that international pharmacy graduates (IPGs) are underrepresented in more clinically challenging work. To examine the association between country of qualifying education for pharmacists in Ontario and the likelihood of practising in a hospital setting. This study was based on publicly available data from the Ontario College of Pharmacists website, specifically records for all Ontario pharmacists with authorization to provide patient care and for whom country of qualifying education and an accredited pharmacy as a place of practice were reported. Pharmacists who met the inclusion criteria were categorized as Canadian graduates or IPGs. The odds ratio (OR) and 95% confidence interval (CI) for reporting hospital pharmacy as a place of practice were estimated by fitting a logistic regression, with adjustment for gender and years since graduation. A total of 14 689 pharmacists were included in the study: 7403 (50.4%) Canadian graduates and 7286 (49.6%) IPGs. These pharmacists worked in a total of 5028 accredited pharmacies (243 hospital pharmacies [4.8%] and 4785 community pharmacies [95.2%]). Among Canadian graduates, 2458 (33.2%) reported at least 1 hospital pharmacy practice site, whereas the proportion was much smaller among IPGs (427, 5.9%). Canadian graduates represented 85.2% (2458/2885) of all pharmacists who reported hospital practice. The estimated crude OR for practice in a hospital pharmacy was 7.98 (95% CI 7.16-8.91), and the adjusted OR was 7.12 (95% CI 6.39-7.98). IPGs may face barriers impeding their ability to practise in a hospital setting. Providing opportunities such as structured clinical training and experiential placements may facilitate integration of IPGs in institutional settings.

OptiDJS+: A Next-Generation Enhanced Dynamic Johnson Sequencing Algorithm for Efficient Resource Scheduling in Distributed Overloading within Cloud Computing Environment

The continuously evolving world of cloud computing presents new challenges in resource allocation as dispersed systems struggle with overloaded conditions. In this regard, we introduce OptiDJS+, a cutting-edge enhanced dynamic Johnson sequencing algorithm made to successfully handle resource scheduling challenges in cloud computing settings. With a solid foundation in the dynamic Johnson sequencing algorithm, OptiDJS+ builds upon it to suit the demands of modern cloud infrastructures. OptiDJS+ makes use of sophisticated optimization algorithms, heuristic approaches, and adaptive mechanisms to improve resource allocation, workload distribution, and task scheduling. To obtain the best performance, this strategy uses historical data, dynamic resource reconfiguration, and adaptation to changing workloads. It accomplishes this by utilizing real-time monitoring and machine learning. It takes factors like load balance and make-up into account. We outline the design philosophies, implementation specifics, and empirical assessments of OptiDJS+ in this work. Through rigorous testing and benchmarking against cutting-edge scheduling algorithms, we show the better performance and resilience of OptiDJS+ in terms of reaction times, resource utilization, and scalability. The outcomes underline its success in reducing resource contention and raising service quality generally in cloud computing environments. In contexts where there is distributed overloading, OptiDJS+ offers a significant advancement in the search for effective resource scheduling solutions. Its versatility, optimization skills, and improved decision-making procedures make it a viable tool for tackling the resource allocation issues that cloud service providers and consumers encounter daily. We think that OptiDJS+ opens the way for more dependable and effective cloud computing ecosystems, assisting in the full realization of cloud technologies’ promises across a range of application areas. In order to use the OptiDJS+ Johnson sequencing algorithm for cloud computing task scheduling, we provide a two-step procedure. After examining the links between the jobs, we generate a Gantt chart. The Gantt chart graph is then changed into a two-machine OptiDJS+ Johnson sequencing problem by assigning tasks to servers. The OptiDJS+ dynamic Johnson sequencing approach is then used to minimize the time span and find the best sequence of operations on each server. Through extensive simulations and testing, we evaluate the performance of our proposed OptiDJS+ dynamic Johnson sequencing approach with two servers to that of current scheduling techniques. The results demonstrate that our technique greatly improves performance in terms of makespan reduction and resource utilization. The recommended approach also demonstrates its ability to scale and is effective at resolving challenging work scheduling problems in cloud computing environments.

Soft Subspace Based Ensemble Clustering for Multivariate Time Series Data.

Recently, multivariate time series (MTS) clustering has gained lots of attention. However, state-of-the-art algorithms suffer from two major issues. First, few existing studies consider correlations and redundancies between variables of MTS data. Second, since different clusters usually exist in different intrinsic variables, how to efficiently enhance the performance by mining the intrinsic variables of a cluster is challenging work. To deal with these issues, we first propose a variable-weighted K-medoids clustering algorithm (VWKM) based on the importance of a variable for a cluster. In VWKM, the proposed variable weighting scheme could identify the important variables for a cluster, which can also provide knowledge and experience to related experts. Then, a Reverse nearest neighborhood-based density Peaks approach (RP) is proposed to handle the problem of initialization sensitivity of VWKM. Next, based on VWKM and the density peaks approach, an ensemble Clustering framework (SSEC) is advanced to further enhance the clustering performance. Experimental results on ten MTS datasets show that our method works well on MTS datasets and outperforms the state-of-the-art clustering ensemble approaches.

Minority of Male Teachers in Kindergartens as a Result of Gender Stereotypes in Society

The phenomenon of the minimum number of male kindergarten teachers is increasingly visible in Indonesia, so that people increasingly think that kindergarten teachers are a woman's profession. This results in an imbalance of gender roles in Kindergarten. Discussion of gender-related issues in kindergarten is considered too commonplace and often escapes society's attention. The aim of this research is to describe and analyze gender stereotypes which result in a minority of male teachers in kindergarten. Not only that, this research also provides an alternative view of the role of a man as a teacher in kindergarten. This research is a literature study that uses a qualitative approach. The results of this research are stereotypes that grow and develop in society regarding male kindergarten teachers, including; firstly, kindergarten teachers are attached to feminine traits, while men are attached to masculine traits, secondly, the assumption is that male kindergarten teachers are "gay", thirdly, the kindergarten profession which is not financially promising is not suitable for men who are charged with the role of "backbone", fourth, men must have challenging work, while the profession of kindergarten teacher is a profession that is not challenging and has low risk.

Sharing Model Framework for Zero‐Shot Sketch‐Based Image Retrieval

AbstractSketch‐based image retrieval (SBIR) is an emerging task in computer vision. Research interests have arisen in solving this problem under the realistic and challenging setting of zero‐shot learning. Given a sketch as a query, the search goal is to retrieve the corresponding photographs in a zero‐shot scenario. In this paper, we divide the aforementioned challenging work into three tasks and propose a sharing model framework that addresses these problems. First, the weights of the proposed sharing model effectively reduced the modality gap between sketches and photographs. Second, semantic information was used to handle different label spaces during the training and testing stages. The sketch and photograph domains share semantic information. Finally, a memory mechanism is used to reduce the intrinsic variety in sketches, even if they all belong to the same class. Sketches and photographs dominate the embeddings in turn. Because sketches are not limited by language, our ultimate goal is to find a method to replace text searches. We also designed a demonstration program to demonstrate the use of the proposed method in real‐world applications. Our results indicate that the proposed method exhibits considerably higher zero‐shot SBIR performance than do other state‐of‐the‐art methods on the challenging Sketchy, TU‐Berlin, and QuickDraw datasets.

Diverse Origins of Gases From Mud Volcanoes and Seeps in Tectonically Fragmented Terrane

AbstractIdentification of methane origins remains a challenging work as current diagnostic signals are often not sufficient to resolve individual formation and post‐formation processes. To address such a knowledge gap in a tectonically active and fragmented terrain, samples from mud volcanoes, gas seeps, and springs distributed along structural features onshore and offshore of Taiwan were analyzed for their isotopic compositions of methane, nitrogen, helium, dissolved inorganic carbon, CO2, and water. Our analyses yielded Δ13CH3D and Δ12CH2D2 values ranging between +1.9‰ and +7.8‰ and between +3.0‰ and +19.9‰, respectively. A portion of the samples were characterized by values that represent the thermodynamic equilibrium at temperatures of 99°–260°C. These temperature estimates, together with the bulk isotopic compositions and local geothermal gradients (25°–30°C/km), suggest that methane was formed by thermal maturation of organic matter at depths of 2–9 km below the land surface and channeled upward along faults. Other samples were found to deviate from equilibrium by varying degrees. Considering the geological background, helium isotopic ratios, and nitrogen isotopologue compositions, and methanogens detected at some sites, these gases are either abiotic in origin or a mixture of microbial and thermogenic sources. Regardless of whether the equilibrium of methane isotopologues was reached, few sites hosted by sedimentary formations were characterized by mantle‐like helium signatures, indicating decoupled origins and potential degassing of helium from the relic igneous source. Overall, these results suggest the extraction of methane and other gases from multiple depths from strata fragmented by fault displacement in an active orogenic belt.

Resilience and empathy in pharmacy interns: Insights from a three-year cohort study

BackgroundResilience and empathy are important attributes for healthcare professionals to navigate challenging work environments and providing patient-centred care. Knowledge about pharmacists' levels of resilience and empathy, particularly during the early stages of their careers, is limited. ObjectivesTo explore pharmacy interns' levels of resilience and empathy using the Connor-Davidson-Resilience-Scale-25 (CD-RISC-25) and the Kiersma-Chen-Empathy-Scale (KCES), examine potential associations with demographic characteristics and ascertain what challenges interns' resilience and which support mechanisms they identify. MethodsHard copies of the surveys were distributed to three cohorts during face-to-face intern pharmacy workshops from 2020 to 2022. Additionally, a qualitative questionnaire explored interns' experiences while completing an accredited internship program during the COVID-19 pandemic. Data were analysed using descriptive and inferential statistics, open-ended questions were analysed through qualitative and quantitative content analysis. ResultsAmong 134 completed surveys, most respondents were female, aged 18–22, and worked in hospitals. The CD-RISC-25 mean score was 66.6 (SD 11.7) and the KCES mean was 84.3 (SD 9.23) indicative of intermediate levels of resilience and empathy. Resilience and empathy scores did not significantly differ between the three cohorts (p-value > 0.05), and both were not consistently correlated with each other (p-value > 0.05). No significant associations were found between demographic characteristics and resilience scores. However, age and pre-internship employment history showed a statistically significant association with empathy scores (p-value < 0.05), with younger age groups and those who worked part-time during undergraduate studies demonstrating higher levels of empathy. Challenges undermining interns' resilience included the COVID-19 pandemic, internship requirements, and feelings of inadequacy and inexperience. ConclusionsThis study showed that resilience and empathy scores among interns were at what can be regarded as intermediate levels, largely unaffected by the COVID-19 pandemic or cohort demographics. It highlights professional aspects and strategies which are professionally sustaining and may assist interns in navigating challenges to their resilience and empathy.

Digital twin model-based smart assembly strategy design and precision evaluation for PCB kit-box build

Research concerning microelectronics assembly has attracted increasing attention from the manufacturing industry. In this context, achieving precise placement of the printed circuit board (PCB) inside the enclosure is the most critical aspect of the kit-box build assembly task. However, automating the PCB kit-box build assembly (PKBA) process remains a challenging work. This study presents a Digital Twin (DT) model that enables accurate perception of object pose for intelligent PKBA assembly, facilitating real-time monitoring and evaluation of its service status. In our system, a symmetry-drive method is proposed to optimize the initial pose in 6-DoF matching during DT assembly. Based on the developed technology, a three-stage learning method is established to achieve grasping point localization and robotic assembly trajectory planning. To ensure accurate and robust robot assembly, we developed a PKBA quality prediction model based on the DT system, which predicts the uncertainty of actual PCB assembly positioning by small displacement torsor (SDT) theory and Monte Carlo methods. Particularly, the assembly quality of the actual product is effectively monitored when the state of the virtual simulation model corresponds to the physical assembly object. Finally, a prototype system and a case study involving dexterous assembly tasks are conducted to verify the effectiveness and feasibility of the proposed method. The results indicate that the proposed PKBA strategy achieves an 82% assembly success rate. By employing well-designed strategies, our method ensures that the majority of errors are below 0.8 mm and 0.6 degrees.

Atomic Layer Deposition of Defective Amorphous TiOx Thin Films with Improved Photoelectrochemical Performance.

A proper control of defects in TiO2 thin films is challenging work for enhancing the photoelectrochemical (PEC) efficiency in water splitting processes. Additionally, a deep understanding of how defects affect the PEC performance of TiO2 thin films is of great interest for achieving better performance. With these aims, we prepared defective amorphous TiOx thin films at various growth temperatures by atomic layer deposition using tetrakis(dimethylamido)titanium as the Ti precursor. Careful X-ray photoelectron spectroscopy and electron spin resonance spectroscopy analyses revealed that the defect concentration in the TiOx thin films can be controlled by adjusting the growth temperature during the ALD process. We also evaluated the light absorption properties of the deposited TiOx thin films using ultraviolet-visible absorption spectroscopy. And it was found that the TiOx thin film deposited at a growth temperature of 200 °C exhibited the highest defect concentration and the highest photocurrent density of 0.051 mA/cm2 at 1.23 V vs reversible hydrogen electrode (RHE) compared to those of the other films. The light absorption efficiency, photogenerated charge separation efficiency, and charge transfer efficiency of defective amorphous TiOx thin films were carefully studied to understand the correlation between the defect concentration in the prepared TiOx thin film and its PEC activity. This study provides insight into the PEC properties of defective amorphous ALD-TiOx thin films.

An Efficient Scheduling Strategy for Collaborative Cloud and Edge Computing in System of Intelligent Buildings

Edge computing is a new computing method, and task scheduling is challenging work. Using edge computing in intelligent buildings for managing smart home devices has gained popularity because it can reduce the delay and network congestion brought by cloud computing. Edge computing has the advantage of fast response speeds, but its computing capacity is limited. To solve this practical problem, a system framework of collaborative cloud and edge computing is constructed for intelligent buildings. First, the communication time, task completion time, and CPU energy consumption are considered comprehensively, and a mathematical model of the system is developed. Considering the compute-intensity task, the splitting ratio is determined for tasks to achieve the collaboration of cloud computing and edge computing. Then, the search mechanism of a single gene mutation in the genetic algorithm (GA) is introduced to compensate for the defects of the salp swarm algorithm (SSA), while focusing on the search ability and optimization efficiency. Finally, the proposed strategy is theoretically analyzed and experimentally evaluated. The simulation results show that the hybrid algorithm of SSA-GA has better performance than other algorithms, and the proposed collaborative cloud and edge computing task scheduling strategy demonstrated a lower delay and makespan.

Versatile side chain turns property and functions of α-cyanostilbene derivatives with near-infrared emission and two-photon property for mitochondrial imaging

Developing red materials with bright near-infrared emission and excellent two-photon performance by a simple preparation process is a meaningful and challenging work. Herein, a series of nitro functionalized D-π-A type α-cyanostilbene derivatives with different side chains (ZH, ZOM, ZOE, and ZOB) have been designed and synthesized by a one-pot method. The compounds show weak emissions and almost the same photophysical properties in solutions. In contrast, in the aggregation state, ZOM, ZOE, and ZOB with side chains of methoxy, ethoxy and benzyloxy emit strong fluorescence, while ZH with no side chain shows weak emission. The aggregate emission mechanism is ascribed to the side chain induced the molecular planarization, and formation of unique “bricks” H-aggregates and “staircase” J-aggregates, investigated by single-crystal analysis and DFT calculations. Considering the excellent photophysical properties of the side chain modified compounds, the triphenylphosphonium is employed to the side chain to obtain a mitochondrial targeting probe Z-TPP, which performs high fluorescence and selectively targeted the mitochondria in live cell and zebrafish under one/two-photon excitation, and further successfully applied to observe the complex mitochondrial network with high signal-to-noise ratio under stimulated emission depletion (STED) nanoscopy.

Contract Labours Working Environments: A Study of Work Conditions

Introduction: In the contemporary global economy, there has been a significant shift in the structure of work and employment relationships, with a heightened focus on contract labour. This research explores the distinctive challenges and opportunities these workers face, shedding light on their essential role in the modern workforce. Objective: To Study the demographic profile of contract labours and understand the working conditions and work nature of contract labours. Methodology: A descriptive research design was conducted to examine work conditions in contract labor environments at L.N Oils Limited, Dharwad, in 2019 as part of a postgraduate dissertation. Purposive sampling selected 60 contract laborers. Data collection involved structured interviews and analysis of secondary sources such as research articles and reports to provide a comprehensive understanding of labor conditions. Findings: the prevalence of unskilled positions due to industrial needs, equitable treatment in payment, leave, and welfare between contract laborers and permanent workers, limited facilities for night shift contract workers, a substantial proportion engaged in overtime work, high job satisfaction among 75% of respondents, widespread ambiguity about promotion procedures, one-third experiencing discrimination, 70% enjoying positive work status, 80% content with safety measures, hygienic concerns for many, insufficient training opportunities, satisfaction with problem-solving strategies, positive personnel management relations, and an impressive 95% job satisfaction rate. Conclusion: Contract labor is widespread in various industries, including skilled and semi-skilled roles, notably in oil fields and services. Contract workers lack job security and face challenging working conditions, often in industrial settings.

Nonlinear and infinite gain scheduling neural predictive control of the outlet temperature in a parabolic trough solar field: A comparative study

Solar thermal plants have high nonlinearities and non-manipulated energy source which make their control task a very challenging work. Linear controllers cannot cope with undesirable deviations of the outlet temperature over all the operation range of the dynamics of this type of plants. Moreover, nonlinear predictive control relying on online nonlinear optimization have the drawback of time consuming and numerical calculus issues. In this paper, an infinite gain scheduling neural predictive control is designed and applied to control the temperature in a distributed parabolic trough solar collector field. The performance of both tracking and disturbance rejection of the proposed controller is compared to those of four nonlinear predictive control variants: Two unconstrained neural predictive control using the Levenberg–Marquardt and the Broyden–Fletcher–Goldfarb–Shanno algorithms, and two constrained nonlinear predictive control using interior point algorithm, one is based on a neural network model and the other one is based on a first principal model. The superiority of the proposed control strategy is well demonstrated through simulation results.

The future of parenting plan evaluations: A view from the trenches

AbstractAs expectations rise for parenting plan evaluators to be well‐trained, skilled, and knowledgeable in numerous subject areas, and scrutiny of evaluators' work intensifies, the pool of qualified evaluators is shrinking nationwide. The future of parenting plan evaluation as a forensic subspecialty relies upon the availability of competent and committed professionals to do this challenging work, yet few are entering the field. Five experienced parenting plan evaluators from various regions of the United States, including the authors, met for a roundtable discussion to ponder the future of parenting plan evaluations. The panel discussed what drew them to the work, their experiences “in the trenches,” and what has kept them committed to doing evaluations despite daunting challenges. Their views of the rewards and risks of doing the work, barriers and disincentives to newcomers entering the field, recommendations to new evaluators, and outlook for the future are presented.

Efficient trivalent chromium ions doped ZnLu2Al4SiO12 garnet phosphor: Crystal structure, optical properties and application

The development of effective trivalent chromium ions doped oxide phosphors with deep-red emission is a challenging but important work. Here, the novel garnet-structured phosphors ZnLu2Al4SiO12:Cr3+ (ZLASO:Cr3+) were created for the first time. Under 402 nm excitation, the prepared phosphors exhibited deep-red emission centered at 689 nm with great internal quantum efficiency of 65.4%. Meanwhile, thermal quenching behavior was investigated and the optimal ZLASO:2.5%Cr3+ performed high thermal stability (83.8%@423 K). The emission spectrum of ZLASO:Cr3+ exhibited excellent responsiveness to the absorption spectra required for plant growth. Consequently, the constructed ZLASO:Cr3+ red phosphors are expected to be used for the application of plant growth.

Electroencephalogram Emotion Recognition Using Combined Features in Variational Mode Decomposition Domain

Using Electroencephalogram (EEG) to recognize human emotion has attracted increasing attention. However, features extraction from EEG is a challenging work because it is a non-stationary continuous sequential signal. To obtain more pattern information, a combined features extraction method in Variational Mode Decomposition (VMD) domain is proposed, which can extract local features of EEG signals to overcome the effects caused by non-stationarity. This method first decomposes EEG into several components using VMD, and then combined features of Differential Entropy (DE) and Short-Time Energy (STE) are extracted from each component. To optimize combined features, the important features are selected by tree modes, and the feature set is dimensionally reduced by further using Linear Discriminant Analysis (LDA). Moreover, an XGBoost classifier with Bayesian optimization is presented to classify different emotional states. Binary-class and multi-class EEG emotion recognition are conducted on the DEAP dataset, from which the experimental results show that accuracy of binary-class classification is 81.77% for High/Low Valence and 80.47% for High/Low Arousal, and accuracy of 91.41%, 94.27%, 94.27% and 93.49% are obtained for HVHA, LVHA, LVLA and HVLA, respectively, which demonstrate its effectiveness.

Estimating Dynamic Non‐Water‐Limited Canopy Resistance Over the Globe: Changes, Contributors, and Implications

AbstractNon‐water‐limited canopy resistance (rcs, also known as the bulk stomatal resistance or surface resistance) is a critical variable in estimating potential evapotranspiration (PET), which is widely used in ecohydrology related fields. However, quantifying rcs is a challenging work. Here we develop an approach for estimating rcs over the globe. Comparing results over the globe and across 10 ET data sets (used as inputs), which are based on diverse mechanisms and algorithms, we find that the approach can capture canopy resistance well (mean correlation of 0.84 ± 0.04, mean relative Root Mean Squared Error of 4.4% ± 1.0%, and mean relative Mean Absolute Error of 5.8% ± 1.4%), and the estimated rcs are very close to those estimated using another method (R2 = 0.92), which is based on a quite different hypothesis that is only suitable for saturated regions. Based on these, we find that the rcs shows an overall increasing trend (0.43 ± 0.13 s m−1 year−1) over the globe (at 77.6% ± 3.9% of the land grid cells) during 1982–2014, and the air temperature dominates the variabilities of rcs in regions with decreasing rcs (mean relative contribution of 57.9% ± 11.4%), while air CO2 concentration controls the changes in rcs in regions with increasing rcs (mean relative contribution of 47.3% ± 8.0%). Moreover, we also find that the traditional PET estimator explicitly overestimates the increasing trends in PET, and tends to overestimate (underestimate) the increasing (decreasing) trends in regions with increasing (decreasing) PET. These findings can improve our knowledge on the complex water‐vegetation‐environment interactions and would be helpful for developing more accurate models for quantifying the impacts of global change on water resources.

Modeling Reviews for Few-Shot Recommendation via Enhanced Prototypical Network

Although some existing models are proposed to exploit reviews for improving performance for recommender systems, few of them can handle the following issues led by the insufficient review data: (i) The regular training process does not exactly fit the scenario of preference prediction with few historical behaviors. (ii) Extracting informative and sufficient semantic features from limited review texts is a challenging work. To alleviate these issues, this paper proposes an enhanced prototypical network, FS-EPN, that leverages reviews for recommendation under the few-shot setting. FS-EPN consists of an attentional prototypical network being the basic architecture, a sentiment encoder and a memory collector cooperating to capture the extra sentimental and collaborative information from both user and item perspectives for semantic information supplement. We train FS-EPN under the meta-learning framework, which models the training process in the episodic manner to mimic the few-shot test environment. Extensive experiments conducted on six publicly available datasets demonstrate the superior capability of FS-EPN over several state-of-the-art models in few-shot recommendation.