Miracle-dz/UniFAR-FTUs huggingface dataset:
Symmetric Fano Profiles of Two-photon Electronic Transitions Observed in an Ultracold Rydberg Gas

Fano profiles are caused by the interference between the discrete states and continuum. It is a very common phenomenon in multi-electron Rydberg states, such as the Rydberg states of group II elements in the periodic table. It often leads to autoionization due to the fact that a discrete state couples with an autoionizing state. Unlike the typical asymmetric line shape, here we report a symmetric unusual Fano line shape that has been predicted. In addition, this profile is caused by molecular states or polymer states instead of multi-electron atomic states. Moreover, it is shown that the fano profile caused by the multi-electron polymer states does not necessarily lead to autoionization. We propose that the Fano profile studied is caused by the interference between discrete levels and the multipole-multipole coupled continuum, or energy band.
Advances in Tumour-Infiltrating Lymphocytes for Triple-Negative Breast Cancer Management

Abstract Triple negative breast cancer (TNBC) is a subtype of breast cancer which does not express or expresses a minimum amount of estrogen receptors (ER), progesterone receptors (PR) and human epidermal growth factor receptor 2 (HER2) protein. TNBCs include a heterogenic group of cancers that are aggressive, grow rapidly and are associated with poor prognosis and overall survival, mainly attributed to a lack of effective therapeutic targets. For a long time, a major issue with predicting the outcome and prognosis of TNBCs was the lack of an accurate biomarker, a molecule that helps us objectively assess a patient’s health status. In recent times, defining the presence of tumor-infiltrating lymphocytes (TIL) is becoming an indispensable method of determining a patient’s prognosis. TILs are found in tumor tissue and the surrounding stroma and carry a prognostic value. Furthermore, they are known to improve the effect of systemic therapy. With the rise of immunotherapy, the role of TIL in this newer therapeutic option is a topic of increased importance. The goal behind this research article is a comprehensive review of the current literature on the importance of tumor-infiltrating lymphocytes in the prognosis of TNBC.
Efficient Resume-Based Re-Education for Career Recommendation in Rapidly Evolving Job Markets

The impact of the COVID-19 pandemic and the introduction of artificial intelligence-based tools created significant job losses across various sectors in all countries around the world. A large portion of these job losses is permanent. Furthermore, the hidden unemployment numbers are higher than currently reported and the impact of Generative Pretrained Transformer (GPT) based tools will further increase the unemployed population in the coming years. Most businesses are likely to experience significant disruptions to their business-as-usual operations and will face business underperformance for long periods. To ensure business continuity and a smooth recovery process following severe disruptions, it is crucial to establish a recovery strategy. To provide enough workforce for the recovery strategy of various businesses, a large-scale rapid re-education of the workforce is required. Intelligent and virtual workplaces will replace traditional offices in various sectors in the upcoming years and many low-skilled jobs are in danger of being permanently lost. In this paper, an artificial intelligence-based framework for rapid work-skill re-education for evolving markets named Career-gAIde is presented. The proposed framework uses automatic analysis of the job resume of the workers for recommendations of a suitable new job with a higher salary and the best rapid re-education path toward that job. Custom build deep neural networks based on CNN-Random along with customized natural language processing tools are designed for large-scale automatic recommendation of a personalized education and career path to each job seeker. The proposed work is focused on software engineering job search and resume upgrades. There is also a book recommendation module for obtaining the knowledge of job seekers. Precision criteria were used to evaluate the job offer recommendations and the proposed framework achieves 67% in this measure. The Recall criteria were used to assess the required skills, with results of 84% and 79%, respectively. The experimental results show that the proposed framework can provide a solution for rapid work-skill re-adjustment for large-scale workforces.
A Light Vehicle License-Plate-Recognition System Based on Hybrid Edge–Cloud Computing

With the world moving towards low-carbon and environmentally friendly development, the rapid growth of new-energy vehicles is evident. The utilization of deep-learning-based license-plate-recognition (LPR) algorithms has become widespread. However, existing LPR systems have difficulty achieving timely, effective, and energy-saving recognition due to their inherent limitations such as high latency and energy consumption. An innovative Edge–LPR system that leverages edge computing and lightweight network models is proposed in this paper. With the help of this technology, the excessive reliance on the computational capacity and the uneven implementation of resources of cloud computing can be successfully mitigated. The system is specifically a simple LPR. Channel pruning was used to reconstruct the backbone layer, reduce the network model parameters, and effectively reduce the GPU resource consumption. By utilizing the computing resources of the Intel second-generation computing stick, the network models were deployed on edge gateways to detect license plates directly. The reliability and effectiveness of the Edge–LPR system were validated through the experimental analysis of the CCPD standard dataset and real-time monitoring dataset from charging stations. The experimental results from the CCPD common dataset demonstrated that the network’s total number of parameters was only 0.606 MB, with an impressive accuracy rate of 97%.
Optimal Power Allocation Under Different Power Availability Scenarios for Multitarget Tracking With C-MIMO Radar Systems

Power allocation has emerged to be a critical problem when exploiting colocated multiple-input and multiple-output (C-MIMO) radar for multi-target tracking. Several prior approaches employing the quality of service-based framework aim to minimize the weighted sum of the target task utility functions. In this article, to utilize power-resource efficiently and further improve the tracking performance of the C-MIMO radar system, an optimal power allocation (OPA) method is proposed. First, the quality of service based power allocation model is generalized to a more general and flexible model, where the task utility functions can be selected from a set of monotonically increasing convex functions, and the construction of the objective function is not limited to a particular filter to approximate the Bayesian Cramér-Rao lower bound (BCRLB). Thus, more efficient non-linear Bayesian filters can be used. Second, quasi-convexity of the non-convex OPA problem under the quality of service-based framework is explored, whose objective function is the weighted sum of a set of separable quasi-convex functions. Then the strong duality between the original non-convex problem and its dual problem is derived. Finally, under any given approximated BCRLB, a dual projection subgradient power allocation (DPSPA) algorithm is proposed to deal with the dual problem and obtain the optimal solution. Illustrative numerical results demonstrate the efficiency and generality of the proposed strategy under different power availability scenarios.
The Influences of Display Highlighting and Size and Event Eccentricity for Aviation Surveillance

The present experiments were designed to assess the influence of display size, display highlighting, and event eccentricity in a surveillance task. Pilots were asked to detect changes in the movement or altitude of weather systems or traffic aircraft, which were represented in integrated hazard displays. Experiment 1 examined change detection as a function of the distance of the event from ownship and the presence of the event in a highlighted or lowlighted hazard domain. Analyses revealed that change detection was superior for events that were in the highlighted display database and that performance was slightly degraded for more eccentric events. Experiments 2 and 3 assessed the role of display size and event eccentricity. Analyses showed that change detection was unaffected by the size of the display, though performance was again degraded for changes located near the perimeter of the display. Findings imply that surveillance of the display perimeters will depreciate and additional methods should be used to ensure that attention is sufficiently directed to these areas.
Application of conventional and new methods for estimation of seismic wave attenuation in carbonate rocks using VSP data in Abu-Dhabi oil fields

Summary The subsurface geology of Abu Dhabi in the United Arab Emirates is primarily composed of carbonate rocks. Such media are known to be highly heterogeneous with complex geology, which makes an accurate estimation of the attenuation in such media challenging. To estimate accurately the attenuation profiles of the medium from the first arrival, we follow several steps of processing on the data before applying two conventional and a new method on the data.
Possible causes of poverty within a group of land reform beneficiaries in the midlands of KwaZulu-Natal: Analysis and policy recommendations

Abstract This study investigates possible causes of poverty afflicting a community of land reform beneficiaries in the Midlands of KwaZulu-Natal. The 38 beneficiary households had previously been clustered into four groups displaying different symptoms of poverty. Linear Discriminant Analysis was used first to distinguish households that were relatively income and asset “rich” from those that were relatively income and asset “poor", and second to distinguish households that were relatively income poor but “asset rich” from those relatively asset poor but “income rich”. In the first analysis it was found that “rich” households could be distinguished from “poor” households using just two indicator variables; gender of the household head and family size. Larger, female-headed households have lower income and wealth per adult equivalent. In the second analysis, it was found that the “asset rich” had more human capital whereas the “income rich” owned vehicles and had fewer dependants per worker. Policy recommendations therefore point to education and vocational training -especially for women, better access to transport, jobs and banking facilities (to mobilise savings) in the long run, and improved and better targeting of social welfare grants for the chronically poor in the short run. These interventions are also expected to increase the demand for family planning and contraception, which in turn helps to reduce family sizes and the premature loss of breadwinners.
Association of Ischemia-Modified Albumin (IMA) in Saliva, Serum, and Urine with Diagnosis of Chronic Kidney Disease (CKD) in Children: A Case-Control Study

Background Ischemia-modified albumin (IMA) is a secreted biomarker for ischemic oxidative stress. This case-control study aimed to evaluate the association of ischemia-modified albumin (IMA) in saliva, serum, and urine with diagnosis of chronic kidney disease (CKD) in 24 children. Material/Methods The study involved 24 children with CKD. CKD was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) diagnostic criteria. The control group consisted of 24 healthy children who were matched for age and gender to the experimental group. The concentration of IMA was determined by the colorimetric method in non-stimulated whole saliva (NWS), stimulated whole saliva (SWS), serum, and urine of children with CKD. The Mann-Whitney U test was used for inter-group comparisons. Results IMA levels were significantly higher in NWS (P=0.0082) and SWS (P=0.0014) of children with CKD than in the control group. The concentration of IMA in NWS was correlated with standard indicators of kidney function, including the estimated glomerular filtration rate (r=-0.798, P≤0.0001), stage of CKD (r=0.814, P≤0.0001), and serum creatinine (r=0.711, P≤0.0001) and urea levels (r=0.738, P≤0.0001). Conclusions Salivary IMA concentration depends on renal function in children. Salivary IMA discriminates children with end-stage kidney disease from children with mild and moderate CKD and healthy children with high sensitivity and specificity. Further research is required, including assessment of the diagnostic usefulness and validation of the biomarker in a clinical diagnostic study.
Bottom Sediment Variability in the Active Layer of the Inner Shelf off the Ebro Delta

Abstract The variability of the bottom sediment grain size was estimated at two sites located at 8.5 and 12.5 m depth across the Ebro Delta inner shelf from cores taken at the beginning and end of three one-month-long current meter + turbidimeter deployments. The sediment variability showed different characteristics in each survey. During winter conditions and after a river flood (December '96–January '97), a mud layer was deposited on the inner shelf overlying sandy deposits. The mud layer was eroded before April '97. During the spring survey (April '97–May '97) a sand layer was deposited after several storms. Finally, a general coarsening of the sediment was observed during the summer deployment (August '97). Potential implications of these sediment changes in the estimation of near bottom sediment fluxes are addressed, considering effects on turbidity measures and the estimation of the vertical profile of suspended sediment.
Optimal source parameters of the 6 April 2009 Mw 6.3 L’Aquila, Italy earthquake from InSAR observations

On 6th April 2009 a Mw6.3 earthquake occurred in the L' Aquila region, central Italy, causing at least 297 fatalities and great economic losses. Using European Space Agency's ENVISAT ASAR data we generated three independent coseismic interferograms. Three popular downsampling techniques (uniform, quadtree and Resolution-based) were employed to create 4 different sets of datapoints, two of which were produced using the uniform approach with different sampling sizes. Uniform models with the 4 sets of datapoints show similar source parameters and residuals, indicating their impacts on uniform modeling are limited. However, their distributed slip models suggest that the resolution-based approach is preferred though similar slip patterns can be observed. Our optimal distributed slip model shows that this event is associated with a buried SW-dipping normal fault with the epicenter at (13.4506°,42.3580°),a strike of 141.3°, and a dip of 50°. In addition, the maximum slip of 1.2 m is observed at a depth of 6.1 km, and the total seismic monent is ~3.65×10^18N·m.
Depth Prediction for Earth-Penetrating Projectiles

An empirical equation is developed for the prediction of total penetration distance of a projectile in many natural earth targets. Development of this equation was based on approximately 160 full-scale penetration tests into a variety of targets, including rock, gypsite, permafrost, ice, desert alluvium, silt, sand and saturated clay. The parameters considered in the development (other than target materials) were (1) projectile weights from 222 to 5,750 lb, (2) projectile diameters from 3.1 to 18 in. , (3) impact velocities from 78 to 1,077 fps, and (4) 11 projectile nose shapes. The equation fits 91% of the data within 20% and fits 98.5% of the data within 25%. The necessary tables of nose-performance coefficients and soil constants are presented for practical engineering usage.
Populations and breeding performance of divers, geese and ducks at Zackenberg, northeast Greenland, 1995-2005

Monitoring at Zackenberg (74°30’N, 20°30’W) since 1995 has provided for the fi rst time long-term data on population trends and breeding performance for a number of high-arctic waterbird species in Greenland. Breeding populations of Red-throated Diver Gavia stellata and Long-tailed Duck Clangula hyemalis were relative stable from year to year, whereas breeding success varied with the abundance of Arctic Fox Alopex lagopus and Collared Lemming Dicrostonyx groenlandicus. Average nest survival in Red-throated Diver was 18% between 1996 and 2005, and at least fi ve pairs produced a total of about 29 potentially fl edged young, or at least 0.5 per pair per year – most of them in two years with few Arctic Foxes. Long-tailed Duck bred successfully in only one year, a year with many Arctic Foxes but also much alternative prey in the form of Collared Lemmings. Few pairs of King Eider Somateria spectabilis were found, and these had poor breeding success. Between four and 32 pairs of Barnacle Geese Branta leucopsis brought their goslings into the study area from nearby colonies each year. An average of about 0.6% of the goslings disappeared per day during the fl edging period. More than 500 immature Icelandic Pink-footed Geese Anser brachyrhynchus moulted in the study area at the beginning of the study period, but most disappeared after a few years in spite of attempts to protect them from human disturbance. There is some indication that numbers of both Pink-footed Goose and Long-tailed Duck at Zackenberg have declined since the 1960s.
Friction Factor and Heat Transfer Enhancement of Hybrid Nanofluids in a Heated Circular Tube

This work investigates the potential of hybrid nanoparticles suspended in pure water to enhance the thermal performance of heat exchangers at minimal weight fractions. A hybrid nanofluid consisting of 50% ZnO and 50% Al 2 O 3 nanoparticles dispersed in pure water at weight fractions of 0.1%, 0.3%, and 0.5% was prepared. An experimental rig, featuring a straight horizontal tube with a constant wall heat flux, was equipped with eight thermocouples positioned at the inlet, outlet, and along the tube's surface. The study focuses on the impact of the hybrid nanofluid on the friction factors and heat transfer coefficients within a Reynolds number range of 5000 to 20000. Observations indicate that the Nusselt number escalates with an increase in the Reynolds number through the horizontal tube, while the friction factor exhibits a converse relationship. The peak Nusselt number and friction factor were observed at a 5% mass fraction of the hybrid nanofluid. Specifically, enhancements in the Nusselt number were recorded at 9%, 11.8%, and 16.7% for the weight fractions of 0.1%, 0.3%, and 0.5% respectively. Additionally, the deviation in the friction factor was noted at 2.3%, 3.6%, and 4.1% in comparison to pure water. This study thus provides critical insights into the role of hybrid nanofluids in optimizing heat transfer in heat exchangers.
To Share or Not to Share? Knowledge Convergence and Divergence in Cross-Disciplinary Collaboration

For cross-disciplinary teams to be effective, what knowledge should be shared and what knowledge should remain unique to individual team members? We adopted a mixed-method approach using a sample of grant-funded teams composed of principal and co-principal investigators of diverse disciplines. Interviewees and survey respondents especially favored knowledge similarity over uniqueness for team vision and teamwork, but less preference for convergence emerged for research outcomes and research content (theory, operational details of methodology, analysis). Moreover, more team knowledge convergence was associated with higher perceived collaboration satisfaction and trended in the direction of more grants, publications, and conference presentations.
Individual differences in the language task-evoked and resting-state functional networks

The resting state functional network is highly variable across individuals. However, inter-individual differences in functional networks evoked by language tasks and their comparison with resting state are still unclear. To address these two questions, we used T1 anatomical data and functional brain imaging data of resting state and a story comprehension task from the Human Connectome Project (HCP) to characterize functional network variability and investigate the uniqueness of the functional network in both task and resting states. We first demonstrated that intrinsic and task-induced functional networks exhibited remarkable differences across individuals, and language tasks can constrain inter-individual variability in the functional brain network. Furthermore, we found that the inter-individual variability of functional networks in two states was broadly consistent and spatially heterogeneous, with high-level association areas manifesting more significant variability than primary visual processing areas. Our results suggested that the functional network underlying language comprehension is unique at the individual level, and the inter-individual variability architecture of the functional network is broadly consistent in language task and resting state.
MACl-Induced Controlled Crystallization in Sequentially Deposited Perovskites for High-Efficiency and Stable Perovskite Solar Cells

Perovskite solar cells are attracting more and more attention due to their higher absorption and low cost. However, fabricating the perovskite film with high crystallinity and ideal morphology, which presents large-size and uniform particles with fewer grain boundaries, still needs further improvement. Herein, we introduce MAPbCl3 crystals into the PbI2 film in the sequential deposition process, which obtained the controlled crystallization in perovskite films. The perovskite films induced by MAPbCl3 have stronger crystallinity, fewer defect states, and larger grain size, reducing carrier recombination and improving carrier transfer. The optimized perovskite solar cell (PSC) has achieved a power conversion efficiency of 20.97%. Furthermore, the stability of PSCs has also been enhanced due to the reduced grain boundaries impeding moisture diffusion. This strategy can be applied in other solution-based fabrication processes to improve the photovoltaic performance of PSCs.
Organic Carbon in Streams

Dissolved organic carbon (DOC) is an abundant form of organic matter in stream ecosystems. Most research has focused on the watershed as the source of DOC in streams, but DOC also comes from leaching of organic matter stored in the stream channel. We used a whole-ecosystem experimental approach to assess the significance of leaching of organic matter in the channel as a source of DOC in a headwater stream. Inputs of leaf litter were excluded from a forested Appalachian headwater stream for 3 years. Stream-water concentration, export, and instream generation of DOC were reduced in the litter-excluded stream as compared with a nearby untreated reference stream. The proportion of high molecular weight (HMW) DOC (more than 10,000 daltons) in stream water was not altered by litter exclusion. Mean DOC concentration in stream water was directly related to benthic leaf-litter standing stock. Instream generation of DOC from leaf litter stored in the stream channel contributes approximately 30% of daily DOC exports in this forested headwater stream. This source of DOC is greatest during autumn and winter and least during spring and summer. It is higher during increasing discharge than during base flow. We conclude that elimination of litter inputs from a forested headwater stream has altered the biogeochemistry of DOC in this ecosystem.