Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation

Reinforcement learning (RL) has been widely applied in recommendation systems due to its potential in optimizing the long-term engagement of users. From the perspective of RL, recommendation can be formulated as a Markov decision process (MDP), where recommendation system (agent) can interact with users (environment) and acquire feedback (reward signals). However, it is impractical to conduct online interactions with the concern on user experience and implementation complexity, and we can only train RL recommenders with offline datasets containing limited reward signals and state transitions. Therefore, the data sparsity issue of reward signals and state transitions is very severe, while it has long been overlooked by existing RL recommenders.Worse still, RL methods learn through the trial-and-error mode, but negative feedback cannot be obtained in implicit feedback recommendation tasks, which aggravates the overestimation problem of offline RL recommender. To address these challenges, we propose a novel RL recommender named model-enhanced contrastive reinforcement learning (MCRL). On the one hand, we learn a value function to estimate the long-term engagement of users, together with a conservative value learning mechanism to alleviate the overestimation problem.On the other hand, we construct some positive and negative state-action pairs to model the reward function and state transition function with contrastive learning to exploit the internal structure information of MDP. Experiments demonstrate that the proposed method significantly outperforms existing offline RL and self-supervised RL methods with different representative backbone networks on two real-world datasets.
Covariance matrices for the Lyman-$\alpha$ forest using the lognormal approximation

We investigate the nature of correlations in the small-scale flux statistics of the Lyman-$\alpha$ (Ly$\alpha$) forest across redshift bins. Understanding these correlations is important for unbiased cosmological and astrophysical parameter inference using the Ly$\alpha$ forest. We focus on the 1-dimensional flux power spectrum (FPS) and mean flux ($\bar F$) simulated using the semi-numerical lognormal model we developed in earlier work. The lognormal model can capture the effects of long wavelength modes with relative ease as compared to full smoothed particle hydrodynamical (SPH) simulations that are limited by box volume. For a single redshift bin of size $\Delta z\simeq 0.1$, we show that the lognormal model predicts positive cross-correlations between $k$-bins in the FPS, and a negative correlation for $\bar F\times$ FPS, in qualitative agreement with SPH simulations and theoretical expectations. For measurements across two neighbouring redshift bins of width $\Delta z$ each (obtained by 'splitting' skewers of length $2\Delta z$ in half), the lognormal model predicts an anti-correlation for FPS $\times$ FPS and a positive correlation for $\bar F\times$ FPS, caused by long wavelength modes. This is in contrast to SPH simulations which predict a negligible magnitude for cross-redshift correlations derived from such `split' skewers, and we discuss possible reasons for this difference. Finally, we perform a preliminary test of the impact of neglecting long wavelength modes on parameter inference, finding that whereas the correlation structure of neighbouring redshift bins has relatively little impact, the absence of long wavelength modes in the model can lead to $\gtrsim2-\sigma$ biases in the inference of astrophysical parameters. Our results motivate a more careful treatment of long wavelength modes in analyses that rely on the small scale Ly$\alpha$ forest for parameter inference.
Relationship between circulating FSH levels and body composition and bone health in patients with prostate cancer who undergo androgen deprivation therapy. The BLADE study

Background: Amongst its extragonadal effects, Follicle-Stimulating Hormone (FSH) has an impact on body composition and bone metabolism. Since androgen deprivation therapy (ADT) has a profound impact on circulating FSH concentrations, this hormone could potentially be implicated in the changes of fat body mass (FBM), lean body mass (LBM) and bone fragility induced by ADT. The objective of this study is to correlate FSH serum levels with body composition parameters, bone mineral density (BMD) and bone turnover markers at baseline conditions and after 12 months of ADT. Methods: 29 consecutive non-metastatic prostate cancer (PC) patients were enrolled from 2017 to 2019 in a phase IV study. All patients underwent administration of the Luteinizing Hormone-Releasing Hormone antagonist degarelix. FBM, LBM and BMD were evaluated by dual-energy x-ray absorptiometry at baseline and after 12 months of ADT. FSH, alkaline phosphatase (ALP) and C-terminal telopeptide of type I collagen (CTX) were assessed at baseline and after 6 and 12 months. For outcome measurements and statistical analysis, T-test or sign test and Pearson or Spearman tests for continuous variables were used when indicated. Results: At baseline conditions, a weak, non-significant, direct relationship was found between FSH serum levels and FBM at arms (r=0.36) and legs (r=0.33). Conversely, a stronger correlation was observed between FSH and total FBM (r=0.52, p=0.006), fat mass at arms (r=0.54, p=0.004) and fat mass at trunk (r=0.45, p=0.018) assessed after 12 months. On the other hand, an inverse relationship between serum FSH and appendicular lean mass index (ALMI)/FBM ratio was observed (r=0.64, p=0.001). This is an ancillary study of a prospective trial and this is the main limitation. Conclusions: FSH serum levels after ADT could have an impact on body composition, in particular on fat body mass. Therefore, FSH could be a promising marker to monitor the risk of sarcopenic obesity and cardiovascular complications in PC patients undergoing ADT. Funding: this research was partially funded by Ferring Pharmaceuticals. The funder had no role in design and conduct of the study, collection, management, analysis, and interpretation of the data and in preparation, review, or approval of the manuscript. Clinical trial number: clinicalTrials.gov NCT03202381, EudraCT Number 2016-004210-10.
The Late Pleistocene Loess Stratigraphy of the Ba ˇ cka and Srem Region (Vojvodina, Serbia) - Old Results in the Light of New Ones

Late Pleistocene loess stratigraphy of the region of Ba ˇ cka and Srem attracted numerous geoscientists in the past century. The first results of investigations were mainly based on descriptions of loess-paleosol sequences and their correlation with other sites in the Danube Valley of Central Europe. Pecsi and Bronger’s studies were the first to be based on mineralogy, micromorphology and soil development of paleosols. Later with the development of luminescence dating techniques SINGHVI and his team suggest the revision of previous results, because the results show that the chernozem and chernozem-like soils are older (interglacial age). In the last decade after international investigations lead by MARKOVI ´ C and his group, the multidisciplinary research of loess-paleosol sequences proves the MIS 5 age of the developed chernozem pedocomplex. According to the recent developments and the derived data the regional loess stratigraphical nomenclature of Pleistocene formations is changed and adapted to the Chinese loess stratigraphy and clearly correlated with the marine oxygen isotope stages. Die spatpleistozane Loss-Stratigraphie des Ba ˇ cka- und Srem-Gebietes (Vojvodina, Serbien) ‐ Alte Ergebnisse in neuem Licht Zusammenfassung Die spatpleistozane Loss-Stratigraphie des Ba ˇ cka- und Srem-Gebietes beschaftigte in vergangenen Jahrhundert zahlreiche Geowissenschaftler. Die ersten Forschungsresultate basierten auf Beschreibungen von Loss-Palaoboden-Abfolgen und ihrer Korrelation mit anderen Lokalitaten des Donauraumes. PECSI und BRONGER begannen mit Studien zur mineralogischen, mikromorphologischen und pedologischen Entwicklung der Palaoboden. Basierend auf Lumineszenz-Datierung schlagen SINGHVI und sein Team eine Revision der fruheren Resultate vor, da die Untersuchungen fur Tschernoseme und tschernosemahnliche Boden ein hoheres (interglaziales) Alter zeigen. Im letzten Jahrzehnt bewies MARKOVI ´ C mit seinem internationalen Team durch multidisziplinare Forschung an Loss-Palaoboden-Sequenzen das MIS-5-Alter des Tschernosem-Pedokomplexes. Nach jungsten Entwicklungen und mit umfangreichem Datenmaterial wird die lossstratigraphische Nomenklatur der pleistozanen Formationen an die chinesische LossStratigraphie angepasst und mit den marinen Sauerstoffisotopen-Stufen korreliert.
All-Digital Leakage Variation Sensor for On-Chip Process and Temperature Monitoring

—Variation in process, voltage and temperature is a major obstacle in achieving energy-efﬁcient operation of LSI. This paper proposes an all-digital on-chip circuit to monitor leakage current variations of both of the nMOSFET and pMOS-FET independently. As leakage current is highly sensitive to threshold voltage and temperature, the circuit is suitable for tracking process and temperature variation. The circuit uses reconﬁgurable inhomogeneity to obtain statistical properties from a single monitor instance. A compact reconﬁgurable inverter topology is proposed to implement the monitor circuit. The compact and digital nature of the inverter enables cell-based design, which will reduce design costs. Measurement results from a 65-nm test chip show the validity of the proposed circuit. For a 124 sample sizes for both of the nMOSFET and pMOSFET, the monitor area is 4500 (cid:22) m 2 and active power consumption is 76 nW at 0.8 V operation. The proposed technique enables area-efﬁcient and low-cost implementation thus can be used in product chips for applications such as dynamic energy and thermal management, testing and post-silicon tuning.
On the normal form of synchronization and resonance between vorticity waves in shear flow instability

A minimal model of linearized two dimensional shear instabilities can be formulated in terms of an action-at-a-distance, phase-locking resonance between two vorticity waves, which propagate counter to their local mean ﬂow as well as counter to each other. Here we analyze the prototype of this interaction as an autonomous, nonlinear dynamical system. The wave interaction equations can be written in a generalized Hamiltonian action-angle form. The pseudo-energy serves as the Hamiltonian of the system, the action coordinates are the contribution of the vorticity waves to the wave-action, and the angles are the phases of the vorticity waves. The term “generalized action-angle” emphasizes that the action of each wave is generally time dependent, which allows instability. The synchronization mechanism between the wave phases depends on the cosine of their relative phase, rather than the sine as in the Kuramoto model. The unstable normal modes of the linearized dynamics correspond to the stable ﬁxed points of the dynamical system and vice versa. Furthermore, the normal form of the wave interaction dynamics reveals a new type of inhomogeneous bifurcation – annihilation of a stable and an unstable star node yields the emergence of two neutral center ﬁxed points of opposite circulation.
of Hopelight (Mammolight) Imaging in Detection of Breast Cancer

: Background: hopelight (mammolight device) is a transillumination of breast tissue with low intensity light for detection of breast lesions; however, its value has not been well established. Objectives: to determine the diagnostic accuracy and sensitivity of hopelight in detection of breast cancer with radiologic-pathologic correlation. Patients and methods: a prospective study was performedin Radiology department at the Oncology Teaching Hospital, Medical City Complex in Baghdad (the main tertiary referral public center for breast disease in Iraq). This study enrolled 100 females attending mammography and ultrasound unit for screening, diagnosis or follow up of breast lesions in the period from March 2014 to November 2014. Breast examination was initially performed for each patient by hand-held hopelight device followed by mammography and/or ultrasound study and results were classified from normal to highly suspicious breast lesions according to breast imaging reporting and data system (BIRADS) then fine needle aspiration cytology or biopsy was acquired for BIRADS-IV and BIRADS-V lesions for histopathological review and final diagnosis. Results: demographic, clinical and imaging findings were reported and statistical analysis obtained and sensitivity, specificity and accuracy were 66.66%, 51.06% and 52% respectively with 8% positive predictive value and 96% negative predictive value. False positive results were detected in 46% of the patients whereas false negative outcomes were 2%. Conclusions: hopelight device cannot be safely used for screening of breast cancer and cannot be used alone because of high false positive outcome and low sensitivity, specificity and overall accuracy in detection of breast cancer.
O-2-absorption theorem for exact groups

We show that, up to strong cocycle conjugacy, every countable exact group admits a unique equivariantly O 2 -absorbing, pointwise outer action on the Cuntz algebra O 2 with the quasi-central approximation property (QAP). In particular, we establish the equivariant analogue of the Kirchberg O 2 -absorption theorem for these groups.
DECLINE AND RECOVERY: AN EXPLORATION THROUGH LOCAL ECOLOGICAL KNOWLEDGE

This study documents local ecological knowledge from Alaska Natives and nonindigenous participants to explore contributing factors for the endangered Cook Inlet beluga whale (Delphinapterus leucas) population decline and lack of recovery. Data were collected through 16 semi-structured interviews with key informants from the region using participatory techniques and analyzed for convergent information. Local knowledge was compared with existing scientific research to explore similarities and differences. Findings identified noticeable beluga whale declines beginning in the mid1980s, shark and northern pike population increases, higher frequency of killer whale sightings, decreased salmon numbers and increased siltation and mudflat expansion all in association with beluga whale habitat. Additional findings of terrestrial plant, animal and insect change and wetland drying suggest broader environmental and climate related changes. These findings contribute to conservation objectives outlined NMFS’s conservation plan and provide direction to future research and conservation management.
Medicinal Plants Used in Folk Recipes by the Inhabitants of Himalayan Region Poonch Valley Azad Kashmir (Pakistan)

Abstract: Plants with medicinal properties were held in the highest esteem in indigenous medicine systems all over the world. All indigenous remedies, whether traditional or modern, have originated directly or indirectly from folklore, rituals and folk medicinal knowledge. The objective of this study was to collect the information about how the local people used the plants of their area to cure a wide variety of ailments in human and livestock. Extensive surveys were carried out during the field work; interviews were conducted with the local inhabitants, the herbalists ‘Hakims’ (local physicians). About fifty informants were interviewed on random basis. The ethnobotanical data obtained was checked and compared with the existing literature and was analysed both qualitatively and quantitatively. In total 68 species of plants belonging to 44 families were recorded as used medicinally for preparations of folk recipes of 68 ailments. During the field study, it was found that the indigenous knowledge related to medicinal uses comes from women age between 30-50 years, whereas the folk medicinal use comes from men. This survey indicated that 72% source of indigenous knowledge related to the medicinal use of plants comes from people between age of 50 years, while 28% of it comes from people between age 30 and 50 years. The survey also indicated that men especially old one’s are more informative of folk knowledge of medicinal plants than women in the area. It was also indicated that about 60% of the homemade drugs were used by people above the age of 50 years, 30% by children below age of 15 years especially infants. While remaining 10% of the traditional medicines of plant origin were utilized by people between ages of 15-50 years.
A simplified method based on terrain complexity for lidar point cloud and its uncertainty analysis

LiDAR is a technology to acquire object surface measurements which intergrates GPS, IMU, laser scanning and ranging system and imaging devices together. LIDAR technology has the characteristics of highly automation, short data production cycle, the little effect of external environment and high precision and accuracy to acquire measurement information. But the number of liDAR point cloud is huge. When using large amounts of point cloud data to construct DEM, instead of improving the accuracy of DEM no significant effect, it will lead to the rapid decline in data processing speed. So it is necessary to simplify the LiDAR point cloud. When simplifying the point cloud, the criterions of point cloud simplification directly influence the distribution and quality of retention points. Usually, the point simplification criterions are based on topographic feature. Hence,this paper will proposal a new approach based on terrain complexity metrics to simplify LiDAR point cloud. Terrain complexity index present a comprehensive description of topographic features. First the index is calculated based on the existing rough precision DEM data;next,find out the point cloud simplification threshold according to the index;then set simplify rules to retain the feature points and simplify the useless points;finally, using geostatistical method,high accuracy DEM is constructed by the retention points and the precision and accuracy of LiDAR point cloud simplification is evaluated. The method will be expected to improve the precision and accuracy of LiDAR point cloud simplification.
Improvement of pavement foundation response with multi-layers of geocell reinforcement: Cyclic plate load test

Comprehensive results from cyclic plate loading at a diameter of 300 mm supported by layers of geocell are presented. The plate load tests were performed in a test pit measuring in plane and 700 mm in depth. To simulate half and full traffic loadings, fifteen loading and unloading cycles were applied to the loading plate with amplitudes of 400 and 800 kPa. The optimum embedded depth of the first layer of geocell beneath the loading plate and the optimum vertical spacing of geocell layers, based on plate settlement, are both approximately 0.2 times loading plate diameter. The results show that installation of the geocell layers in the foundation bed, increase the resilient behavior in addition to reduction of accumulated plastic and total settlement of pavement system. Efficiency of geocell reinforcement was decreased by increasing the number of the geocell layers for all applied stress levels and number of cycles of applied loading. The results of the testing reveal the ability of the multiple layers of geocell reinforcement to 'shakedown' to a fully resilient behavior after a period of plastic settlement except when there is little or no reinforcement and the applied cyclic pressure are large. When shakedown response is observed, then both the accumulated plastic settlement prior to a steady-state response being obtained and the resilient settlements thereafter are reduced. The use of four layers of geocell respectively decreases the total and residual plastic settlements about 53% and 63% and increases the resilient settlement 145% compared with the unreinforced case. The inclusion of the geocell layers also reduces the vertical stress transferred down through the pavement by distributing the load over a wider area. For example, at the end of the load cycle of the applied pressure of 800 kPa, the transferred pressure at the depth of 510 mm is reduced about 21.4%, 43.9%, 56.1% for the reinforced bases with one, two, and three layers of geocell, respectively, compared to the stress in the unreinforced bed.
Policies, Technology and Leadership Support on Work-Life Balance among Employees of Selected Private Hospital in Klang Valley

Work-life balance experience has significant consequences on employees' engagement with the organization. Hence, the objective of this research was to investigate the relationship between organizational support namely policy support, technology support and leadership support on work-life balance. The researcher conducted quantitative research and used structured survey by distributing electronic questionnaires to a sample size of 225 employees of in private hospital. To assess and measure the level of the relationship under investigation, descriptive analysis, normality analysis, reliability analysis, Pearson’s correlation analysis and linear regression were used to assess the significance of the relationship between the independent variables and dependent variable of this study. The result of the finding concluded that the most influential independent variable to the work-life balance was the leadership support, followed by the technology support. This result suggested that the better the leadership and technology support on the employees the better the work-life balance can be. The leadership passion for providing tangible and non-tangible support and making available relevant technology infrastructure, and the leader’s ability to drive effective work-life balance policies for the employees to enable them to effectively perform their jobs are essential for an engaged employees and productive organization. As the outcome of this research, it is hoped that the organization will be able to make a decisive decision in helping its employees improves their work-life balance by providing clear guideline in term of written policy, appropriate leadership supports and the right technology tool which in turn will enhances the employee's engagement and organizational efficiency.
Enhancing Microdroplet Image Analysis with Deep Learning

Microfluidics is a highly interdisciplinary field where the integration of deep-learning models has the potential to streamline processes and increase precision and reliability. This study investigates the use of deep-learning methods for the accurate detection and measurement of droplet diameters and the image restoration of low-resolution images. This study demonstrates that the Segment Anything Model (SAM) provides superior detection and reduced droplet diameter error measurement compared to the Circular Hough Transform, which is widely implemented and used in microfluidic imaging. SAM droplet detections prove to be more robust to image quality and microfluidic images with low contrast between the fluid phases. In addition, this work proves that a deep-learning super-resolution network MSRN-BAM can be trained on a dataset comprising of droplets in a flow-focusing microchannel to super-resolve images for scales ×2, ×4, ×6, ×8. Super-resolved images obtain comparable detection and segmentation results to those obtained using high-resolution images. Finally, the potential of deep learning in other computer vision tasks, such as denoising for microfluidic imaging, is shown. The results show that a DnCNN model can denoise effectively microfluidic images with additive Gaussian noise up to σ = 4. This study highlights the potential of employing deep-learning methods for the analysis of microfluidic images.