Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaborative Neural Social Recommendation

Collaborative filtering (CF) is one of the most popular techniques for building recommender systems. To overcome the data sparsity in CF, social recommender systems have emerged to boost recommendation performance by utilizing social correlation among users’ interests. Recently, inspired by the immense success of deep learning for embedding learning, neural network-based recommender systems have shown promising recommendation performance. Nevertheless, few researchers have attempted to tackle the social recommendation problem with neural models. To this end, in this paper, we design a neural architecture that organically combines the intrinsic relationship between social network structure and user–item interaction behavior for social recommendation. Two key challenges arise in this process: first, how to incorporate the social correlation of users’ interests in this neural model, and second, how to design a neural architecture to capture the unique characteristics of user–item interaction behavior for recommendation. To tackle these two challenges, we develop a model named collaborative neural social recommendation (CNSR) with two parts: 1) a social embedding part and 2) a collaborative neural recommendation (CNR) part. In CNSR, the user embedding leverages each user’s social embedding learned from an unsupervised deep learning technique with social correlation regularization. The user and item embeddings are then fed into a unique neural network with a newly designed collaboration layer to model both the shallow collaborative and deep complex interaction relationships between users and items. We further propose a joint learning framework to allow the social embedding part and the CNR part to mutually enhance each other. Finally, extensive experimental results on two real-world datasets clearly demonstrate the effectiveness of our proposed model.
Relationship between the Intermediate Soil State and Settlement Control Measures during Tunnel Construction Undercrossing the Existing Station

Settlement control of existing stations has consistently been a key issue in tunnel construction. Intermediate soil has a significant influence on the settlement of the existing station as a connector between the new tunnel and the existing station which should be considered when selecting settlement control measures. To clarify the relationship between the state of the intermediate soil and the settlement and control measures of the existing station, this study investigated 49 new tunnel projects under existing stations and elucidated the relationship between the settlement and the settlement control measures of the existing station and the intermediate soil. The relationship between the failure of the intermediate soil and the settlement of the existing station was further analyzed by numerical simulation. Lastly, a simple mechanical model of intermediate soil failure was constructed to determine the stress state of the intermediate soil in constructing a tunnel under the existing station to guide the formulation of settlement control measures for the existing station. Hence, when the intermediate soil is completely destroyed, active control measures, such as jack or grouting lifting, should be implemented; when the intermediate soil is partially damaged, passive control measures should be undertaken. Thus, this study can provide a reference for settlement control of tunnels under existing stations.
“It’s real. It’s a thing:” Mental health counselors’ listening exhaustion during COVID-19

Mental health counselors regularly use active listening skills to be present with each client; however, active listening may cause burnout due to high emotional labor, inadequate staffing, excessive workload, and many other issues, each of which contributes to career exits. COVID-19 exacerbated all of these factors, and—adding to already stressful conditions—most mental health professionals were forced to conduct therapy sessions via telehealth. For this study, twenty licensed mental health counselors at various stages of their careers were interviewed during the height of the pandemic to understand their experiences with the technology and other factors related to their workload during that time. Thematic qualitative analysis was used to explore effects of active listening—including requisite adjustments made for virtual therapy sessions—on counselors’ emotional exhaustion and burnout levels. Results show how back-to-back, daily therapy sessions increased listening exhaustion levels and that counselors experienced both long-term and short-term listening exhaustion when utilizing telehealth due to lack of nonverbal cues and other related factors pertaining to online delivery. Implications for counselors, social workers, and other mental health professionals are discussed.
Halal Korean Cuisine: Understanding The Drivers Of Purchase Intention Among Indonesian Muslims

The purpose of this study is to better understand the reasons that motivate Indonesian Muslims to buy Korean food that has received MUI Halal certification. This study used a purposive sampling methodology with the following criteria: Muslims in Indonesia who are familiar with Korean cuisine and who have obtained MUI Halal certification. 190 people participated in this study, and the PLS-SEM method was used to process the data. Knowledge about Halal cuisine, attitudes, religion, and buying intentions are the factors used in this study. The findings of this study suggest that religiosity and understanding of halal cuisine have a positive and significant impact on sentiments about Korean food that has received MUI Halal certification. Awareness of halal food and attitudes toward it have a positive and considerable impact on consumers' intentions to purchase Korean food that has received MUI Halal certification. The intention to purchase Korean cuisine that has received MUI Halal certification, however, was found to be unaffected by religion.The findings of this study are anticipated to assist Korean food businesses in creating features that will improve Muslim consumers' inclinations to buy Korean food that has received MUI Halal certification.
Analysis and Classification of Bone Fractures Using Machine Learning Techniques

Human bones are the hard organs that protect vital organs such as the heart, lungs, and other internal organs. Fractures of the bones are a prevalent issue among humans. Bone fractures may develop from an accident or another circumstance when there is great pressure on the bones. It may be difficult and time-consuming to determine the site of a fracture in a patient who is suffering discomfort. The manual examination of fractures during radiological interpretation is a time-consuming and error-prone process. This may result in erroneous detection, poor fracture healing, and an extensive procedure. So, this research proposed an effective approach to rectifying bone fractures with the inclusion of the latest technologies. The solution is proposed by employing a Deep learning model. Moreover, a novel concept of classification is also incorporated. Firstly; the MURA dataset was collected from Stanford. Secondly; The proposed model used techniques like DCNN (Deep Convolution Neural Network) and use Alex Net model. Bones are classified into fractured or non-fractured through a classification approach. The proposed model was created using Google Colab. The proposed model was trained by repeating several experiments. The performance was evaluated based on accuracy. The suggested model results were compared with baseline algorithms as well. Consequently, the findings of this work will be useful for the medical industry.
Designing Optimal Frequency Offsets for Frequency Diverse Array MIMO Radar

Frequency diverse array (FDA) radars provide a potential solution to target localization along the slant range and azimuth angle due to the range-angle-dependent transmit beampattern caused by the used frequency increments. However, the S-shaped beampattern resulting from the standard FDA leads to multiple candidate location estimates, introducing ambiguity in the target localization. To make full use of the degrees of freedom (DOF) allowed by the frequency increments, we, here, propose an optimal FDA multiple-input multiple-output (MIMO) frequency design scheme based on the Cramér–Rao lower bound (CRLB). The resulting system, here termed the optimal FDA-MIMO (OFDA-MIMO), is formed by optimizing the expected localization estimation accuracy, given the available prior knowledge of potential target locations. We examine two different modeling scenarios, one where the prior information is known up to intervals on the parameters, formulated using the worst-case CRLB (WCRLB), and one where the parameters are known to come from prior distributions, formulated using the corresponding Bayesian CRLB (BCRLB). The used frequency offsets are found as those minimizing the CRLBs, and may be iteratively refined as further information becomes available in a multipulse scenario. Both theoretical analysis and simulation results validate the preferable performance of the proposed system as compared with alternative frequency selection schemes.
Adult immersion test for assessment of amitraz resistance in Rhipicephalus sanguineus ticks

Ticks are obligate blood sucking ectoparasites recognised globally as vectors of various pathogens, next to mosquitoes. The present study is conducted on brown dog ticks collected from naturally infested dogs in and around Thrissur district. Adult immersion test was performed and the parameters such as engorged tick weight, egg mass weight as well as tick mortality were recorded to derive the reproductive indices, percentage inhibition of oviposition and percentage mortalities. Non-linear regression analysis of the dose response data yielded the LC50 values at 95% confidence intervals and, the slopes and regression coefficients of the different parameters were also derived. The Resistance factors (RF) were calculated to categorise resistance levels into I, II, III and IV. Resistance to amitraz was detected at level II in tick isolates collected from Choolissery and Mundur, at level III and level IV in isolates collected from Mannuthy and Paravattani, respectively. Two isolates collected from Mannuthy were found to be susceptible. One way ANOVA of resistance levels revealed that the resistance levels III and IV were significantly different from that of susceptible and resistance level II. This is the first report on detection of amitraz resistance levels in dog ticks from south India calling for proper implementation of tick control strategies to prevent spread of amitraz resistance.
A Lightweight User Authentication Scheme for Multi-Gateway Based Wireless Sensor Networks Using Rabin Cryptosystem

The existing authentication schemes in wireless sensor networks (WSNs) are mostly used in single-gateway mode. With the wide deployment of WSNs, the drawbacks of single-gateway mode are gradually becoming more noticeable. In traditional single-gateway WSNs, high-speed data streams are prone to conflict during data aggregation, which may reduce the performance of the network. Most of the existing multi-gateway schemes are based on lightweight operations such as hash functions, exclusive OR (XOR), and symmetric encryption algorithms, which cannot achieve forward secrecy. In this paper, we propose a lightweight multi-gateway authentication scheme based on the Rabin cryptosystem. Since Rabin only requires a module-square operation for encryption, its computational overhead is relatively low. Therefore, the encryption operation is usually used on the sensor side with resource constraints to save resources. In addition, Scyther is used to prove the security of the proposed scheme. The analysis shows that the proposed scheme can achieve higher security with lower computational overhead.
Choices and Challenges With Treatment of Myasthenia Gravis in Pregnancy: A Systematic Review

Myasthenia gravis (MG) is an autoimmune disease affecting young women in their second and third decades, coinciding with their reproductive years. We aim to explore the choices and challenges in the treatment of MG in pregnancy. Cochrane, PubMed, Google Scholar, and Embase were the four databases systematically searched for studies with patients reporting pregnancy outcomes for women with MG during pregnancy using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) technique. Quality assessment was done using the Joanna Briggs Institute critical tool (JBI, Adelaide, Australia) for methodological quality. From 2000 to 2023, 40 studies from database search results were considered. There is a substantial risk of complications with MG, especially if it appears during pregnancy. In particular, widespread weakness is a cause of severe, life-threatening disorders, but several treatment options are available.
Unplanned 30-Day Readmission in Glioblastoma Patients: Implications for the Extent of Resection and Adjuvant Therapy

Simple Summary Unplanned early hospital readmission (UER) within 30 days seems to be associated with reduced overall survival in patients diagnosed with glioblastoma (GBM). In this study, we retrospectively analyzed how the extent of tumor resection or adjuvant tumor treatment affected the prognosis in GBM patients that experienced UER. A total of 276 patients were included in the study. UER occurred in 13.4% of all cases and significantly reduced the median survival prognosis (5.7 vs. 14.5 months). Moreover, GBM patients suffering from UER did not benefit from extensive tumor resection (5.1 vs. 5.7 months). Concerning post-operative treatment strategies, the application of radio-chemotherapy prolonged the overall survival of GBM patients, even when UER occurred (1.1 (without post-operative therapy) vs. 4.3 (radiotherapy alone) vs. 7.8 months (radio-chemotherapy)). Therefore, GBM patients experiencing unplanned early readmission within 30 days still benefitted from more aggressive post-operative therapy. Abstract Background: Unplanned early readmission (UER) within 30 days after hospital release is a negative prognostic marker for patients diagnosed with glioblastoma (GBM). This work analyzes the impact of UER on the effects of standard therapy modalities for GBM patients, including the extent of resection (EOR) and adjuvant therapy regimen. Methods: Records were searched for patients with newly diagnosed GBM between 2014 and 2020 who were treated at our facility. Exclusion criteria were being aged below 18 years or missing data. An overall survival (OS) analysis (Kaplan–Meier estimate; Cox regression) was performed on various GBM patient sub-cohorts. Results: A total of 276 patients were included in the study. UER occurred in 13.4% (n = 37) of all cases, significantly reduced median OS (5.7 vs. 14.5 months, p < 0.001 by logrank), and was associated with an increased hazard of mortality (hazard ratio 3.875, p < 0.001) in multivariate Cox regression when other clinical parameters were applied as confounders. The Kaplan–Meier analysis also showed that patients experiencing UER still benefitted from adjuvant radio-chemotherapy when compared to radiotherapy or no adjuvant therapy (p < 0.001 by logrank). A higher EOR did not improve OS in GBM patients with UER (p = 0.659). Conclusion: UER is negatively associated with survival in GBM patients. In contrast to EOR, adjuvant radio-chemotherapy was beneficial, even after UER.
Growth Pattern of Preterm Newborns under 34 Weeks of Gestation in a Tertiary Care Hospital, Tamil Nadu, India: A Retrospective Study

Introduction: The proportion of preterm babies is increasing now a days and these babies are more prone to short and long term disabilities. Hence, growth monitoring is essential, to identify the premature infants, who are at increased risk of growth lag and poor neurodevelopmental outcomes. Aim: To assess the growth pattern of infants, who are born ≤34 weeks of gestational age using the intergrowth-21st growth charts. Materials and Methods: This retrospective study was conducted in the Department of Neonatology at Chengalpattu Medical College and Hospital, a Tertiary Care Center Chengalpattu, Tamil Nadu, India. The duration of the study was one year, from January 2020 to December 2020. A total of 118 neonates born at ≤34 weeks gestational age, who were admitted in the hospital and stayed for 14 days and more were included in the study. The data was collected from discharge sheets and an electronic database. Intergrowth-21st growth charts are used to assess growth. Weight, duration of hospital stay and Extrauterine Growth Restriction (EUGR) were assessed for all the newborns. At discharge, the EUGR status of the babies was determined using a weight ≤-1.28 Standard Deviation (SD) criterion. Continuous variables were presented as means with SD. The data was analysed using Statistical Package for Social Sciences (SPSS) version 24.0. Results: The mean maternal and gestational age of the study participants was 24.9±4.14 years and 31.6 ±1.42 weeks and birth weight of babies were 1608.06 gm (±275), respectively. The proportions of Appropriate for gestational age (AGA) and Small For Gestational Age (SGA) were 95 (80.5%) and 18 (15.2%), respectively. The mean time to reach full feeds was 10.4 days (±2.7days), and the duration of stay in the hospital was 24.8 days (±9.6 days). The mean discharge weight and gestational age of babies were 1732 gm (±226 gm) and 35.4 weeks (±1.47 weeks), respectively. The common complications observed, were those requiring antibiotics (73.7%), respiratory support (61.01%), and Respiratory Distress Syndrome (RDS) (22.8%). Conclusion: Preterm newborns are more vulnerable to EUGR. The EUGR proportion in present study was 72.8%. The issues that raise the risk of EUGR, during the hospital stay must be adequately addressed in order to ensure that, preterm neonates develops normally.
The Role of WISHE in Secondary Eyewall Formation

Numerical simulations are conducted to examine the role of the wind-induced surface heat exchange (WISHE) mechanism in secondary eyewall formation (SEF). The control experiment exhibits a coherent secondary eyewall structure as quantified by various parameters (e.g., the azimuthal-mean tangential wind and vertical velocity). Prior to SEF, an area characterized by increasing diabatic heating, enhanced inertial stability, and increasing supergradient winds at the top of the boundary layer is observed outside the eyewall. While these characteristics offer the possibility of both balanced and unbalanced dynamical pathways to SEF, the focus of this study is to evaluate the impact of WISHE. To examine the sensitivity of SEF to WISHE, the surface wind used for the calculation of surface heat fluxes is capped at several designated values and at different radial intervals. When the heat fluxes are moderately suppressed around and outside the SEF region observed in the control experiment, sensitivity experiments show that the formation of the outer eyewall is delayed, and the intensity of both eyewalls is weaker. When the heat fluxes are strongly suppressed in the same region, SEF does not occur. In contrast, suppressing the surface heat fluxes in the storm’s inner-core region has limited effect on the evolution of the outer eyewall. This study provides important physical insight into SEF, indicating that WISHE plays a crucial role in SEF and tropical cyclone evolution.
Novel Discovery of the Somatostatin Receptor (SSTR2) in Pleomorphic Adenomas via Immunohistochemical Analysis of Tumors of the Salivary Glands

Simple Summary Currently, the diagnosis of salivary gland tumors using current imaging techniques is unreliable. In this study we examined salivary gland tumors and discovered that the pleomorphic adenoma, a tumor which should be surgically removed because it has a tendency to become malign, has a strong concentration of the somatostatin receptor 2. This characteristic may allow physicians to identify and potentially treat the tumor in a non-invasive manner. Abstract Reliable preoperative diagnosis between salivary gland tumor entities is difficult. In this monocentric retrospective study, we examined the somatostatin receptor 2 (SSTR2) status of salivary gland tumors after salivary gland tumor resection via immunohistochemistry (IHC), and stains were compared in analogy to the HER2 mamma scale. A total of 42.3% of all pleomorphic adenoma (PA) tumors (42 of 99, 95% confidence interval 32.5–52.8%) demonstrated ≥20% of cells displaying the SSTR2 as compared to just 1% of all other tumors (1/160, 95% CI 0.02–3.4%). The other tumor was a neuroendocrine carcinoma. PA had a higher intensity of SSTR2 staining, with 90.9% staining ≥ an intensity of 2 (moderate). Tumors with an intensity of SSTR2 expression equal to or greater than 2 had an 89.9% likelihood of being a PA (95% CI: 82.2–95.0%, AUC: 0.928). Only one Warthin tumor demonstrated a ‘strong’ SSTR2 staining intensity. No Warthin tumor showed a percentage of cells staining for SSTR2 above ≥20%. This result demonstrates consistent and strong expression of SSTR2 in PAs as compared to Warthin tumors, which may allow physicians to utilize radioligand-somatostatin analog PET CT/MR imaging to diagnose the PA. SSTR2 positivity, if shown to be clinically relevant, may allow peptide receptor radionuclide therapy in the future.
Global Potential Distribution of Sarcophaga dux and Sarcophaga haemorrhoidalis under Climate Change

Climate change has a direct impact on biodiversity, affecting ecosystems and altering their balance. Many taxa, including insects, are likely to be affected by climate change in terms of geographic distribution. Sarcophagid flies, such as Sarcophaga dux and Sarcophaga haemorrhoidalis, are important flies because of their apparent ecological, forensic, and medical significance. Global habitat suitability varies as a result of climate change. In wildlife management, models that predict species’ spatial distribution are being used more and more, which emphasizes the need for reliable methods to evaluate their accuracy. Consequently, the statistical robustness of maximum entropy was implemented in Maxent to model the current and future global distribution of both flies, involving occurrence data of 155 and 87 points for S. dux and S. haemorrhoidalis, respectively. Based on the Pearson correlation and Jackknife test, five bioclimatic variables were used for current and future predictive models. For future models, two representative concentration pathways (RCPs), 2.6 and 8.5, for 2050 and 2070 were applied. Both statistical parameters, AUC and TSS, were used to assess the resulting models with values equal to 0.80 (±0.01) and 0.9, respectively, for S. dux and equal to 0.86 (±0.01) and 0.92 for S. haemorrhoidalis. The resulting models for S. dux showed high and very high suitability in Europe, Tropical Africa, India, Canada, the United States from Alaska to Florida, Brazil, and Australia. In the case of S. haemorrhoidalis Europe and North and South America displayed low to medium suitability, but North Africa, including Egypt; Tropical Africa; Asia, including Saudi Arabia, India, and China; and Australia showed increased suitability. Decision-makers are put in conflict with their duties to avert destruction in the economic, medical, and ecological sectors by such anticipated models, and use these predictive models as a cornerstone for building a control strategy for such forensically important flies at local spatial scales.
The Contribution of the Individual Rib to Thoracic Response Under Dynamic Loading Conditions: A Preliminary Hierarchical Approach

ii Dedication.iv Acknowledgments . v Vita.viii List of Tables.xiiii List of Figures.xiv Chapter 1: Introduction.1 1.1 Thoracic Injury Risk.1 1.1.1 Thorax Anatomy.1 1.1.2 Thorax Injuries.3 1.1.3 Thorax Response.5 1.2 Component Level Testing.8 1.3 Relationship Between the Rib and Thorax.10 1.4 Project Goals.11