bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinicopathological and Imaging Features of Breast Papillary Lesions and Their Association with Pathologic Nipple Discharge
Authors: Oh Jeongeum , Park Ji Yeon
Published: February 2023

No studies have evaluated whether any clinicopathological or imaging characteristics of breast papillary lesions are associated with pathological nipple discharge (PND). We analyzed 301 surgically confirmed papillary breast lesions diagnosed between January 2012 and June 2022. We evaluated clinical (age of patient, size of lesion, pathologic nipple discharge, palpability, personal/family history of breast cancer or papillary lesion, location, multiplicity, and bilaterality) and imaging characteristics (Breast Imaging Reporting and Data System (BI-RADS), sonographic, and mammographic findings) and compared malignant versus non-malignant lesions and papillary lesions with versus without PND. The malignant group was significantly older than the non-malignant group (p < 0.001). Those in the malignant group were more palpable and larger (p < 0.001). Family history of cancer and peripheral location in the malignant group were more frequent than in the non-malignant group (p = 0.022 and p < 0.001). The malignant group showed higher BI-RADS, irregular shape, complex cystic and solid echo pattern, posterior enhancement on ultrasound (US), fatty breasts, visibility, and mass type on mammography (p < 0.001, 0.003, 0.009, <0.001, <0.001, <0.001, and 0.01, respectively). On multivariate logistic regression analysis, peripheral location, palpability, and age of ≥50 years were factors significantly associated with malignancy (OR: 4.125, 3.556, and 3.390, respectively; p = 0.004, 0.034, and 0.011, respectively). Central location, intraductal nature, hyper/isoechoic pattern, and ductal change were more frequent in the PND group (p = 0.003, p < 0.001, p < 0.001, and p < 0.001, respectively). Ductal change was significantly associated with PND on multivariate analysis (OR, 5.083; p = 0.029). Our findings will help clinicians examine patients with PND and breast papillary lesions more effectively.
Ethnic Differences in Western and Asian Sacroiliac Joint Anatomy for Surgical Planning of Minimally Invasive Sacroiliac Joint Fusion
Authors: Wu Christopher , Liu Yu-Cheng , Koga Hiroaki , Lee Ching-Yu , Wang Po-Yao , Cher Daniel , Reckling W. Carlton , Huang Tsung-Jen , Wu Meng-Huang
Published: February 2023

Pain originating in the sacroiliac joint (SIJ) is a contributor to chronic lower back pain. Studies on minimally invasive SIJ fusion for chronic pain have been performed in Western populations. Given the shorter stature of Asian populations compared with Western populations, questions can be raised regarding the suitability of the procedure in Asian patients. This study investigated the differences in 12 measurements of sacral and SIJ anatomy between two ethnic populations by analyzing computed tomography scans of 86 patients with SIJ pain. Univariate linear regression was performed to evaluate the correlations of body height with sacral and SIJ measurements. Multivariate regression analysis was used to evaluate systematic differences across populations. Most sacral and SIJ measurements were moderately correlated with body height. The anterior–posterior thickness of the sacral ala at the level of the S1 body was significantly smaller in the Asian patients compared with the Western patients. Most measurements were above standard surgical thresholds for safe transiliac placement of devices (1026 of 1032, 99.4%); all the measurements below these surgical thresholds were found in the anterior–posterior distance of the sacral ala at the S2 foramen level. Overall, safe placement of implants was allowed in 84 of 86 (97.7%) patients. Sacral and SIJ anatomy relevant to transiliac device placement is variable and correlates moderately with body height, and the cross-ethnic variations are not significant. Our findings raise a few concerns regarding sacral and SIJ anatomy variation that would prevent safe placement of fusion implants in Asian patients. However, considering the observed S2-related anatomic variation that could affect placement strategy, sacral and SIJ anatomy should still be preoperatively evaluated.
Multi-Parametric Cardiac Magnetic Resonance for Prediction of Heart Failure Death in Thalassemia Major
Authors: Meloni Antonella , Pistoia Laura , Gamberini Maria Rita , Cuccia Liana , Lisi Roberto , Cecinati Valerio , Ricchi Paolo , Gerardi Calogera , Restaino Gennaro , Righi Riccardo , Positano Vincenzo , Cademartiri Filippo
Published: February 2023

We assessed the prognostic value of multiparametric cardiovascular magnetic resonance (CMR) in predicting death from heart failure (HF) in thalassemia major (TM). We considered 1398 white TM patients (30.8 ± 8.9 years, 725 women) without a history of HF at baseline CMR, which was performed within the Myocardial Iron Overload in Thalassemia (MIOT) network. Iron overload was quantified by using the T2* technique, and biventricular function was determined with cine images. Late gadolinium enhancement (LGE) images were acquired to detect replacement myocardial fibrosis. During a mean follow-up of 4.83 ± 2.05 years, 49.1% of the patients changed the chelation regimen at least once; these patients were more likely to have significant myocardial iron overload (MIO) than patients who maintained the same regimen. Twelve (1.0%) patients died from HF. Significant MIO, ventricular dysfunction, ventricular dilation, and replacement myocardial fibrosis were identified as significant univariate prognosticators. Based on the presence of the four CMR predictors of HF death, patients were divided into three subgroups. Patients having all four markers had a significantly higher risk of dying for HF than patients without markers (hazard ratio (HR) = 89.93; 95%CI = 5.62–1439.46; p = 0.001) or with one to three CMR markers (HR = 12.69; 95%CI = 1.60–100.36; p = 0.016). Our findings promote the exploitation of the multiparametric potential of CMR, including LGE, for better risk stratification for TM patients.
A Mutation in CACNA1S Is Associated with Multiple Supernumerary Cusps and Root Maldevelopment
Authors: Kantaputra Piranit , Leelaadisorn Niramol , Hatsadaloi Athiwat , Quarto Natalina , Intachai Worrachet , Tongsima Sissades , Kawasaki Katsushige , Ohazama Atsushi , Ngamphiw Chumpol , Wiriyakijja Paswach
Published: February 2023

Background: Enamel knots and Hertwig epithelial root sheath (HERS) regulate the growth and folding of the dental epithelium, which subsequently determines the final form of tooth crown and roots. We would like to investigate the genetic etiology of seven patients affected with unique clinical manifestations, including multiple supernumerary cusps, single prominent premolars, and single-rooted molars. Methods: Oral and radiographic examination and whole-exome or Sanger sequencing were performed in seven patients. Immunohistochemical study during early tooth development in mice was performed. Results: A heterozygous variant (c. 865A>G; p.Ile289Val) in CACNA1S was identified in all the patients, but not in an unaffected family member and control. Immunohistochemical study showed high expression of Cacna1s in the secondary enamel knot. Conclusions: This CACNA1S variant seemed to cause impaired dental epithelial folding; too much folding in the molars and less folding in the premolars; and delayed folding (invagination) of HERS, which resulted in single-rooted molars or taurodontism. Our observation suggests that the mutation in CACNA1S might disrupt calcium influx, resulting in impaired dental epithelium folding, and subsequent abnormal crown and root morphology.
Cooperative Obstacle-Aware Surveillance for Virtual Emotion Intelligence with Low Energy Configuration
Authors: Lee Seungheyon , Lee Sooeon , Choi Yumin , Son Junggab , Bellavista Paolo , Kim Hyunbum
Published: February 2023

In this article, we introduce a cooperative obstacle-aware surveillance system for virtual emotion intelligence which is supported by low energy configuration with the minimal wasted communication cost in self-sustainable network with 6G components. We make a formal definition of the main research problem whose goal is to minimize the wasted communication range of system members on condition that the required detection accuracy with the given number of obstacles is satisfied when the requested number of obstacle-aware surveillance low energy barriers are built in self-sustainable network. To solve the problem, we have originally designed and implemented two different approaches, and then thoroughly evaluated them through extensive simulations. Then, their performances based on numerical outcomes are demonstrated with detailed discussions.
Improved Image Synthesis with Attention Mechanism for Virtual Scenes via UAV Imagery
Authors: Mo Lufeng , Zhu Yanbin , Wang Guoying , Yi Xiaomei , Wu Xiaoping , Wu Peng
Published: February 2023

Benefiting from the development of unmanned aerial vehicles (UAVs), the types and number of datasets available for image synthesis have greatly increased. Based on such abundant datasets, many types of virtual scenes can be created and visualized using image synthesis technology before they are implemented in the real world, which can then be used in different applications. To achieve a convenient and fast image synthesis model, there are some common issues such as the blurred semantic information in the normalized layer and the local spatial information of the feature map used only in the generation of images. To solve such problems, an improved image synthesis model, SYGAN, is proposed in this paper, which imports a spatial adaptive normalization module (SPADE) and a sparse attention mechanism YLG on the basis of generative adversarial network (GAN). In the proposed model SYGAN, the utilization of the normalization module SPADE can improve the imaging quality by adjusting the normalization layer with spatially adaptively learned transformations, while the sparsified attention mechanism YLG improves the receptive field of the model and has less computational complexity which saves training time. The experimental results show that the Fréchet Inception Distance (FID) of SYGAN for natural scenes and street scenes are 22.1, 31.2; the Mean Intersection over Union (MIoU) for them are 56.6, 51.4; and the Pixel Accuracy (PA) for them are 86.1, 81.3, respectively. Compared with other models such as CRN, SIMS, pix2pixHD and GauGAN, the proposed image synthesis model SYGAN has better performance and improves computational efficiency.
Files Cooperative Caching Strategy Based on Physical Layer Security for Air-to-Ground Integrated IoV
Authors: Wang Weiguang , Li Hui , Liu Yang , Cheng Wei , Liang Rui
Published: February 2023

Mobile edge cache (MEC)-enabled air-to-ground integrated Internet of Vehicles (IoV) technology can solve wireless network backhaul congestion and high latency, but security problems such as eavesdropping are often ignored when designing cache strategies. In this paper, we propose a joint design of cache strategy and physical layer transmission to improve the security offloading ratio of MEC-enabled air-to-ground IoV. By using the random geometry theory and Laplace transform, we derive the closed-form expression of the network security offloading ratio, which is defined as the probability that the request vehicle (RV) successfully finds the required file around it and obtains the file with a data rate larger than a given threshold. During the file acquisition process, we collectively consider the impact of the successful connection and secure transmission in the vehicle wireless communication. Then, we establish an optimization problem for maximizing the network security offloading ratio, in which the cache strategy and the secure transmission rate are jointly optimized. Furthermore, we propose an alternating optimization algorithm to solve the joint optimization problem. Simulation experiments verify the correctness of our theoretical derivation, and prove that the proposed cache strategy is superior to other existing cache strategies.
Acute Leukemia Diagnosis Based on Images of Lymphocytes and Monocytes Using Type-II Fuzzy Deep Network
Authors: Ansari Sanam , Navin Ahmad , Babazadeh Sangar Amin , Vaez Gharamaleki Jalil , Danishvar Sebelan
Published: February 2023

A cancer diagnosis is one of the most difficult medical challenges. Leukemia is a type of cancer that affects the bone marrow and/or blood and accounts for approximately 8% of all cancers. Understanding the epidemiology and trends of leukemia is critical for planning. Specialists diagnose leukemia using morphological analysis, but there is a possibility of error in diagnosis. Since leukemia is so difficult to diagnose, intelligent methods of diagnosis are required. The primary goal of this study is to develop a novel method for extracting features hierarchically and accurately, in order to diagnose various types of acute leukemia. This method distinguishes between acute leukemia types, namely Acute Lymphocytic Leukemia (ALL) and Acute Myeloid Leukemia (AML), by distinguishing lymphocytes from monocytes. The images used in this study are obtained from the Shahid Ghazi Tabatabai Oncology Center in Tabriz. A type-II fuzzy deep network is designed for this purpose. The proposed model has an accuracy of 98.8% and an F1-score of 98.9%, respectively. The results show that the proposed method has a high diagnostic performance. Furthermore, the proposed method has the ability to generalize more satisfactorily and has a stronger learning performance than other methods.
Maximum Power Point Tracking in Photovoltaic Systems Based on Global Sliding Mode Control with Adaptive Gain Scheduling
Authors: Uswarman Rudi , Munawar Khalid , Ramli Makbul A. M. , Bouchekara Houssem R. E. H. , Hossain Md Alamgir
Published: February 2023

Maximum power point tracking (MPPT) controllers have already achieved remarkable efficiencies. For smaller photovoltaic (PV) systems, any improvement will not really be worth mentioning as an achievement. However, for large solar farms, even a fractional improvement will eventually create a significant impact. This paper presents an MPPT control scheme using global sliding mode control (GSMC) with adaptive gain scheduling. In the two-loop controller, the first loop determines the maximum power point (MPP) reference using online calculations, while the GSMC with adaptive gain scheduling in the second loop adjusts the boost converter’s pulse width modulation (PWM) to force the PV system to operate at the MPP with improved performance. The adaptive gain scheduling regulates the gain of the switching control to maintain the controller performance over a wide range of operating conditions, while GSMC guarantees the system robustness throughout the control process by eliminating the reaching phase and improving MPPT performance. The overall PV system also has Lyapunov stability. Furthermore, the robustness analysis of the proposed controller is also performed under load variations and parametric uncertainties at various temperatures and irradiances. In the simulations, the proposed MPPT control scheme has shown faster response than other controllers, reaching the set point with rise time 0.03 s as compared to 0.07 s and 0.13 s for quasi sliding mode control (QSMC) and conventional sliding mode control (CSMC), respectively. The proposed controller showed an overshoot of 1.2 V around a steady state value of 21.9 V as compared to 1.51 V and 1.45 V, respectively, for QSMC and CSMC for a certain parametric variation. Furthermore, the proposed controller and the QSMC-based scheme showed a steady-state error of 0.3 V, while the CSMC-based approach has a more significant error. In conclusion, the proposed MPPT control scheme has a faster response and low tracking error with minimal oscillations.
The Prior Model-Guided Network for Bearing Surface Defect Detection
Authors: Feng Hanfeng , Zhuang Jiayan , Chen Xiyu , Song Kangkang , Xiao Jiangjian , Ye Sichao
Published: February 2023

Surface defect detection is a key task in industrial production processes. However, the existing methods still suffer from low detective accuracy to pit and small defects. To solve those problems, we establish a dataset of pit defects and propose a prior model-guided network for defect detection. This network is composed of a segmentation network with a weight label, classification network, and pyramid feature fusion module. The segmentation network as the prior model can improve the accuracy of the classification network. The weight label with center distance transformation can reduce the label cost of the segmentation network. The pyramid feature fusion module can adapt defects of different scales and avoid information loss of small defects. The comparison experiments are implemented to identify the performance of the proposed network. Ablation experiments are designed to specify the effectiveness of every module. Finally, the network is performed on a public dataset to verify its robustness. Experimental results reveal that the proposed method can effectively identify pit defects of different scales and improve the accuracy of defect detection. The accuracy can reach 99.3%, which is increased by 2~5% compared with other methods, revealing its excellent applicability in automatic quality inspection of industrial production.
A Knowledge Inference and Sharing-Based Open-Set Device Recognition Approach for Satellite-Terrestrial-Integrated IoT
Authors: Yang Ying , Zhu Lidong
Published: February 2023

Satellite-terrestrial-integrated internet of things (IoT) is an inevitable trend in future development, but open satellite link and massive IoT device access will bring serious security risks. However, most existing recognition models are unable to discover and reject malicious IoT devices since they lack the decision information of these unauthorized devices during training. To address this dilemma, this paper proposes a knowledge inference and sharing-based open-set recognition approach to protect satellite-terrestrial-integrated IoT. It proceeds in two steps. First, knowledge inference, where we construct ideal substitutes for unauthorized devices after reasonable inference on the training set, aims to compensate the model’s missing decision information. Second, knowledge sharing, where we inherit the existing knowledge and modify the model’s decision boundaries through model expansion and knowledge distillation, achieves accurate open-set recognition. Experiments on the ORACLE dataset demonstrated that our approach outperforms other state-of-the-art OSR methods in terms of accuracy and running time. In short, our approach has excellent performance while only slightly increasing computational complexity.
A 64-MHz 2.15-µW/MHz On-Chip Relaxation Oscillator with 130-ppm/°C Temperature Coefficient
Authors: Hosseini Asl S. Ali , Rad Reza E. , Hejazi Arash , Pu YoungGun , Lee Kang-Yoon
Published: February 2023

This paper presents a 2.15 µW/MHz at the frequency of 64 MHz relaxation oscillator with a dynamic range of frequency from 47.5 MHz to 80 MHz. To reduce the power consumption and improve energy efficiency, this work employs only one comparator and one capacitor to generate the output clock in comparison with conventional relaxation oscillator structures. A total of 50% ± 5% of the duty cycle is obtained for the output clock by implementing an auxiliary comparator. The proposed relaxation oscillator uses the output voltages of an external low-dropout (LDO) voltage and bandgap reference (BGR) for the required supply and reference voltages, respectively. Two current sources are implemented to provide the required currents for trimming the output frequency and driving the comparators. Measurement results indicate that the relaxation oscillator achieves a temperature coefficient (TC) of 130 ppm/°C over a wide temperature range from −25 °C to 135 °C at the frequency of 64 MHz. The relaxation oscillator consumes 115 µA of current at the frequency of 64 MHz under a low-dropout (LDO) voltage of 1.2 V. The proposed relaxation oscillator is analyzed and fabricated in standard 90 nm complementary metal-oxide semiconductor (CMOS) process, and the die area is 130 µm × 90 µm.
Water Retention Capacity of Leaf Litter According to Field Lysimetry
Authors: Kim Taehyun , Kim Jungyoon , Lee Jeman , Kim Hyun Seok , Park Juhan , Im Sangjun
Published: February 2023

The water retention capacity of forest leaf litter was estimated through lysimeter measurements under field conditions. Six lysimeters were placed in Pinus koraiensis and Quercus acutissima forests and filled with the surrounding leaf litter to represent the effects of litter type on the water retention capacity. Two years of measurements for rainfall and litter weight have been conducted in all lysimeters at 30 min intervals. Field measurements showed that P. koraiensis litter stored more water during rainfall periods than did Q. acutissima litter. As a result, immediately after the cessation of rainfall, 1.82 mm and 3.00 mm of water were retained per unit mass of Q. acutissima and P. koraiensis litter, respectively. Following rainfall, after the gravitational flow had entirely drained, the remaining water adhered to the litter was estimated to be 1.66 ± 1.72 mm and 2.72 ± 2.82 mm per unit mass per rainfall event for Q. acutissima and P. koraiensis litter, respectively. During the study period, approximately 83.7% of incident rainfall drained into the uppermost soil layer below the Q. acutissima litter, whereas 84.5% of rainfall percolated through the P. koraiensis litter. The moisture depletion curves indicated that 50% of the water retained in the Q. acutissima and P. koraiensis litter was lost via evaporation within 27 h and 90 h after the cessation of rainfall, respectively. This study demonstrated the water retention storage of leaf litter and its contribution to the water balance over floor litter according to litter and rainfall characteristics. The results also proved that lysimetry is a reliable method to quantify the variation of litter moisture under natural conditions.
Indoor Experiments on the Moisture Dynamic Response to Wind Velocity for Fuelbeds with Different Degrees of Compactness
Authors: Zhang Yunlin
Published: February 2023

The semiphysical method is presently the most widely used for predicting litter moisture content, but it produces some errors. These are mainly due to the simplification of the water loss process and not accounting for the fuelbed structure, which can have a serious impact on the accuracy of litter moisture content predictions and, consequently, on forest fire management. As such, in this study, we constructed fuelbeds with different degrees of compactness, and the moisture content is saturated at this time. The drying process is recorded every 10 min under different wind velocity, and the experiment is stopped when the moisture content is not changing. Taking the saturated fibers’ moisture content (30%) as the threshold value, the drying process was artificially divided into two stages (from the initial moisture content to 30%, it is a process of free water drying, and from 30% to the equilibrium moisture content, this is the process of drying of bound water), which is called the distinguishing drying process. The whole drying process (from the initial to the equilibrium moisture content) is called the undistinguishing drying process. Drying coefficient and effect factors were calculated by distinguishing and not distinguishing the drying process, respectively. This established a prediction model based on compactness and wind velocity. The results show that the drying coefficients, k2 and k, of the two litter types were significantly different: the k2 of the white oak fuelbed was significantly lower than its k, with a maximum variation difference of 57.10%. The k2 in the Masson pine fuelbed was significantly higher than its k, with a maximum variation difference of 72.76%. Wind velocity and compactness had significant effects on all the drying coefficients of the two litter types, but with changes in the effect factors. The changes in k2 were weaker than those of the other drying coefficients. Compared with the model that did not distinguish the drying process, the MRE of the prediction models for white oak and Masson pine decreased by 27.39% and 2.35%, respectively. The prediction accuracy of the model of the drying coefficient obtained by distinguishing the drying loss process was higher than that of the model that did not distinguish the drying process. This study was an indoor simulation experiment that elucidated the drying mechanism of litter and established a prediction model for the drying coefficient based on effect factors. It is of great significance for further field verification and for improving the accuracy of moisture content predictions based on the semiphysical method and will significantly improve the accuracy of fire risk and fire behavior prediction.
Effects of Aging Uncertainty on the Estimation of Growth Functions of Major Tuna Species
Authors: Lu Dongqi , Lin Qinqin , Zhu Jiangfeng , Zhang Fan
Published: February 2023

Fishery stock assessment requires accurate specification of the growth function of target species, and aging uncertainty is an important factor that affects the estimation of growth parameters. In this study, we used simulations to study the effects of two types of aging uncertainty, aging error and sampled age range, on the parameter estimation of the Von Bertalanffy growth function, including asymptotic length (L∞), growth coefficient (k), and theoretical age in the year at zero length (t0) of five important tuna species. We found that the uncertainty of the estimated growth curves increased with increasing aging errors. When aging errors were fixed among ages, the effects of age range on estimation error of growth parameters were different among species and growth parameters. When the aging error increased with age, the estimation uncertainty of L∞ and k was the greatest when only young age groups were sampled, while the estimation uncertainty of t0 was the greatest when only old age groups were sampled. Therefore, reducing the aging error and sampling individuals with a wider age range are important for increasing the accuracy and decreasing the uncertainty of the estimated growth function, which will further reduce the uncertainty in fishery stock assessment.
Dietary Selenium-Rich Lactobacillus plantarum Alleviates Cadmium-Induced Oxidative Stress and Inflammation in Bulatmai barbel Luciobarbus capito
Authors: Zhang Qing , Shang Xinchi , Geng Longwu , Che Xinghua , Wei Haijun , Tang Shizhan , Xu Wei
Published: February 2023

Cadmium (Cd) poses a great threat to the breeding of aquatic economic animals. The present study aimed to explain the antagonistic effects of selenium-enriched Lactobacillus plantarum (SL) on Cd toxicity through the expression of oxidative and inflammatory factors. A total of 225 Bulatmai barbel Luciobarbus capito (L. capito) were divided into 3 groups, namely, the control group, the Cd group (Cd, 0.05 mg·L−1), and the SL + Cd group (Cd, 0.05 mg·L−1; Nano Se, 5 mg·kg−1; L. plantarum, 105 CFU·g−1). The experiment lasted for 28 d, Sampling at 14 and 28 d, respectively. The results showed that Cd exposure caused obvious pathological damage to the liver and kidney, and the serum parameter ALT increased significantly (p < 0.05). In the Cd group, the concentration of Cd in the kidney was significantly increased (p < 0.05), and the activities of catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) in the kidney and gill were significantly decreased; malonaldehyde (MDA) increased significantly (p < 0.05) Then the mRNA expression levels in the kidney and liver were measured. Cd exposure significantly decreased the mRNA expressions of SOD, CAT, GSH-Px, HO-1, I-κBα, and Nrf2 (p < 0.05). The Cd-treated group showed significantly increased NF-kBp65, TGF-β, IL-8, IL-1, Keap1, and TNF-α expression levels. SL significantly alleviated the changes in the above indicators. The results of this study suggest that SL can trigger the Nrf2 signalling pathway and NF-kB signalling pathway to alleviate Cd toxicity. SL might be a potential drug for the treatment of Cd poisoning.
The Impact of Order Effects on the Framing of Trust and Reciprocity Behaviors
Authors: Bayat Davood , Mohamadpour Hadi , Fang Huihua , Xu Pengfei , Krueger Frank
Published: February 2023

Trust and reciprocity have paramount importance in cooperative relationships. The influence of psychological effects such as framing and anchoring on trust and reciprocity has been investigated; however, the impact of an order effect on them is still unexplored. The goal of our study was to examine how order impacts the framing of trust and reciprocity by manipulating framing and order as within- and between-subjects factors, respectively. Different groups of participants first completed two framings of the one-shot trust game (give vs. take frame) in a counterbalanced order (give first and then take second vs. take first then give second) in the role of trustors or trustees and rated the expectations of their counterparts’ decisions afterward. Our results revealed higher trust in the take than give frame in the first decision and a reverse outcome in the second decision due to strong anchoring. Reciprocity was higher in the give than take frame in the first decisions, and no difference in the second decisions was observed due to weak anchoring. Anchoring also caused an order effect in trust and reciprocity, with higher trust when the take frame was played first, and higher reciprocity when the give frame was played first. Our results contribute to our knowledge about situational factors that shape trust and reciprocity, highlighting the impact of the context of the decision environment in terms of the impact of the order on framing.
A Stereometry of Non-Memory: Mapping a Lost Past in W.G. Sebald’s Austerlitz
Authors: Holden Michael
Published: February 2023

This article presents a consideration of W.G. Sebald’s 2001 work Austerlitz—his final novel—according to a variety of spatial and cartographic concepts, including ‘fluid cartography,’ and the notion of countermapping. Particularly, the article will explore the eponymous protagonist’s sense that ‘time [does] not exist at all, only various spaces interlocking according to the rules of a higher form of stereometry,’ and will demonstrate how this subjective experience of time is a consequence of the absence of memory experienced by the protagonist in relation to his origins as a Kindertransport survivor of the Holocaust. Similarly, the article will explore how spaces—particularly buildings—and material artefacts come to act as an (insufficient) surrogate for memory within the text. All of the above will be framed according to a reading of the fundamental spatiality of Sebald’s works, and particularly their map-like quality.
Reduced OPA1, Mitochondrial Fragmentation and Increased Susceptibility to Apoptosis in Granular Corneal Dystrophy Type 2 Corneal Fibroblasts
Authors: Choi Seung-Il , Lee Ga-Hyun , Woo Jong-Hwan , Jun Ikhyun , Kim Eung Kweon
Published: February 2023

The progressive degeneration of granular corneal dystrophy type 2 (GCD2) corneal fibroblasts is associated with altered mitochondrial function, but the underlying mechanisms are incompletely understood. We investigated whether an imbalance of mitochondrial dynamics contributes to mitochondrial dysfunction of GCD2 corneal fibroblasts. Transmission electron microscopy revealed several small, structurally abnormal mitochondria with altered cristae morphology in GCD2 corneal fibroblasts. Confocal microscopy showed enhanced mitochondrial fission and fragmented mitochondrial tubular networks. Western blotting revealed higher levels of MFN1, MFN2, and pDRP1 and decreased levels of OPA1 and FIS1 in GCD2. OPA1 reduction by short hairpin RNA (shRNA) resulted in fragmented mitochondrial tubular networks and increased susceptibility to mitochondrial stress-induced apoptosis. A decrease in the mitochondrial biogenesis-related transcription factors NRF1 and PGC1α was observed, while there was an increase in the mitochondrial membrane proteins TOM20 and TIM23. Additionally, reduced levels of mitochondrial DNA (mtDNA) were exhibited in GCD2 corneal fibroblasts. These observations suggest that altered mitochondrial fission/fusion and biogenesis are the critical molecular mechanisms that cause mitochondrial dysfunction contributing to the degeneration of GCD2 corneal fibroblasts.
Functional Genetics to Understand the Etiology of Autoimmunity
Authors: Hatano Hiroaki , Ishigaki Kazuyoshi
Published: February 2023

Common variants strongly influence the risk of human autoimmunity. Two categories of variants contribute substantially to the risk: (i) coding variants of HLA genes and (ii) non-coding variants at the non-HLA loci. We recently developed a novel analytic pipeline of T cell receptor (TCR) repertoire to understand how HLA coding variants influence the risk. We identified that the risk variants increase the frequency of auto-reactive T cells. In addition, to understand how non-coding variants contribute to the risk, the researchers conducted integrative analyses using expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) and demonstrated that the risk non-coding variants dysregulate specific genes’ expression and splicing. These studies provided novel insight into the immunological consequences of two major genetic risks, and we will introduce these research achievements in detail in this review.
Efficient Selection of Gaussian Kernel SVM Parameters for Imbalanced Data
Authors: Tsai Chen-An , Chang Yu-Jing
Published: February 2023

For medical data mining, the development of a class prediction model has been widely used to deal with various kinds of data classification problems. Classification models especially for high-dimensional gene expression datasets have attracted many researchers in order to identify marker genes for distinguishing any type of cancer cells from their corresponding normal cells. However, skewed class distributions often occur in the medical datasets in which at least one of the classes has a relatively small number of observations. A classifier induced by such an imbalanced dataset typically has a high accuracy for the majority class and poor prediction for the minority class. In this study, we focus on an SVM classifier with a Gaussian radial basis kernel for a binary classification problem. In order to take advantage of an SVM and to achieve the best generalization ability for improving the classification performance, we will address two important problems: the class imbalance and parameter selection during SVM parameter optimization. First of all, we proposed a novel adjustment method called b-SVM, for adjusting the cutoff threshold of the SVM. Second, we proposed a fast and simple approach, called the Min-max gamma selection, to optimize the model parameters of SVMs without carrying out an extensive k-fold cross validation. An extensive comparison with a standard SVM and well-known existing methods are carried out to evaluate the performance of our proposed algorithms using simulated and real datasets. The experimental results show that our proposed algorithms outperform the over-sampling techniques and existing SVM-based solutions. This study also shows that the proposed Min-max gamma selection is at least 10 times faster than the cross-validation selection based on the average running time on six real datasets.
Genetic Variants of HOTAIR Associated with Colorectal Cancer: A Case-Control Study in the Saudi Population
Authors: Alzeer Haya Saad , Shaik Jilani P. , Reddy Parine Narasimha , Alanazi Mohammad , Alamri Abdullah Al , Bhat Ramesa Shafi , Daihan Sooad Al
Published: February 2023

Genetic polymorphism in long noncoding RNA (lncRNA) HOTAIR is linked with the risk and susceptibility of various cancers in humans. The mechanism involved in the development of CRC is not fully understood but single nucleotide polymorphisms (SNPs) can be used to predict its risk and prognosis. In the present case-control study, we investigated the relationship between HOTAIR (rs12826786, rs920778, and rs1899663) polymorphisms and CRC risk in the Saudi population by genotyping using a TaqMan genotyping assay in 144 CRC cases and 144 age- and sex-matched controls. We found a significant (p < 0.05) association between SNP rs920778 G > A and CRC risk, and a protective role of SNPs rs12826786 (C > T) and rs1899663 (C > A) was noticed. The homozygous mutant “AA” genotype at rs920778 (G > A) showed a significant correlation with the female sex and colon tumor site. The homozygous TT in SNP rs12816786 (C > T) showed a significant protective association in the male and homozygous AA of SNP rs1899663 (C > A) with colon tumor site. These results indicate that HOTAIR can be a powerful biomarker for predicting the risk of colorectal cancer in the Saudi population. The association between HOTAIR gene polymorphisms and the risk of CRC in the Saudi population was reported for the first time here.
Cell Type Annotation Model Selection: General-Purpose vs. Pattern-Aware Feature Gene Selection in Single-Cell RNA-Seq Data
Authors: Vasighizaker Akram , Trivedi Yash , Rueda Luis
Published: February 2023

With the advances in high-throughput sequencing technology, an increasing amount of research in revealing heterogeneity among cells has been widely performed. Differences between individual cells’ functionality are determined based on the differences in the gene expression profiles. Although the observations indicate a great performance of clustering methods, manual annotation of the clusters of cells is a challenge yet to be addressed more scalable and faster. On the other hand, due to the lack of enough labelled datasets, just a few supervised techniques have been used in cell type identification, and they obtained more robust results compared to clustering methods. A recent study showed that a complementary step of feature selection helped support vector machine (SVM) to outperform other classifiers in different scenarios. In this article, we compare and evaluate the performance of two state-of-the-art supervised methods, XGBoost and SVM, with information gain as a feature selection method. The results of the experiments on three standard scRNA-seq datasets indicate that XGBoost automatically annotates cell types in a simpler and more scalable framework. Additionally, it sheds light on the potential use of boosting tree approaches combined with deep neural networks to capture underlying information of single-cell RNA-Seq data more effectively. It can be used to identify marker genes and other applications in biological studies.
Syndepositional Uptake of Uranium, Molybdenum and Vanadium into Modern Bahamian Carbonate Sediments during Early Diagenesis
Authors: Magette Evan , Turner Adam , Peng Yongbo , Herrmann Achim D.
Published: February 2023

Syndepositional diagenesis is a complicating factor when interpreting geochemical proxies in carbonate sedimentary environments. Previous studies have suggested that carbonate deposits may preserve the geochemical and isotopic signatures of seawater that can be used for paleo-redox reconstructions. However, more work is necessary to understand how these trace metals are preserved. The present study examines shallow marine carbonate sediments from the Bahamas to better understand diagenetic effects on trace metal uptake and sequestration. Analysis of diagenetic effects and trace metal uptake follows a multi-method approach, combining sequential extraction, stable isotope analyses, and rare earth elemental analysis. Stable isotopes track bacterial sulfate reduction, denitrification, and organic matter source and provide insight into thresholds and processes for the authigenic trace metal uptake. Importantly, exchangeable phases exhibit authigenic accumulation of molybdenum, uranium and vanadium, and intensified bacterial sulfate reduction is evidenced by most depleted sulfur isotope signatures. In addition, rare earth element values are very indicative proxies that suggest altered primary seawater trace element in carbonates (no cerium or lanthanum anomaly, moderate heavy rare earth element enrichment, decreased y/ho ratios and positive correlations between aluminum, manganese, and iron). Taken together, these results allow the development of a framework to better understand how to apply sedimentary geochemistry of carbonate rocks to paleo-environments as this study shows significant authigenic accumulation of redox-sensitive trace metals by exchangeable phases.
Regional Identity and Intangible Heritage Related to Saffron Cultivation in Castilla-La Mancha (Spain)
Authors: Ruiz Pulpón Ángel Raúl , Cañizares Ruiz María del Carmen , Martínez Sánchez-Mateos Héctor S.
Published: February 2023

Agriculture is an important economic activity across much of the Western world. Beyond its productive purpose, we can also identify a cultural function that is expressed in the existence of a rich heritage associated with the interactions between nature and humans over time. This heritage includes tangible and intangible assets, the latter including traditional knowledge, history, knowledge of natural cycles, and the identification of the local population with its landscapes; in short, resources are understood as a legacy that needs to be reappraised and passed on to future generations. Saffron cultivation is an example of an agricultural landscape with significant intangible heritage values associated with the know-how and the family-run nature of the farms. The resources linked to saffron cultivation in the region of Castilla-La Mancha (Spain) are described in this paper, with an emphasis on how local communities perceive them as an integral part of their geographical identity. The results, following in-depth interviews with different local actors, demonstrate the potential for the intangible values associated with saffron to drive local development in many rural areas once they have been reappraised and classified as assets for attracting tourism.
The Role of Dyadic Teacher–Student Relationships for Primary School Teachers’ Well-Being
Authors: Haldimann Manuela , Morinaj Julia , Hascher Tina
Published: February 2023

Teacher well-being is not only relevant for the effectiveness of individual teaching and student learning but also for general school quality and societal functioning, because teacher well-being is related to lower burnout risks and lower attrition. Previous research identified social relationships in school as a crucial source of teacher well-being. However, studies investigating the role of teacher–student relationships as a determining factor for teacher well-being are still scarce. This study takes a qualitative approach toward investigating the role of dyadic teacher–student relationships in teacher well-being. We analyzed twenty-six semi-structured interviews with Swiss primary school teachers, using a qualitative content analysis. The results showed that dyadic teacher–student relationships played an important to a very important role in the everyday life of teachers and were a source of both positive and negative emotions, cognitions, and physical sensations. The quality of the dyadic teacher–student relationship was reflected in the social–emotional competence of both teachers and students. Conflicts were not necessarily inhibiting teacher well-being. The findings of this study can be used to inform teacher-training institutions, as well as authorities, on how to support teachers in building relationships with their students and, in turn, foster their well-being.
The Impact of a Pulsed Light Stream on the Quality and Durability of the Cold-Stored Longissimus Dorsal Muscle of Pigs
Authors: Duma-Kocan Paulina , Rudy Mariusz , Gil Marian , Stanisławczyk Renata , Żurek Jagoda , Zaguła Grzegorz
Published: February 2023

The purpose of this study was to investigate the effect of pulsed light application (exposure to a pulsed light beam (PL) of 400 Hz for a period of 60 s, with an energy dose of 600 mW and wavelengths of 660 and 405 nm) on the physicochemical, technological, and sensory properties, as well as the nutritional value and shelf life of cold-storage pig longissimus dorsi muscle. Each muscle was divided into six parts, three of which were control samples, and the rest were exposed to pulsed light. The detailed laboratory tests of the meat were conducted 1, 7, and 10 days after slaughter. The meat was cold stored at +3 °C ± 0.5 °C. The study showed that the application of pulsed light has a favorable effect on lowering the TBARS index, oxidation-reduction potential, and water activity values. In addition, the application of PL had no statistically significant effect on the variation in the perception of selected sensory characteristics of meat. Furthermore, PL processing, as a low-energy-intensive method that can be environmentally friendly and thus have a large potential for implementation, is an innovative way to extend the shelf life, especially of raw meat, without a negative impact on its quality. This is of particular importance for food security (especially in the quantitative and qualitative aspects of food, but also in terms of food safety).
Evidence from Human Studies for Utilising Cannabinoids for the Treatment of Substance-Use Disorders: A Scoping Review with a Systematic Approach
Authors: Gharbi Kayvan Ali , Bonomo Yvonne Ann , Hallinan Christine Mary
Published: February 2023

Substance-use disorders are pervasive, comorbid with a plethora of disease and possess limited treatment options. Medicinal cannabinoids have been proposed as a novel potential treatment based on preclinical/animal trials. The objective of this study was to examine the efficacy and safety of potential therapeutics targeting the endocannabinoid system in the treatment of substance-use disorders. We performed a scoping review using a systematic approach of systematic reviews, narrative reviews, and randomised control trials that utilised cannabinoids as treatment for substance-use disorders. For this scoping review we used the PRISMA guidelines, a framework for systematic reviews and meta-analyses, to inform our methodology. We conducted a manual search of Medline, Embase, and Scopus databases in July 2022. Of the 253 results returned by the databases, 25 studies including reviews were identified as relevant, from which 29 randomised controlled trials were derived and analysed via a primary study decomposition. This review captured a small volume of highly heterogenous primary literature investing the therapeutic effect of cannabinoids for substance-use disorders. The most promising findings appeared to be for cannabis-use disorder. Cannabidiol appeared to be the cannabinoid showing the most promise for the treatment of multiple-substance-use disorders.