Miracle-dz/UniFAR-FTUs huggingface dataset:
Review of Time Series Traffic Forecasting Methods

Traffic forecasting is an important part of the smart transportation system, and accurate traffic forecasting is crucial for urban traffic scheduling and public travel planning. The traffic forecasting problem is greatly affected by the time dimension, and it is of great significance to investigate and summarize the related methods of time series traffic forecasting. Aiming at the problem of time series traffic forecasting, this paper focuses on the existing time series traffic forecasting models based on deep learning, and studies and analyzes the application fields and structural characteristics of different forecasting models. Finally, the current mainstream traffic prediction datasets are introduced, and the main challenges and solutions in the current traffic prediction field are discussed, which provides a reference for solving the problem of intelligent traffic prediction.
Genome-Wide Association Study for Grain Protein, Thousand Kernel Weight, and Normalized Difference Vegetation Index in Bread Wheat (Triticum aestivum L.)

Genomic regions governing grain protein content (GPC), 1000 kernel weight (TKW), and normalized difference vegetation index (NDVI) were studied in a set of 280 bread wheat genotypes. The genome-wide association (GWAS) panel was genotyped using a 35K Axiom array and phenotyped in three environments. A total of 26 marker-trait associations (MTAs) were detected on 18 chromosomes covering the A, B, and D subgenomes of bread wheat. The GPC showed the maximum MTAs (16), followed by NDVI (6), and TKW (4). A maximum of 10 MTAs was located on the B subgenome, whereas, 8 MTAs each were mapped on the A and D subgenomes. In silico analysis suggest that the SNPs were located on important putative candidate genes such as NAC domain superfamily, zinc finger RING-H2-type, aspartic peptidase domain, folylpolyglutamate synthase, serine/threonine-protein kinase LRK10, pentatricopeptide repeat, protein kinase-like domain superfamily, cytochrome P450, and expansin. These candidate genes were found to have different roles including regulation of stress tolerance, nutrient remobilization, protein accumulation, nitrogen utilization, photosynthesis, grain filling, mitochondrial function, and kernel development. The effects of newly identified MTAs will be validated in different genetic backgrounds for further utilization in marker-aided breeding.
True and false forbidden patterns in deterministic and random dynamics

In this letter we discuss some properties of order patterns both in deterministic and random orbit generation. As it turns out, the orbits of one-dimensional maps have always forbidden patterns, i.e., order patterns that cannot occur, in contrast with random time series, in which any order pattern appears with probability one. However, finite random sequences may exhibit “false” forbidden patterns with non-vanishing probability. In this case, forbidden patterns decay with the sequence length, thus unveiling the random nature of the sequence. Last but not least, true forbidden patterns are robust against noise and disintegrate with a rate that depends on the noise level. These properties can be embodied in a simple method to distinguish deterministic, finite time series with very high levels of observational noise, from random ones. We present numerical evidence for white noise.
COMMON FIXED POINT THEOREMS FOR TWO SELFMAPPINGS OF GENERALIZATION OF A b-METRIC SPACE SATISFYING AN IMPLICIT RELATION

I n this paper, we prove common fixed point theorems for two self mappings of generalization of a b-metric space satisfying an implicit relation and a property (E.A) introduced in [M.Aamri, D.El Moutawakil, some new common fixed point theorems under strict contractive conditions, J.Math.Anal.Appl. 270 (2002) 181-188]. In the setting of a b-metric space (see Stefan Czerwik, Contraction mappings in b-metric spaces, Acta Math. Inform. Univ. Ostraviensis 1, 5–11, 1993 and nonlinear set-valued contraction mappings in b-metric spaces, Atti Sem. Mat. Fis. Univ. Modena 46 (2), 263–276, 1998), our theorem generalizes Theorem 4.1 of (Mohamed Akkouchi, common fixed point theorems for two self mappings of a b-metric space under an implicit relation, Hacettepe Journal of Mathematics and Statistics Volume 40 (6) (2011), 805 – 810[2].
First Organoid Intelligence (OI) workshop to form an OI community

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22–24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.
Coupling and interaction between science and technology finance and green development: Based on coupling coordination degree model and panel vector autoregression model

Exploring the coupling and coordination between science and technology finance and green development is a critical action that needs to be addressed in achieving high-quality development in China. Based on the coupling coordination degree model and panel vector autoregression (PVAR) model, this paper uses the relevant data of 274 cities in China from 2003 to 2020 to study the relationship between science and technology finance and green development. The results show that: 1) The relationship between science and technology finance and green development has changed from low coupling coordination to medium coupling coordination in the sample period. 2) The Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta regions are at a relatively high level of coupling and coordination as a whole, while other regions are at a relatively low level of coupling and coordination. 3) Through the analysis of the spatial characteristics of the coupling coordination degree, it is found that the coupling coordination degree of China’s urban science and technology finance and green development is generally positive spatial autocorrelation. Spatial correlations continue to strengthen over time. 4) By establishing a PVAR model, we examined the interaction between science and technology finance, green development, and their coupling coordination. Science and technology finance, green development and their coupling coordination degree are themselves affected. We have comprehensively and objectively grasped the matching status of China’s urban science and technology finance and green development, providing a reference for promoting the adaptation of science and technology finance to green development.
Damage correlations in semiconductors exposed to gamma, electron and proton radiations

The use of nonionizing energy loss (NIEL) in predicting the effect of gamma, electron, and proton irradiations on Si, GaAs, and InP devices is discussed. The NIEL for electrons and protons has been calculated from the displacement threshold to 200 MeV. Convoluting the electron NIEL with the slowed down Compton secondary electron spectrum gives an effective NIEL for CO/sup 60/ gammas, enabling gamma-induced displacement damage to be correlated with particle results. The fluences of 1 MeV electrons equivalent to irradiation with 1 Mrad(Si) for Si, GaAs, and InP are given. Analytic proton NIEL calculations and results derived from the Monte Carlo TRIM agree exactly, as long as straggling is not significant. The NIEL calculations are compared with experimental proton and electron damage coefficients using solar cells as examples. A linear relationship is found between the NIEL and proton damage coefficients for Si, GaAs, and InP devices. For electrons, there appears to be a linear dependence for n-Si and n-GaAs, but for p-Si there is a quadratic relationship which decreases the damage coefficient at 1 MeV by a factor of approximately 10 below the value for n-Si. >
Numerical Investigation of Contrasting Flow Physics in Different Zones of a High-Lift Low Pressure Turbine Blade

© 2016 by ASME. Using a range of high-fidelity large eddy simulations (LES), the contrasting flow physics on the suction surface, pressure surface, and endwalls of a low-pressure turbine (LPT) blade (T106A) was studied. The current paper attempts to provide an improved understanding of the flow physics over these three zones under the influence of different inflow boundary conditions. These include: (a) the effect of wakes at low and high turbulence intensity on the flow at midspan and (b) the impact of the state of the incoming boundary layer on endwall flow features. On the suction surface, the pressure fluctuations on the aft portion significantly reduced at high freestream turbulence (FST). The instantaneous flow features revealed that this reduction at high FST (HF) is due to the dominance of "streak-based" transition over the "Kelvin-Helmholtz" (KH) based transition. Also, the transition mechanisms observed over the turbine blade were largely similar to those on a flat plate subjected to pressure gradients. On pressure surface, elongated vortices were observed at low FST (LF). The possibility of the coexistence of both the Gortler instability and the severe straining of the wakes in the formation of these elongated vortices was suggested. While this was true for the cases under low turbulence levels, the elongated vortices vanished at higher levels of background turbulence. At endwalls, the effect of the state of the incoming boundary layer on flow features has been demonstrated. The loss cores corresponding to the passage vortex and trailing shed vortex were moved farther from the endwall with a turbulent boundary layer (TBL) when compared to an incoming laminar boundary layer (LBL). Multiple horse-shoe vortices, which constantly moved toward the leading edge due to a low-frequency unstable mechanism, were captured.
A Tumor-admixture Model to Interrogate Immune Cell–dependent Tumorigenesis

A rigorous determination of effector contributions of tumor-infiltrating immune cells is critical for identifying targetable molecular mechanisms for the development of novel cancer immunotherapies. A tumor/immune cell–admixture model is an advantageous strategy to study tumor immunology as the fundamental methodology is relatively straightforward, while also being adaptable to scale to address increasingly complex research queries. Ultimately, this method can provide robust experimental information to complement more traditional murine models of tumor immunology. Here, we describe a tumor/macrophage-admixture model using bone marrow–derived macrophages to investigate macrophage-dependent tumorigenesis. Additionally, we provide commentary on potential branch points for optimization with other immune cells, experimental techniques, and cancer types.
Association between KEGG Biological Pathways and Adverse Drug Reactions of HIV, TB and Other Drugs Frequently Implicated in ADRs

—In South Africa, the proportion of patients admitted to hospitals with Adverse Drug Reactions (ADRs) range between 2-21.4% and between 1.7 to 25.1% of hospital in-patients are reported to have developed ADRs in hospitals. Drugs are therefore responsible for significant mobility and mortality amongst people in South Africa. The use and uptake of medicines results in ADRs due to medicine’s toxicity and interactions with other medicines. A large number of ADRs are preventable. This research aims to investigate the association between Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathways involved in cellular response to drugs and occurrence of Adverse Drug Reactions (ADRs). A Pearson’s Product-Moment Correlation (PPMC) was run to assess the relationship between the frequency of ADRs and biological pathways for 33 drugs that included 18 HIV drugs commonly called Anti-Retrovirals (ARVs), 5 anti-tuberculosis (TB) drugs and 10 drugs frequently implicated in ADRs (DFAs) comprising of 3 opioids, 2 loop diuretics, 2 beta agonists, 2 low molecular heparins and 1 systemic corticoid. The ratios of biological pathways/ADRs for ARVs, TB drugs and DFAs were found to be 0.02, 0.33 and 0.06 respectively. ARVs had on average more ADRs (165.22±3.94) compared to TB drugs (67.60±29.17) and DFAs (160.9±49.99). However, TB drugs were linked to a comparatively larger number of KEGG biological pathways (22±9.95) compared to ARVs (3.94± 0.74) and DFAs (9.50±1.79). Further research is required to understand the importance of these research findings towards the development of more effective drugs characterized by reduced prevalence of ADRs. 
The Symptomatic Outcomes of Cholecystectomy for Gallstones

Cholecystectomy is the definite treatment for symptomatic gallstones, and rates are rapidly rising. Symptomatic complicated gallstones are generally treated with cholecystectomy, but there is no consensus on the clinical selection of patients with symptomatic uncomplicated gallstones for cholecystectomy. The aim of this review is to describe symptomatic outcomes before versus after cholecystectomy in patients with symptomatic gallstones as reported in prospective clinical studies and to discuss patient selection for cholecystectomy. Following cholecystectomy, resolution of biliary pain is high and reported for 66–100%. Dyspepsia has an intermediate resolution of 41–91% and may co-exist with biliary pain but may also develop following cholecystectomy with an increase of 150%. Diarrhea has a high increase and debuts in 14–17%. Persisting symptoms are mainly determined by preoperative dyspepsia, functional disorders, atypical pain locations, longer duration of symptoms, and poor psychological or physical health. Patient satisfaction following cholecystectomy is high and may reflect symptom alleviation or a change in symptoms. Comparison of symptomatic outcomes in available prospective clinical studies is limited by variations in preoperative symptoms, clinical presentations, and clinical management of post-cholecystectomy symptoms. When selecting patients with biliary pain only in a randomized controlled trial, 30–40% still have persisting pain. Strategies for the selection of patients with symptomatic uncomplicated gallstones based on symptoms alone are exhausted. For the development of a selection strategy, future studies should explore the impact of objective determinants for symptomatic gallstones on pain relief following cholecystectomy.
A longan yield estimation approach based on UAV images and deep learning

Longan yield estimation is an important practice before longan harvests. Statistical longan yield data can provide an important reference for market pricing and improving harvest efficiency and can directly determine the economic benefits of longan orchards. At present, the statistical work concerning longan yields requires high labor costs. Aiming at the task of longan yield estimation, combined with deep learning and regression analysis technology, this study proposed a method to calculate longan yield in complex natural environment. First, a UAV was used to collect video images of a longan canopy at the mature stage. Second, the CF-YD model and SF-YD model were constructed to identify Cluster_Fruits and Single_Fruits, respectively, realizing the task of automatically identifying the number of targets directly from images. Finally, according to the sample data collected from real orchards, a regression analysis was carried out on the target quantity detected by the model and the real target quantity, and estimation models were constructed for determining the Cluster_Fruits on a single longan tree and the Single_Fruits on a single Cluster_Fruit. Then, an error analysis was conducted on the data obtained from the manual counting process and the estimation model, and the average error rate regarding the number of Cluster_Fruits was 2.66%, while the average error rate regarding the number of Single_Fruits was 2.99%. The results show that the method proposed in this paper is effective at estimating longan yields and can provide guidance for improving the efficiency of longan fruit harvests.
Study on Denoising Method of Vibration Signal Induced by Tunnel Portal Blasting Based on WOA-VMD Algorithm

Because of the impact of the complex environment of tunnel portals, the measured blasting vibration signals in a tunnel portal contains a lot of high-frequency noise. To achieve effective noise reduction, a novel method of noise reduction for blasting vibration signals based on the whale optimization algorithm (WOA) optimized with the variational mode decomposition (VMD) algorithm was proposed. The WOA algorithm is used to optimize globally for the mode number K and penalty factor α of VMD for measured signals and to determine the optimal parameters of [K, α], and to obtain the intrinsic mode function (IMF). Multi-scale permutation entropy (MPE) was used to identify and remove noise components in IMF, and then the reserved IMF was reconstructed to achieve a denoised signal. The method is applied to the blasting vibration analysis of the Xiali tunnel of the Jixin expressway in the Henan Province. Results indicate that the novel method can acquire the optimal decomposition mode number and identify the high frequency noise. Its denoising effect is better than the conventional VMD algorithm and the complete ensemble empirical mode decomposition with adaptive ability (CEEMDAN), which verifies the self-adaptivity and effectiveness of the WOA-VMD denoising method.
Dynamic Response of the Pitot Tube with Pressure Sensor

This paper presents an attempt to determine the dynamic properties of a measuring system based on total pressure measurement with the use of a Pitot tube and a semiconductor pressure transducer. The presented research uses computed fluid dynamics (CFD) simulation and real data from the pressure measurement system for determination of the dynamical model of the Pitot tube with the transducer. An identification algorithm is applied to the data from the simulation, and the model in the form of a transfer function is an identification result. The oscillatory behavior is detected, and this result is confirmed by frequency analysis of the recorded pressure measurements. One of the resonant frequencies is the same in both experiments, but the second is slightly different. The identified dynamical models permit the possibility to predict deviations caused by dynamics and to select the appropriate tube for a particular experiment.
Knockdown of SPON2 inhibits the growth of triple-negative breast cancer

Objective Spondin-2 (SPON2) is highly expressed in a variety of tumors and has been associated with poor prognosis, but the relationship to triple-negative breast cancer (TNBC) is unclear. The aim of this study is to investigate the expression of SPON2 in TNBC and its function. Methods Immunohistochemistry was used to detect the expression of the SPON2 protein in TNBC and in normal tissue adjacent to cancer and breast fibroadenoma. The GEO database GSE76275 dataset was used to study the expression of SPON2 mRNA in TNBC and non-TNBC. The expression of SPON2 mRNA was detected by qPCR in TNBC cells MDA-MB-231, non-TNBC breast cancer cells MCF-7, and normal breast cells MCF-10A. Kaplan Meier-Plotter database was used to analyze the relationship between SPON2 expression and TNBC prognosis. ShRNA lentivirus was used to knock down high expression of SPON2 in TNBC cells. The effects of knockdown of SPON2 expression on the proliferation, migration, invasion, apoptosis, and subcutaneous tumorigenic ability of TNBC cells in nude mice were analyzed using CCK8, clone formation assay, scratch assay, transwell migration assay, transwell invasion assay, Hoechst apoptosis assay, and tumorigenic ability in nude mice. Transcriptome sequencing of TNBC cells with knockdown SPON2 expression. In combination with the GEO database, GO and KEGG analyses were performed, and psychophysiological interaction Protein-Protein Interaction Networks (PPI) analysis was performed for transcriptome sequencing of the differentially expressed genes. The changes in the expression of PI3K-ATK pathway proteins after SPON2 knockdown were detected by Western blot. Results Our study shows that upregulation of SPON2 in TNBC is associated with poorer patient outcomes. Knockdown of SPON2 inhibited TNBC cell proliferation, clone formation, migration, invasion, and tumorigenic ability and promoted apoptosis. Knockdown of SPON2 up-regulated TNBC cell adhesion and down-regulated PI3K-ATK pathway, and PPI results showed that CCL2 was the key protein. Conclusions SPON2 may be a valuable biomarker for the diagnosis and prognosis of TNBC and is a potential therapeutic target for TNBC.
Child and Adolescent Mental Health during the COVID-19 Pandemic: Challenges of Psychiatric Outpatient Clinics

Background: Worldwide national surveys show a rising mental health burden among children and adolescents (C&A) during COVID-19. The objective of the current study is to verify the expected rise in visits to psychiatric outpatient clinics of C&A, especially of new patients. Methods: a cross-sectional study focusing on visits as recorded in electronic medical records of eight heterogeneous C&A psychiatric outpatient clinics. The assessment was based on visits held from March to December of 2019 (before the pandemic) in comparison to visits held in 2020 (during the pandemic). Results: The number of visits was similar for both periods. However, in 2020, 17% of the visits used telepsychiatry (N = 9885). Excluding telepsychiatry reveals a monthly decrease in traditional in-person activities between 2020 and 2019 (691.6 ± 370.8 in 2020 vs. 809.1 ± 422.8 in 2019, mean difference = −117.5, t (69) = −4.07, p = 0.0002, Cohen’s d = −0.30). Acceptation of new patients declined during 2020, compared to 2019 (50.0 ± 38.2 in 2020 vs. 62.8 ± 42.9 in 2019; Z = −3.12, p = 0.002, r = 0.44). Telepsychiatry was not used for new patients. Conclusions: The activity of C&A psychiatric outpatient clinics did not rise but was guarded due to the use of telepsychiatry. The decline in visits of new patients was explained by the lack of use of telepsychiatry for these patients. This calls for expanding the use of telepsychiatry, especially for new patients.