Application and design of a decision-making model in ethical dilemma for self-driving cars.

Artificial intelligence (AI) has promoted application and development of self-driving cars. However, when self-driving cars encounter ethical dilemma, it is still hard to make a satisficing and clear decision-making by these present moral rules and mechanisms, which makes people distrust in self-driving cars in real life. It is necessary to design a computational and multi-factor decision-making model for self-driving cars.

lncRNA PAARH impacts liver cancer cell proliferation by engaging miR‑6512‑3p to target LASP1.

Long non-coding (lnc)RNAs serve a pivotal role as regulatory factors in carcinogenesis. The present study aimed to assess the involvement of the lncRNA progression and angiogenesis-associated RNA in hepatocellular carcinoma (PAARH) in liver cancer, along with the associated underlying mechanism. Through the use of reverse transcription-quantitative (RT-q)PCR, differences in the expression levels of PAARH in HepG2, HEP3B2.

Applying AVWEWM to ethical decision-making during autonomous vehicle crashes.

At present, a few scholars studied influencing factors, rules and mechanisms of decision-making in ethical dilemmas. Many factors have been identified, and a few rules and mechanisms have been proposed. However, due to the inability to evaluate the weight and role of each factor in decision-making, it is difficult to establish a computational decision-making model to solve ethical dilemmas.

METTL3/16-mediated mA modification of ZNNT1 promotes hepatocellular carcinoma progression by activating ZNNT1/osteopontin/S100A9 positive feedback loop-mediated crosstalk between macrophages and tumour cells.

Macrophages are the major components of tumour microenvironment, which play critical roles in tumour development. N-methyladenosine (mA) also contributes to tumour progression. However, the potential roles of mA in modulating macrophages in hepatocellular carcinoma (HCC) are poorly understood.

LncRNA MEG3 Inhibits Tumor Progression by Modulating Macrophage Phenotypic Polarization via miR-145-5p/DAB2 Axis in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is the predominant histological type of primary liver cancer, which ranks sixth among the most common human tumors. Tumor-associated macrophages (TAMs) are an important component of tumor microenvironment (TME) and the M2 macrophage polarization substantially contributes to tumor growth and metastasis. Long non-coding RNA (lncRNA) MEG3 was reported to restrain HCC development.

E3 ubiquitin ligase HECTD3 is a tumor suppressor and mediates the polyubiquitination of SLC7A11 to promote ferroptosis in colon cancer.

Homologous to the E6-associated protein carboxyl terminus domain containing 3 (HECTD3) has been reported to play an essential role in biological processes, including drug resistance, metastasis or apoptosis. However, the relationships between HECTD3 and Colorectal cancer (CRC) remain to be unclear. In this study, we discovered that HECTD3 expressed lowly in CRC compared with normal tissues and patients with low HECTD3 suffered from poorer survival outcomes relative to those with high HECTD3 levels.

N -methyladenosine-modified FAM111A-DT promotes hepatocellular carcinoma growth via epigenetically activating FAM111A.

As an epitranscriptomic modulation manner, N -methyladenosine (m A) modification plays important roles in various diseases, including hepatocellular carcinoma (HCC). m A modification affects the fate of RNAs. The potential contributions of m A to the functions of RNA still need further investigation.

Long non-coding RNA PAARH promotes hepatocellular carcinoma progression and angiogenesis via upregulating HOTTIP and activating HIF-1α/VEGF signaling.

Hepatocellular carcinoma (HCC) is one of the leading lethal malignancies and a hypervascular tumor. Although some long non-coding RNAs (lncRNAs) have been revealed to be involved in HCC. The contributions of lncRNAs to HCC progression and angiogenesis are still largely unknown.

Weak Knock Characteristic Extraction of a Two-Stroke Spark Ignition UAV Engine Burning RP-3 Kerosene Fuel Based on Intrinsic Modal Functions Energy Method.

To solve the problem of the weak knock characteristic extraction for a port-injected two-stoke spark ignition (SI) unmanned aerial vehicle (UAV) engine burning aviation kerosene fuel, which is also known as the Rocket Propellant 3 (RP-3), the Intrinsic modal Functions Energy (IMFE) method is proposed according to the orthogonality of the intrinsic modal functions (IMFs). In this method, engine block vibration signals of the two-stroke SI UAV engine are decomposed into a finite number of intrinsic modal function (IMF) components. Then, the energy weight value of each IMF component is calculated, and the IMF component with the largest energy weight value is selected as the dominant characteristic component.