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In this paper, we explore the noncommutative space–time to revive the idea that gamma-ray excess in the galactic center may stem from the annihilation of particle dark matter. In the noncommutative theory, the photon spectrum is produced by direct emission during this annihilation wherein a photon can be embed in the final state together with other direct products in new vertices. In the various configurations of dark matter phenomenology, we pursue the most prevalent model known as singlet scalar. Calculating the relevant aspects of the model and determining the parameters phase space, we derive the photon flux in the galactic center. This region, known for its high density and occasional existence of robust magnetic fields, serves as an ideal location for investigating theories that encompass the concept of Lorentz symmetry breaking. Upon comparing our numerical achievements with experimental data, it becomes evident that noncommutative space–time can be a reliable framework to explain the gamma-ray excess. [ABSTRACT FROM AUTHOR]

The global spread of the coronavirus has generated one of the most critical circumstances forcing healthcare systems to deal with it everywhere in the world. The complexity of crisis management, particularly in Iran, the unfamiliarity of the disease, and a lack of expertise, provided the foundation for researchers and implementers to propose innovative solutions. One of the most important obstacles in COVID-19 crisis management is the lack of information and the need for immediate and real-time data on the situation and appropriate solutions. Such complex problems fall into the category of semi-structured problems. In this respect, decision support systems use people's mental resources with computer capabilities to improve the quality of decisions. In synergetic situations, for instance, healthcare domains cooperating with spatial solutions, coming to a decision needs logical reasoning and high-level analysis. Therefore, it is necessary to add rich semantics to different classes of involved data, find their relationships, and conceptualize the knowledge domain. For the COVID-19 case in this study, ontologies allow for querying over such established relationships to find related medical solutions based on description logic. Bringing such capabilities to a spatial decision support system (SDSS) can help with better control of the COVID-19 pandemic. Ontology-based SDSS solution has been developed in this study due to the complexity of information related to coronavirus and its geospatial aspect in the city of Tehran. According to the results, ontology can rationalize different classes and properties about the user's clinical information, various medical centers, and users' priority. Then, based on the user's requests in a web-based SDSS, the system focuses on the inference made, advises the users on choosing the most related medical center, and navigates the user on a map. The ontology's capacity for reasoning, overcoming knowledge gaps, and combining geographic and descriptive criteria to choose a medical center all contributed to promising outcomes and the satisfaction of the sample community of evaluators. [ABSTRACT FROM AUTHOR]

What is clear is that judges usually judge cases based on their knowledge, experience, personality, and sentiment. Due to high pressures and stress, it may be difficult for them to carefully examine documents and evidence, which leads to more subjective judgments. Legal judgment prediction with artificial intelligence algorithms can benefit judicial bodies, legal experts, and litigants as well as judges. In this research, we are looking at predicting legal sentences in drug cases involving the purchase, possession, concealment, or transportation of illicit drugs, using machine learning methods, and the effect of sentiment and emotions in case texts on predicting the severity of whipping, fines, and imprisonment. So, the text documents of 6000 Persian drug-related cases were pre-processed and then the translation of the NRC Glossary of Emotions and sentiment was used to give each item a score for positive or negative sentiment and a score for emotion. Then machine learning methods were used for modeling. BERT, TFIDF+Adaboost, and Skipgram+LSTM+CNN methods had the highest accuracy, respectively. Also, evaluation criteria were analyzed in situations where sentiment scores, emotional scores, or both were used in the prediction process along with judicial texts. Finally, it was found that the use of sentiment and emotion scores improves the accuracy of legal judgment predictions for all three types of sentences and that sentiments have a greater impact on the accuracy of legal judgment predictions than emotions. [ABSTRACT FROM AUTHOR]

Background: Lower limb injuries are widely recognized as the most prevalent injuries among female soccer players. Joint position sense plays a vital role in muscle reflexes, joint stability dynamics, and movement planning for neuromuscular control. Decreased accuracy in joint position sense can be considered an internal injury risk factor. Objective: The current study aims to investigate the immediate effect of a short-term balance protocol with a wobble board on knee and ankle joint position sense. Methods: Forty female participants were recruited and then randomly allocated into two groups: balance training (BTR; n = 20, age 23.50 ± 1.50 years) and control (CON; n = 20, age 23.10 ± 1.77 years). Knee and ankle joint reconstruction errors were measured using a gyroscope at 60° of knee flexion and 30° of ankle plantarflexion. Following this, the BTR group participated in a short-term balance protocol (one session). Immediately following training and then one hour later, the reconstruction error was measured in both groups. Results: A mixed-repeated measures analysis of variance demonstrated that for the BTR group, the absolute angular error (AAE) before and after intervention decreased by 2.14° and 2.95° in the knee (p = .001) and ankle (p = .001) joints, respectively. In addition, an hour after intervention, the AAE remained below the initial value in the two joints (p = .001). Specifically, in the CON group, the AAE in the knee joint did not show a significant decrease, and similarly, no significant change was observed in the AAE in the ankle joint, and also an hour after the intervention. Conclusions: A wobble board training session may stimulate the sensory receptors of the knee and ankle joints of female amateur soccer players and increased joint position sense accuracy and is present one hour post intervention. [ABSTRACT FROM AUTHOR]

Background: Retroperitoneal schwannoma is a rare tumor rising from Schwann cells in peripheral nerve sheaths. Retroperitoneal schwannoma is really infrequent and has nonspecific symptoms and imperfect radiologic features, and is often identified histologically after surgery. Case Report: We report the case of a 73-year-old man presented with flank mass. Imaging shows a hypoechoic macro lobulated solid cystic mass in retroperitoneum. Intraoperatively, after complete resection of retroperitoneal mass, a suspected lesion in upper pole of right kidney was observed. Histopathology evaluation after surgery shows coexistence of a large retroperitoneal schwannoma and papillary renal cell carcinoma, type 1. Conclusion: Schwannoma should be considered in the differential diagnosis of retroperitoneal spindle cell tumor. Schwannoma coexisted with renal cell carcinoma in a patient is an unusual event. Thus, it can show the importance of appropriate evaluation before any surgery. [ABSTRACT FROM AUTHOR]

Background: Mental disorders can significantly impact maternal health and neonatal health and development. This study investigated maternal anxiety, depression, and stress during pregnancy concerning their children's development. Methods: In this follow-up study, all pregnant women with gestational age > 12 weeks referring to an obstetrics and gynecology clinic affiliated with Shahid Sadoughi University of Medical Sciences over six months were included. Data on mothers were collected using a personal information questionnaire and the Depression Anxiety Stress Scale (DASS)-42 standard questionnaire. Finally, based on the inclusion and exclusion criteria, the children of 73 mothers were included in the study. Infant development was assessed based on the Persian version of the Ages and Stages Questionnaire (ASQ) at six months postpartum. Data analysis was conducted using the Pearson correlation test and multiple regression analysis. Statistical analyzes were carried out using SPSS 21. A P-value <0.05 was considered statistically significant. Results: In this study, 39.7%, 63%, and 56.2% of women suffered from depression, anxiety, and stress, respectively. In this study, a significant relationship was found between antenatal maternal depression and gross motor (P: 0.022), fine motor (P: 0.003), personal-social (P: 0.009), and communication skills (P: 0.0180). Moreover, there was a significant relationship between maternal anxiety and personal-social (P: 0.012) and gross motor domains (P: 0.008). Also, a significant association was observed between personal-social skills and maternal stress (P: 0.030). Conclusion: As shown by the results, antenatal maternal mental illness can interfere with the development of children. Therefore, paying attention to the mental health of pregnant women is necessary. [ABSTRACT FROM AUTHOR]