bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of roof cutting by directionally single cracking technique in automatic roadway formation for thick coal seam mining
Authors: Gao Yubing , Gai Qiukai , Zhang Xingxing , Xi Xun , He Manchao 
Published: November 2023

AbstractAutomatic roadway formation by roof cutting is a sustainable nonpillar mining method that has the potential to increase coal recovery, reduce roadway excavation and improve mining safety. In this method, roof cutting is the key process for stress relief, which significantly affects the stability of the formed roadway. This paper presents a directionally single cracking (DSC) technique for roof cutting with considerations of rock properties. The mechanism of the DSC technique was investigated by explicit finite element analyses. The DSC technique and roof cutting parameters were evaluated by discrete element simulation and field experiment. On this basis, the optimized DSC technique was tested in the field. The results indicate that the DSC technique could effectively control the blast-induced stress distribution and crack propagation in the roof rock, thus, achieve directionally single cracking on the roadway roof. The DSC technique for roof cutting with optimized parameters could effectively reduce the deformation and improve the stability of the formed roadway. Field engineering application verified the feasibility and effectiveness of the evaluated DSC technique for roof cutting.
Apparent activation energy of mineral in open pit mine based upon the evolution of active functional groups
Authors: Lu Shipng , Zhao Jingyu , Song Jiajia , Chang Jiaming , Shu Chi-Min 
Published: November 2023

AbstractThis study aimed to investigate the mechanism of mineral spontaneous combustion in an open pit. On the study of coal and mineral mixture in open pit mines, as well as through the specific surface area and Search Engine Marketing (SEM) experiments, the specific surface area and aperture characteristics of distribution of open pit coal sample and pit mineral mixture samples were analyzed. Thermal analysis experiments were used to divide the oxidation process was divided into three stages, and the thermal behavior characteristics of experimental samples were characterized. On the basis of the stage division, we explored the transfer law of the key active functional groups of the experimental samples. The apparent activation energy calculation of the key active groups, performed by combining the Achar differential method with the Coats–Redfern integral method, microstructural and oxidation kinetic properties were revealed. The resulted showed that the mixed sample had high ash, the fixed carbon content was reduced, the specific surface area was far lower than the raw coal, the large aperture distribution was slightly higher than the medium hole, the micropore was exceptionally low, the gas adsorption capacity was weaker than the raw coal, the pit coal sample had the exceedingly more active functional groups, easy to react with oxygen, more likely to occur naturally, and its harm was relatively large. The mixed sample contained the highest C–O–C functional group absorbance. The functional groups were mainly influenced by the self-OH content, alkyl side chain, and fatty hydrocarbon in the sample. The main functional groups of the four-like mixture had the highest apparent activation energy, and the two reactions were higher in the low-temperature oxidation phase.
Elimination mechanism of coal and gas outburst based on geo-dynamic system with stress–damage–seepage interactions
Authors: Xu Lingjin , Fan Chaojun , Luo Mingkun , Li Sheng , Han Jun , Fu Xiang , Xiao Bin 
Published: November 2023

AbstractCoal and gas outburst is a complex dynamic disaster during coal underground mining. Revealing the disaster mechanism is of great significance for accurate prediction and prevention of coal and gas outburst. The geo-dynamic system of coal and gas outburst is proposed. The framework of geo-dynamic system is composed of gassy coal mass, geological dynamic environment and mining disturbance. Equations of stress–damage–seepage interaction for gassy coal mass is constructed to resolve the outburst elimination process by gas extraction with boreholes through layer in floor roadway. The results show the occurrence of outburst is divided into the evolution process of gestation, formation, development and termination of geo-dynamic system. The scale range of outburst occurrence is determined, which provides a spatial basis for the prevention and control of outburst. The formation criterion and instability criterion of coal and gas outburst are established. The formation criterion F1 is defined as the scale of the geo-dynamic system, and the instability criterion F2 is defined as the scale of the outburst geo-body. According to the geo-dynamic system, the elimination mechanism of coal and gas outburst—‘unloading + depressurization’ is established, and the gas extraction by boreholes through layer in floor roadway for outburst elimination is given. For the research case, when the gas extraction is 120 days, the gas pressure of the coal seam is reduced to below 0.4 MPa, and the outburst danger is eliminated effectively.
A multidisciplinary approach to facies evaluation at regional level using well log analysis, machine learning, and statistical methods
Authors: Ullah Jar , Li Huan , Ashraf Umar , Ehsan Muhsan , Asad Muhammad 
Published: November 2023

AbstractGeological facies evaluation is crucial for the exploration and development of hydrocarbon reservoirs. To achieve accurate predictions of litho-facies in wells, a multidisciplinary approach using well log analysis, machine learning, and statistical methods was proposed for the Lower Indus Basin. The study utilized five supervised machine learning techniques, including Random Forest (FR), Support Vector Machine (SVM), Artificial Neural Network (ANN), Extreme Gradient Boosting (XGB), and Multilayer Perceptron (MLP), to analyse gamma ray, resistivity, density, neutron porosity, acoustic, and photoelectric factor logs. The Concentration-Number (C-N) fractal model approach and log–log plots were also used to define geothermal features. In a study on machine learning models for classifying different rock types in the Sawan field of the Southern Indus Basin, it was discovered that sand (fine, medium and coarse) facies were most accurately classified (87–94%), followed by shale (70–85%) and siltstone facies (65–79%). The accuracy of the machine learning models was assessed using various statistical metrics, such as precision, recall, F1 score, and ROC curve. The study found that all five machine learning methods successfully predicted different litho-facies in the Lower Indus Basin. In particular, sand facies were most accurately classified, followed by shale and siltstone facies. The multilayer perceptron method performed the best overall. This multidisciplinary approach has the potential to save time and costs associated with traditional core analysis methods and enhance the efficiency of hydrocarbon exploration and development.
Fast-kinetics adsorption of a binary solution containing cationic and ionic pollutants using high-surface area activated carbon derived from macadamia nutshell
Authors: Duque-Brito Estefania , Lobato-Peralta Diego Ramón , Okolie Jude A. , Arias Dulce Maria , Sebastian Pathiyamattom Joseph , Okoye Patrick U. 
Published: November 2023

AbstractWastewater is characterized by multipollutant, and the presence of competitive adsorption could affect removal efficiency. Hence, the decontamination of water by adsorption in a multicomponent system allows an understanding of the practically and adsorbent efficiency. In this study, we present an analysis of the adsorption phenomena in a binary solution comprising compounds from distinct families, a dye, and an antibiotic, utilizing activated carbon obtained through a sustainable procedure. Locally available agricultural biowaste, specifically macadamia nutshell (MNS), served as a sustainable precursor to produce hierarchical porous activated carbon. The activation conditions were fine-tuned using the Box–Behnken experimental design. The resultant activated carbon was employed to remove a binary solution (BS) comprising the cationic dye, methylene blue (MB) and an ionic molecule amoxicillin (AMX) under specified conditions, including a pH range of 2 to 12, an initial concentration of BS ranging from 50 to 800 mg/L, and an adsorbent dosage within the range of 0.1 g to 0.3 g in a single adsorption system. The results revealed that higher temperatures adversely impacted the carbon yield, with a pronounced interaction effect observed between temperature and time. The activation temperature and K2CO3:precursor molar ratio predominantly influenced the textural and morphological properties of the activated carbon. Under optimal conditions (900 °C, 1 h, and a K2CO3:precursor ratio of 2:1), remarkably high-surface area (1225 m2/g), pore volume (0.801 cm3/g), and a nanopore size of 0.406 nm were achieved. In binary adsorption studies, R2-MNS demonstrated a maximum adsorption capacity of 578.925 mg/g. A pH above 4.5 produced an antagonistic effect on the removal of AMX due to competitive adsorption. Evaluation of three isotherm models demonstrated that the Khan isotherm best describes the affinity of BS to R2-MNS. The pseudo-second-order kinetic model best describes the data, indicating a chemisorption mechanism. The interparticle diffusion test revealed that the adsorbent exhibited very fast adsorption behaviour at the initial stage.
Graphical abstract
The neurohypophyseal hormone oxytocin and eating behaviors: a narrative review
Authors: Iovino Michele , Messana Tullio , Marucci Simonetta , Triggiani Domenico , Giagulli Vito Angelo , Guastamacchia Edoardo , Piazzolla Giuseppina , De Pergola Giovanni , Lisco Giuseppe , Triggiani Vincenzo 
Published: November 2023

Abstract
Background
The neuropeptide oxytocin (OT) is crucial in several conditions, such as lactation, parturition, mother-infant interaction, and psychosocial function. Moreover, OT may be involved in the regulation of eating behaviors.

Methods
This review briefly summarizes data concerning the role of OT in eating behaviors. Appropriate keywords and medical subject headings were identified and searched for in PubMed/MEDLINE. References of original articles and reviews were screened, examined, and selected.

Results
Hypothalamic OT-secreting neurons project to different cerebral areas controlling eating behaviors, such as the amygdala, area postrema, nucleus of the solitary tract, and dorsal motor nucleus of the vagus nerve. Intracerebral/ventricular OT administration decreases food intake and body weight in wild and genetically obese rats. OT may alter food intake and the quality of meals, especially carbohydrates and sweets, in humans.

Discussion
OT may play a role in the pathophysiology of eating disorders with potential therapeutic perspectives. In obese patients and those with certain eating disorders, such as bulimia nervosa or binge/compulsive eating, OT may reduce appetite and caloric consumption. Conversely, OT administered to patients with anorexia nervosa may paradoxically stimulate appetite, possibly by lowering anxiety which usually complicates the management of these patients. Nevertheless, OT administration (e.g., intranasal route) is not always associated with clinical benefit, probably because intranasally administered OT fails to achieve therapeutic intracerebral levels of the hormone.

Conclusion
OT administration could play a therapeutic role in managing eating disorders and disordered eating. However, specific studies are needed to clarify this issue with regard to dose-finding and route and administration time.
A semi-agnostic ansatz with variable structure for variational quantum algorithms
Authors: Bilkis M. , Cerezo M. , Verdon Guillaume , Coles Patrick J. , Cincio Lukasz 
Published: November 2023

AbstractQuantum machine learning—and specifically Variational Quantum Algorithms (VQAs)—offers a powerful, flexible paradigm for programming near-term quantum computers, with applications in chemistry, metrology, materials science, data science, and mathematics. Here, one trains an ansatz, in the form of a parameterized quantum circuit, to accomplish a task of interest. However, challenges have recently emerged suggesting that deep ansatzes are difficult to train, due to flat training landscapes caused by randomness or by hardware noise. This motivates our work, where we present a variable structure approach to build ansatzes for VQAs. Our approach, called VAns (Variable Ansatz), applies a set of rules to both grow and (crucially) remove quantum gates in an informed manner during the optimization. Consequently, VAns is ideally suited to mitigate trainability and noise-related issues by keeping the ansatz shallow. We employ VAns in the variational quantum eigensolver for condensed matter and quantum chemistry applications, in the quantum autoencoder for data compression and in unitary compilation problems showing successful results in all cases.
Staying hungry: a roadmap to harnessing central regulators of symbiotic nitrogen fixation under fluctuating nitrogen availability
Authors: Qiao Lijin , Lin Jieshun , Suzaki Takuya , Liang Pengbo 
Published: November 2023

AbstractLegumes have evolved specific inventions to enhance nitrogen (N) acquisition by establishing symbiotic interactions with N-fixing rhizobial bacteria. Because symbiotic N fixation is energetically costly, legumes have developed sophisticated mechanisms to ensure carbon–nitrogen balance, in a variable environment, both locally and at the whole plant level, by monitoring nodule number, nodule development, and nodular nitrogenase activity, as well as controlling nodule senescence. Studies of the autoregulation of nodulation and regulation of nodulation by nodule inception (NIN) and NIN-LIKE PROTEINs (NLPs) have provided great insights into the genetic mechanisms underlying the nitrate-induced regulation of root nodulation for adapting to N availability in the rhizosphere. However, many aspects of N-induced pleiotropic regulation remain to be fully explained, such as N-triggered senescence in mature nodules. Wang et al. determined that this process is governed by a transcriptional network regulated by NAC-type transcription factors. Characterization and dissection of these soybean nitrogen-associated NAPs (SNAPs) transcription factor-mastered networks have yielded a roadmap for exploring how legumes rewire nodule functions across a range of N levels, laying the foundation for enhancing the growth of N-deprived crops in agricultural settings.
Retroperitoneal para-aortic ectopic pregnancies: A review of reported cases
Authors: Ren Junxiang , Han Hongjing 
Published: November 2023

AbstractObjectiveTo gain insights into the diagnosis and treatment of retroperitoneal para-aortic ectopic pregnancies (RPEP).MethodsWe conducted a review of the existing literature from the web of science, PubMed, and CNKI using the search terms "ectopic pregnancy" and "retroperitoneal." The present review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.ResultsAfter applying the inclusion and exclusion criteria, we included a total of 54 relevant works, encompassing 55 cases. The studies have revealed that a history of artificial abortion, embryo transfer, salpingectomy, and uterine cavity operation, accounted for 65.5 ​% (36/55) of the cases. Typical symptoms of RPEP include abdominal pain (43.6 ​%, 24/55) and vaginal bleeding (36.4 ​%, 20/55), with only 32.7 ​% (18/55) of cases being asymptomatic. The most common sites of RPEP are the abdominal aorta and the inferior vena cava (74.5 ​%, 41/55). There were no statistically significant differences in the incidence of acute abdomen, diameter of the pregnancy sac, number of surgeries, and the time for postoperative hCG to normalize in different pregnant site. The most effective imaging examination for RPEP was found to be abdominal ultrasound (72.7 ​%, 40/55), and the most commonly used treatment method was laparoscopy surgery (55.3 ​% ,21/38).ConclusionIt is crucial to consider the possibility of RPEP when a pregnancy mass cannot be located during routine examinations. Expanding the scope of the scan may significantly expedite diagnosis and treatment.
3D Shear‐Wave Velocity Model of Central Makran Using Ambient‐Noise Adjoint Tomography
Authors: Enayat Mohammad , Ghods Abdolreza 
Published: November 2023

AbstractThe Makran subduction zone is unique in its wide onshore thick accretionary prism, and volcanic arc not parallel to the E–W trend of the Makran accretionary prism. To investigate the internal structure of the accretionary prism, the crustal nature of Jaz Murian Depression, and the trend of the subducting plate hinge, we have calculated a 3D shear‐wave velocity model for a region around the border between eastern and western Makran using ambient‐noise adjoint tomography and data from IASBS/CAM Makran temporary seismic network. In close agreement with previous works, our velocity model shows that the onshore accretionary prism consists of a low‐velocity zone in the south and a high‐velocity zone in the north with an average thickness of accreted sediments of 22 and 30 km, respectively. The young age of the surface rocks of the high‐velocity part of the prism suggests the presence of a significant volume of igneous rocks and metamorphosed sedimentary rocks. The velocity model indicates a continental crust of ∼40 km with a thick sedimentary cover of ∼20 km for the eastern part of Jaz Murian Depression. The presence of a NE‐SW trending low‐velocity region at a depth interval of 40–60 km subparallel with the trend of the volcanic arc, intermediate‐depth earthquakes, and geometry of the overriding plate might be related to the trend of the subducting plate hinge. This implies that the observed NE‐SW trending volcanic arc might be related to the geometry of the subducting plate hinge and not the eastward reduction of the subduction angle.
Endosymbionts modulate virus effects on aphid-plant interactions
Authors: Sanches Patricia , De Moraes Consuelo M , Mescher Mark C 
Published: November 2023

Abstract
Vector-borne pathogens frequently modify traits of their primary hosts and vectors in ways that influence disease transmission. Such effects can themselves be altered by the presence of other microbial symbionts, yet we currently have limited understanding of these interactions. Here we show that effects of pea enation mosaic virus (PEMV) on interactions between host plants and aphid vectors are modulated by the presence of different aphid endosymbionts. In a series of laboratory assays, we found strong interactive effects of virus infection and endosymbionts on aphid metabolomic profiles, population growth, behavior, and virus transmission during aphid feeding. Furthermore, the strongest effects—and those predicted to favor virus transmission—were most apparent in aphid lines harboring particular endosymbionts. These findings show that virus effects on host-vector interactions can be strongly influenced by other microbial symbionts and suggest a potentially important role for such interactions in disease ecology and evolution.
Association between microbiome and the development of adverse posttraumatic neuropsychiatric sequelae after traumatic stress exposure
Authors: Zeamer Abigail L. , Salive Marie-Claire , An Xinming , Beaudoin Francesca L. , House Stacey L. , Stevens Jennifer S. , Zeng Donglin , Neylan Thomas C. , Clifford Gari D. , Linnstaedt Sarah D. , Rauch Scott L. , Storrow Alan B. , Lewandowski Christopher , Musey Paul I. , Hendry Phyllis L. , Sheikh Sophia , Jones Christopher W. , Punches Brittany E. , Swor Robert A. , Hudak Lauren A. , Pascual Jose L. , Seamon Mark J. , Harris Erica , Pearson Claire , Peak David A. , Merchant Roland C. , Domeier Robert M. , Rathlev Niels K. , O’Neil Brian J. , Sergot Paulina , Sanchez Leon D. , Bruce Steven E. , Kessler Ronald C. , Koenen Karestan C. , McLean Samuel A. , Bucci Vanni , Haran John P. 
Published: November 2023

AbstractPatients exposed to trauma often experience high rates of adverse post-traumatic neuropsychiatric sequelae (APNS). The biological mechanisms promoting APNS are currently unknown, but the microbiota-gut-brain axis offers an avenue to understanding mechanisms as well as possibilities for intervention. Microbiome composition after trauma exposure has been poorly examined regarding neuropsychiatric outcomes. We aimed to determine whether the gut microbiomes of trauma-exposed emergency department patients who develop APNS have dysfunctional gut microbiome profiles and discover potential associated mechanisms. We performed metagenomic analysis on stool samples (n = 51) from a subset of adults enrolled in the Advancing Understanding of RecOvery afteR traumA (AURORA) study. Two-, eight- and twelve-week post-trauma outcomes for post-traumatic stress disorder (PTSD) (PTSD checklist for DSM-5), normalized depression scores (PROMIS Depression Short Form 8b) and somatic symptom counts were collected. Generalized linear models were created for each outcome using microbial abundances and relevant demographics. Mixed-effect random forest machine learning models were used to identify associations between APNS outcomes and microbial features and encoded metabolic pathways from stool metagenomics. Microbial species, including Flavonifractor plautii, Ruminococcus gnavus and, Bifidobacterium species, which are prevalent commensal gut microbes, were found to be important in predicting worse APNS outcomes from microbial abundance data. Notably, through APNS outcome modeling using microbial metabolic pathways, worse APNS outcomes were highly predicted by decreased L-arginine related pathway genes and increased citrulline and ornithine pathways. Common commensal microbial species are enriched in individuals who develop APNS. More notably, we identified a biological mechanism through which the gut microbiome reduces global arginine bioavailability, a metabolic change that has also been demonstrated in the plasma of patients with PTSD.
Multi-modal deformation and temperature sensing for context-sensitive machines
Authors: Baines Robert , Zuliani Fabio , Chennoufi Neil , Joshi Sagar , Kramer-Bottiglio Rebecca , Paik Jamie 
Published: November 2023

AbstractOwing to the remarkable properties of the somatosensory system, human skin compactly perceives myriad forms of physical stimuli with high precision. Machines, conversely, are often equipped with sensory suites constituted of dozens of unique sensors, each made for detecting limited stimuli. Emerging high degree-of-freedom human-robot interfaces and soft robot applications are delimited by the lack of simple, cohesive, and information-dense sensing technologies. Stepping toward biological levels of proprioception, we present a sensing technology capable of decoding omnidirectional bending, compression, stretch, binary changes in temperature, and combinations thereof. This multi-modal deformation and temperature sensor harnesses chromaticity and intensity of light as it travels through patterned elastomer doped with functional dyes. Deformations and temperature shifts augment the light chromaticity and intensity, resulting in a one-to-one mapping between stimulus modes that are sequentially combined and the sensor output. We study the working principle of the sensor via a comprehensive opto-thermo-mechanical assay, and find that the information density provided by a single sensing element permits deciphering rich and diverse human-robot and robot-environmental interactions.