bluuebunny/crossref_metadata_2025 huggingface dataset:
Alloimperatorin activates apoptosis, ferroptosis, and oxeiptosis to inhibit the growth and invasion of breast cancer cells in vitro
Authors: Zhang Jing , Gao Run-fang , Li Jie , Yu Ke-da , Bi Kai-xin
Published: March 2022

Breast cancer is the most common malignant tumour in women. Our research on alloimperatorin from Angelica dahurica showed that alloimperatorin inhibited breast cancer cell viability in a concentration- and time-dependent manner; it also showed that apoptosis and ferroptosis inhibitors significantly weakened the antisurvival effect of alloimperatorin. Alloimperatorin clearly induced breast cancer cell apoptosis and increased the activities of caspase-3, caspase-8, caspase-9, and poly (ADP-ribose) polymerase; it also caused significant mitochondrial shrinkage, promoted the accumulation of Fe2+, reactive oxygen species, and malondialdehyde, and significantly reduced mRNA and protein expression levels of SLC7A11 and GPX4, indicating that alloimperatorin induces ferroptosis. In addition, alloimperatorin significantly promoted Kelch-like ECH-associated protein 1 (Keap1) expression; although it did not affect the expression of PGAM5 (mitochondrial serine/threonine protein phosphatase) and apoptosis-inducing factor mitochondria associated 1 (AIFM1), it significantly reduced the phosphorylation level of AIFM1. After downregulating the expression of Keap1, PGAM5, or AIFM1, the inhibitory effect of alloimperatorin on cell viability was significantly weakened, indicating that alloimperatorin regulates the Keap1/PGAM5/AIFM1 pathway to promote oxeiptosis. Alloimperatorin significantly inhibited the invasion of breast cancer cells, while Keap1 siRNA or GPX4 overexpression vectors significantly enhanced cell invasion and effectively reversed the anti-invasive effect of alloimperatorin. Therefore, alloimperatorin induces breast cancer cell apoptosis, ferroptosis, and oxeiptosis, thereby inhibiting cell growth and invasion.
EXTRACTION OF PRESSURE AND TEMPERATURE DISTRIBUTION OF HIGH INTENSITY FOCUSED ULTRASOUND CONSIDERING NONLINEAR PROPAGATION
Authors: MORTAZAVI SARE , MOKHTARI-DIZAJI MANIJHE
Published: March 2022

The aim of this study is the extraction of acoustic pressure distribution in the target tissue layers based on the nonlinear behavior of waves. The nonlinear behavior effect of high intensity focused ultrasound (HIFU) on the temperature distribution of the tissue was extracted and compared with the linear behavior. The acoustic pressure field was calculated using the Westervelt equation and was coupled with Pennes thermal transfer equation. The simulations were performed for three layers of skin, fat and muscle using Comsol software. The disagreement between two linear and nonlinear models was analyzed with Kolmogorov–Smirnov test. The pressure and temperature distributions were calculated in nonlinear model by changing the acoustical parameters of the transducer including intensity, effective radiation area, focal length and sonication time. Model results were validated with experimental results with 98% correlation coefficient ([Formula: see text]). There is no significant difference between the pressure amplitude and temperature distribution in linear and nonlinear models at low intensity ([Formula: see text]), but with increasing intensity to 10[Formula: see text]W/cm2, in nonlinear model, maximum pressure and maximum temperature increased 40% and 20% compared with linear model. For input intensities of 1.5, 2, 8 and 10[Formula: see text]W/cm2, the maximum pressure (at focal point) increased 10%, 12%, 22%, 40% and maximum temperature increased 1%, 2%, 12%, 20% in nonlinear model compared to linear model. At 0.8[Formula: see text]cm2 and 1.5[Formula: see text]cm2 effective radiation area, the maximum acoustic pressure and temperature in nonlinear model increased from 12[Formula: see text]MPa to 30[Formula: see text]MPa and 43∘C to 79∘C, respectively. By decreasing the focal lengths from 10[Formula: see text]mm to 7.5[Formula: see text]mm, the maximum temperature increased from 45∘C to 87∘C. It is concluded a change in the input parameters of the transducer; it can be very effective in treating. The results emphasize the effects of nonlinear propagation and acoustical radiation parameters to improve the HIFU treatment.
Regional importance detection of 3D mesh via fusion of local color difference and curvature entropy
Authors: Wang Xiaodong , Kang Fengju , Gu Hao , Liang Hongtao
Published: March 2022

Predicting relative visual salient regions on three-dimensional (3D) meshes benefits many computer graphics applications. Most computation models for mesh saliency focus on geometrical information alone. Nevertheless, the ignored texture, lighting and material also provide more detailed appearance information, especially in the context of static scene rendering. In this paper, we propose a mesh saliency detection algorithm considering both geometrical and colorimetric information to address this challenge. Our model first computes the local curvature entropy at multi-scale to capture the geometrical details. Second, a set of images are projected onto the screen at several viewpoints with specified material and lighting model. Potentially salient regions on the rendered images are detected by fusion of multiple color difference maps measured with an approximated multi-scale Laplacian of Gaussian filter. A Gaussian distribution-based central bias model is applied to the image saliency map to emphasize the global rarity of salient regions. Third, the saliency maps of rendered images are projected back to the 3D mesh via the ray casting method. In the end, both saliency maps are combined linearly as the saliency map of 3D mesh. Experiment on the human fixation database demonstrates the performance of our method compared to the classic methods in terms of linear correlation coefficient and AUC.
HOW DO WESTERN EUROPEAN FARMS BEHAVE AND RESPOND TO CLIMATE CHANGE? A SIMULTANEOUS IRRIGATION-CROP DECISION MODEL
Authors: VANSCHOENWINKEL JANKA , VANCAUTEREN MARK , VAN PASSEL STEVEN
Published: March 2022

Most farm adaptations are reactive actions that run the risk of locking farm systems into suboptimal long-term trajectories. This is especially the case with regard to water management as water scarcity will be aggravated by climate change. This paper looks into farm irrigation choices in combination with crop choices because a proper crop choice has the potential to reduce water requirements. It proposes an extended Ricardian model to capture multiple adaptation decisions explicitly. The new simultaneous irrigation-crop farm decision model uses spatially detailed farm-level data of over 18,000 European farms on irrigation and seven different crop choices. The analysis shows that larger farmers and farmers in less water-scarce regions that use irrigation are more sensitive to temperature increases than rain-fed agriculture. This might be explained by the fact that these farmers do not experience the real cost of water scarcity because of which they take less efficient decisions.
FoodMatch: Batching and Matching for Food Delivery in Dynamic Road Networks
Authors: Joshi Manas , Singh Arshdeep , Ranu Sayan , Bagchi Amitabha , Karia Priyank , Kala Puneet
Published: March 2022

Food delivery, today, is a multi-billion dollar industry. Minimizing food delivery time is a key contributor towards building positive customer experiences. More precisely, given a stream of food orders and available delivery vehicles, how should orders be assigned to vehicles so the delivery time is minimized? Several decisions have to be made: (1) assignment of orders to vehicles, (2) grouping orders into batches to cope with limited vehicle availability, (3) adapting to dynamic positions of delivery vehicles, and (4) ensuring scalability to the demands of real-world workloads. We show that the minimization problem is not only
NP-hard
but
inapproximable
in polynomial time. To mitigate this computational bottleneck, we develop an algorithm called
FoodMatch
, which maps the vehicle assignment problem to that of
minimum weight perfect matching
on a bipartite graph. To further reduce the quadratic construction cost of the bipartite graph, we deploy
best-first search
to only compute a subgraph that is highly likely to contain the minimum matching. The solution quality is further enhanced by reducing batching to a graph batching problem and anticipating dynamic positions of vehicles through
angular distance
. We perform extensive experiments on real food-delivery data from large metropolitan cities. Our results establish that
FoodMatch
imparts substantial improvements over baseline strategies across a host of metrics such as food delivery time, waiting time at restaurants, and orders delivered per kilometer. Furthermore,
FoodMatch
is efficient enough to handle real-world workloads.
Applying Probabilistic Model Checking to the Behavior Guidance and Abnormality Detection for A-MCI Patients under Wireless Sensor Network
Authors: Gao Honghao , Zhou Lin , Kim Jung Yoon , Li Ying , Huang Wanqiu
Published: March 2022

With the development of the
Internet of Medical Things (IoMT)
, indoor
wireless sensor networks (WSNs)
have been used to monitor Alzheimer's disease patients daily and guide their behaviors. Alzheimer's disease may seriously impact patients’ memory, and thoughts of “what should I do” can unexpectedly form in their mind. This cognitive impairment can affect patients’ independence and well-being. As a basic infrastructure for future healthcare systems, WSN can collect patient behaviors, such as their positions and states, to support safety and health analyses. Therefore, this paper proposes a probabilistic model checking-based method to predict patient behaviors and detect abnormal behaviors related to mild cognitive impairment to help patients rebuild their confidence and perception. First, the layout of the home environment is abstracted as a formal grid, and a
user activity model (UAM)
is proposed in the form of
discrete-time Markov chain (DTMC)
to describe patients’ activity based on data collected by sensors. Second, because
Alzheimer's patients with mild cognitive impairment (A-MCI)
often forget their next daily activities, we classify and describe their daily behaviors as verification requirements in the form of
probabilistic computational tree logic (PCTL)
. Then, the UAM is input into a probabilistic model checking tool and compared against the verification property PCTL to calculate the probability values and assess temporal behaviors. As result, the activity with the largest probability is selected for behavior guidance. Third, we demonstrate the process of detecting abnormalities, including activities with abnormal temporal behaviors and activities with normal temporal behaviors but unexpected probabilities that may be repeated more than twice. The key states are extracted from the UAM to specify the verification properties for abnormality detection. Finally, a case study is presented to demonstrate the usability and feasibility of our proposed method.
Co-Optimization of Design and Fabrication Plans for Carpentry
Authors: Zhao Haisen , Willsey Max , Zhu Amy , Nandi Chandrakana , Tatlock Zachary , Solomon Justin , Schulz Adriana
Published: March 2022

Past work on optimizing fabrication plans given a carpentry design can provide Pareto-optimal plans trading off between material waste, fabrication time, precision, and other considerations. However, when developing fabrication plans, experts rarely restrict to a
single design
, instead considering
families of design variations
, sometimes adjusting designs to simplify fabrication. Jointly exploring the design and fabrication plan spaces for each design is intractable using current techniques. We present a new approach to jointly optimize design and fabrication plans for carpentered objects. To make this bi-level optimization tractable, we adapt recent work from program synthesis based on equality graphs (e-graphs), which encode sets of equivalent programs. Our insight is that subproblems within our bi-level problem share significant substructures. By representing both designs and fabrication plans in a new
bag of parts
(BOP) e-graph, we amortize the cost of optimizing design components shared among multiple candidates. Even using BOP e-graphs, the optimization space grows quickly in practice. Hence, we also show how a feedback-guided search strategy dubbed
Iterative Contraction and Expansion on E-graphs
(ICEE) can keep the size of the e-graph manageable and direct the search towards promising candidates. We illustrate the advantages of our pipeline through examples from the carpentry domain.
A Practical Model for Realistic Butterfly Flight Simulation
Authors: Chen Qiang , Lu Tingsong , Tong Yang , Luo Guoliang , Jin Xiaogang , Deng Zhigang
Published: March 2022

Butterflies are not only ubiquitous around the world but are also widely known for inspiring thrill resonance, with their elegant and peculiar flights. However, realistically modeling and simulating butterfly flights—in particular, for real-time graphics and animation applications—remains an under-explored problem. In this article, we propose an efficient and practical model to simulate butterfly flights. We first model a butterfly with parametric maneuvering functions, including wing-abdomen interaction. Then, we simulate dynamic maneuvering control of the butterfly through our force-based model, which includes both the aerodynamics force and the vortex force. Through many simulation experiments and comparisons, we demonstrate that our method can efficiently simulate realistic butterfly flight motions in various real-world settings.
OptiTrap: Optimal Trap Trajectories for Acoustic Levitation Displays
Authors: Paneva Viktorija , Fleig Arthur , Plasencia Diego MartíNez , Faulwasser Timm , Müller Jörg
Published: March 2022

Acoustic levitation has recently demonstrated the ability to create volumetric content by trapping and quickly moving particles along reference paths to reveal shapes in mid-air. However, the problem of specifying physically feasible trap trajectories to display desired shapes remains unsolved. Even if only the final shape is of interest to the content creator, the trap trajectories need to determine where and when the traps need to be, for the particle to reveal the intended shape. We propose
OptiTrap
, the first structured numerical approach to compute trap trajectories for acoustic levitation displays. Our approach generates trap trajectories that are physically feasible and nearly time-optimal, and reveal generic mid-air shapes, given only a reference path (i.e., a shape with no time information). We provide a multi-dimensional model of the acoustic forces around a trap to model the trap-particle system dynamics and compute optimal trap trajectories by formulating and solving a non-linear path following problem. We formulate our approach and evaluate it, demonstrating how
OptiTrap
consistently produces feasible and nearly optimal paths, with increases in size, frequency, and accuracy of the shapes rendered, allowing us to demonstrate larger and more complex shapes than ever shown to date.
Learning Relation Ties with a Force-Directed Graph in Distant Supervised Relation Extraction
Authors: Shang Yu-Ming , Huang Heyan , Sun Xin , Wei Wei , Mao Xian-Ling
Published: March 2022

Relation ties, defined as the correlation and mutual exclusion between different relations, are critical for distant supervised relation extraction. Previous studies usually obtain this property by greedily learning the local connections between relations. However, they are essentially limited because of failing to capture the global topology structure of relation ties and may easily fall into a locally optimal solution. To address this issue, we propose a novel force-directed graph to comprehensively learn relation ties. Specifically, we first construct a graph according to the global co-occurrence of all relations. Then, we borrow the idea of Coulomb’s law from physics and introduce the concept of attractive force and repulsive force into this graph to learn correlation and mutual exclusion between relations. Finally, the obtained relation representations are applied as an inter-dependent relation classifier. Extensive experimental results demonstrate that our method is capable of modeling global correlation and mutual exclusion between relations, and outperforms the state-of-the-art baselines. In addition, the proposed force-directed graph can be used as a module to augment existing relation extraction systems and improve their performance.
Dynamic Nuclear Polarization Solid-State NMR Spectroscopy for Materials Research
Authors: Moroz Ilia B. , Leskes Michal
Published: March 2022

Solid-state nuclear magnetic resonance (NMR) spectroscopy has increasingly been used for materials characterization as it enables selective detection of elements of interest, as well as their local structure and dynamic properties. Nevertheless, utilization of NMR is limited by its inherent low sensitivity. The development of dynamic nuclear polarization (DNP) approaches, which provide enormous sensitivity gain in NMR through the transfer of polarization from electron spins, has transformed the application of solid-state NMR in materials science. In this review, we outline the opportunities for materials characterization that DNP has opened up. We describe the main DNP mechanisms available, their implementation, and the kinds of insight they can provide across different materials classes, from surfaces and interfaces to defects in the bulk of solids. Finally, we discuss the current limitations of the approach and provide an outlook on future developments for DNP-enhanced NMR spectroscopy in materials science.
Breathing Rhythm and Pattern and Their Influence on Emotion
Authors: Ashhad Sufyan , Kam Kaiwen , Del Negro Christopher A. , Feldman Jack L.
Published: March 2022

Breathing is a vital rhythmic motor behavior with a surprisingly broad influence on the brain and body. The apparent simplicity of breathing belies a complex neural control system, the breathing central pattern generator (bCPG), that exhibits diverse operational modes to regulate gas exchange and coordinate breathing with an array of behaviors. In this review, we focus on selected advances in our understanding of the bCPG. At the core of the bCPG is the preBötzinger complex (preBötC), which drives inspiratory rhythm via an unexpectedly sophisticated emergent mechanism. Synchronization dynamics underlying preBötC rhythmogenesis imbue the system with robustness and lability. These dynamics are modulated by inputs from throughout the brain and generate rhythmic, patterned activity that is widely distributed. The connectivity and an emerging literature support a link between breathing, emotion, and cognition that is becoming experimentally tractable. These advances bring great potential for elucidating function and dysfunction in breathing and other mammalian neural circuits.
Relationship between Mechanical and Electrochemical Property in Silicon Alloy Designed by Grain Size as Anode for Lithium-Ion Batteries
Authors: Ji Sang-Gu , Umirov Nurzhan , Kim Hyang-Yeon , Kim Sung-Soo
Published: March 2022

While silicon has a very high theoretical capacity but has relatively the stresses produced by volume changes during charge/discharge cycling lead to structural modifications (around 300%). To overcome this problem, many studies are being conducted to commercialize silicon. Herein, we produced amorphous silicon alloy using a melt-spinning method. Then, through annealing under various temperatures, we gradually recrystallized the silicon phase. Average silicon grain sizes were 70 and 130 nm for silicon alloys annealed at 800 and 873 K, respectively. The initial reversible capacities of silicon alloy-based anodes were 844.3 (800 K) and 865.1 mAh g−1 (873 K), and, after 100 cycles, capacity retention rates were found to be 68.5 (800 K) and 40.5% (873 K). At this stage, to elucidate the effect of grain sizes on cycle life retention rate, we determined mechanical hardness through nanoindentation. And, by measuring volume expansion values between cycles through in situ dilation, we could identify the relationship between electrochemical property and mechanical hardness of silicon alloy samples depending on recrystallized grain sizes. Thus, by analyzing the mechanical and electrochemical properties of silicon alloys depending on silicon grain sizes, we want to highlight the importance of controlling silicon grain size.
Comparative X-ray Photoelectron Spectroscopy Study of the SEI and CEI in Three Different Lithium Ion Cell Formats
Authors: Heidrich Bastian , Pritzlaff Lars , Börner Markus , Winter Martin , Niehoff Philip
Published: March 2022

The solid electrolyte interphase (SEI) and cathode electrolyte interphase (CEI) of three lithium ion cell formats, i.e., coin, lab-scale pouch and multi-layer pouch, are compared. Half the cells are additionally dried prior to electrolyte filling and cycling. The highest water content per cell, determined by Karl Fischer titration, is found for lab-scale pouch cells due to their disadvantageous ratio of cell housing area to electrode area. The water content influences the performance during electrochemical formation as well as the impedance. This is linked to increasing lithium fluoride concentration, as determined by X-ray photoelectron spectroscopy. For dried cells, this is not the case because there is less conducting salt hydrolysis. The CEI thickness decreases for dried pouch cells, while the organic SEI thickness increases in all cell formats for dried cells. It is concluded that the initial thickness of the porous organic SEI depends on the insulation of the dense inorganic SEI close to the electrode surface. Organic species are more likely to contribute to negative electrode passivation when the extent of conducting salt hydrolysis is low. For coin cells, the presence of atmospheric gases during formation results in thicker SEI and CEI, no matter whether cells are additionally dried.
Correlation of Blood Biochemical Markers with Tardive Dyskinesia in Schizophrenic Patients
Authors: Wu Qian , Yuan Fengjuan , Zhang Shuo , Liu Weiting , Miao Qing , Zheng Xinhua , Lu Suxiang , Hou Kaijian
Published: March 2022

Objective. Oxidative stress factors and proinflammatory cytokines had been found to be involved in the pathogenesis of patients with tardive dyskinesia (TD). This study assumes that blood biochemical markers would have a link with TD in schizophrenia patients. To explore the correlation between blood biochemical markers and tardive dyskinesia in patients with schizophrenia (SCH). Methods. From January 2010 to August 2021, the inpatients who met the diagnostic criteria of schizophrenia in the Chinese Classification and Diagnosis Criteria of Mental Disorders (DSM-4) and the American Diagnostic and Statistical Manual of Mental Disorders (DSM-4) were followed up in the psychiatric outpatient department of Jinxia Street Community Health Service Center, Longhu District, Shantou City. The diagnostic criteria of Abnormal Involuntary Movement Scale (AIMS) used in the TD study of Schooler and Kane were used to screen the patients. Patients were divided into the schizophrenia (SCH group) and the schizophrenia with TD groups (TD group). Oxidative stress factors including Superoxide Dismutase1 (SOD1), Glutathione Peroxidase1 (GPX1), Malondialdehyde1 (MDA1), Catalase Activity1 (CAT1), and brain-derived neurotrophic factor 1 (BDNF1) and some inflammatory cytokines including interleukin-2 (IL-2), interleukin-6 (IL-6), interleukin-8 (IL-8), serum tumor necrosis factor (TNF-α), prolactin, estrogen, and cortisol were measured in 121 schizophrenic patients with tardive dyskinesia and 118 schizophrenic patients. The correlation analysis was conducted on the data. Results. Age and female were immutable risk factors for the development of TD, and there were significant differences in blood biochemical indices GPX1, MDA1, CAT1, and TNF-α in schizophrenic patients with and without TD. Conclusion. This study supports that oxidative stress and immune disorders are associated with TD patients. Blood biochemical markers GPX1, MDA1, CAT1, and TNF-α may play an important role in the pathogenesis of schizophrenia combined with TD patients, and they may be useful in the diagnosis of schizophrenia with tardive dyskinesia.
Relatively Lower FT3 Levels Are Associated with Impaired Quality of Life in Levothyroxine-Treated Patients with Hashimoto Thyroiditis
Authors: Cui Zhijun , Ding Xiaoyu , Bian Nannan , Chang Xiaona , Wang Jiaxuan , An Yu , Liu Jia , Wang Guang
Published: March 2022

Objective. Patients with Hashimoto thyroiditis (HT) frequently have some complaints despite achieving euthyroidism after levothyroxine (LT4) treatment. This study aimed to investigate the relevant factors affecting the quality of life (QoL) in euthyroid HT patients after LT4 treatment. Methods. In this case-control study, 133 participants with HT were included. They were divided into two groups: 64 euthyroid HT subjects (control group) and 69 HT patients were rendered euthyroid by LT4 treatment (well-controlled group). QoL was measured with the Thyroid-Related Patient-Reported Outcome (ThyPRO-39) questionnaire. Results. Both study groups were well matched with respect to gender, age, BMI, euthyroidism, and thyroid antibodies (TPOAb and TGAb). Compared with the control group, the well-controlled group had lower FT3 (

P
<
0.01

) levels. Of note, QoL was impaired on all scales in the well-controlled group. Moreover, ThyPRO-39 scores among the well-controlled group were significantly higher (worse) than the control group in all scales. Regarding the composite scale, its score was related to FT3 (r = −0.176,

P
=
0.043

) but not to FT4 and TSH levels. Further logistic regression analysis revealed FT3 was significantly associated with elevated composite QoL [0.128 (0.029–0.577),

P
<
0.01

] after adjustment of potential confounders. Conclusion. Relatively lower FT3 concentrations, even within the normal reference range, were related to impaired QoL in HT patients treated with LT4. This finding supports the great value of FT3 in clinical decision-making on dose adequacy.
Contextual Awareness Service of Internet of Things User Interaction Mode in Intelligent Environment
Authors: Song Lingling
Published: March 2022

In order to reduce the difficulty of the Internet of Things intelligent environment system to provide users with layout services and optimize the system structure, this paper proposes to design a context-aware service system based on the user interaction mode of the Internet of Things. This article first collected a large amount of data through the literature survey method, which laid a sufficient theoretical foundation for the subsequent research; then, using smart sensors, smart interaction technology, and context awareness methods is employed to design and build a context-aware service system based on the user interaction modality of the Internet of Things; in order to test the performance and effect of the situational awareness system, take the elderly home care behavior as the research object, collect the 28-day home behavior of the elderly as sample data, and divide it into 7-day data, 14-day data, 21-day data, and 28-day data, by adopting rule pruning demand reasoning algorithm and evidence theory algorithm to reason about the service demand of the elderly. Finally, the experimental results show that the rule-pruning-based service demand reasoning algorithm combined with the evidence theory algorithm optimizes the system, which can better perceive the situation of the elderly living alone and can well reason about the elderly’s service demand, which is of great significance for solving the life and safety problems of the elderly.
Ultrasonic Synthesis of Al‐SBA‐15 Nanoporous Catalyst for t-Butylation of Ethylbenzene
Authors: Prabhu Azhagapillai , Sudha Venugopal , Pachamuthu Muthusamy Poomalai , Sundaravel Balachandran , Bellucci Stefano
Published: March 2022

Mesoporous Al‐SBA‐15 (Si/Al = 25) catalysts were synthesised by the ultrasonic (US) irradiation method at different time durations (1, 3, and 5 h) using the pluronic P123 triblock copolymer as a template. The synthesised catalysts were examined in detail by XRD, ICP‐AES, N2 adsorption‐desorption, SEM, TEM, FT‐IR, and TGA characterization techniques. The characterization results reveal that the catalysts possess a well‐ordered hexagonal mesoporous structure. The catalytic activity of synthesised materials was investigated in the tert-butylation of ethylbenzene at different reaction conditions, and their identified products are para-tert‐butylethylbenzene (p-tert‐BEB) and meta-tert‐butylethylbenzene (m-tert‐BEB). It was found that high ethylbenzene conversion (69%) is achieved at 200°C with high selectivity towards p-tert‐butylethylbenzene (80%). The optimum feed ratio (ethylbenzene: t‐butyl alcohol) was 1 : 2, and the feed rate was 2 ml/h for high conversion and product selectivity. All these synthesised Al‐SBA‐15 (US) catalysts are compared with hydrothermally synthesised Al‐SBA‐15 (HT) at the same reaction conditions.
Load Deflection Relationship of a Solid Slab under the Action of Construction Loads
Authors: Kigoye Eriya , Kyakula Michael
Published: March 2022

Over the past decades, there has been a tremendous improvement in the concrete placement technology in Uganda. The methods have moved from being manual to the use of concrete pumps. A concrete pump is capable of pumping high volumes of concrete per minute. This implies that for small volume slabs before the setting of concrete, the whole weight of the fresh concrete of the upper slab, formwork, and props is transferred to the lower supporting slab. During construction, slabs are stacked with materials like bricks, blocks, sand, and aggregates. Construction loads such as block loads and loads due to props, formwork, and freshly cast solid concrete slabs on the lower floor are usually greater than the imposed loads and are not catered for in design. A baseline survey carried out on 118 randomly selected sites in Kampala revealed that in 87% of the cases, supports are removed from a lower reinforced concrete slab, and then props are put on its top to support a yet to be cast slab on an upper floor. It also revealed that 80.6% of the slabs had construction loads such as bricks, blocks, sand, timber, and aggregates. Deflections were measured using dial gauges for construction loads owing to freshly cast slab and concrete blocks in a physical model of a multistory structure with dimensions of 4 m long, 2 m wide, 2 m high to 2nd level, and 2 m to 3rd level. Loads due to freshly cast concrete were 158% more than unfactored design live loads. The maximum deflection at center of the slab due to a freshly cast slab and blocks loaded instantly was 1.15 mm and 11.815 mm, respectively, compared to the immediate deflection equal to 0.103 mm due to a design‐imposed load of 2 KN/m2.
Sportsman’s Mental State Evaluation and Early Warning Method Based on Intelligent CNN
Authors: Xing Suxuan
Published: March 2022

Aiming at the intelligent needs of psychological state assessment of university students, the text information-based psychological problem identification approach is investigated in the paper. This approach uses the text of student forums within universities as the database and introduces the convolutional neural network (CNN) model in deep learning, which contains a convolutional layer, a pooling layer, and a fully connected layer. After the convolution is completed, the convolution result is delinearized by the activation function, and then, pooling is performed to improve the fitting ability of the network for nonlinearities. For data processing, behavioral features, attribute features, content features, and social relationship features are extracted from text information as the input of the CNN. The psychological lexicon of expertise (LIWC) is used to enhance the efficiency of text word frequency statistics when performing text content extraction. To evaluate the performance of the proposed method, simulations are performed in the open dataset of CLPsyh2017 ReachOut Forum, and the FastText method is used as a comparison. The results show that the CNN model achieves an accuracy of 0.71 in the full-sample domain, which is significantly higher than that of the FastText model at 0.64. In the early warning evaluation of mental states, the CNN performance is better than that of FastText.
Comparative Assessment of the Effects of Hydroxyethyl Starch and Normal Saline on Severe Hypotension in Patients with Aluminum Phosphide Poisoning: A Retrospective Study
Authors: Nakhostin-Ansari Amin , Kafi Gholamabbas , Arefi Mohammad , Barzegari Dahaj Nasrin , Akbarpour Samaneh , Mansouri Asieh , Behnoush Behnam , Soroosh Davood
Published: March 2022

Background. Aluminum phosphide poisoning is one of the most common forms of poisoning which requires immediate and urgent treatment. Objective. This study aimed to compare the efficiency of two solutions, including hydroxyethyl starch and normal saline, in treating hypotension in patients with aluminum phosphide poisoning. Methods. This retrospective cohort study was conducted on 35 patients with aluminum phosphide poisoning. We reviewed the profile of 18 patients treated with hydroxyethyl starch and 17 patients treated with normal saline. Within-group and between-group differences in systolic blood pressure before and after treatment were compared using paired t-test and independent t-test, respectively. Results. The mean ± standard deviation (SD) age of the subjects in the starch and normal saline groups was 27.06 ± 9.72 and 27.88 ± 9.08, respectively. The levels of blood pressure in the two groups were not significantly different before the treatment; the mean ± SD of systolic blood pressure in the starch and normal saline groups was 72.67 ± 14.49 and 68.59 ± 8.3, respectively (

P
=
0.313

). After the treatment, it was significantly increased to 94 ± 24.45 and 85.18 ± 19.9 in the starch group (

P
=
0.001

) and the normal saline group (

P
=
0.004

), respectively. However, there was no significant difference between the two groups (

P
=
0.245

). Only one person survived in each group. Conclusion. According to the results of this study, although there was no significant difference between the two groups in terms of their effects on hypotension, these treatments could not prevent mortality.
A Randomized Controlled Trial for Prevention of Postspinal Anesthesia Shivering in Gynecological Surgeries: Mirtazapine vs. Dexamethasone
Authors: Esmat Ibrahim M. , Elsayed Ahmed M. , El-Hariri Hazem M. , Ashoor Tarek M.
Published: March 2022

Background. The frequency of shivering regarding regional anesthesia is 55%. Newer effective and tolerable options for postspinal anesthesia shivering (PSAS) prophylaxis are necessary to improve patients’ quality of care. This research assessed the impact of preemptive mirtazapine versus preemptive dexamethasone to decrease frequency and severity of PSAS in gynecological procedures. Methods. 300 patients booked for gynecological procedures under spinal anesthesia (SA) were randomly apportioned into three groups (100 each) to get one preemptive dose of 30 mg mirtazapine tablet (M group), 8 mg dexamethasone diluted in 100 ml of saline infusion (D group) or placebo (C group) two hours before surgery. Incidence of clinically significant PSAS was the primary outcome. Core temperature, shivering score, hemodynamics changes, adverse events, and patient satisfaction score were documented as secondary outcomes. Results. Compared with C group, mirtazapine and dexamethasone decreased incidence of clinically significant shivering (74% vs. 16% and 31%, respectively;

P
<
0.001

). M and D groups had less hypotensive episodes during 5–25 min after intrathecal injection (

P
<
0.001

). 90 min after SA, tympanic temperatures were lower than baseline values in the three groups (

P
<
0.001

). Pruritus, nausea, and vomiting were more often in C group (

P
<
0.001

), whereas sedation was more frequent in M group (

P
<
0.001

). C group had the lowest satisfaction scores (

P
<
0.001

). Conclusion. Prophylactic administration of mirtazapine or dexamethasone attenuated shivering with minimal hazards in patients scheduled for gynecological surgeries under spinal anesthesia with priority to mirtazapine. The trial is registered with NCT03675555.
A Hybrid Feature Extraction Method for Nepali COVID-19-Related Tweets Classification
Authors: Shahi T.B. , Sitaula C. , Paudel N.
Published: March 2022

COVID-19 is one of the deadliest viruses, which has killed millions of people around the world to this date. The reason for peoples’ death is not only linked to its infection but also to peoples’ mental states and sentiments triggered by the fear of the virus. People’s sentiments, which are predominantly available in the form of posts/tweets on social media, can be interpreted using two kinds of information: syntactical and semantic. Herein, we propose to analyze peoples’ sentiment using both kinds of information (syntactical and semantic) on the COVID-19-related twitter dataset available in the Nepali language. For this, we, first, use two widely used text representation methods: TF-IDF and FastText and then combine them to achieve the hybrid features to capture the highly discriminating features. Second, we implement nine widely used machine learning classifiers (Logistic Regression, Support Vector Machine, Naive Bayes, K-Nearest Neighbor, Decision Trees, Random Forest, Extreme Tree classifier, AdaBoost, and Multilayer Perceptron), based on the three feature representation methods: TF-IDF, FastText, and Hybrid. To evaluate our methods, we use a publicly available Nepali-COVID-19 tweets dataset, NepCov19Tweets, which consists of Nepali tweets categorized into three classes (Positive, Negative, and Neutral). The evaluation results on the NepCOV19Tweets show that the hybrid feature extraction method not only outperforms the other two individual feature extraction methods while using nine different machine learning algorithms but also provides excellent performance when compared with the state-of-the-art methods.
Evaluation of Product Innovation Practice of Chinese Internet Companies Based on DANP Model
Authors: Sun Chu , Xia Qing , Mei Xiaoren
Published: March 2022

Purpose. Internet companies have played an important supporting role in China’s economic growth and social resource allocation in the advent of an exogenous shock: the coronavirus disease (COVID-19) pandemic. This is owing to their digital, networked, and platform-based characteristics amidst an environment of intensified competition and stagnation of innovation activities due to the pandemic shock. Thus, based on the social network theory and resource-based theory, this study combines the DANP model with corporate innovation to build a product innovation performance evaluation framework for Chinese Internet companies. From a value network perspective, this study considers the different performance aspects of network embeddedness, knowledge management, environmental triggering, and organizational effectiveness. Methodology. The performance of Internet enterprise product innovation may be considered a complex multicriteria decision-making problem. This study used the decision-making trial and evaluation laboratory-based analytic network algorithms to analyze the complex influencing relationship among the factors and calculate their weights. Preference ranking organization method for enrichment evaluation was used for selecting the final solution of multiobjective optimization. Three representative and influential Internet companies in China were selected for empirical analysis and practical evaluation, to find the gap between product innovation performance and expectations and present development suggestions. Findings. The study results reveal that relational embeddedness, knowledge sharing degree, cognitive embeddedness, structural embeddedness, knowledge absorptive capacity, and corporate strategic orientation are important to Chinese Internet enterprise product innovation performance. Practical Implications. This Internet enterprise product innovation performance evaluation framework can be used by Internet business operators to assess product innovation performance and identify areas of improvement. This study provides new product innovation ideas for Chinese Internet companies during an epidemic situation. Originality/Value. This study contributes to the present body of knowledge by using the DANP model to conduct empirical analysis, considering value network-related performance aspects to evaluate the product innovation performance of Internet enterprise in China.
CMY Color Spaced-Based Visual Cryptography Scheme for Secret Sharing of Data
Authors: Sherine Anli , Peter Geno , Stonier Albert Alexander , Praghash K. , Ganji Vivekananda
Published: March 2022

Visual cryptography technique allows visual information to be encrypted in such a way that the decrypted information appears as a visual image. Visual cryptography allows digital images to be separate into few shares called transparent shares. For security reasons, it ensures that hackers cannot find any clues about the secret image from a single cover image. The proposed technique uses CMY (cyan, magenta, yellow) color space to enhance visual cryptography, and mean visual cryptography can be used on color images. The other techniques used were color decomposition and error diffusion. Error diffusion is a type of half toning in which the quantization residual is distributed to neighboring pixels that have not yet been processed. The image will be encrypted by four shares which is cyan, magenta, yellow, and mask. Mask will be using random function to random generate half black and half white pixel in

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block. Stack all the shares for reviewing the secret image. After that, do the image preprocessing of the image and use OCR (optical character recognition) to recognize the message.
Solid Organ Transplant Graft-Versus-Host Disease in a Kidney/Pancreas Transplant Patient: Use of Chimerism Testing and a Rare Presentation of Cutaneous GVHD
Authors: Goyal Amrita , Allred Jeremy , Kandaswamy Raja , Finger Erik B. , Keys Daniel O. , Riad Samy , Giubellino Alessio , Miller Daniel D. , Lian Christine G. , Holtan Shernan G.
Published: March 2022

Introduction. Solid organ transplant graft-versus-host disease (SOT-GVHD) is a rare phenomenon in which recipients of solid organ transplant develop GVHD due to the presence of donor lymphocytes in the graft. SOT-GVHD most often occurs in patients receiving small bowel or liver transplants. Diagnosis is typically via identification of lymphocytic infiltration on histopathology and molecular demonstration of donor T cell chimerism in the target organ. The gastrointestinal (GI) system is the most common target of SOT-GVHD, and one estimate places long-term survival of patients with SOT-GVHD at 20% at 5 years. In this report, we present the case of a patient with sequential kidney and pancreas transplant who developed SOT-GVHD targeting host lymphocytes, skin, and liver, with a long period of stability before treatment with antithymocyte globulin. Peripheral blood chimerism testing was used to track response to therapy. Remarkably, he survived 1.5 years despite recurrent infections before dying of unrelated causes.
A New Maintainability Evaluation Method Based on Virtual-real Fusion Scene Construction
Authors: Ge Zhexue , Zhang Yi , Yang Yongmin , Luo Xu , Li Qiang , Wang Fang
Published: March 2022

Maintainability is one important attribute of product quality. Maintainability evaluation is important to reduce maintenance cost and improve availability. With this research work, an effective maintainability evaluation method is proposed by mingling virtual environment and real world physical equipment. In order to reduce the cost of maintainability test scenario construction, the surrounding environment of physical equipment is replaced by virtual model for virtual-real fusion. The virtual environment is mainly used to simulate the impact on maintenance operation space. The difficulty of realizing the test concept deals with how to accurately identify the pose of the physical equipment and register the virtual environment around the physical equipment. In the proposed method, initially the ORB feature of the physical product is extracted through binocular vision. Secondly, the ICP method is used to match the physical product feature with the digital prototype feature, so as to identify the relative pose of the physical equipment. The virtual maintenance environment is then accurately superimposed. Thirdly, the experimental evaluation method of virtual reality fusion maintainability qualitative and quantitative indicators is formulated. Finally, taking an engine as an example, a virtual-real fusion maintainability test case study is carried out to verify the effectiveness and feasibility of maintainability evaluation based on virtual-real fusion test scenario. With 5 test groups, evaluation is carried out in three scenes-real environment, virtual-real fusion and without surrounding environment. Results of the evaluation revealed that error rate of the proposed virtual reality fusion maintainability method are somehow closer to maintainability in real environment. The average error rate of the three maintainability qualitative indexes in the virtual-real fusion scene is 9.90%, whereas the average error of the maintenance time is 3.25%. The proposed system offers an absorbing simulation environment where users are privileged to interact with the maintenance objects. The research work bears great significance in maintenance, product designing, visualization and related domains. As maintenance in real environment happens to be costlier and hazardous, the proposed method is suitable to ensure substantial cost reduction and safety in all stages of maintainability. Moreover, outcomes of the evaluation and the generated data of simulation can be generalized to improve maintainability of equipment.
Design of Teaching System of Physical Yoga Course in Colleges and Universities Based on Computer Network
Authors: Zheng Hongyan , Zhang Haijun , Zhang Hao
Published: March 2022

The new generation of computer network technology has driven the development of the whole society and brought about earth-shaking changes. In the context of “Internet +”, the combination of the Internet and education has created today’s diversified online course model. Fitness yoga can stretch our limbs well. The teaching of physical education courses of fitness yoga in colleges and universities can alleviate the students’ long-term tension for learning and play a role in exercising and cultivating all-round development talents. This article takes the current status of online sports yoga courses in ordinary universities as the research object and uses a series of research methods to organize and summarize the teaching team, number of class selections, course evaluations, learning resources, etc. of online yoga courses in ordinary universities. Further, this paper designed a set of course teaching system based on computer network. The system is embedded with multimodal yoga action posture detection, which can solve related problems in yoga online teaching. The realization result proves that the system effectively improves the learning effect and comprehensive quality of students and has strong operability and feasibility.