bluuebunny/crossref_metadata_2025 huggingface dataset:
Regional Language Speech Recognition from Bone-Conducted Speech Signals through Different Deep Learning Architectures
Authors: Putta Venkata Subbaiah , Selwin Mich Priyadharson A. , Sundramurthy Venkatesa Prabhu
Published: August 2022

Bone-conducted microphone (BCM) senses vibrations from bones in the skull during speech to electrical audio signal. When transmitting speech signals, bone-conduction microphones (BCMs) capture speech signals based on the vibrations of the speaker’s skull and have better noise-resistance capabilities than standard air-conduction microphones (ACMs). BCMs have a different frequency response than ACMs because they only capture the low-frequency portion of speech signals. When we replace an ACM with a BCM, we may get satisfactory noise suppression results, but the speech quality and intelligibility may suffer due to the nature of the solid vibration. Mismatched BCM and ACM characteristics can also have an impact on ASR performance, and it is impossible to recreate a new ASR system using voice data from BCMs. The speech intelligibility of a BCM-conducted speech signal is determined by the location of the bone used to acquire the signal and accurately model phonemes of words. Deep learning techniques such as neural network have traditionally been used for speech recognition. However, neural networks have a high computational cost and are unable to model phonemes in signals. In this paper, the intelligibility of BCM signal speech was evaluated for different bone locations, namely the right ramus, larynx, and right mastoid. Listener and deep learning architectures such as CapsuleNet, UNet, and S-Net were used to acquire the BCM signal for Tamil words and evaluate speech intelligibility. As validated by the listener and deep learning architectures, the Larynx bone location improves speech intelligibility.
State Estimation for Standard Neural Network Models with Time‐Varying Delays
Authors: Zhu Jin , Li Tai-Fang , Wang Huanqing
Published: August 2022

The paper deals with the issue of state estimation for standard neural network models with time‐varying delays. A new augmented vector with the derivative of the state is introduced in the Lyapunov–Krasovskii functional. The state estimation criteria are obtained by constructing the suitable Lyapunov–Krasovskii functional; meanwhile, the observer gain and the controller gain are derived in terms of linear matrix inequality. The free matrix‐based integral inequality is utilized to handle the integral terms, and the zero equation is added to the derivative of the Lyapunov–Krasovskii functional, which decreases the conservatism. The effectiveness and feasibility of the proposed methods are demonstrated by two numerical examples.
Effects of Transcranial Magnetic Stimulation Combined with Computer-Aided Cognitive Training on Cognitive Function of Children with Cerebral Palsy and Dysgnosia
Authors: Chen Jun , Yu Xiaoming , Luo Guangjin
Published: August 2022

Objective. This study is aimed at researching transcranial magnetic stimulation (TMS) effects combined with computer-aided cognitive training (CACT) on cognitive function of children suffering from cerebral palsy and dysgnosia. Methods. From December 2019 to October 2021, 86 children with cerebral palsy and dysgnosia who were treated at our hospital were recruited and assigned into observation and control groups (

n
=
43

, each) using the random number table technique. The observation group received TMS combined with CACT (TMS+CACT), whereas the control group received only TMS. Chinese Wechsler Young Children Scale of Intelligence (C-WYCSI) and Chinese-Wechsler Intelligence Scale for Children (C-WISC) were used to evaluate the intelligence level of the two groups; Gross Motor Function Measure-88 (GMFM-88) of Fudan Chinese version was employed for evaluating the gross motor function of the two groups; a comparison was drawn among the two groups for the cerebral hemodynamic parameters before and after the treatment. Results. For young children, the verbal intelligence quotient (VIQ) scores at 6 and 12 weeks of treatment in the observation group were increased when compared to those in the control group (

48.91
±
3.70

vs.

47.32
±
3.33

,

54.25
±
4.46

vs.

49.48
±
3.36

), and the observation group’s performance intelligence quotient (PIQ) score at 12 weeks of treatment was higher as to that of the control group (

65.38
±
4.23

vs.

62.81
±
4.74

, all

P
<
0.05

). For older age children, the observation group’s VIQ and PIQ scores were greater than the control group’s at 6 and 12 weeks of treatment, with statistical significance (

63.80
±
3.76

vs.

59.50
±
5.32

,

74.64
±
12.04

vs.

65.08
±
6.30

;

63.91
±
5.96

vs.

58.42
±
3.70

,

72.73
±
5.06

vs.

66.42
±
5.93

; all

P
<
0.05

). The GMFM-88 scale scores in both groups were increased after 6 and 12 weeks of treatment. After treatment for 12 weeks, the observation group’s A-E scores were greater than those of the control group (all

P
<
0.05

). The peak systolic velocity (

V

s

), end-diastolic velocity (

V

d

), and mean velocity (

V

m

) at the anterior cerebral artery (ACA), middle cerebral artery (MCA), and posterior cerebral artery (PCA) in the observation group were dramatically increased than those in the control group (all

P
<
0.05

) after 12 weeks of treatment. Conclusion. TMS+CACT can effectively improve the intelligence level, cognitive ability, gross motor function, and cerebral blood flow of children suffering from cerebral palsy and intellectual disability.
Machine Learning-Based Fragility Assessment of Reinforced Concrete Buildings
Authors: Rasheed Abdur , Usman Muhammad , Zain Muhammad , Iqbal Nadeem
Published: August 2022

In the past, large earthquakes caused the collapse of infrastructure and killed thousands of people in Pakistan, a seismically active region. Therefore, the seismic assessment of infrastructure is a dire need that can be done using the fragility analysis. This study focuses on the fragility analysis of school buildings in Muzaffarabad district, seismic zone-4 of Pakistan. Fragility curves were developed using incremental dynamic analysis (IDA); however, the numerical analysis is computationally time-consuming and expensive. Therefore, soft computing techniques such as Artificial Neural Network (ANN) and Gene Expression Programming (GEP) were employed as alternative methods to establish the fragility curves for the prediction of seismic performance. The optimized ANN model [5-25-1] was used. The feedforward backpropagation network was considered in this study. To achieve a reliable model, 70% of the data was selected for training and 15% for validation and 15% of data was used for testing the model. Similarly, the GEP model was also employed to predict the fragility curves. The results of both ANN and GEP were compared based on the coefficient of determination, R2. The ANN model accurately predicts the global drift values with R2 equal to 0.938 compared to the GEP model having R2 equal to 0.87.
Optimization and Application of Communication Resource Allocation Algorithm for Urban Rail Transit Planning
Authors: Fang Hui , Zhang Wei
Published: August 2022

The construction and operation of China’s rail transit system have entered a high-speed development stage, and the rapid increase of train speed and mileage has brought greater challenges to the safety and reliability of the rail transit system. Network planning evaluation is the key to the early decision-making of urban rail transit project, which directly determines the success or failure of the whole project. How to scientifically and reasonably evaluate the urban rail transit information resource network planning has become a difficult problem for many urban planners to solve. Therefore, this paper studies the optimization of the communication resource allocation algorithm and the comprehensive evaluation of its application for urban rail transit planning. In this paper, based on CVNN structure, the network prototype is an extension of RVNN structure. In the abstract, its processing unit is composed of a pair of real-number processors that can realize certain operations. HNN is a fully connected recurrent neural network based on the idea of the energy function, which is helpful to understand the calculation mode of HNN, and the research shows that HNN can solve many combinatorial optimization problems. In addition, the combination of neural network and genetic algorithm with simulated annealing mechanism can also bring new directions for research. On the basis of experimental analysis, it can be concluded that in general, the error reduction rate of the optimization scheme designed in this paper can reach 58.6% on average. In practical application, the accuracy of the optimal bit error rate is 52.4%.
An Overview of DNA Methylation Indicators for the Course of Oral Precancer
Authors: Wang Wenjing , Li Wei , Zhang Hongyi
Published: August 2022

DNA methylation is a physiologically epigenetic alteration that happens when a methyl group is introduced to a CpG dinucleotide in the gene-regulating sequence of DNA. However, the majority of oral cancers have a well-defined precancerous stage; there are few clinical and morphological parameters for detecting and signalling the progression of precancerous to malignant tumours. DNA methylation forms are dynamic and reversible, allowing them to adjust to environmental or therapeutic changes. We did an extensive investigation to compile the data supporting aberrant DNA methylation forms as a possible biomarker for prediction. According to two longitudinal studies, p16 hypermethylation was considerably higher in precancerous lesions that progressed to cancer than in lesions that shrank. Most of the studies examined for this study were tiny cross-sectional research with scant validation and inadequately specified control groups. Existing evidence suggests that DNA methylation sequences can be relevant as a diagnostic biomarker for OPS development; however, sample size and research design restrictions make it difficult to draw definitive conclusions. Strong studies, including extensive epigenome-wide methylation scans of OPS with longitudinal monitoring, are necessary in this study in order to corroborate the recently discovered signals and discover new risk loci and disease progression molecular pathways.
FogDedupe: A Fog-Centric Deduplication Approach Using Multi-Key Homomorphic Encryption Technique
Authors: Yoosuf Mohamed Sirajudeen , Muralidharan C. , Shitharth S. , Alghamdi Mohammed , Maray Mohammed , Rabie Osama Bassam J.
Published: August 2022

The advancements in communication technologies and a rapid increase in the usage of IoT devices have resulted in an increased data generation rate. Storing, managing, and processing large quantities of unstructured data generated by IoT devices remain a huge challenge to cloud service providers (CSP). To reduce the storage overhead, CSPs implement deduplication algorithms on the cloud storage servers. It identifies and eliminates the redundant data blocks. However, implementing post-progress deduplication schemes does not address the bandwidth issues. Also, existing convergent key-based deduplication schemes are highly vulnerable to confirmation of file attacks (CFA) and can leak confidential information. To overcome these issues, FogDedupe, a fog-centric deduplication framework, is proposed. It performs source-level deduplication on the fog nodes to reduce the bandwidth usage and post-progress deduplication to improve the cloud storage efficiency. To perform source-level deduplication, a distributed index table is created and maintained in the fog nodes, and post-progress deduplication is performed using a multi-key homomorphic encryption technique. To evaluate the proposed FogDedupe framework, a testbed environment is created using the open-source Eucalyptus v.4.2.0 software and fog project v1.5.9 package. The proposed scheme tightens the security against CFA attacks and improves the storage overhead by 27% and reduces the deduplication latency by 12%.
Study on Intelligent Diagnosis of Railway Turnout Switch Based on Improved FastDTW and Time Series Segmentation under Big Data Monitoring
Authors: Gao Yuxin , Yang Yong , Ma Yuan , Xu Weixiang
Published: August 2022

Turnout equipment is a key component to ensure the safe operation of trains. How to identify turnout faults is one of the important tasks of railway engineering departments and electrical departments. We used machine learning algorithm to analyze the similarity of mechanical characteristic data during turnout actions and then realized the intelligent diagnosis of turnout faults under the background of big data. We segmented the mechanical motion curve according to the characteristics of the original curve, calculated the similarity between the motion curve to be diagnosed and the template motion curve through the improved fast dynamic time warping algorithm (FastDTW), and diagnosed the fault according to the dynamically determined optimal threshold. Experiments show that the algorithm for predicting turnout faults based on improved FastDTW and time series segmentation algorithm is an accurate and effective method, which can improve the key technology of intelligent monitoring, early warning of the whole process of turnout movement, and more detailed analysis of the motion curve for the railway department.
Trend Analysis of Hydrometeorological Data of Gilgel Gibe Catchment, Ethiopia
Authors: Rabba Zeinu Ahmed
Published: August 2022

Trend analysis of hydrometeorological data is vital for proper water resources planning and management. This paper examines the trends of the hydrometeorological data in Gilgel Gibe catchment and whether the trends are significant. Daily rainfall, temperature, and streamflow data of the stations in/around (nearby) the catchment (7 stations for rainfall, 4 stations for temperatures, and 6 stations for streamflow) for a period longer than 25 years were collected and then analyzed to detect the variability and the changes in trend. Prior to conducting trend tests, the missed data were filled, and their inconsistencies were also adjusted. The nonparametric Mann-Kendall test along with Sen’s slope technique was employed to detect monotonic trends in the data series. The results showed that, on average, the rainfall exhibits an insignificant increasing tendency. It was also observed that there is, in general, an increasing trend in temperature (both maximum and minimum) in the study area. The analysis of the stream flows indicated that only one station (Bulbul Nr. Serbo) showed a positive slope at a 5% significance level. Two stations (Aweitu Nr. Babu and Gibe Nr. Seka) showed a slightly increasing trend, whereas the remaining 3 stations (Gibe Nr. Assendabo, Aweitu at Jimma, and Kitto Nr. Jimma) indicated an insignificant decreasing trend. The streamflow of the catchment generally shows a tiny decreasing tendency (0.007% per year) at its outlet. However, the results in general specified statistically insignificant trend changes of the hydrometrological data of the study catchment.
Conformable Double Laplace–Sumudu Transform Decomposition Method for Fractional Partial Differential Equations
Authors: Honggang Jia , Yanmin Zhao
Published: August 2022

In this work, we proposed a new method called conformable fractional double Laplace–Sumudu transform decomposition method (CFDLSTDM) to solve fractional partial differential equations (FPDEs).This method is a combination of the Laplace–Sumudu transform method and the Adomian decomposition method. Besides, we presented some excellent properties and results of conformable double Laplace–Sumudu transform (CDLST). Illustrative examples results are given to show that the CFDLSTDM is an effective and accurate approach for fractional partial differential equations.
A Low-Latency and High-Throughput Multipath Technique to Overcome Black Hole Attack in Mobile Ad Hoc Network (MTBD)
Authors: Ramachandran Dhanagopal , S Sasikumar , Rajeev Ratna Vallabhuni , S Vijayprasath , R Suresh Kumar , P T Vasanth Raj , Garip Ilhan , K Umamahesawari
Published: August 2022

Security in MANETs is a highly contentious topic in the field of network management. The availability and functionality of a MANET might be compromised by a variety of attacks. One of the most prevalent active attacks used to degrade network speed and reliability is the black hole attack, which leads the compromised agent to discard all data packets. The purpose of a black hole node is to trick other access points into thinking that they must use their node as their route to a certain destination. The black hole node in a cable network cannot be detected or eliminated in an AODV network. We improved AODV in this study by utilizing a lighter-weight technique based on timing and baiting for detecting and separating single and collaboration black hole attacks. MANETs have a dynamic topology, an open medium, and a lack of a highly centralized monitoring point, all of which offer security problems. Attacks on security are one of the sorts of attacks. In MANETs, it has no central administration, and mobile devices link to other devices wirelessly. Black holes, insider attacks, gray holes, parallel universes, faulty nodes, and packet drops are all threats that can cause considerable disruption in secure communication. Simulation findings demonstrate that the proposed method significantly outperforms previous techniques in terms of end-to-end delay, throughput, packet delivery ratio, and average energy. A multipath methodology is used in our proposed method to mitigate the black hole attack in MANET. The proposed technique is tested in a simulation reality to see how stable it is in the face of an attack. When the proposed method’s results are compared to those of existing state-of-the-art approaches, it is discovered that the acquired results are satisfactory.
Web Log Analysis and Security Assessment Method Based on Data Mining
Authors: Jin Jingquan , Lin Xin
Published: August 2022

Web content mining describes the classification, clustering, and attribute analysis of a large number of text documents and multimedia files on the web. Special tasks include retrieval of data from the Internet search engine tool W; structured processing and analysis of web data. Today’s blog analysis has security concerns. We do experiments to investigate its safety. Through experiments, we draw the following conclusions: (1) Web log extraction can use efficient data mining algorithms to systematically extract logs from web servers, then determine the main access types or interests of users, and then to a certain extent, based on the discovered user patterns, analyze the user’s access settings and behavior. (2) No matter in the test set or the mixed test set, the curve value of deep mining is very stable, the curve value has been kept at 0.95, and the curve value of fuzzy statistics method and quantitative statistics method is stable within the interval of 0.90–095. The results also show that the data mining method has the highest identification accuracy and the best security performance. (3) Web usage analysis requires data abstraction for pattern discovery. This data abstraction can be achieved through data preprocessing, which introduces different formats of web server log files and how web server log data is preprocessed for web usage analysis. One of the most critical parts of the web mining field is web log mining. Web log mining can use powerful data mining algorithms to systematically mine the logs in the web server and then learn the user’s access or preferred interests and then conduct a certain degree of user preferences and behavior patterns according to the discovered user patterns. Based on the above analysis, the current web log analysis is faced with security problems. We conduct experiments to study to verify the security performance of web logs and draw conclusions through experiments.
An Agile and Efficient Neural Network Based on Knowledge Distillation for Scene Text Detection
Authors: Lin Weiwei , Zhang Zeqing , Xue Xingsi
Published: August 2022

Text detection is increasingly in demand recently and poses significant challenges for the tradeoff among the detection accuracy, memory resources, and inference speed in the case of applying to the portable device such as mobile phones. Current methods mainly focus on the detection accuracy but neglect either the running speed or the memory consumption. To this end, an agile and efficient neural network for scene text detection that balances the detection performance, running speed, and the model size is hereby proposed. In order to reduce the network parameters and speed up, the neural network for text detection is firstly pruned; and then, the pruned neural network is trained with the structured knowledge distillation for improving the detection performance. The method is implemented on three benchmark text datasets, i.e., ICDAR2015, Total-Text, and MSRA-TD500. The experimental results demonstrate that the hereby proposed method achieves the best comprehensive performance with a faster running speed and much less memory resources while the text detection accuracy is comparable to that acquired using the excellent text detection methods.
ptk2 and mt2a Genes Expression in Gastritis and Gastric Cancer Patients with Helicobacter pylori Infection
Authors: Ahmadi Hedayati Manouchehr , Khani Delniya , Sheikhesmaeili Farshad , Nouri Bijan
Published: August 2022

Background. ptk2 and mt2a genes contribute to the cell cycle during proliferation and apoptosis, respectively. Designing a case-control study including gastric adenocarcinoma and gastritis patients with and without Helicobacter pylori infection would lead to determinate of the correlations between ptk2 and mt2a genes expression with H. pylori infection in gastric antral epithelial cells. Methods. Overall, 50 and 30 gastric antral biopsy samples of gastric cancer (case group) and gastritis (control group) patients were included into study, respectively. All biopsy samples were collected considering the exclusion criteria including patients with a history of consumption of tobacco, alcohol, and anti-H. pylori drugs. Each patient group is divided into with and without H. pylori infection to detect cDNA fold changes of ptk2 and mt2a genes by using Real Time RT PCR. Furthermore, the presence of H. pylori virulence genes was detected directly by using specific primers and simple PCR on cDNA synthesized from total RNA of gastric antral biopsy samples. Results. A negative correlation was revealed between age and clinical manifestations with the ΔCt value of the ptk2 gene (

P
<
0.05

). The H. pylori iceA1/2 and cagE genes revealed positive and negative correlations with the ΔCt value of the ptk2 gene (

P
<
0.05

), respectively. Furthermore, a weak correlation was detectable between H. pylori babA2/B, oipA, and cagY genes and the ΔCt value of the mt2a gene in gastric antral epithelial cells of patients (

P
<
0.1

). Conclusions. The results of the current study opened a view for more investigation on the stunning roles of H. pylori infection in clinical outcomes through mt2a and ptk2 gene expression in gastric antral epithelial cells.
Evaluation of Gas-Fired Combi Boilers with HF-AHP-MULTIMOORA
Authors: Samanlioglu Funda , Ayağ Zeki , Kirkil Gökhan , Yucal Esra
Published: August 2022

There are many alternative gas-fired combi boilers that can be used to heat residential homes. Evaluation and selection of gas-fired combi boilers for buildings is an intricate multi-criteria decision-making (MCDM) problem involving perhaps contradictory quantifiable and qualitative criteria. In this research, as the MCDM approach, hesitant fuzzy linguistic analytic hierarchy process (HF-AHP) and hesitant fuzzy linguistic “multiple objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA)” (HF-MULTIMOORA) are integrated to assess and rank combi boiler alternatives for buildings. First, with HF-AHP, fuzzy criteria weights are determined and then with HF-MULTIMOORA, boiler alternatives are ranked from best to worst. In this integrated HF-AHP-MULTIMOORA method, evaluations of decision-makers are combined with fuzzy envelope approach and then triangular fuzzy numbers are utilized. For comparison analysis, HF-AHP-TOPSIS method is also applied to the same problem. A case study in Turkey is presented where ten combi boiler alternatives are assessed based on fifteen criteria by five decision-makers. We have used various selection criteria for boilers ranging from maximum temperature, heating capacity up to environmental effects and decided on the best combi boiler for heating residential buildings in Turkey.
[Retracted] Long Intergenic Nonprotein Coding RNA 00174 Aggravates Lung Squamous Cell Carcinoma Progression via MicroRNA‐185‐5p/Nuclear Factor IX axis
Authors: Gu Peipei , Lin Lin
Published: August 2022

Extensive studies have presented that long noncoding RNAs (lncRNAs) are closely implicated in the pathogenesis of various human malignancies, including lung squamous cell carcinoma (LUSC). This study explored the biological role and the underlying mechanism of long intergenic nonprotein coding RNA 00174 (LINC00174) in LUSC. LINC00174 expression was measured by reverse transcription quantitative real‐time polymerase chain reaction (RT‐qPCR). Both in vitro and in vivo experiments were conducted to determine LINC00174 function in LUSC. Mechanical assays were performed to investigate the molecular mechanism involving LINC00174 and related genes. LINC00174 expression was high in LUSC cells. Silencing of LINC00174 could restrain LUSC cells proliferation, migration, and invasion while promoting cell apoptosis. Mechanically, LINC00174 could interact with miR‐185‐5p to upregulate nuclear factor IX (NFIX), which was the direct target gene of miR‐185‐5p. Notably, NFIX elevation could rescue the repressing effect of LINC00174 silence on LUSC cell malignant behaviors. Our data suggested that LINC00174 aggravated LUSC progression via serving as a competing endogenous RNA (ceRNA) to sponge miR‐185‐5p and ultimately upregulate NFIX, which offered a promising novel target for LUSC therapy.
A Weak Convergence Theorem for Common Fixed Points of Two Nonlinear Mappings in Hilbert Spaces
Authors: Ibaraki Takanori , Kajiba Shunsuke , Takeuchi Yukio
Published: August 2022

In this paper, by using properties of attractive points, we study an iteration scheme combining simplified Baillon type and Mann type to find a common fixed point of commutative two nonlinear mappings in Hilbert spaces. Then, we apply the obtained results to prove a new weak convergence theorem.
Multilingual Machine Translation System Based on Decoder Recurrent Neural Network
Authors: Deng Fei
Published: August 2022

In order to solve the problem that traditional machine translation cannot meet users’ needs due to its slow translation speed, an in-depth study on English translation model based on neural network was proposed. Firstly, three methods of model frame design, translation system design, and training frame design are studied. In order to improve the effectiveness and stability of the English translation model of recursive neural network, a model of English-Chinese machine translation system is designed. The system uses a knowledge-based context vector to map English and Chinese words, and uses a codec recursive neural network to achieve the results. After experiments and researches, the neural network can also efficiently deal with the long-distance reordering problem of multilanguage machine translation, which is difficult for statistical machine translation to deal with effectively. The neural network has opened a broad field of vision for machine translation research.
Digital Contact Tracing Applications against COVID-19: A Systematic Review
Authors: Nabeel Ahmad , Al-Sabah Salman K. , Ashrafian Hutan
Published: August 2022

Objective: The novel coronavirus 2019 (COVID-19) pandemic has triggered public anxiety around the world. So far, the evidence suggests that prevention on a public scale is the most effective health measure for thwarting the progress of COVID-19. Another critical aspect of preventing COVID-19 is contact tracing. We aimed to investigate the effectiveness of digital contact tracing applications currently available in the context of the COVID-19 pandemic. Methods: We undertook a systematic review and narrative synthesis of all literature relating to digital contact tracing applications in the context of COVID-19. We searched 3 major scientific databases. Only articles that were published in English and were available as full-text articles were selected for review. Data were extracted and narrative syntheses conducted. Results: Five studies relating to COVID-19 were included in the review. Our results suggest that digitalized contact tracing methods can be beneficial for impeding the progress of COVID-19. Three key themes were generated from this systematic review. First, the critical mass of adoption of applications must be attained at the population level before the sensitivity and positive predictive value of the solution can be increased. Second, usability factors such as access, ease of use, and the elimination of barriers are essential in driving this uptake. Third, privacy must be ensured where possible as it is the single most significant barrier against achieving critical mass. Conclusion: Contact tracing methods have proved to be beneficial for impeding the progress of COVID-19 as compared to older, more labour-intensive manual methods.
Alterations in Hypothalamic Mechanisms Associated with Reduced Suckling-Induced Prolactin Secretion in the Lactation-Deficient OFA hr/hr Rat
Authors: Pennacchio Gisela Erika , Ayala Carolina , Sanchez María Belén , Moreno-Sosa María Tamara , Campo-Verde-Arbocco Fiorella , Jahn Graciela Alma , Valdez Susana Ruth , Soaje Marta
Published: August 2022

Introduction: OFA hr/hr rats have deficient lactation with impaired suckling-induced PRL release. Unlike their background strain, Sprague-Dawley (SD) rats, OFA rats display abnormal mediobasal hypothalamus (MBH) dopaminergic tone during late pregnancy and lactation. We explored if the expression of MBH components, including various receptors (R) and proteins that regulate the dopaminergic system, is altered in mid-lactating OFA compared to SD rats, which may be associated with the abnormality. Methods: Four groups of mid-lactating rats were used: continuous lactation; pups separated overnight; 30-min suckling (S); and 2 h or 4 h S after separation. Mothers were sacrificed to obtain serum for PRL RIA and MBHs to determine tyrosine hydroxylase (TH), PRL-R, PRL signaling molecules (activator: STAT5b; inhibitors: SOCS1, SOCS3, CIS), opioids (PENK, PDYN), and µ- and κ-opioid R (MOR, KOR) mRNA expression by qPCR and phospho-TH (p-TH) and TH proteins by Western blot. Results: Suckling-induced PRL was lower in OFA and p-TH expression diminished in both strains. Separation increased TH mRNA and protein in SD, which decreased after 4 h S, but OFA protein levels remained unchanged. Separation of pups also resulted in decreased PRL-R and CIS expression in SD but increased PRL-R and SOCS3 in OFA. Despite the lower PRL-R, STAT5b, SOCS1, and SOCS3 levels in OFA compared to SD, suckling diminished them further. We observed subtle changes in SD opioids and their R, but in OFA, suckling decreased PENK, KOR, and MOR. Conclusion: The different patterns of TH, opioids, their R, and PRL signaling inhibitor expression with conserved TH activation by suckling may disturb the balance between stimulation and inhibition of PRL release resulting in impaired suckling-induced PRL secretion in OFA rats.
SECONDARY METABOLITE OF SUMBAWA ALGAE AND ITS POTENTIAL AS NATURAL PRESERVATIVE CANDIDATES (AN ANTIMICROBIAL STUDIES)
Authors: Manguntungi Baso , Sari Arlinda Puspita , Ariandi Ariandi , Vanggy Leggina Rezzy , Erlangga Robby , Mahesa Muhammad Abdi
Published: August 2022

Pathogenic bacterial contamination was a serious matter due to its capability in reducing food quality and health. This study aimed to select various types of algae in Luk Coast, Sumbawa Regency that have the potential to produce antibacterial compounds for natural food preservatives. Algae on Luk Coast was identified by means of morphological characters, followed by sample preparation and extraction of secondary metabolites (bioactive compounds). Algae extracts were used in antibacterial tests against food spoilage bacteria, such as Escherecia coli, Staphylococcus aureus, Salmonella thypi, Enterobacter cloacae and Pantoea agglomerans. Five types of algae identified were Padina sp., Halimeda opuntia, Sargassum horneri, Sargassum crassifolium and Galaxaura rugose. The five algae have the growth-inhibiting ability toward the tested bacteria. The highest inhibition zone was obtained from the 100% algae extract concentration.
MACROZOOBENTHIC COMMUNITY STRUCTURES IN SEAWEED CULTURE PONDS IN MUARA GEMBONG ESTUARY, BEKASI , WEST JAVA PROVINCE, INDONESIA
Authors: Indarjani Raden , Siti Nurhayati
Published: August 2022

The study of macrozoobenthic in seaweed culture in Muara Gembong Estuary, Bekasi District, West Java Province, was conducted in May to July 2018. The study was aimed at understanding the roles of macrozoobenthic organisms as ecosystem engineering in seaweed habitat by identifying macrozoobenthic community structures using various biological indices. Sampling sites were conducted at three selected intertidal ponds used for seaweed culture at different distances and perpendicular to the coastline. Samples of macrozoobenthic organisms were collected using an Ekman grab during low tide periods. The study results showed that the macrozoobenthic community from the three ponds were consisted of 9 major benthic families and 14 genera with a total of 139 individuals. The results also showed that gastropod of the genus Cerithiidae was the dominant taxa found in every pond which contributed to 42.45% of the total macrozoobenthic found in the three ponds and became the main contributing taxa to the macrozoobenthic community structure. In addition, genus Platynereis of the Polychaeta Class was found to be another important taxon which contributed to 14.39% of the total macrozoobenthic found in the three ponds. The genus Platynereis were mostly found in the second pond with muddy coarse sandy sediment substrate containing more silt compared to the other two ponds. The rare taxon was the genus Lithophaga from family Mytilidae represented by 1 individual. Our study concluded that the macrozoobenthic community structure in the three ponds was categorized as poorly diverse indicating that the pond system was unstable. The Shannon-Wiener Diversity Index (H’) was only 0.87 on average with the highest diversity index (H’=1.47) was found in the third pond located at the farthest area of the coastline. Meanwhile, the average of Evenness Index was 0.34 indicating that the distribution of the taxa was uneven with a tendency of being dominated by certain taxa.
MONITORING FOREST AREA CHANGE USING QUICKBIRD
Authors: ENDAYANI SRI , STEFANO ANDREW , FATHIAH  , PURBAWATI  , ROSANTI IDA
Published: August 2022

A study was conducted to compare the urban forest management in three urban forests in Samarinda City. The application of GIS (Geographic Information System) is one of the alternatives to conduct a variety of processes such as: providing geographical information system, identifying the areas of urban forests in Samarinda, helping to plan the process of map digitalization and performing overlay process. The main method used for the data analysis process on the map was the overlay process data analysis technique. The research findings showed that: 1) the appointment of urban forests as the initial step of urban forest development needed more implementation from the government; 2) the urban forest determination needed more socialization to the owner of the urban forest and the public in 1992 and 2019; 3) the urban forests needed more management. There were some similarities and differences in the management of urban forests in the three study locations. The similarities among the three locations were that the three locations had already met the minimum standards of one urban forest location even though there was still one location outside of these three locations which did not meet the minimum standard. The differences were in managing the urban forests. These differences indicated that the urban forest policy was not fully implemented in Samarinda City.
First report of the mymarid genus Proarescon Huber (Hymenoptera: Chalcidoidea: Mymaridae) from India
Authors: Ayyavu Athithya  , Sagadai Manickavasagam
Published: August 2022

Fairyfly genus Proarescon Huber, 2017 (Hymenoptera: Mymaridae) is reported for the first time from India and the specific identity is confirmed as P. primitivus (Huber, 2002) after consulting keys from Huber (2017); this genus is still known only from the Oriental region.  A note on diagnosis and distribution of this species is also provided.
Sam & Bram
Authors: Houppermans Sjef
Published: August 2022

Entre Sam et Bram les lignes sont complexes et les couleurs varient. Amis et compagnons, sur des chemins de traverse, ils se rencontrent dans leur conception absolue de l’œuvre d’art. Beckett tente de parler des peintures et y reconnaît (là aussi) un inévitable échec. Bram lit Sam et aime s’y perdre.
« Vu autrement »
Authors: Genetti Stefano
Published: August 2022

La mise en scène de Cap au pire conçue en 2006 par la chorégraphe Maguy Marin et interprétée par Françoise Leick plonge dans la pénombre la lecture intégrale en voix off du texte beckettien. L’installation de Peter Welz whenever on on on nohow on|airdrawing (2004) multiplie les captations de la performance que William Forsythe improvise à partir d’une phrase inspirée de Worstward Ho. En illustrant les apparitions et les disparitions des images et en inscrivant dans l’espace des traces de mots à la croisée de danse, vidéo-sculpture, dessin et architecture, ces deux œuvres visualisent et interrogent les tensions entre perception et imagination, présence et absence, voir et dire.
De La Cerisaie à En attendant Godot
Authors: Mével Yann
Published: August 2022

Une mise en scène de La Cerisaie présentée en 2021 par Tiago Rodrigues dans le cadre du festival d’Avignon permettait de prendre conscience des liens étroits qu’entretient cette pièce avec En attendant Godot. Notre analyse des convergences prend d’abord pour objets les rapports entre tragique et comique – ce dernier l’emportant selon Tchekhov –, ce qu’il reste d’action(s) et de psychologie. La représentation de l’espace et du temps, dans ces pièces, échappe au symbolisme. Le langage y exprime la difficulté d’éviter le monologue, malgré le besoin de rester en relation avec autrui. La comparaison de plusieurs scènes met en lumière de remarquables analogies entre ces pièces.
Anti-Colonialism Versus Self-Determination
Authors: Paranzino Michelle
Published: August 2022

The 1982 Falklands/Malvinas conflict pitted two of the most foundational principles of postwar international relations—anti-colonialism and self-determination—against each other, creating dilemmas for the great powers and smaller states alike in determining where to place their loyalties. The British consistently upheld the self-determination of the islanders, while portraying the war as a struggle between the forces of democracy and those of dictatorship. Though the United States strove for the appearance of neutrality, support for the United Kingdom resulted in the effective abandonment of the anti-colonialism of the Monroe Doctrine. The Soviet Union viewed the war as an anachronistic return to open imperialist aggression, and backed the fiercely anti-communist military junta in Argentina, even as it waged what was viewed as a “third world war” against the transnational forces of Marxism-Leninism. Meanwhile, the countries of the Western Hemisphere polarised into Latin American demands for decolonisation and the devotion of the Anglophone Caribbean to the principle of self-determination. This division was reflected in the debates and resolutions of the Organization of American States, the Non-Aligned Movement, and the United Nations.
The Tenebrionidae Latreille, 1802 (Coleoptera: Tenebrionoidea) of the Philippines. Part 2. Two new species of the genus Gauromaia Pascoe, 1866 (Cnodalonini) from Mindanao Island
Authors: MEDINA MILTON NORMAN , CABRAS ANALYN , RUZZIER ENRICO
Published: August 2022

In the present contribution two new species of the genus Gauromaia (Tenebrionidae: Cnodalonini), namely G. ruffordi sp. nov. and G. kitangladensis sp. nov. from the island of Mindanao (Philippines) are described and illustrated.
Finding Goldilocks Influencers: How Follower Count Drives Social Media Engagement
Authors: Wies Simone , Bleier Alexander , Edeling Alexander
Published: August 2022

Influencers’ follower count, or indegree, is a key criterion that advertisers use when devising influencer marketing campaigns. However, whether influencers with lower or higher follower count are more effective in generating engagement remains an open question. This multimethod research effort—involving an observational field data analysis, based on 802 Instagram marketing campaigns featuring more than 1,700 influencers, together with an eye-tracking study and laboratory experiments—establishes conclusive evidence of an inverted U-shaped relationship between influencers’ follower count and engagement with sponsored content. A higher follower count implies broader reach but also cues a weaker relationship that reduces followers’ engagement likelihood. That is, engagement first increases, then decreases, as influencer follower count rises. The authors further test the potential moderating effects of two campaign properties: content customization and brand familiarity. Higher content customization and lower familiarity of the sponsored brand signal that influencers value their relationships with followers and thereby flatten the inverted U-shaped relationship. Managers can leverage these novel results and the related actionable guidelines to improve their influencer marketing strategies.
Five Steps to Teach Simple Sentence Writing to Students With Learning Disabilities
Authors: Datchuk Shawn M. , Zimmermann Leah M. , Wagner Kyle , Poch Apryl L.
Published: August 2022

Many students with learning disabilities struggle with sentence writing fluency, the skill of quickly and accurately generating words that follow rules of semantics, spelling, syntax, and usage within sentence structures understandable to readers. Students who struggle with sentence writing fluency may face difficulty fully expressing their ideas while engaging in academic writing. In the present article, we describe how a combination of explicit instruction and fluency practice can improve the simple sentence writing fluency of students with learning disabilities. We detail how five design and delivery steps can help to create a supplemental writing intervention that addresses simple sentence structure, syntax, and usage.
Robot Drama: Investigating Frictions between Vision and Demonstration in Care Robotics
Authors: Lipp Benjamin
Published: August 2022

Roboticists are faced with a striking discrepancy between vision and demonstration of care with robots. On the one hand, research funders, policy makers, and entrepreneurs expect robots to become a panacea to impending demographic change. On the other hand, efforts to demonstrate that vision in care practice have largely remained unfulfilled. In this article, I investigate how roboticists manage and deal with this discrepancy between high expectations toward robotics research and what robots are capable of doing in practice. I will offer an extensive analysis of the efforts by roboticists and others to install, repair, stage, and, surprisingly, suspend robot dramas. Robot dramas comprise an ambivalent mix of experimental practices that seek to stage visions of care robotics while at the same time testing precarious phenomena of human–robot interaction. This relates two prominent but still largely disconnected strands of research in Science and Technology Studies: works on techno-scientific demonstrations, and on high and low expectations. Here, robot dramas are a crucial site for studying the conflicting interrelation between the theatrical performativity of demonstrations and the interplay of high and low expectations.
Porous synthetic hydrogel carrying basic fibroblast growth factor with controllable and rapid degradation rate to promote wound healing
Authors: Wu Qian , Gu Huijie , Cui Haiyan , Zhou Shu
Published: August 2022

Porous hydrogel dressings show breathability and possibility to carry and release basic fibroblast growth factor (bFGF) to promote wound healing. However, the difficult replacement may lead to the secondary damage. Thus, there is an urgent need to develop a method platform to control the degradation rate of hydrogel, so as to realize the on-demand replacement. The present study fabricated a porous hydrogel from co-polymized N,N′-bis(acryloyl) cystamine (BAC), allyl polyethylene glycol 500 (APEG500) and acrylic acid (AA) with the presence of polycaprolactone (PCL). BAC contains disulfide bond, which crosslinked the hydrogel. The pore size of the porous hydrogel was 400–600 μm. Higher content of BAC indicated higher crosslinking density, which reduced swelling ratio of hydrogel, while promoted hydrogel storage modulus. At the same time, the presence of PCL reduced swelling ratio of hydrogel, while promoted hydrogel mechanical properties, endowing hydrogel with tough feature. Porous hydrogels that crosslinked by disulfide bonds immersed in glutathione solution were found to degrade spontaneously and quickly due to the response to glutathione. Both crosslinking density and PCL content affected the degradation rate. The porous hydrogel carrying bFGF was applied to wound, promoting angiogenesis, thus accelerating wound healing within 12 d. Due to the spontaneous and rapid degradation of optimized porous hydrogel on wound within 3 days, there was no operation of removing dressing during treatment, avoiding damage during dressing replacement.