Tackling Social Value Tasks with Multilingual NLP

In recent years, deep learning applications have shown promise in tackling social value tasks such as hate speech and misinformation in social media. Neural networks provide an efficient automated solution that has replaced hand-engineered systems. Existing studies that have explored building resources, e.g. datasets, models, and NLP solutions, have yielded significant performance. However, most of these systems are limited to providing solutions in only English, neglecting the bulk of hateful and misinformation content that is generated in other languages, particularly so-called low-resource languages that have a low amount of labeled or unlabeled language data for training machine learning models (e.g. Turkish). This limitation is due to the lack of a large collection of labeled or unlabeled corpora or manually crafted linguistic resources sufficient for building NLP systems in these languages. In this thesis, we set out to explore solutions for low-resource languages to mitigate the language gap in NLP systems for social value tasks. This thesis studies two tasks. First, we show that developing an automated classifier that captures hate speech and nuances in a low-resource language variety with limited data is extremely challenging. To tackle this, we propose HateMAML, a model-agnostic meta-learning-based framework that effectively performs hate speech detection in low resource languages. The proposed method uses a self-supervision strategy to overcome the limitation of data scarcity and produces a better pre-trained model for fast adaptation to an unseen target language. Second, this thesis aims to address the research gaps in rumour detection by proposing a modification over the standard Transformer and building on a multilingual pre-trained language model to perform rumour detection in multiple languages. Specifically, our proposed model MUSCAT prioritizes the source claims in multilingual conversation threads with co-attention transformers. Both of these methods can be seen as the incorporation of efficient transfer learning methods to mitigate issues in model training with small data. The findings yield accurate and efficient transfer learning models for low-resource languages. The results show that our proposed approaches outperform the state-of-the-art baselines in the cross-domain multilingual transfer setting. We also conduct ablation studies to analyze the characteristics of proposed solutions and provided empirical analysis outlining the challenges of data collection to performing detection tasks in multiple languages

First record of important biological parameters of Badis badis: A small indigenous species in Bangladesh

A total of 286 Badis badis were collected from the Sutiyahali Reservoir in Mymensingh from January to December 2022, and their sex ratios, first sexual maturity, length-weight relationships and condition factors were evaluated. The weight and length of B. badis varied from 0.81 to 1.01g (0.89±0.30) and 4.08 to 4.60cm (4.36±0.31), respectively. Logistic curves depicting a sex ratio and 50% maturity (L50) estimated at 4.5cm for females and 4.05cm for males, as well as males reaching first sexual maturity with a shorter length than females. Regression coefficients in every month differ significantly (p<0.05), according to the regression equations. Each month, the values of the exponent b were less than 3 (b<3), with the highest value of b recorded in August (2.80) and the lowest value recorded in January (2.33). This led to a monthly negative allometric growth being seen. A strong positive relationship is evident from the coefficient of determination (r2) values, which ranged from 0.92-0.98 with an average of 0.961. During the study, the average condition factor (Kn) value for B. badis was found to be 1.02±0.13, which is a positive indicator of the fish's physical well-being. The condition factor values varied between 0.84 to 1.39, making it abundantly clear that B. badis are in good health and the waterbody is an ideal habitat for their survival. Relative condition factor (Kr) values, which varied between studies and ranged from 0.78 to 1.01, also exhibited a noteworthy difference (p<0.05). For its long-term management, the above findings will be very helpful

Domestication performance of the striped snakehead Channa striata fry in pond conditions using different diets

The experiment was conducted to assess the performance of growth, rate of survival and FCR of the different feed types in Channa striata fry at the freshwater station of the Bangladesh Fisheries Research Institute. The experiment was undertaken with 3 treatments (T1, T2, and T3) and each having three replications (R1, R2, and R3).  Each treatment included the provision of three different feed types, with a stocking density of 1,00,000 individuals per hectare. Fry in T1 was fed a commercial feed that contained 40–35% protein at 40–10% of total body weight. In T2, 40–10% of the body weight of commercial feed, which included fish paste, was given. Contrarily, in T3 live fish fry and chopped fish were provided at 30–10% of total body weight. The mean weight gains in T1, T2, and T3 were 128.7, 140.7, and 162.3g, respectively with percentage weight gains were 81279, 87867, and 100999 respectively, as well as SGR, were 3.34%, 3.37%, and 3.45%, respectively. T1 revealed the lowest amount of weight gain, weight gain percent and SGR, whereas T3 revealed the highest. The mean survival rates at T1, T2, and T3, respectively, were 45.5%, 71.8%, and 82.67%, whereas the FCR values were 2.26, 2.05, and 1.79. T1 had the lowest survival rate and FCR values, while T3 showed the highest. These experiment findings revealed that chopped fish and live fish fry had a more optimistic effect on the survival and growth of the C. striata fry compared with other commercial feeds

The Present Conditions of Patients with Spinal Cord Injury at Rehabilitation Center in Bangladesh

Spinal Cord Injury (SCI) is one of the major cause of disability in developing country like Bangladesh. The study aims to identify present conditions of Patients with Spinal Cord Injury at Rehabilitation Center in Bangladesh. A quantitative cross-sectional study was conducted among 61 participants (47 from rural areas and 14 from urban areas) who were recruited through purposive sampling. A self-developed questionnaire was used to collect the data. Data were analyzed by SPSS version 20.0. There were 61 patients involved in the research: 83.6% - male, 16.4% female. Average age:  18-35 years. 37.7% patients were tetraplegic whereas 62.3% were paraplegic, employment of participants in this study was 77.0%. Most common complication was: pressure sore 55.70%, decrease joint range of motion 67.20%, joint stiffness 34.40%, spasticity developed 83.6%, urinary tract infection 63.9%, autonomic dysreflexia 36.1%, leg swelling 47.5%, postural hypotension 42.6%, sexual problem 34.4%, mentally and psychologically change 100.0%, respiratory complication 37.7%. Finally, the study explained their current status after SCI the maximum patient were dependent and their pattern of working is long sitting. Moreover, most of they are interested to involve in non-bed exercise like group exercise and play activities in outdoor settings. So it is necessary to raise awareness in local community about post SCI healthy lifestyle

Reproductive biology and length-weight relationship of the Pool Barb Puntius sophore (Hamilton, 1832) in Mymensingh, Bangladesh

The study was conducted within the Freshwater station of the Bangladesh Fisheries Research Institute in Mymensingh from November 2019 to October 2020. The main objectives were to acquire additional knowledge regarding length-weight connection, condition factor, sex ratio, gonadosomatic index, and fecundity of P. sophore. It was possible to determine the spawning season each month by comparing the levels of the gonadosomatic index for the two sexes. Both sexes of the P. sophore species showed negative allometric growth, as indicated by the length-weight relationships of TW=0.0165TL2.852 for females and TW=0.035TL2.956 for males. For females, the average condition factor was 1.17±0.096, while for males, it was 3.24±0.19. Both times, the condition factor's value was high (>1), demonstrating that both sexes are in good health. From collected fish, 147 (55.12%) of the 264 fish samples that were taken were females, whereas 117 (44.88%) were males (Females: Males=1:0.82). The chi-square test showed that the male-to-female ratio during the sample months was not significantly different from 1:1 (χ2= 0.15, p>0.05). The spawning season extended from May through July, with June representing both sexes' peak spawning time. According to the study, the month of June had the highest absolute fecundity, which was 7829 and the absolute fecundity value was found to be lowest in the month of October 803 with an average value of about 3560 throughout the study period. For the management and protection of this species, this data will be valuable to researchers and those who decide on fisheries policy

Architecture and network-on-chip implementation of a new hierarchical interconnection network

A Midimew-connected Mesh Network (MMN) is a minimal distance mesh with wrap-around links network of multiple basic modules (BMs), in which the BMs are 2D-mesh networks that are hierarchically interconnected for higher-level networks. In this paper, we present the architecture of the MMN, addressing of node, routing of message, and evaluate the static network performance of MMN, TESH, mesh and torus networks. In addition, we propose the network-on-chip (NoC) implementation of MMN. With innovative combination of diagonal and hierarchical structure, the MMN possesses several attractive features, including constant degree, small diameter, low cost, small average distance, moderate bisection width and high fault tolerant performance than that of other conventional and hierarchical interconnection networks. The simple architecture of MMN is also highly suitable for NoC implementation. To implement all the links of level-3 MMN, only four layers are needed which is feasible with current and future VLSI technologies

Evaluating GPT-3 Generated Explanations for Hateful Content Moderation

Recent research has focused on using large language models (LLMs) to generate explanations for hate speech through fine-tuning or prompting. Despite the growing interest in this area, these generated explanations' effectiveness and potential limitations remain poorly understood. A key concern is that these explanations, generated by LLMs, may lead to erroneous judgments about the nature of flagged content by both users and content moderators. For instance, an LLM-generated explanation might inaccurately convince a content moderator that a benign piece of content is hateful. In light of this, we propose an analytical framework for examining hate speech explanations and conducted an extensive survey on evaluating such explanations. Specifically, we prompted GPT-3 to generate explanations for both hateful and non-hateful content, and a survey was conducted with 2,400 unique respondents to evaluate the generated explanations. Our findings reveal that (1) human evaluators rated the GPT-generated explanations as high quality in terms of linguistic fluency, informativeness, persuasiveness, and logical soundness, (2) the persuasive nature of these explanations, however, varied depending on the prompting strategy employed, and (3) this persuasiveness may result in incorrect judgments about the hatefulness of the content. Our study underscores the need for caution in applying LLM-generated explanations for content moderation. Code and results are available at https://github.com/Social-AI-Studio/GPT3-HateEval.Comment: 9 pages, 2 figures, Accepted by International Joint Conference on Artificial Intelligence(IJCAI

State-of-the-Art Developments of Acoustic Energy Transfer

Acoustic energy transfer (AET) technology has drawn significant industrial attention recently. This paper presents the reviews of the existing AETs sequentially, preferably, from the early stage. From the review, it is evident that, among all the classes of wireless energy transfer, AET is the safest technology to adopt. Thus, it is highly recommended for sensitive area and devices, especially implantable devices. Though, the efficiency for relatively long distances (i.e., >30 mm) is less than that of inductive or capacitive power transfer; however, the trade-off between safety considerations and performances is highly suitable and better than others. From the presented statistics, it is evident that AET is capable of transmitting 1.068 kW and 5.4 W of energy through wall and in-body medium (implants), respectively. Progressively, the AET efficiency can reach up to 88% in extension to 8.6 m separation distance which is even superior to that of inductive and capacitive power transfer