Miracle-dz/UniFAR-FTUs huggingface dataset:
Length frequency distribution, length-weight relationship and condition factors of Hilsa Shad, Tenualosa ilisha from Bangladesh

Hilsa shad, Tenualosa ilisha, a cherished and economically vital species, thrives in the waters of Bangladesh. It holds a prominent role in bolstering the nation's food security and influencing the ecological dynamics of aquatic ecosystems along the Bangladeshi coast and estuaries. This comprehensive study encompasses data collection efforts on the Hilsa fish species, conducted at 12 commercial landing centers throughout Bangladesh over the course of 2020. The study describes some fundamental components, including length frequency distribution, length-weight relationships, and condition factors, offers invaluable insights into the growth, health, and overall well-being of Hilsa population. Notably, the length-weight relationship analysis revealed size ranges of 11.5-59.2 cm and 11.0-49.0 cm total length for females and males, respectively. The observed b values indicated positive allometric growth (b > 3.00) for female population and negative allometric growth (b < 3.00) for male population in the length-weight relationship. Among the condition factors scrutinized, Fulton's condition factor emerged as the most reliable indicator for assessing the health and condition of the Hilsa population. This study offers valuable insights for biologists, aiding in the assessment of the species' status and providing essential information for fishery biologists and conservation biologists. Such insights are instrumental in the management and ultimate conservation of this iconic species in Bangladesh.
Structure based modular ontologies composition

Ontologies are the main component of the semantic Web. Constructing large ontologies typically requires to reuse previously existing ones. Modularity is a key requirement for collaborative ontology engineering and for distributed ontology reuse on the Web. In this paper, we propose an approach to automatically compose ontology modules into a global ontology. Our approach is based on similarity measures computed against concept names, attributes and relationships. We also detail the algorithm allowing to merge the ontology modules into a global ontology.
Accelerating Learning in multi-objective systems through Transfer Learning

Large-scale, multi-agent systems are too complex for optimal control strategies to be known at design time and as a result good strategies must be learned at runtime. Learning in such systems, particularly those with multiple objectives, takes a considerable amount of time because of the size of the environment and dependencies between goals. Transfer Learning (TL) has been shown to reduce learning time in single-agent, single-objective applications. It is the process of sharing knowledge between two learning tasks called the source and target. The source is required to have been completed prior to the target task. This work proposes extending TL to multi-agent, multi-objective applications. To achieve this, an on-line version of TL called Parallel Transfer Learning (PTL) is presented. The issues involved in extending this algorithm to a multi-objective form are discussed. The effectiveness of this approach is evaluated in a smart grid scenario. When using PTL in this scenario learning is significantly accelerated. PTL achieves comparable performance to the base line in one third of the time.
Solution Concepts in A-Loss Recall Games: Existence and Computational Complexity

Imperfect recall games represent dynamic interactions where players forget previously known information, such as a history of played actions. The importance of imperfect recall games stems from allowing a concise representation of strategies compared to perfect recall games where players remember all information. However, most of the algorithmic results are negative for imperfect recall games -- a Nash equilibrium~(NE) does not have to exist and computing a best response or a maxmin strategy is NP-hard. We focus on a subclass of imperfect recall games, called A-loss recall games, where a best response can be found in polynomial time. We derive novel properties of A-loss recall games, including (1) a sufficient and necessary condition for the existence of NE in A-loss recall games, (2) example where both NE and maxmin require irrational numbers for rational input, and (3) NP-hardness of problems related to finding maxmin strategies and existence of a NE strategy.
Structured Local Predictors for image labelling

In this paper we introduce Structured Local Predictors (SLP) - A new formulation that considers the image labelling problem from a structured learning point of view. SLP are locally operating models, which provide a per-pixel labelling by exploiting contextual relations, learned from complex interactions between labels and a customizable intermediate representation of the image data. Our first key contribution is to handle flexible configurations of pairwise interactions between image pixels while allowing them to be made arbitrarily dependent on the image data. Moreover, we pose the parameter learning process as a convex, structured-learning problem, which can be efficiently solved in a globally optimal way due to the introduction of a continuous, structured output space. Finally, we provide an interface to our model by means of a quantization space, allowing to define task-specific intermediate representations for the input data. In our experiments we demonstrate the broad applicability of our model for tasks like inpainting and semantic labelling.
Finding impressive social content creators: searching for SNS illustrators using feedback on motifs and impressions

We propose a method for finding impressive creators in online social network sites (SNSs). Many users are actively engaged in publishing their own works, sharing visual content on sites such as YouTube or Flickr. In this paper, we focus on the Japanese illustration-sharing SNS, Pixiv. We implement an illustrator search system based on user impression categories. The impressions of illustrators are estimated from clues in the crowdsourced social-tag annotations on their illustrations. We evaluated our system in terms of normalized discounted cumulative gain and found that using feedback on motifs and impressions for illustrations of relevant illustrators improved illustrator search by 11%.
Optimizing Recall in Deep Graph Hashing Framework for Item Retrieval (Student Abstract)

Hashing-based recommendation (HR) methods, whose core idea is mapping users and items into hamming space, are common practice to improve item retrieval efficiency. However, existing HR fails to align optimization objective (i.e., Bayesian Personalized Ranking) and evaluation metric (i.e., Recall), leading to suboptimal performance. In this paper, we propose a smooth recall loss (termed as SRLoss), which targets Recall as the optimization objective. Due to the existence of discrete constraints, the optimization problem is NP-hard. To this end, we propose an approximation-adjustable gradient estimator to solve our problem. Experimental Results demonstrate the effectiveness of our proposed method.
Validating of Survey Instrument in the Perspective of Computer Technology-based Learning

ICT plays an essential component in Higher education institutes (HEIs). A critical step in confirming that the results to be achieved are reliable in solving a study's problem is content validation. The goal of this research paper is to describe usage of survey instrument Content Validity Index (CVI) to confirm content of survey instrument created based on ICT acceptance impact on students' academic performance. The content validity index was used to determine the usability of a survey questionnaire. Ten field specialist/professionals were selected, and used Expert Panel Rating chart (EPRC), the opinions of these experts were considered using an approach of item-level CVI (I-CVI) and scale-level CVI (S-CVI). While certain latent variables and study items were either eliminated or changed, the outcome achieved an acceptable level of validity for the remaining items maintained systematically. In conclusion, students’ academic performances will be analyzed to assess the generally performance of the proposed model.
Phytochemical Investigation and Biological Studies of Coffea benghalensis B. Heyne Ex Schult

The qualitative phytochemical screening of leaves and stems of Coffea benghalensis B. Heyne Ex Schult showed the presence of saponins, flavonoids, steroids, and cardiac glycoside. Stigmasterol, 1, 3- stearyl-oleyl-glyceride and stigmasterol glucoside were isolated and characterized from the dichloromethane extract of this plant leaves and stems by chromatographic and spectroscopic methods. Total caffeine content per hundred grams was estimated. Fatty acids were analyzed quantitatively by GLC. Total antioxidant capacity and antimicrobial activity of the plant leaves and stems extract were studied. Dhaka Univ. J. Sci. 72(1): 92-97, 2024 (January)
Immunotherapy in Non-Small Cell Lung Cancer (NSCLC): Chance and Challenge

Non-small cell lung cancer (NSCLC) is the major type of lung cancer, accounting for 85%. The common options for treatment include surgery, radiotherapy, chemotherapy, immunotherapy, and molecularly targeted therapy depending on the stage, histology, genetic changes, and health condition of patients. Sadly, just 15% of individuals with stage III NSCLC are still alive after five years, which indicates a bad outlook. Because of the use of PD-1 and CTLA-4 immune checkpoint inhibitors (ICIs), immunotherapy has unquestionably made the most progress in the field of NSCLC. This article offers a comprehensive exploration of NSCLC, encompassing its epidemiological characteristics, pathological processes of different classification, and the diverse treatment modalities available. It emphasizes the pivotal role of immunotherapy, particularly immune checkpoint inhibitors (ICIs) for treatment some classification of patients. The article discusses challenges and prospects, such as identifying patient populations that benefit most from immunotherapy and addressing issues like immune-related adverse events (irAEs) and immune resistance. Through this analysis, the article underscores the significant strides made in NSCLC treatment and the ongoing efforts to improve patient outcomes.
Using the Web to Obtain Frequencies for Unseen Bigrams

This article shows that the Web can be employed to obtain frequencies for bigrams that are unseen in a given corpus. We describe a method for retrieving counts for adjective-noun, noun-noun, and verb-object bigrams from the Web by querying a search engine. We evaluate this method by demonstrating: (a) a high correlation between Web frequencies and corpus frequencies; (b) a reliable correlation between Web frequencies and plausibility judgments; (c) a reliable correlation between Web frequencies and frequencies recreated using class-based smoothing; (d) a good performance of Web frequencies in a pseudo disambiguation task.
Modeling and Control of a Snake Robot using SimMechanics

Snake robots are biological inspired robots designed to locomote in an unwanted environment. The mechanism comprises of serially connected links through rotational joints capable of rotating its body in one or more plans. In this paper, snake robot model is proposed. The proposed model consists of a 10-links physically connected through joints. The aim of this work is to propel a snake robot consisting of 10-link through the n-1 rotary joint on the serpentine aisle. Structure of the entire mechanical model of a snake is created in Simmechanics, MATLAB library tool within Simulink environment. The mechanics for the motion of snake robot including dynamics, kinematics and friction force models are developed in order to find the nth link location in a 3D environment. In addition, we have also established the joint angle to activate the robot’s link on a serpenoid terrain. To control the entire movement comprising position, speed and torque at each joint of the snake robot, control system is altered. This system is further composed of 3 proportional controllers having a sensor to take measurement results from an actuator. The simulation studies showing performance of the system are conducted to determine the control parameters of the system measured through joint sensor via scope, graph and display units. From simulation results it is shown that the snake robot followed the serpentine wave motion.
Physicochemical and Microbiological Properties of Stirred Bio-Yoghurt Manufactured from Sheep Milk

Sheep milk is considered an important nutritional and health-promoting food source due to its high protein content and minerals. The current study aimed to ascertain the impact of probiotic bacteria ( Bifidobacterium longum ) on the physicochemical properties, bacterial evaluation and sensory assessment of stirred bio-yoghurt made from sheep milk. Stirred bio-yoghurt was prepared with various inoculation levels of Bifi. longum (3, 6, 9 and 12% for T1, T2, T3 and T4; respectively). According to the study's findings, the moisture content of all treatments steadily declined with increasing of storage periods at 4±1°C up to 15 days. The control samples had higher moisture than that of stirred bio-yoghurt made with various amounts of Bifi. longum . While the fresh samples had lower moisture that that of other treatments. The fat content of stirred bio-yoghurt as well as control samples found to decrease and significantly differences with increasing the storage periods at refrigerator temperature up to 15 days. In addition, the incorporation of Bifi. longum significantly raised protein and ash contents of stirred bio-yoghurt than that of control samples, and their contents were increase and significantly differences with increasing the storage periods at refrigerator temperature up to 15 days. There were astatically significant change in the syneresis of all moduli (treatment and control sample). Stirred bio-yoghurt treatments and the control samples had no coliform as well as mould and yeast levels in all treatments.
MetaSMT: a unified interface to SMT-LIB2

Various problems from artificial intelligence and formal methods are solved utilizing Satisfiability Modulo Theories (SMT) solvers. Selecting the best SMT solver for a specific application, however, is a daunting task. In this paper, we present the novel metaSMT TCP server and client architecture which can be used to solve SMT instances expressed in SMT-LIB2 by multiple solver processes in parallel. The metaSMT TCP server provides a unified interface for SMT-LIB2 instances with the capability to either use the API or the file interface of a solver process and thus serves as a highly customizable portfolio solver. We show that the run-time overhead required by the metaSMT TCP server and client architecture is marginal using selected benchmarks from SMT-LIB.
Language-Based Augmentation to Address Shortcut Learning in Object-Goal Navigation

Deep Reinforcement Learning (DRL) has shown great potential in enabling robots to find certain objects (e.g., ‘find a fridge’) in environments like homes or schools. This task is known as Object-Goal Navigation (ObjectNav). DRL methods are predominantly trained and evaluated using environment simulators. Although DRL has shown impressive results, the simulators may be biased or limited. This creates a risk of shortcut learning, i.e., learning a policy tailored to specific visual details of training environments. We aim to deepen our understanding of shortcut learning in ObjectNav, its implications and propose a solution. We design an experiment for inserting a shortcut bias in the appearance of training environments. As a proof-of-concept, we associate room types to specific wall colors (e.g., bedrooms with green walls), and observe poor generalization of a state-of-the-art (SOTA) ObjectNav method to environments where this is not the case (e.g., bedrooms with blue walls). We find that shortcut learning is the root cause: the agent learns to navigate to target objects, by simply searching for the associated wall color of the target object's room. To solve this, we propose Language-Based (L-B) augmentation. Our key insight is that we can leverage the multimodal feature space of a Vision-Language Model (VLM) to augment visual representations directly at the feature-level, requiring no changes to the simulator, and only an addition of one layer to the model. Where the SOTA ObjectNav method's success rate drops 69%, our proposal has only a drop of 23%. Code is available at https://github.com/Dennishoftijzer/L-B_Augmentation
Colorimetry of Hemoglobin in Plasma with 2 , 2 ’-Azino-di ( 3-ethylbenzthiazoline-6-suffonic acid ) ( ABTS )

Hemoglobin in plasma can be determined by the colordeveloping action of 2,2’-azino-di(3-ethylbenzthiazoline-6sulfonic acid), which is oxidized to a colored form by a peroxidase-like effect of hemoglobin in the presence of hydrogen peroxide. Sensitivity, precision, and accuracy are discussed. The calibration curve is linear for hemoglobin concentrations up to 1 g/L; the minimum detectable concentration is 20 mg/L. The within-run precision (CV) was 2.39%, analytical recovery 101.8%. Interference from plasma proteins and lipids was eliminated by centrifuging the reaction mixture before measuring its absorbarice at 410 nm.
Predictive properties of risk assessment instruments following self-harm

Summary This month's BJPsych publishes two important studies concerned with the use of risk assessment scales after self-harm, one a systematic review and the other a multicentre cohort study. We agree with the authors: that each study adds weight to the existing evidence that points towards avoiding the use of such scales in clinical practice.
Receptor editing: an approach by autoreactive B cells to escape tolerance

To determine the fate of anti-DNA antibody-bearing B cells in normal mice, we generated transgenic mice bearing the heavy (H) and light (L) chain genes of a well-characterized anti-double-stranded DNA antibody. This antibody was originally isolated from a diseased MRL/lpr mouse and has characteristics common to spontaneously arising anti-DNA antibodies. Results show that the H/L transgene (tg) immunoglobulin receptor is not expressed by animals bearing both tgs, although single tg animals (H or L) express their transgenes. Young H/L tg animals express few B cells, whereas adult H/L tg animals maintain almost normal B cell numbers. Analysis of the immunoglobulin receptors used by adult B cells shows that all contain the tg H chain in association with endogenous L chains. These B cells transcribe the L tg as well as the rearranged endogenous L chain gene, and loss of endogenous L chain gene transcription results in resurrection of the 3H9 H/L tg product. Examination of the endogenous L chains used by these cells shows that they represent a highly restricted subset of V genes. Taken together, these data suggest that autoreactive transgenic B cells can rearrange endogenous L chain genes to alter surface receptors. Those L chains that compete successfully with the L tg for H chain binding, and that create a nonautoreactive receptor, allow the B cell to escape deletion. We suggest that this receptor editing is a mechanism used by immature autoreactive B cells to escape tolerance.
A Proof-of-Concept Demonstration of Hybrid Li-Fi/Wi-Fi Network on a Prototype Testbed

The increasing demand for extensive data requirements in indoor wireless communication has become a center of attention. In response, Light-Fidelity (Li-Fi) technology has emerged as a viable alternative to Wireless-Fidelity (Wi-Fi), offering a multitude of benefits. These include higher data rates, access to a wide unlicensed spectrum, and a secure and environmental friendly communication system. However, Li-Fi has limited coverage. In contrast, Wi-Fi has better coverage albeit with lower data rates. The judicious utilization of both Li-Fi and Wi-Fi can provide higher throughput with broad coverage. In this work, we develop a realistic experimental setup for a hybrid Li-Fi/Wi-Fi network (HLWN) to showcase the performance of HLWN superiority over a Wi-Fi-only network in terms of network throughput and coverage. The results validate the potential of HLWN to meet the increasing demands of indoor wireless communication, particularly for scenarios with multiple users and mobility requirements. This research contributes to the advancement of HLWN technology and paves the way for its practical implementation in real-world scenarios. Through these evaluations, we measured the average throughput performance of HLWN. This metric provides valuable insights into the network’s ability to efficiently transmit data and seamlessly handle device transitions between Li-Fi and Wi-Fi access points.
Repozitoriji u otvorenom pristupu: interoperabilnost kao jedini put

Arhiviranje cjelovitih tekstova u repozitorije u otvorenom pristupu (OAR) jedan je od nacina osiguravanja otvorenog pristupa znanstvenoj literaturi. Danas gotovo svaka znacajnija znanstvena institucija u svijetu posjeduje vlastiti institucijski repozitorij u koji arhivira cjelovite tekstove objavljenih radova svojih djelatnika. Iako sve brojniji i popunjeniji, OAR-i ne ispunjavaju svoju svrhu ukoliko se ne umreže u globalnu mrežu repozitorija u otvorenom pristupu i ne posvete dovoljno pozornosti interoperabilnosti s drugim slicnim i srodnim sustavima. Stoga se prilikom uspostave OAR-a mora voditi racuna o standardima metapodataka koji ce se koristiti za opis pohranjenih zapisa, kontroli kvalitete unesenih metapodataka, koristenim kontroliranim rjecnicima, trajnim identifikatorima digitalnih dokumenata, jedinstvenom identifikacijom autora, implementaciji raznih standarda i protokola koji ce omoguciti pobiranje i/ili razmjenu metapodataka između sustava i dr. Na taj se nacin stjecu preduvjeti za međusobno povezivanje repozitorija, sto osigurava vecu vidljivost radova pohranjenih u repozitorije i laksu dostupnost znanstvene literature. U radu se donosi pregled glavnih podrucja i važnijih inicijativa vezanih uz pitanja interoperabilnosti kojima je potrebno posvetiti posebnu pažnju prilikom izgradnje jednog takvog repozitorija u otvorenom pristupu.
People, Places, Things: Web Presence for the Real World

The convergence of Web technology, wireless networks, and portable client devices provides new design opportunities for computer/communications systems. In the HP Labs' “Cooltown” project we have been exploring these opportunities through an infrastructure to support “web presence” for people, places and things. We put web servers into things like printers and put information into web servers about things like artwork; we group physically related things into places embodied in web servers. Using URLs for addressing, physical URL beaconing and sensing of URLs for discovery, and localized web servers for directories, we can create a location-aware but ubiquitous system to support nomadic users. On top of this infrastructure we can leverage Internet connectivity to support communications services. Web presence bridges the World Wide Web and the physical world we inhabit, providing a model for supporting nomadic users without a central control point.
A Small World Overlay Network for Semantic Based Search in P2P

For a peer-to-peer (P2P) system holding massive amount of data, efficient search for resources (such as data or services) is a key determinant to its scalability. This paper presents semantic small world (SSW), an overlay network and index structure for semantic based P2P search. By dynamically clustering peer nodes in a semantic space based on the semantics of their data and organizing the clusters into a small world network, SSW achieves a very competitive trade-off between the search latencies/traffic and maintenance overheads. Preliminary evaluation shows that SSW is much more scalable to very large network sizes and very large numbers of data objects compared to pSearch, the stateof-the-art semantic-based search technique for P2P systems.